From 4a57b7cd1e59e0f52d187c0ce5aef5cc9fa36f5f Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Fri, 22 Sep 2023 05:33:10 -0400 Subject: [PATCH 01/40] added the argument (ARG) to dockerfiles --- .../download_convert_inference_totalseg_radiomics/Dockerfile | 2 ++ Dockerfiles/inference_totalseg/Dockerfile | 2 ++ Dockerfiles/per_frame_functional_group_sequence/Dockerfile | 2 ++ 3 files changed, 6 insertions(+) diff --git a/Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile b/Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile index 8d99877..862160c 100644 --- a/Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile +++ b/Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile @@ -1,5 +1,7 @@ FROM nvidia/cuda@sha256:e1a2b842633d9b48588553c699fe5369199fba724729ea165fd0e1c7a5baf3cb +ARG GIT_HASH + LABEL BASE_DOCKER_IMAGE="nvidia/cuda:12.1.0-base-ubuntu20.04"\ MAINTAINER="IDC " \ GIT_HASH=${GIT_HASH}\ diff --git a/Dockerfiles/inference_totalseg/Dockerfile b/Dockerfiles/inference_totalseg/Dockerfile index 89abc30..f78589a 100644 --- a/Dockerfiles/inference_totalseg/Dockerfile +++ b/Dockerfiles/inference_totalseg/Dockerfile @@ -1,5 +1,7 @@ FROM nvidia/cuda@sha256:bed19cc4270a4624f732de7a69beb061a7dfb2ab2e05e1a58e157a483ed25185 +ARG GIT_HASH + LABEL BASE_DOCKER_IMAGE="nvidia/cuda:12.1.0-base-ubuntu22.04"\ MAINTAINER="IDC " \ GIT_HASH=${GIT_HASH}\ diff --git a/Dockerfiles/per_frame_functional_group_sequence/Dockerfile b/Dockerfiles/per_frame_functional_group_sequence/Dockerfile index 407806e..2d7a0bf 100644 --- a/Dockerfiles/per_frame_functional_group_sequence/Dockerfile +++ b/Dockerfiles/per_frame_functional_group_sequence/Dockerfile @@ -1,5 +1,7 @@ FROM python@sha256:5b287042a6150052420e6a7fb7c1606b6403740880897ae9610faf434da28693 +ARG GIT_HASH + LABEL BASE_DOCKER_IMAGE="python:3.11.2-slim-buster"\ MAINTAINER="IDC " \ GIT_HASH=${GIT_HASH}\ From 02f175ce8d4e5b3fb0b6c852c212682de7b89011 Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Fri, 22 Sep 2023 06:07:40 -0400 Subject: [PATCH 02/40] Add .gitignore for dev branch --- .gitignore | 4 ++++ 1 file changed, 4 insertions(+) create mode 100644 .gitignore diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..c8e6f3e --- /dev/null +++ b/.gitignore @@ -0,0 +1,4 @@ +# .gitignore in the dev branch + +# Ignore all YAML files in the .github/workflows directory +.github/workflows/**.yml From 386777324154add30e0d29d18c7b71c90481d9a3 Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Fri, 22 Sep 2023 06:09:54 -0400 Subject: [PATCH 03/40] using env var instd of set-output as it is depcrtd --- .github/workflows/download_convert.yml | 10 +++++++--- .github/workflows/download_convert_inference.yml | 8 +++++--- ...download_convert_inference_totalseg_radiomics.yml | 12 ++++++++---- .github/workflows/inference_totalseg.yml | 12 ++++++++---- .../per_frame_functional_group_sequence.yml | 10 +++++++--- .github/workflows/radiomics.yml | 10 +++++++--- 6 files changed, 42 insertions(+), 20 deletions(-) diff --git a/.github/workflows/download_convert.yml b/.github/workflows/download_convert.yml index e3d6b6e..79a1101 100644 --- a/.github/workflows/download_convert.yml +++ b/.github/workflows/download_convert.yml @@ -15,11 +15,15 @@ jobs: uses: actions/checkout@v4 - name: Set up Git - run: git config --global user.email "actions@github.com" && git config --global user.name "GitHub Actions" + run: | + git config --global user.email "actions@github.com" + git config --global user.name "GitHub Actions" - name: Get Git Commit Hash id: git-commit-hash - run: echo "::set-output name=commit_hash::$(git rev-parse HEAD)" + run: | + COMMIT_HASH=$(git rev-parse HEAD) + echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - name: Login to Docker Hub uses: docker/login-action@v3 @@ -35,4 +39,4 @@ jobs: push: true tags: imagingdatacommons/download_convert build-args: | - GIT_HASH=${{ steps.git-commit-hash.outputs.commit_hash }} + GIT_HASH=$COMMIT_HASH diff --git a/.github/workflows/download_convert_inference.yml b/.github/workflows/download_convert_inference.yml index 78f8f80..d8bc083 100644 --- a/.github/workflows/download_convert_inference.yml +++ b/.github/workflows/download_convert_inference.yml @@ -15,8 +15,10 @@ jobs: uses: actions/checkout@v4 - name: Set up Git - run: git config --global user.email "actions@github.com" && git config --global user.name "GitHub Actions" - + run: | + git config --global user.email "actions@github.com" + git config --global user.name "GitHub Actions" + - name: Get Git Commit Hash id: git-commit-hash run: echo "::set-output name=commit_hash::$(git rev-parse HEAD)" @@ -39,4 +41,4 @@ jobs: push: true tags: imagingdatacommons/download_convert_inference_totalseg build-args: | - GIT_HASH=${{ steps.git-commit-hash.outputs.commit_hash }} + GIT_HASH=$COMMIT_HASH diff --git a/.github/workflows/download_convert_inference_totalseg_radiomics.yml b/.github/workflows/download_convert_inference_totalseg_radiomics.yml index 163fa07..1d96810 100644 --- a/.github/workflows/download_convert_inference_totalseg_radiomics.yml +++ b/.github/workflows/download_convert_inference_totalseg_radiomics.yml @@ -15,12 +15,16 @@ jobs: uses: actions/checkout@v4 - name: Set up Git - run: git config --global user.email "actions@github.com" && git config --global user.name "GitHub Actions" + run: | + git config --global user.email "actions@github.com" + git config --global user.name "GitHub Actions" - name: Get Git Commit Hash id: git-commit-hash - run: echo "::set-output name=commit_hash::$(git rev-parse HEAD)" - + run: | + COMMIT_HASH=$(git rev-parse HEAD) + echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV + - name: Copy additional files to build context run: | cp Dockerfiles/download_convert_inference_totalseg_radiomics/weights_download.sh . @@ -39,4 +43,4 @@ jobs: push: true tags: imagingdatacommons/download_convert_inference_totalseg_radiomics build-args: | - GIT_HASH=${{ steps.git-commit-hash.outputs.commit_hash }} + GIT_HASH=$COMMIT_HASH diff --git a/.github/workflows/inference_totalseg.yml b/.github/workflows/inference_totalseg.yml index 2527fc1..8dd5fef 100644 --- a/.github/workflows/inference_totalseg.yml +++ b/.github/workflows/inference_totalseg.yml @@ -14,12 +14,16 @@ jobs: uses: actions/checkout@v4 - name: Set up Git - run: git config --global user.email "actions@github.com" && git config --global user.name "GitHub Actions" + run: | + git config --global user.email "actions@github.com" + git config --global user.name "GitHub Actions" - name: Get Git Commit Hash id: git-commit-hash - run: echo "::set-output name=commit_hash::$(git rev-parse HEAD)" - + run: | + COMMIT_HASH=$(git rev-parse HEAD) + echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV + - name: Copy additional files to build context run: | cp Dockerfiles/inference_totalseg/weights_download.sh . @@ -38,4 +42,4 @@ jobs: push: true tags: imagingdatacommons/inference_totalseg build-args: | - GIT_HASH=${{ steps.git-commit-hash.outputs.commit_hash }} + GIT_HASH=$COMMIT_HASH \ No newline at end of file diff --git a/.github/workflows/per_frame_functional_group_sequence.yml b/.github/workflows/per_frame_functional_group_sequence.yml index bcb960f..906cbe7 100644 --- a/.github/workflows/per_frame_functional_group_sequence.yml +++ b/.github/workflows/per_frame_functional_group_sequence.yml @@ -15,11 +15,15 @@ jobs: uses: actions/checkout@v4 - name: Set up Git - run: git config --global user.email "actions@github.com" && git config --global user.name "GitHub Actions" + run: | + git config --global user.email "actions@github.com" + git config --global user.name "GitHub Actions" - name: Get Git Commit Hash id: git-commit-hash - run: echo "::set-output name=commit_hash::$(git rev-parse HEAD)" + run: | + COMMIT_HASH=$(git rev-parse HEAD) + echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - name: Login to Docker Hub uses: docker/login-action@v3 @@ -35,4 +39,4 @@ jobs: push: true tags: imagingdatacommons/per_frame_functional_group_sequence build-args: | - GIT_HASH=${{ steps.git-commit-hash.outputs.commit_hash }} + GIT_HASH=$COMMIT_HASH \ No newline at end of file diff --git a/.github/workflows/radiomics.yml b/.github/workflows/radiomics.yml index bdedd5b..bc2b199 100644 --- a/.github/workflows/radiomics.yml +++ b/.github/workflows/radiomics.yml @@ -15,11 +15,15 @@ jobs: uses: actions/checkout@v4 - name: Set up Git - run: git config --global user.email "actions@github.com" && git config --global user.name "GitHub Actions" + run: | + git config --global user.email "actions@github.com" + git config --global user.name "GitHub Actions" - name: Get Git Commit Hash id: git-commit-hash - run: echo "::set-output name=commit_hash::$(git rev-parse HEAD)" + run: | + COMMIT_HASH=$(git rev-parse HEAD) + echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - name: Login to Docker Hub uses: docker/login-action@v3 @@ -35,4 +39,4 @@ jobs: push: true tags: imagingdatacommons/radiomics build-args: | - GIT_HASH=${{ steps.git-commit-hash.outputs.commit_hash }} + GIT_HASH=$COMMIT_HASH \ No newline at end of file From a0040fe59d05e4852e702f4cd0bf6fcf4d77bd1a Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Fri, 22 Sep 2023 06:21:34 -0400 Subject: [PATCH 04/40] dev docker images, invoke gh actions whnevr wrkflw files are updated --- .github/workflows/download_convert.yml | 5 +++-- .github/workflows/download_convert_inference.yml | 5 +++-- .../download_convert_inference_totalseg_radiomics.yml | 5 +++-- .github/workflows/inference_totalseg.yml | 6 ++++-- .github/workflows/per_frame_functional_group_sequence.yml | 5 +++-- .github/workflows/radiomics.yml | 5 +++-- 6 files changed, 19 insertions(+), 12 deletions(-) diff --git a/.github/workflows/download_convert.yml b/.github/workflows/download_convert.yml index 79a1101..2a49aba 100644 --- a/.github/workflows/download_convert.yml +++ b/.github/workflows/download_convert.yml @@ -3,9 +3,10 @@ name: download_convert on: push: branches: - - main + - dev paths: - 'Dockerfiles/download_convert/**' + - .github/workflows/download_convert.yml jobs: build-and-push: @@ -37,6 +38,6 @@ jobs: context: . file: ./Dockerfiles/download_convert/Dockerfile push: true - tags: imagingdatacommons/download_convert + tags: imagingdatacommons/download_convert:dev build-args: | GIT_HASH=$COMMIT_HASH diff --git a/.github/workflows/download_convert_inference.yml b/.github/workflows/download_convert_inference.yml index d8bc083..dc0ed67 100644 --- a/.github/workflows/download_convert_inference.yml +++ b/.github/workflows/download_convert_inference.yml @@ -3,9 +3,10 @@ name: download_convert_inference_totalseg on: push: branches: - - main + - dev paths: - 'Dockerfiles/download_convert_inference_totalseg/**' + - .github/workflows/download_convert_inference_totalseg.yml jobs: build-and-push: @@ -39,6 +40,6 @@ jobs: context: . file: ./Dockerfiles/download_convert_inference_totalseg/Dockerfile push: true - tags: imagingdatacommons/download_convert_inference_totalseg + tags: imagingdatacommons/download_convert_inference_totalseg:dev build-args: | GIT_HASH=$COMMIT_HASH diff --git a/.github/workflows/download_convert_inference_totalseg_radiomics.yml b/.github/workflows/download_convert_inference_totalseg_radiomics.yml index 1d96810..d235f71 100644 --- a/.github/workflows/download_convert_inference_totalseg_radiomics.yml +++ b/.github/workflows/download_convert_inference_totalseg_radiomics.yml @@ -3,9 +3,10 @@ name: download_convert_inference_totalseg_radiomics on: push: branches: - - main + - dev paths: - 'Dockerfiles/download_convert_inference_totalseg_radiomics/**' + - .github/workflows/download_convert_inference_totalseg_radiomics.yml jobs: build-and-push: @@ -41,6 +42,6 @@ jobs: context: . file: ./Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile push: true - tags: imagingdatacommons/download_convert_inference_totalseg_radiomics + tags: imagingdatacommons/download_convert_inference_totalseg_radiomics:dev build-args: | GIT_HASH=$COMMIT_HASH diff --git a/.github/workflows/inference_totalseg.yml b/.github/workflows/inference_totalseg.yml index 8dd5fef..8f5494c 100644 --- a/.github/workflows/inference_totalseg.yml +++ b/.github/workflows/inference_totalseg.yml @@ -3,9 +3,11 @@ name: inference_totalseg on: push: branches: - - main + - dev paths: - 'Dockerfiles/inference_totalseg/**' + - .github/workflows/inference_totalseg.yml + jobs: build-and-push: runs-on: ubuntu-latest @@ -40,6 +42,6 @@ jobs: context: . file: ./Dockerfiles/inference_totalseg/Dockerfile push: true - tags: imagingdatacommons/inference_totalseg + tags: imagingdatacommons/inference_totalseg:dev build-args: | GIT_HASH=$COMMIT_HASH \ No newline at end of file diff --git a/.github/workflows/per_frame_functional_group_sequence.yml b/.github/workflows/per_frame_functional_group_sequence.yml index 906cbe7..14e0487 100644 --- a/.github/workflows/per_frame_functional_group_sequence.yml +++ b/.github/workflows/per_frame_functional_group_sequence.yml @@ -3,9 +3,10 @@ name: per_frame_functional_group_sequence on: push: branches: - - main + - dev paths: - 'Dockerfiles/per_frame_functional_group_sequence/**' + - .github/workflows/per_frame_functional_group_sequence.yml jobs: build-and-push: @@ -37,6 +38,6 @@ jobs: context: . file: ./Dockerfiles/per_frame_functional_group_sequence/Dockerfile push: true - tags: imagingdatacommons/per_frame_functional_group_sequence + tags: imagingdatacommons/per_frame_functional_group_sequence:dev build-args: | GIT_HASH=$COMMIT_HASH \ No newline at end of file diff --git a/.github/workflows/radiomics.yml b/.github/workflows/radiomics.yml index bc2b199..820f658 100644 --- a/.github/workflows/radiomics.yml +++ b/.github/workflows/radiomics.yml @@ -3,9 +3,10 @@ name: radiomics on: push: branches: - - main + - dev paths: - 'Dockerfiles/radiomics/**' + - .github/workflows/radiomics.yml jobs: build-and-push: @@ -37,6 +38,6 @@ jobs: context: . file: ./Dockerfiles/radiomics/Dockerfile push: true - tags: imagingdatacommons/radiomics + tags: imagingdatacommons/radiomics:dev build-args: | GIT_HASH=$COMMIT_HASH \ No newline at end of file From 9ba4c9c33fc859a0ca66231f325775d8b0a96a95 Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Fri, 22 Sep 2023 06:28:24 -0400 Subject: [PATCH 05/40] added totalseg suffix to download_convert_inference file name for consistency --- .../workflows/download_convert_inference.yml | 45 ------------------- 1 file changed, 45 deletions(-) delete mode 100644 .github/workflows/download_convert_inference.yml diff --git a/.github/workflows/download_convert_inference.yml b/.github/workflows/download_convert_inference.yml deleted file mode 100644 index dc0ed67..0000000 --- a/.github/workflows/download_convert_inference.yml +++ /dev/null @@ -1,45 +0,0 @@ -name: download_convert_inference_totalseg - -on: - push: - branches: - - dev - paths: - - 'Dockerfiles/download_convert_inference_totalseg/**' - - .github/workflows/download_convert_inference_totalseg.yml - -jobs: - build-and-push: - runs-on: ubuntu-latest - steps: - - name: Checkout code - uses: actions/checkout@v4 - - - name: Set up Git - run: | - git config --global user.email "actions@github.com" - git config --global user.name "GitHub Actions" - - - name: Get Git Commit Hash - id: git-commit-hash - run: echo "::set-output name=commit_hash::$(git rev-parse HEAD)" - - - name: Copy additional files to build context - run: | - cp Dockerfiles/download_convert_inference_totalseg/weights_download.sh . - - - name: Login to Docker Hub - uses: docker/login-action@v3 - with: - username: ${{ secrets.DOCKER_USERNAME }} - password: ${{ secrets.DOCKER_PASSWORD }} - - - name: Build and push Docker image - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/download_convert_inference_totalseg/Dockerfile - push: true - tags: imagingdatacommons/download_convert_inference_totalseg:dev - build-args: | - GIT_HASH=$COMMIT_HASH From 67e634c82607edb93301300a04e56be4af82cbfa Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Fri, 22 Sep 2023 06:36:34 -0400 Subject: [PATCH 06/40] add download_convert_inference_totalseg.yml --- .../download_convert_inference_totalseg.yml | 45 +++++++++++++++++++ 1 file changed, 45 insertions(+) create mode 100644 .github/workflows/download_convert_inference_totalseg.yml diff --git a/.github/workflows/download_convert_inference_totalseg.yml b/.github/workflows/download_convert_inference_totalseg.yml new file mode 100644 index 0000000..b129c15 --- /dev/null +++ b/.github/workflows/download_convert_inference_totalseg.yml @@ -0,0 +1,45 @@ +name: download_convert_inference_totalseg + +on: + push: + branches: + - dev + paths: + - 'Dockerfiles/download_convert_inference_totalseg/**' + - .github/workflows/download_convert_inference_totalseg.yml + +jobs: + build-and-push: + runs-on: ubuntu-latest + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Git + run: | + git config --global user.email "actions@github.com" + git config --global user.name "GitHub Actions" + + - name: Get Git Commit Hash + id: git-commit-hash + run: echo "::set-output name=commit_hash::$(git rev-parse HEAD)" + + - name: Copy additional files to build context + run: | + cp Dockerfiles/download_convert_inference_totalseg/weights_download.sh . + + - name: Login to Docker Hub + uses: docker/login-action@v3 + with: + username: ${{ secrets.DOCKER_USERNAME }} + password: ${{ secrets.DOCKER_PASSWORD }} + + - name: Build and push Docker image + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/download_convert_inference_totalseg/Dockerfile + push: true + tags: imagingdatacommons/download_convert_inference_totalseg:dev + build-args: | + GIT_HASH=$COMMIT_HASH From 861b06c9517907bdc88d4ac523638cd6413819fe Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Fri, 22 Sep 2023 06:51:02 -0400 Subject: [PATCH 07/40] troublesshooting GIT_HASH --- .github/workflows/download_convert.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/.github/workflows/download_convert.yml b/.github/workflows/download_convert.yml index 2a49aba..bde4f41 100644 --- a/.github/workflows/download_convert.yml +++ b/.github/workflows/download_convert.yml @@ -24,6 +24,7 @@ jobs: id: git-commit-hash run: | COMMIT_HASH=$(git rev-parse HEAD) + echo $COMMIT_HASH echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - name: Login to Docker Hub From 25630ddc6f1e7eea366f540f2a6802e5248fad20 Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Fri, 22 Sep 2023 06:56:56 -0400 Subject: [PATCH 08/40] corrected GIT_HASH variable --- .github/workflows/download_convert.yml | 2 +- .github/workflows/download_convert_inference_totalseg.yml | 2 +- .../workflows/download_convert_inference_totalseg_radiomics.yml | 2 +- .github/workflows/inference_totalseg.yml | 2 +- .github/workflows/per_frame_functional_group_sequence.yml | 2 +- .github/workflows/radiomics.yml | 2 +- 6 files changed, 6 insertions(+), 6 deletions(-) diff --git a/.github/workflows/download_convert.yml b/.github/workflows/download_convert.yml index bde4f41..92901e8 100644 --- a/.github/workflows/download_convert.yml +++ b/.github/workflows/download_convert.yml @@ -41,4 +41,4 @@ jobs: push: true tags: imagingdatacommons/download_convert:dev build-args: | - GIT_HASH=$COMMIT_HASH + GIT_HASH=${COMMIT_HASH} diff --git a/.github/workflows/download_convert_inference_totalseg.yml b/.github/workflows/download_convert_inference_totalseg.yml index b129c15..0907e4e 100644 --- a/.github/workflows/download_convert_inference_totalseg.yml +++ b/.github/workflows/download_convert_inference_totalseg.yml @@ -42,4 +42,4 @@ jobs: push: true tags: imagingdatacommons/download_convert_inference_totalseg:dev build-args: | - GIT_HASH=$COMMIT_HASH + GIT_HASH=${COMMIT_HASH} diff --git a/.github/workflows/download_convert_inference_totalseg_radiomics.yml b/.github/workflows/download_convert_inference_totalseg_radiomics.yml index d235f71..e544850 100644 --- a/.github/workflows/download_convert_inference_totalseg_radiomics.yml +++ b/.github/workflows/download_convert_inference_totalseg_radiomics.yml @@ -44,4 +44,4 @@ jobs: push: true tags: imagingdatacommons/download_convert_inference_totalseg_radiomics:dev build-args: | - GIT_HASH=$COMMIT_HASH + GIT_HASH=${COMMIT_HASH} diff --git a/.github/workflows/inference_totalseg.yml b/.github/workflows/inference_totalseg.yml index 8f5494c..e1d1d72 100644 --- a/.github/workflows/inference_totalseg.yml +++ b/.github/workflows/inference_totalseg.yml @@ -44,4 +44,4 @@ jobs: push: true tags: imagingdatacommons/inference_totalseg:dev build-args: | - GIT_HASH=$COMMIT_HASH \ No newline at end of file + GIT_HASH=${COMMIT_HASH} \ No newline at end of file diff --git a/.github/workflows/per_frame_functional_group_sequence.yml b/.github/workflows/per_frame_functional_group_sequence.yml index 14e0487..e8073fc 100644 --- a/.github/workflows/per_frame_functional_group_sequence.yml +++ b/.github/workflows/per_frame_functional_group_sequence.yml @@ -40,4 +40,4 @@ jobs: push: true tags: imagingdatacommons/per_frame_functional_group_sequence:dev build-args: | - GIT_HASH=$COMMIT_HASH \ No newline at end of file + GIT_HASH=${COMMIT_HASH} \ No newline at end of file diff --git a/.github/workflows/radiomics.yml b/.github/workflows/radiomics.yml index 820f658..803d7c1 100644 --- a/.github/workflows/radiomics.yml +++ b/.github/workflows/radiomics.yml @@ -40,4 +40,4 @@ jobs: push: true tags: imagingdatacommons/radiomics:dev build-args: | - GIT_HASH=$COMMIT_HASH \ No newline at end of file + GIT_HASH=${COMMIT_HASH} \ No newline at end of file From e406c78bbb7b824b97229f21937c6752cf636a2f Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Fri, 22 Sep 2023 07:15:13 -0400 Subject: [PATCH 09/40] corrected GIT_HASH variable --- .github/workflows/download_convert.yml | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.github/workflows/download_convert.yml b/.github/workflows/download_convert.yml index 92901e8..97cebff 100644 --- a/.github/workflows/download_convert.yml +++ b/.github/workflows/download_convert.yml @@ -42,3 +42,5 @@ jobs: tags: imagingdatacommons/download_convert:dev build-args: | GIT_HASH=${COMMIT_HASH} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} From aa667672cd571602993e3ddf99081304ca62badd Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Fri, 22 Sep 2023 07:27:39 -0400 Subject: [PATCH 10/40] corrected GIT_HASH variable --- .github/workflows/download_convert.yml | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/.github/workflows/download_convert.yml b/.github/workflows/download_convert.yml index 97cebff..0b5a9cd 100644 --- a/.github/workflows/download_convert.yml +++ b/.github/workflows/download_convert.yml @@ -1,4 +1,4 @@ -name: download_convert +name: download_convert on: push: @@ -41,6 +41,6 @@ jobs: push: true tags: imagingdatacommons/download_convert:dev build-args: | - GIT_HASH=${COMMIT_HASH} + GIT_HASH=${{ env.COMMIT_HASH }} env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} + COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file From ac279e2f7aa50027c830da51ed1feb355a6d2530 Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Fri, 22 Sep 2023 07:32:38 -0400 Subject: [PATCH 11/40] fixed referencing GIT HASH variable --- .github/workflows/download_convert_inference_totalseg.yml | 4 +++- .../download_convert_inference_totalseg_radiomics.yml | 4 +++- .github/workflows/inference_totalseg.yml | 4 +++- .github/workflows/per_frame_functional_group_sequence.yml | 4 +++- .github/workflows/radiomics.yml | 4 +++- 5 files changed, 15 insertions(+), 5 deletions(-) diff --git a/.github/workflows/download_convert_inference_totalseg.yml b/.github/workflows/download_convert_inference_totalseg.yml index 0907e4e..c08579e 100644 --- a/.github/workflows/download_convert_inference_totalseg.yml +++ b/.github/workflows/download_convert_inference_totalseg.yml @@ -42,4 +42,6 @@ jobs: push: true tags: imagingdatacommons/download_convert_inference_totalseg:dev build-args: | - GIT_HASH=${COMMIT_HASH} + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} diff --git a/.github/workflows/download_convert_inference_totalseg_radiomics.yml b/.github/workflows/download_convert_inference_totalseg_radiomics.yml index e544850..681cdb7 100644 --- a/.github/workflows/download_convert_inference_totalseg_radiomics.yml +++ b/.github/workflows/download_convert_inference_totalseg_radiomics.yml @@ -44,4 +44,6 @@ jobs: push: true tags: imagingdatacommons/download_convert_inference_totalseg_radiomics:dev build-args: | - GIT_HASH=${COMMIT_HASH} + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} diff --git a/.github/workflows/inference_totalseg.yml b/.github/workflows/inference_totalseg.yml index e1d1d72..37dd3ee 100644 --- a/.github/workflows/inference_totalseg.yml +++ b/.github/workflows/inference_totalseg.yml @@ -44,4 +44,6 @@ jobs: push: true tags: imagingdatacommons/inference_totalseg:dev build-args: | - GIT_HASH=${COMMIT_HASH} \ No newline at end of file + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file diff --git a/.github/workflows/per_frame_functional_group_sequence.yml b/.github/workflows/per_frame_functional_group_sequence.yml index e8073fc..d339d0e 100644 --- a/.github/workflows/per_frame_functional_group_sequence.yml +++ b/.github/workflows/per_frame_functional_group_sequence.yml @@ -40,4 +40,6 @@ jobs: push: true tags: imagingdatacommons/per_frame_functional_group_sequence:dev build-args: | - GIT_HASH=${COMMIT_HASH} \ No newline at end of file + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file diff --git a/.github/workflows/radiomics.yml b/.github/workflows/radiomics.yml index 803d7c1..7f509d5 100644 --- a/.github/workflows/radiomics.yml +++ b/.github/workflows/radiomics.yml @@ -40,4 +40,6 @@ jobs: push: true tags: imagingdatacommons/radiomics:dev build-args: | - GIT_HASH=${COMMIT_HASH} \ No newline at end of file + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file From b5c55c851d062c0944f2cb31173e3584b55f8101 Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Fri, 22 Sep 2023 07:46:32 -0400 Subject: [PATCH 12/40] fixed referencing GIT HASH variable --- .github/workflows/download_convert_inference_totalseg.yml | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/.github/workflows/download_convert_inference_totalseg.yml b/.github/workflows/download_convert_inference_totalseg.yml index c08579e..f2b2954 100644 --- a/.github/workflows/download_convert_inference_totalseg.yml +++ b/.github/workflows/download_convert_inference_totalseg.yml @@ -22,7 +22,9 @@ jobs: - name: Get Git Commit Hash id: git-commit-hash - run: echo "::set-output name=commit_hash::$(git rev-parse HEAD)" + run: | + COMMIT_HASH=$(git rev-parse HEAD) + echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - name: Copy additional files to build context run: | From c93e3b97ab5dbbe1a9140b417ecdb7c446a3f7b6 Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Fri, 22 Sep 2023 07:50:11 -0400 Subject: [PATCH 13/40] corrected path of dockerfile ref while building image --- Dockerfiles/radiomics/Dockerfile | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Dockerfiles/radiomics/Dockerfile b/Dockerfiles/radiomics/Dockerfile index cd841ee..1d20b63 100644 --- a/Dockerfiles/radiomics/Dockerfile +++ b/Dockerfiles/radiomics/Dockerfile @@ -5,7 +5,7 @@ ARG GIT_HASH LABEL PYTHON_BASE_DOCKER_IMAGE="python:3.11.2-slim-buster"\ MAINTAINER="IDC " \ GIT_HASH=${GIT_HASH}\ - PATH_TO_DOCKER_FILE="https://github.com/imagingdatacommons/Cloud-Resources-Workflows/blob/${GIT_HASH}/Dockerfiles/TotalSegmentator/splitWorkflow/task3/Dockerfile"\ + PATH_TO_DOCKER_FILE="https://github.com/imagingdatacommons/Cloud-Resources-Workflows/blob/${GIT_HASH}/Dockerfiles/radiomics/Dockerfile"\ IMAGE_NAME_ON_DOCKERHUB="imagingdatacommons/radiomics" # Install some basic system utilities From 359090d0f79746170cffb737a280559cf69f02c8 Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Fri, 22 Sep 2023 09:56:29 -0400 Subject: [PATCH 14/40] correct expected docker image in the label --- Dockerfiles/per_frame_functional_group_sequence/Dockerfile | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Dockerfiles/per_frame_functional_group_sequence/Dockerfile b/Dockerfiles/per_frame_functional_group_sequence/Dockerfile index 2d7a0bf..63b7475 100644 --- a/Dockerfiles/per_frame_functional_group_sequence/Dockerfile +++ b/Dockerfiles/per_frame_functional_group_sequence/Dockerfile @@ -6,7 +6,7 @@ LABEL BASE_DOCKER_IMAGE="python:3.11.2-slim-buster"\ MAINTAINER="IDC " \ GIT_HASH=${GIT_HASH}\ PATH_TO_DOCKER_FILE="https://github.com/imagingdatacommons/Cloud-Resources-Workflows/blob/${GIT_HASH}/Dockerfiles/per_frame_functional_group_sequence/Dockerfile"\ - IMAGE_NAME_ON_DOCKERHUB="imagingdatacommons/inference_totalseg" + IMAGE_NAME_ON_DOCKERHUB="imagingdatacommons/per_frame_functional_group_sequence" RUN apt-get update && \ apt-get install -y --no-install-recommends \ From ba133199ba1df62747ca202d363f4adc1b55421e Mon Sep 17 00:00:00 2001 From: Vamsi Thiriveedhi <115020590+vkt1414@users.noreply.github.com> Date: Fri, 22 Sep 2023 10:18:52 -0400 Subject: [PATCH 15/40] Update README.md --- Dockerfiles/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Dockerfiles/README.md b/Dockerfiles/README.md index 94e3985..da4399d 100644 --- a/Dockerfiles/README.md +++ b/Dockerfiles/README.md @@ -1,6 +1,6 @@ # An example docker command to run an image: -##### `docker run --entrypoint="/bin/bash" -d --rm -it --name=nocudav1 vamsithiriveedhi/totalsegmentator:nocuda_v1` +##### `docker run --entrypoint="/bin/bash" -d --rm -it --name=get_idc_data imagingdatacommons/download_convert` What's happening with the arguments chosen? - `entry-point`: will switch from the default entry point to bash From 585b676039976cb4e7ac5e5ff587dea9a4718a58 Mon Sep 17 00:00:00 2001 From: Vamsi Thiriveedhi <115020590+vkt1414@users.noreply.github.com> Date: Fri, 22 Sep 2023 10:24:57 -0400 Subject: [PATCH 16/40] Create ReadMe.MD --- .github/workflows/ReadMe.MD | 4 ++++ 1 file changed, 4 insertions(+) create mode 100644 .github/workflows/ReadMe.MD diff --git a/.github/workflows/ReadMe.MD b/.github/workflows/ReadMe.MD new file mode 100644 index 0000000..7d14623 --- /dev/null +++ b/.github/workflows/ReadMe.MD @@ -0,0 +1,4 @@ +#####These files are used by GitHub actions to dynamically build docker images whenever a dockerfile or files an image depends, or these files themselves are updated: + + + From 3844e25916fa6806bc7d7bfbc462f4021fe31f73 Mon Sep 17 00:00:00 2001 From: Vamsi Thiriveedhi <115020590+vkt1414@users.noreply.github.com> Date: Fri, 22 Sep 2023 10:25:42 -0400 Subject: [PATCH 17/40] Update ReadMe.MD --- .github/workflows/ReadMe.MD | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/ReadMe.MD b/.github/workflows/ReadMe.MD index 7d14623..30f44ec 100644 --- a/.github/workflows/ReadMe.MD +++ b/.github/workflows/ReadMe.MD @@ -1,4 +1,4 @@ -#####These files are used by GitHub actions to dynamically build docker images whenever a dockerfile or files an image depends, or these files themselves are updated: +#These files are used by GitHub actions to dynamically build docker images whenever a dockerfile or files an image depends, or these files themselves are updated From 3554d899f8cc4294ca1a63d07de732a48f52b170 Mon Sep 17 00:00:00 2001 From: Vamsi Thiriveedhi <115020590+vkt1414@users.noreply.github.com> Date: Fri, 22 Sep 2023 10:26:09 -0400 Subject: [PATCH 18/40] Update ReadMe.MD --- .github/workflows/ReadMe.MD | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/ReadMe.MD b/.github/workflows/ReadMe.MD index 30f44ec..af913b2 100644 --- a/.github/workflows/ReadMe.MD +++ b/.github/workflows/ReadMe.MD @@ -1,4 +1,4 @@ -#These files are used by GitHub actions to dynamically build docker images whenever a dockerfile or files an image depends, or these files themselves are updated +These files are used by GitHub actions to dynamically build docker images whenever a dockerfile or files an image depends, or these files themselves are updated From efc123369d12e3c1fabf5bcd1d647633f4d9f858 Mon Sep 17 00:00:00 2001 From: Vamsi Thiriveedhi <115020590+vkt1414@users.noreply.github.com> Date: Fri, 22 Sep 2023 10:38:51 -0400 Subject: [PATCH 19/40] Update and rename ReadMe.MD to README.md --- .github/workflows/README.md | 4 ++++ .github/workflows/ReadMe.MD | 4 ---- 2 files changed, 4 insertions(+), 4 deletions(-) create mode 100644 .github/workflows/README.md delete mode 100644 .github/workflows/ReadMe.MD diff --git a/.github/workflows/README.md b/.github/workflows/README.md new file mode 100644 index 0000000..764ea8f --- /dev/null +++ b/.github/workflows/README.md @@ -0,0 +1,4 @@ +

These files are used by GitHub actions to dynamically build docker images whenever a dockerfile or files an image depends, or these files themselves are updated

+ + + diff --git a/.github/workflows/ReadMe.MD b/.github/workflows/ReadMe.MD deleted file mode 100644 index af913b2..0000000 --- a/.github/workflows/ReadMe.MD +++ /dev/null @@ -1,4 +0,0 @@ -These files are used by GitHub actions to dynamically build docker images whenever a dockerfile or files an image depends, or these files themselves are updated - - - From 492cc70a4817c0b9f55862487351b2690e4acb14 Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Fri, 22 Sep 2023 10:45:33 -0400 Subject: [PATCH 20/40] created actions files for dev and main branches --- .github/workflows/download_convert-dev.yml | 46 +++++++++++++++++ .github/workflows/download_convert.yml | 4 +- ...ownload_convert_inference_totalseg-dev.yml | 49 +++++++++++++++++++ .../download_convert_inference_totalseg.yml | 4 +- ...nvert_inference_totalseg_radiomics-dev.yml | 49 +++++++++++++++++++ ...d_convert_inference_totalseg_radiomics.yml | 4 +- .github/workflows/inference_totalseg-dev.yml | 49 +++++++++++++++++++ .github/workflows/inference_totalseg.yml | 4 +- ...er_frame_functional_group_sequence-dev.yml | 45 +++++++++++++++++ .../per_frame_functional_group_sequence.yml | 4 +- .github/workflows/radiomics-dev.yml | 45 +++++++++++++++++ .github/workflows/radiomics.yml | 4 +- 12 files changed, 295 insertions(+), 12 deletions(-) create mode 100644 .github/workflows/download_convert-dev.yml create mode 100644 .github/workflows/download_convert_inference_totalseg-dev.yml create mode 100644 .github/workflows/download_convert_inference_totalseg_radiomics-dev.yml create mode 100644 .github/workflows/inference_totalseg-dev.yml create mode 100644 .github/workflows/per_frame_functional_group_sequence-dev.yml create mode 100644 .github/workflows/radiomics-dev.yml diff --git a/.github/workflows/download_convert-dev.yml b/.github/workflows/download_convert-dev.yml new file mode 100644 index 0000000..0b5a9cd --- /dev/null +++ b/.github/workflows/download_convert-dev.yml @@ -0,0 +1,46 @@ +name: download_convert + +on: + push: + branches: + - dev + paths: + - 'Dockerfiles/download_convert/**' + - .github/workflows/download_convert.yml + +jobs: + build-and-push: + runs-on: ubuntu-latest + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Git + run: | + git config --global user.email "actions@github.com" + git config --global user.name "GitHub Actions" + + - name: Get Git Commit Hash + id: git-commit-hash + run: | + COMMIT_HASH=$(git rev-parse HEAD) + echo $COMMIT_HASH + echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV + + - name: Login to Docker Hub + uses: docker/login-action@v3 + with: + username: ${{ secrets.DOCKER_USERNAME }} + password: ${{ secrets.DOCKER_PASSWORD }} + + - name: Build and push Docker image + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/download_convert/Dockerfile + push: true + tags: imagingdatacommons/download_convert:dev + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file diff --git a/.github/workflows/download_convert.yml b/.github/workflows/download_convert.yml index 0b5a9cd..5d1b33e 100644 --- a/.github/workflows/download_convert.yml +++ b/.github/workflows/download_convert.yml @@ -3,7 +3,7 @@ name: download_convert on: push: branches: - - dev + - main paths: - 'Dockerfiles/download_convert/**' - .github/workflows/download_convert.yml @@ -39,7 +39,7 @@ jobs: context: . file: ./Dockerfiles/download_convert/Dockerfile push: true - tags: imagingdatacommons/download_convert:dev + tags: imagingdatacommons/download_convert build-args: | GIT_HASH=${{ env.COMMIT_HASH }} env: diff --git a/.github/workflows/download_convert_inference_totalseg-dev.yml b/.github/workflows/download_convert_inference_totalseg-dev.yml new file mode 100644 index 0000000..f2b2954 --- /dev/null +++ b/.github/workflows/download_convert_inference_totalseg-dev.yml @@ -0,0 +1,49 @@ +name: download_convert_inference_totalseg + +on: + push: + branches: + - dev + paths: + - 'Dockerfiles/download_convert_inference_totalseg/**' + - .github/workflows/download_convert_inference_totalseg.yml + +jobs: + build-and-push: + runs-on: ubuntu-latest + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Git + run: | + git config --global user.email "actions@github.com" + git config --global user.name "GitHub Actions" + + - name: Get Git Commit Hash + id: git-commit-hash + run: | + COMMIT_HASH=$(git rev-parse HEAD) + echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV + + - name: Copy additional files to build context + run: | + cp Dockerfiles/download_convert_inference_totalseg/weights_download.sh . + + - name: Login to Docker Hub + uses: docker/login-action@v3 + with: + username: ${{ secrets.DOCKER_USERNAME }} + password: ${{ secrets.DOCKER_PASSWORD }} + + - name: Build and push Docker image + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/download_convert_inference_totalseg/Dockerfile + push: true + tags: imagingdatacommons/download_convert_inference_totalseg:dev + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} diff --git a/.github/workflows/download_convert_inference_totalseg.yml b/.github/workflows/download_convert_inference_totalseg.yml index f2b2954..31af54b 100644 --- a/.github/workflows/download_convert_inference_totalseg.yml +++ b/.github/workflows/download_convert_inference_totalseg.yml @@ -3,7 +3,7 @@ name: download_convert_inference_totalseg on: push: branches: - - dev + - main paths: - 'Dockerfiles/download_convert_inference_totalseg/**' - .github/workflows/download_convert_inference_totalseg.yml @@ -42,7 +42,7 @@ jobs: context: . file: ./Dockerfiles/download_convert_inference_totalseg/Dockerfile push: true - tags: imagingdatacommons/download_convert_inference_totalseg:dev + tags: imagingdatacommons/download_convert_inference_totalseg build-args: | GIT_HASH=${{ env.COMMIT_HASH }} env: diff --git a/.github/workflows/download_convert_inference_totalseg_radiomics-dev.yml b/.github/workflows/download_convert_inference_totalseg_radiomics-dev.yml new file mode 100644 index 0000000..681cdb7 --- /dev/null +++ b/.github/workflows/download_convert_inference_totalseg_radiomics-dev.yml @@ -0,0 +1,49 @@ +name: download_convert_inference_totalseg_radiomics + +on: + push: + branches: + - dev + paths: + - 'Dockerfiles/download_convert_inference_totalseg_radiomics/**' + - .github/workflows/download_convert_inference_totalseg_radiomics.yml + +jobs: + build-and-push: + runs-on: ubuntu-latest + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Git + run: | + git config --global user.email "actions@github.com" + git config --global user.name "GitHub Actions" + + - name: Get Git Commit Hash + id: git-commit-hash + run: | + COMMIT_HASH=$(git rev-parse HEAD) + echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV + + - name: Copy additional files to build context + run: | + cp Dockerfiles/download_convert_inference_totalseg_radiomics/weights_download.sh . + + - name: Login to Docker Hub + uses: docker/login-action@v3 + with: + username: ${{ secrets.DOCKER_USERNAME }} + password: ${{ secrets.DOCKER_PASSWORD }} + + - name: Build and push Docker image + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile + push: true + tags: imagingdatacommons/download_convert_inference_totalseg_radiomics:dev + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} diff --git a/.github/workflows/download_convert_inference_totalseg_radiomics.yml b/.github/workflows/download_convert_inference_totalseg_radiomics.yml index 681cdb7..5a59193 100644 --- a/.github/workflows/download_convert_inference_totalseg_radiomics.yml +++ b/.github/workflows/download_convert_inference_totalseg_radiomics.yml @@ -3,7 +3,7 @@ name: download_convert_inference_totalseg_radiomics on: push: branches: - - dev + - main paths: - 'Dockerfiles/download_convert_inference_totalseg_radiomics/**' - .github/workflows/download_convert_inference_totalseg_radiomics.yml @@ -42,7 +42,7 @@ jobs: context: . file: ./Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile push: true - tags: imagingdatacommons/download_convert_inference_totalseg_radiomics:dev + tags: imagingdatacommons/download_convert_inference_totalseg_radiomics build-args: | GIT_HASH=${{ env.COMMIT_HASH }} env: diff --git a/.github/workflows/inference_totalseg-dev.yml b/.github/workflows/inference_totalseg-dev.yml new file mode 100644 index 0000000..37dd3ee --- /dev/null +++ b/.github/workflows/inference_totalseg-dev.yml @@ -0,0 +1,49 @@ +name: inference_totalseg + +on: + push: + branches: + - dev + paths: + - 'Dockerfiles/inference_totalseg/**' + - .github/workflows/inference_totalseg.yml + +jobs: + build-and-push: + runs-on: ubuntu-latest + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Git + run: | + git config --global user.email "actions@github.com" + git config --global user.name "GitHub Actions" + + - name: Get Git Commit Hash + id: git-commit-hash + run: | + COMMIT_HASH=$(git rev-parse HEAD) + echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV + + - name: Copy additional files to build context + run: | + cp Dockerfiles/inference_totalseg/weights_download.sh . + + - name: Login to Docker Hub + uses: docker/login-action@v3 + with: + username: ${{ secrets.DOCKER_USERNAME }} + password: ${{ secrets.DOCKER_PASSWORD }} + + - name: Build and push Docker image + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/inference_totalseg/Dockerfile + push: true + tags: imagingdatacommons/inference_totalseg:dev + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file diff --git a/.github/workflows/inference_totalseg.yml b/.github/workflows/inference_totalseg.yml index 37dd3ee..51182f1 100644 --- a/.github/workflows/inference_totalseg.yml +++ b/.github/workflows/inference_totalseg.yml @@ -3,7 +3,7 @@ name: inference_totalseg on: push: branches: - - dev + - main paths: - 'Dockerfiles/inference_totalseg/**' - .github/workflows/inference_totalseg.yml @@ -42,7 +42,7 @@ jobs: context: . file: ./Dockerfiles/inference_totalseg/Dockerfile push: true - tags: imagingdatacommons/inference_totalseg:dev + tags: imagingdatacommons/inference_totalseg build-args: | GIT_HASH=${{ env.COMMIT_HASH }} env: diff --git a/.github/workflows/per_frame_functional_group_sequence-dev.yml b/.github/workflows/per_frame_functional_group_sequence-dev.yml new file mode 100644 index 0000000..d339d0e --- /dev/null +++ b/.github/workflows/per_frame_functional_group_sequence-dev.yml @@ -0,0 +1,45 @@ +name: per_frame_functional_group_sequence + +on: + push: + branches: + - dev + paths: + - 'Dockerfiles/per_frame_functional_group_sequence/**' + - .github/workflows/per_frame_functional_group_sequence.yml + +jobs: + build-and-push: + runs-on: ubuntu-latest + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Git + run: | + git config --global user.email "actions@github.com" + git config --global user.name "GitHub Actions" + + - name: Get Git Commit Hash + id: git-commit-hash + run: | + COMMIT_HASH=$(git rev-parse HEAD) + echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV + + - name: Login to Docker Hub + uses: docker/login-action@v3 + with: + username: ${{ secrets.DOCKER_USERNAME }} + password: ${{ secrets.DOCKER_PASSWORD }} + + - name: Build and push Docker image + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/per_frame_functional_group_sequence/Dockerfile + push: true + tags: imagingdatacommons/per_frame_functional_group_sequence:dev + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file diff --git a/.github/workflows/per_frame_functional_group_sequence.yml b/.github/workflows/per_frame_functional_group_sequence.yml index d339d0e..86ec423 100644 --- a/.github/workflows/per_frame_functional_group_sequence.yml +++ b/.github/workflows/per_frame_functional_group_sequence.yml @@ -3,7 +3,7 @@ name: per_frame_functional_group_sequence on: push: branches: - - dev + - main paths: - 'Dockerfiles/per_frame_functional_group_sequence/**' - .github/workflows/per_frame_functional_group_sequence.yml @@ -38,7 +38,7 @@ jobs: context: . file: ./Dockerfiles/per_frame_functional_group_sequence/Dockerfile push: true - tags: imagingdatacommons/per_frame_functional_group_sequence:dev + tags: imagingdatacommons/per_frame_functional_group_sequence build-args: | GIT_HASH=${{ env.COMMIT_HASH }} env: diff --git a/.github/workflows/radiomics-dev.yml b/.github/workflows/radiomics-dev.yml new file mode 100644 index 0000000..7f509d5 --- /dev/null +++ b/.github/workflows/radiomics-dev.yml @@ -0,0 +1,45 @@ +name: radiomics + +on: + push: + branches: + - dev + paths: + - 'Dockerfiles/radiomics/**' + - .github/workflows/radiomics.yml + +jobs: + build-and-push: + runs-on: ubuntu-latest + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Git + run: | + git config --global user.email "actions@github.com" + git config --global user.name "GitHub Actions" + + - name: Get Git Commit Hash + id: git-commit-hash + run: | + COMMIT_HASH=$(git rev-parse HEAD) + echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV + + - name: Login to Docker Hub + uses: docker/login-action@v3 + with: + username: ${{ secrets.DOCKER_USERNAME }} + password: ${{ secrets.DOCKER_PASSWORD }} + + - name: Build and push Docker image + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/radiomics/Dockerfile + push: true + tags: imagingdatacommons/radiomics:dev + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file diff --git a/.github/workflows/radiomics.yml b/.github/workflows/radiomics.yml index 7f509d5..e3068a8 100644 --- a/.github/workflows/radiomics.yml +++ b/.github/workflows/radiomics.yml @@ -3,7 +3,7 @@ name: radiomics on: push: branches: - - dev + - main paths: - 'Dockerfiles/radiomics/**' - .github/workflows/radiomics.yml @@ -38,7 +38,7 @@ jobs: context: . file: ./Dockerfiles/radiomics/Dockerfile push: true - tags: imagingdatacommons/radiomics:dev + tags: imagingdatacommons/radiomics build-args: | GIT_HASH=${{ env.COMMIT_HASH }} env: From 47dea00633af204de5612afed9feff916e7bab21 Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Fri, 22 Sep 2023 10:49:41 -0400 Subject: [PATCH 21/40] rectify trigger files for dev branches --- .github/workflows/download_convert-dev.yml | 2 +- .github/workflows/download_convert_inference_totalseg-dev.yml | 2 +- .../download_convert_inference_totalseg_radiomics-dev.yml | 2 +- .github/workflows/inference_totalseg-dev.yml | 2 +- .github/workflows/per_frame_functional_group_sequence-dev.yml | 2 +- .github/workflows/radiomics-dev.yml | 2 +- 6 files changed, 6 insertions(+), 6 deletions(-) diff --git a/.github/workflows/download_convert-dev.yml b/.github/workflows/download_convert-dev.yml index 0b5a9cd..6866808 100644 --- a/.github/workflows/download_convert-dev.yml +++ b/.github/workflows/download_convert-dev.yml @@ -6,7 +6,7 @@ on: - dev paths: - 'Dockerfiles/download_convert/**' - - .github/workflows/download_convert.yml + - .github/workflows/download_convert-dev.yml jobs: build-and-push: diff --git a/.github/workflows/download_convert_inference_totalseg-dev.yml b/.github/workflows/download_convert_inference_totalseg-dev.yml index f2b2954..605a78b 100644 --- a/.github/workflows/download_convert_inference_totalseg-dev.yml +++ b/.github/workflows/download_convert_inference_totalseg-dev.yml @@ -6,7 +6,7 @@ on: - dev paths: - 'Dockerfiles/download_convert_inference_totalseg/**' - - .github/workflows/download_convert_inference_totalseg.yml + - .github/workflows/download_convert_inference_totalseg-dev.yml jobs: build-and-push: diff --git a/.github/workflows/download_convert_inference_totalseg_radiomics-dev.yml b/.github/workflows/download_convert_inference_totalseg_radiomics-dev.yml index 681cdb7..f74181b 100644 --- a/.github/workflows/download_convert_inference_totalseg_radiomics-dev.yml +++ b/.github/workflows/download_convert_inference_totalseg_radiomics-dev.yml @@ -6,7 +6,7 @@ on: - dev paths: - 'Dockerfiles/download_convert_inference_totalseg_radiomics/**' - - .github/workflows/download_convert_inference_totalseg_radiomics.yml + - .github/workflows/download_convert_inference_totalseg_radiomics-dev.yml jobs: build-and-push: diff --git a/.github/workflows/inference_totalseg-dev.yml b/.github/workflows/inference_totalseg-dev.yml index 37dd3ee..3de879a 100644 --- a/.github/workflows/inference_totalseg-dev.yml +++ b/.github/workflows/inference_totalseg-dev.yml @@ -6,7 +6,7 @@ on: - dev paths: - 'Dockerfiles/inference_totalseg/**' - - .github/workflows/inference_totalseg.yml + - .github/workflows/inference_totalseg-dev.yml jobs: build-and-push: diff --git a/.github/workflows/per_frame_functional_group_sequence-dev.yml b/.github/workflows/per_frame_functional_group_sequence-dev.yml index d339d0e..8b4949f 100644 --- a/.github/workflows/per_frame_functional_group_sequence-dev.yml +++ b/.github/workflows/per_frame_functional_group_sequence-dev.yml @@ -6,7 +6,7 @@ on: - dev paths: - 'Dockerfiles/per_frame_functional_group_sequence/**' - - .github/workflows/per_frame_functional_group_sequence.yml + - .github/workflows/per_frame_functional_group_sequence-dev.yml jobs: build-and-push: diff --git a/.github/workflows/radiomics-dev.yml b/.github/workflows/radiomics-dev.yml index 7f509d5..8415894 100644 --- a/.github/workflows/radiomics-dev.yml +++ b/.github/workflows/radiomics-dev.yml @@ -6,7 +6,7 @@ on: - dev paths: - 'Dockerfiles/radiomics/**' - - .github/workflows/radiomics.yml + - .github/workflows/radiomics-dev.yml jobs: build-and-push: From b06eebf79253e7c15d3502cef94bf236e92c3691 Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Fri, 22 Sep 2023 10:52:43 -0400 Subject: [PATCH 22/40] rename actions names for dev to distinguish --- .github/workflows/download_convert-dev.yml | 2 +- .github/workflows/download_convert_inference_totalseg-dev.yml | 2 +- .../download_convert_inference_totalseg_radiomics-dev.yml | 2 +- .github/workflows/inference_totalseg-dev.yml | 2 +- .github/workflows/per_frame_functional_group_sequence-dev.yml | 2 +- .github/workflows/radiomics-dev.yml | 2 +- 6 files changed, 6 insertions(+), 6 deletions(-) diff --git a/.github/workflows/download_convert-dev.yml b/.github/workflows/download_convert-dev.yml index 6866808..df4c176 100644 --- a/.github/workflows/download_convert-dev.yml +++ b/.github/workflows/download_convert-dev.yml @@ -1,4 +1,4 @@ -name: download_convert +name: dev-download_convert on: push: diff --git a/.github/workflows/download_convert_inference_totalseg-dev.yml b/.github/workflows/download_convert_inference_totalseg-dev.yml index 605a78b..c0b1c28 100644 --- a/.github/workflows/download_convert_inference_totalseg-dev.yml +++ b/.github/workflows/download_convert_inference_totalseg-dev.yml @@ -1,4 +1,4 @@ -name: download_convert_inference_totalseg +name: dev-download_convert_inference_totalseg on: push: diff --git a/.github/workflows/download_convert_inference_totalseg_radiomics-dev.yml b/.github/workflows/download_convert_inference_totalseg_radiomics-dev.yml index f74181b..b028174 100644 --- a/.github/workflows/download_convert_inference_totalseg_radiomics-dev.yml +++ b/.github/workflows/download_convert_inference_totalseg_radiomics-dev.yml @@ -1,4 +1,4 @@ -name: download_convert_inference_totalseg_radiomics +name: dev-download_convert_inference_totalseg_radiomics on: push: diff --git a/.github/workflows/inference_totalseg-dev.yml b/.github/workflows/inference_totalseg-dev.yml index 3de879a..0f95b54 100644 --- a/.github/workflows/inference_totalseg-dev.yml +++ b/.github/workflows/inference_totalseg-dev.yml @@ -1,4 +1,4 @@ -name: inference_totalseg +name: dev-inference_totalseg on: push: diff --git a/.github/workflows/per_frame_functional_group_sequence-dev.yml b/.github/workflows/per_frame_functional_group_sequence-dev.yml index 8b4949f..468ef1d 100644 --- a/.github/workflows/per_frame_functional_group_sequence-dev.yml +++ b/.github/workflows/per_frame_functional_group_sequence-dev.yml @@ -1,4 +1,4 @@ -name: per_frame_functional_group_sequence +name: dev-per_frame_functional_group_sequence on: push: diff --git a/.github/workflows/radiomics-dev.yml b/.github/workflows/radiomics-dev.yml index 8415894..8656520 100644 --- a/.github/workflows/radiomics-dev.yml +++ b/.github/workflows/radiomics-dev.yml @@ -1,4 +1,4 @@ -name: radiomics +name: dev-radiomics on: push: From 9150654afe890cda0525f179f6ae51e97c5dea97 Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Fri, 22 Sep 2023 11:21:18 -0400 Subject: [PATCH 23/40] fix docker image references in wdl files --- Terra/TotalSegmentator/postProcessing/perFrame.wdl | 2 +- Terra/TotalSegmentator/splitWorkflow/oneVM.wdl | 2 +- Terra/TotalSegmentator/splitWorkflow/threeVM.wdl | 6 +++--- Terra/TotalSegmentator/splitWorkflow/twoVM.wdl | 4 ++-- 4 files changed, 7 insertions(+), 7 deletions(-) diff --git a/Terra/TotalSegmentator/postProcessing/perFrame.wdl b/Terra/TotalSegmentator/postProcessing/perFrame.wdl index 7d0a4a6..465c72a 100644 --- a/Terra/TotalSegmentator/postProcessing/perFrame.wdl +++ b/Terra/TotalSegmentator/postProcessing/perFrame.wdl @@ -8,7 +8,7 @@ workflow PerFrameFunctionalGroupsSequence { File jsonServiceAccountFile #Docker Images for each task - String docker_PerFrameFunctionalGroupsSequence = "imagingdatacommons/extract_perframe_functional_group_sequence" + String docker_PerFrameFunctionalGroupsSequence = "imagingdatacommons/per_frame_functional_group_sequence" #Preemptible retries Int preemptibleTries_PerFrameFunctionalGroupsSequence = 3 diff --git a/Terra/TotalSegmentator/splitWorkflow/oneVM.wdl b/Terra/TotalSegmentator/splitWorkflow/oneVM.wdl index 97bfa27..ae4f492 100644 --- a/Terra/TotalSegmentator/splitWorkflow/oneVM.wdl +++ b/Terra/TotalSegmentator/splitWorkflow/oneVM.wdl @@ -11,7 +11,7 @@ workflow TotalSegmentator { String dicomToNiftiConverterTool #Docker Images for each task - String totalSegmentatorDocker = "imagingdatacommons/totalsegmentator:end_to_end_v1" + String totalSegmentatorDocker = "imagingdatacommons/download_convert_inference_totalseg_radiomics" #Preemptible retries Int totalSegmentatorPreemptibleTries = 3 diff --git a/Terra/TotalSegmentator/splitWorkflow/threeVM.wdl b/Terra/TotalSegmentator/splitWorkflow/threeVM.wdl index 5a6f88d..74e0249 100644 --- a/Terra/TotalSegmentator/splitWorkflow/threeVM.wdl +++ b/Terra/TotalSegmentator/splitWorkflow/threeVM.wdl @@ -11,9 +11,9 @@ workflow TotalSegmentator { String dicomToNiftiConverterTool #Docker Images for each task - String downloadDicomAndConvertDocker = "imagingdatacommons/totalsegmentator:task1_v1" - String inferenceTotalSegmentatorDocker = "imagingdatacommons/totalsegmentator:task2_v3" - String dicomsegAndRadiomicsSR_Docker = "imagingdatacommons/totalsegmentator:task3_v3" + String downloadDicomAndConvertDocker = "imagingdatacommons/download_convert" + String inferenceTotalSegmentatorDocker = "imagingdatacommons/inference_totalseg" + String dicomsegAndRadiomicsSR_Docker = "imagingdatacommons/radiomics" #Preemptible retries Int downloadAndConvertPreemptibleTries = 3 diff --git a/Terra/TotalSegmentator/splitWorkflow/twoVM.wdl b/Terra/TotalSegmentator/splitWorkflow/twoVM.wdl index dc644d2..27a1fad 100644 --- a/Terra/TotalSegmentator/splitWorkflow/twoVM.wdl +++ b/Terra/TotalSegmentator/splitWorkflow/twoVM.wdl @@ -11,8 +11,8 @@ workflow TotalSegmentator { String dicomToNiftiConverterTool #Docker Images for each task - String downloadDicomAndConvertAndInferenceTotalSegmentatorDocker = "imagingdatacommons/totalsegmentator:task1and2_v4" - String dicomsegAndRadiomicsSR_Docker = "imagingdatacommons/totalsegmentator:task3_v4" + String downloadDicomAndConvertAndInferenceTotalSegmentatorDocker = "imagingdatacommons/download_convert_inference_totalseg" + String dicomsegAndRadiomicsSR_Docker = "imagingdatacommons/radiomics" #Preemptible retries From 807dbfb90d8ac7115d188cfe939ae99d87a6c195 Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Fri, 22 Sep 2023 11:33:05 -0400 Subject: [PATCH 24/40] fix docker image references in cwl files --- .../TotalSegmentator/splitWorkflow/oneVM.cwl | 20 +++-- .../splitWorkflow/threeVM.cwl | 82 +++++++++++-------- .../TotalSegmentator/splitWorkflow/twoVM.cwl | 62 ++++++++------ 3 files changed, 98 insertions(+), 66 deletions(-) diff --git a/SevenBridges/TotalSegmentator/splitWorkflow/oneVM.cwl b/SevenBridges/TotalSegmentator/splitWorkflow/oneVM.cwl index 407820c..e463b6f 100644 --- a/SevenBridges/TotalSegmentator/splitWorkflow/oneVM.cwl +++ b/SevenBridges/TotalSegmentator/splitWorkflow/oneVM.cwl @@ -5,7 +5,7 @@ cwlVersion: v1.2 sbg: https://sevenbridges.com baseCommand: - wget -- https://raw.githubusercontent.com/vkt1414/Cloud-Resources-Workflows/main/Notebooks/Totalsegmentator/endToEndTotalSegmentatorNotebook.ipynb +- https://raw.githubusercontent.com/ImagingDataCommons/Cloud-Resources-Workflows/main/Notebooks/Totalsegmentator/endToEndTotalSegmentatorNotebook.ipynb - "&&" - set - "-e" @@ -98,7 +98,7 @@ requirements: - class: ShellCommandRequirement - class: LoadListingRequirement - class: DockerRequirement - dockerPull: vamsithiriveedhi/totalsegmentator:end_to_end_v1 + dockerPull: download_convert_inference_totalseg_radiomics - class: InlineJavascriptRequirement hints: - class: sbg:AWSInstanceType @@ -113,14 +113,18 @@ sbg:revisionsInfo: sbg:modifiedBy: vamsikrishna14 sbg:modifiedOn: 1685411485 sbg:revisionNotes: '' +- sbg:revision: 2 + sbg:modifiedBy: vamsikrishna14 + sbg:modifiedOn: 1695396409 + sbg:revisionNotes: '' sbg:image_url: sbg:appVersion: - v1.2 -id: https://cgc-api.sbgenomics.com/v2/apps/vamsikrishna14/idc/totalsegmentatorend-to-end/1/raw/ -sbg:id: vamsikrishna14/idc/totalsegmentatorend-to-end/1 -sbg:revision: 1 +id: https://cgc-api.sbgenomics.com/v2/apps/vamsikrishna14/idc/totalsegmentatorend-to-end/2/raw/ +sbg:id: vamsikrishna14/idc/totalsegmentatorend-to-end/2 +sbg:revision: 2 sbg:revisionNotes: '' -sbg:modifiedOn: 1685411485 +sbg:modifiedOn: 1695396409 sbg:modifiedBy: vamsikrishna14 sbg:createdOn: 1685410682 sbg:createdBy: vamsikrishna14 @@ -129,7 +133,7 @@ sbg:sbgMaintained: false sbg:validationErrors: [] sbg:contributors: - vamsikrishna14 -sbg:latestRevision: 1 +sbg:latestRevision: 2 sbg:publisher: sbg -sbg:content_hash: a167b937f080f99d795d977209c6217bf0ca43aa483083f6fd0523c82ab323097 +sbg:content_hash: a1591a79810696eea5ddb434a5d742085374137bbe32ad15b03dd174e31b8f841 sbg:workflowLanguage: CWL diff --git a/SevenBridges/TotalSegmentator/splitWorkflow/threeVM.cwl b/SevenBridges/TotalSegmentator/splitWorkflow/threeVM.cwl index 5bc96fb..b9523d2 100644 --- a/SevenBridges/TotalSegmentator/splitWorkflow/threeVM.cwl +++ b/SevenBridges/TotalSegmentator/splitWorkflow/threeVM.cwl @@ -129,10 +129,10 @@ steps: cwlVersion: v1.2 "$namespaces": sbg: https://sevenbridges.com - id: vamsikrishna14/idc/downloaddicomandconvert/2 + id: vamsikrishna14/idc/downloaddicomandconvert/3 baseCommand: - wget - - https://raw.githubusercontent.com/vkt1414/Cloud-Resources-Workflows/main/Notebooks/Totalsegmentator/downloadDicomAndConvertNotebook.ipynb + - https://raw.githubusercontent.com/ImagingDataCommons/Cloud-Resources-Workflows/main/Notebooks/Totalsegmentator/downloadDicomAndConvertNotebook.ipynb - "&&" - set - "-e" @@ -192,7 +192,7 @@ steps: - class: ShellCommandRequirement - class: LoadListingRequirement - class: DockerRequirement - dockerPull: vamsithiriveedhi/totalsegmentator:task1_v1 + dockerPull: imagingdatacommons/download_convert - class: InlineJavascriptRequirement hints: - class: sbg:AWSInstanceType @@ -211,13 +211,17 @@ steps: sbg:modifiedBy: vamsikrishna14 sbg:modifiedOn: 1681840727 sbg:revisionNotes: '' + - sbg:revision: 3 + sbg:modifiedBy: vamsikrishna14 + sbg:modifiedOn: 1695396114 + sbg:revisionNotes: '' sbg:image_url: sbg:appVersion: - v1.2 - sbg:id: vamsikrishna14/idc/downloaddicomandconvert/2 - sbg:revision: 2 + sbg:id: vamsikrishna14/idc/downloaddicomandconvert/3 + sbg:revision: 3 sbg:revisionNotes: '' - sbg:modifiedOn: 1681840727 + sbg:modifiedOn: 1695396114 sbg:modifiedBy: vamsikrishna14 sbg:createdOn: 1681833288 sbg:createdBy: vamsikrishna14 @@ -226,9 +230,9 @@ steps: sbg:validationErrors: [] sbg:contributors: - vamsikrishna14 - sbg:latestRevision: 2 + sbg:latestRevision: 3 sbg:publisher: sbg - sbg:content_hash: a06cee4ff549980ea24181509b5ff33641b37fc106922c1dc5b7c18b2a2453555 + sbg:content_hash: a2fff83cdce6f5974ed918b5730d473ca7bbe4c51fc8899051f9f8ed2542055e5 sbg:workflowLanguage: CWL label: downloadDicomAndConvert sbg:x: 259.817138671875 @@ -249,10 +253,10 @@ steps: cwlVersion: v1.2 "$namespaces": sbg: https://sevenbridges.com - id: vamsikrishna14/idc/inferencetotalsegmentatordocker/6 + id: vamsikrishna14/idc/inferencetotalsegmentatordocker/7 baseCommand: - wget - - https://raw.githubusercontent.com/vkt1414/Cloud-Resources-Workflows/main/Notebooks/Totalsegmentator/inferenceTotalSegmentatorNotebook.ipynb + - https://raw.githubusercontent.com/ImagingDataCommons/Cloud-Resources-Workflows/main/Notebooks/Totalsegmentator/inferenceTotalSegmentatorNotebook.ipynb - "&&" - set - "-e" @@ -313,7 +317,7 @@ steps: - class: ShellCommandRequirement - class: LoadListingRequirement - class: DockerRequirement - dockerPull: vamsithiriveedhi/totalsegmentator:task2_v3 + dockerPull: imagingdatacommons/inference_totalseg - class: InlineJavascriptRequirement hints: - class: sbg:AWSInstanceType @@ -348,13 +352,17 @@ steps: sbg:modifiedBy: vamsikrishna14 sbg:modifiedOn: 1685297796 sbg:revisionNotes: removed metadata as required outputs + - sbg:revision: 7 + sbg:modifiedBy: vamsikrishna14 + sbg:modifiedOn: 1695396371 + sbg:revisionNotes: '' sbg:image_url: sbg:appVersion: - v1.2 - sbg:id: vamsikrishna14/idc/inferencetotalsegmentatordocker/6 - sbg:revision: 6 - sbg:revisionNotes: removed metadata as required outputs - sbg:modifiedOn: 1685297796 + sbg:id: vamsikrishna14/idc/inferencetotalsegmentatordocker/7 + sbg:revision: 7 + sbg:revisionNotes: '' + sbg:modifiedOn: 1695396371 sbg:modifiedBy: vamsikrishna14 sbg:createdOn: 1681836278 sbg:createdBy: vamsikrishna14 @@ -363,9 +371,9 @@ steps: sbg:validationErrors: [] sbg:contributors: - vamsikrishna14 - sbg:latestRevision: 6 + sbg:latestRevision: 7 sbg:publisher: sbg - sbg:content_hash: adcdf56421b92579ce7d5f1904ae38c1472cd1e8fe20c03036f0a3a3789c63dc3 + sbg:content_hash: ab851c5f011008d0250dffee373ec54ae770f1b34b524501f01b040d8d9ee68a0 sbg:workflowLanguage: CWL label: inferenceTotalSegmentator sbg:x: 795.6659545898438 @@ -390,10 +398,10 @@ steps: cwlVersion: v1.2 "$namespaces": sbg: https://sevenbridges.com - id: vamsikrishna14/idc/dicomsegandradiomicssr/1 + id: vamsikrishna14/idc/dicomsegandradiomicssr/2 baseCommand: - wget - - https://raw.githubusercontent.com/vkt1414/Cloud-Resources-Workflows/main/Notebooks/Totalsegmentator/dicomsegAndRadiomicsSR_Notebook.ipynb + - https://raw.githubusercontent.com/ImagingDataCommons/Cloud-Resources-Workflows/main/Notebooks/Totalsegmentator/dicomsegAndRadiomicsSR_Notebook.ipynb - "&&" - set - "-e" @@ -474,7 +482,7 @@ steps: - class: ShellCommandRequirement - class: LoadListingRequirement - class: DockerRequirement - dockerPull: vamsithiriveedhi/totalsegmentator:task3_v3 + dockerPull: imagingdatacommons/radiomics - class: InlineJavascriptRequirement hints: - class: sbg:AWSInstanceType @@ -489,13 +497,17 @@ steps: sbg:modifiedBy: vamsikrishna14 sbg:modifiedOn: 1685298787 sbg:revisionNotes: updated task3 + - sbg:revision: 2 + sbg:modifiedBy: vamsikrishna14 + sbg:modifiedOn: 1695396190 + sbg:revisionNotes: '' sbg:image_url: sbg:appVersion: - v1.2 - sbg:id: vamsikrishna14/idc/dicomsegandradiomicssr/1 - sbg:revision: 1 - sbg:revisionNotes: updated task3 - sbg:modifiedOn: 1685298787 + sbg:id: vamsikrishna14/idc/dicomsegandradiomicssr/2 + sbg:revision: 2 + sbg:revisionNotes: '' + sbg:modifiedOn: 1695396190 sbg:modifiedBy: vamsikrishna14 sbg:createdOn: 1685298038 sbg:createdBy: vamsikrishna14 @@ -504,9 +516,9 @@ steps: sbg:validationErrors: [] sbg:contributors: - vamsikrishna14 - sbg:latestRevision: 1 + sbg:latestRevision: 2 sbg:publisher: sbg - sbg:content_hash: a75556be18f1ecf2535f6d414adff727aa056f49a974989de22bce3da346ed857 + sbg:content_hash: a32120ab84bdb935639d78709618996d0108b5048e4eb87e3e5beeb31cb0dae64 sbg:workflowLanguage: CWL label: dicomsegAndRadiomicsSR sbg:x: 1274.7718505859375 @@ -536,14 +548,18 @@ sbg:revisionsInfo: sbg:modifiedBy: vamsikrishna14 sbg:modifiedOn: 1685301628 sbg:revisionNotes: '' -sbg:image_url: https://cgc.sbgenomics.com/ns/brood/images/vamsikrishna14/idc/totalsegmentatorthreevmworkflow/4.png +- sbg:revision: 5 + sbg:modifiedBy: vamsikrishna14 + sbg:modifiedOn: 1695396679 + sbg:revisionNotes: '' +sbg:image_url: https://cgc.sbgenomics.com/ns/brood/images/vamsikrishna14/idc/totalsegmentatorthreevmworkflow/5.png sbg:appVersion: - v1.2 -id: https://cgc-api.sbgenomics.com/v2/apps/vamsikrishna14/idc/totalsegmentatorthreevmworkflow/4/raw/ -sbg:id: vamsikrishna14/idc/totalsegmentatorthreevmworkflow/4 -sbg:revision: 4 +id: https://cgc-api.sbgenomics.com/v2/apps/vamsikrishna14/idc/totalsegmentatorthreevmworkflow/5/raw/ +sbg:id: vamsikrishna14/idc/totalsegmentatorthreevmworkflow/5 +sbg:revision: 5 sbg:revisionNotes: '' -sbg:modifiedOn: 1685301628 +sbg:modifiedOn: 1695396679 sbg:modifiedBy: vamsikrishna14 sbg:createdOn: 1685299575 sbg:createdBy: vamsikrishna14 @@ -552,7 +568,7 @@ sbg:sbgMaintained: false sbg:validationErrors: [] sbg:contributors: - vamsikrishna14 -sbg:latestRevision: 4 +sbg:latestRevision: 5 sbg:publisher: sbg -sbg:content_hash: ad136186a986d73930c2fefd54443c36e908aef5885493541735f3b1acdc90f5b +sbg:content_hash: a9e9ea5f19f18761b3dbcb4babc86e58ae5011bc602f60c1988548307cb9a8be9 sbg:workflowLanguage: CWL diff --git a/SevenBridges/TotalSegmentator/splitWorkflow/twoVM.cwl b/SevenBridges/TotalSegmentator/splitWorkflow/twoVM.cwl index f365e92..4c76592 100644 --- a/SevenBridges/TotalSegmentator/splitWorkflow/twoVM.cwl +++ b/SevenBridges/TotalSegmentator/splitWorkflow/twoVM.cwl @@ -117,10 +117,10 @@ steps: cwlVersion: v1.2 "$namespaces": sbg: https://sevenbridges.com - id: vamsikrishna14/idc/example/18 + id: vamsikrishna14/idc/example/19 baseCommand: - wget - - https://raw.githubusercontent.com/vkt1414/Cloud-Resources-Workflows/main/Notebooks/Totalsegmentator/downloadDicomAndConvertAndInferenceTotalSegmentatorNotebook.ipynb + - https://raw.githubusercontent.com/ImagingDataCommons/Cloud-Resources-Workflows/main/Notebooks/Totalsegmentator/downloadDicomAndConvertAndInferenceTotalSegmentatorNotebook.ipynb - "&&" - set - "-e" @@ -185,7 +185,7 @@ steps: - class: ShellCommandRequirement - class: LoadListingRequirement - class: DockerRequirement - dockerPull: vamsithiriveedhi/totalsegmentator:task1and2_v3 + dockerPull: imagingdatacommons/download_convert_inference_totalseg - class: InlineJavascriptRequirement hints: - class: sbg:AWSInstanceType @@ -268,13 +268,17 @@ steps: sbg:modifiedBy: vamsikrishna14 sbg:modifiedOn: 1685297484 sbg:revisionNotes: removed metadata as we no longer capture png files + - sbg:revision: 19 + sbg:modifiedBy: vamsikrishna14 + sbg:modifiedOn: 1695396244 + sbg:revisionNotes: '' sbg:image_url: sbg:appVersion: - v1.2 - sbg:id: vamsikrishna14/idc/example/18 - sbg:revision: 18 - sbg:revisionNotes: removed metadata as we no longer capture png files - sbg:modifiedOn: 1685297484 + sbg:id: vamsikrishna14/idc/example/19 + sbg:revision: 19 + sbg:revisionNotes: '' + sbg:modifiedOn: 1695396244 sbg:modifiedBy: vamsikrishna14 sbg:createdOn: 1674046555 sbg:createdBy: vamsikrishna14 @@ -283,9 +287,9 @@ steps: sbg:validationErrors: [] sbg:contributors: - vamsikrishna14 - sbg:latestRevision: 18 + sbg:latestRevision: 19 sbg:publisher: sbg - sbg:content_hash: ab5c89dfe9499f944779c4d604fd785601c1609535de6a6822d0c67b991f028d1 + sbg:content_hash: affc3b50184ebba59c7e99fd080393efffc6b6a933334e251bd69cc94e9af2307 sbg:workflowLanguage: CWL label: downloadDicomAndConvertAndInferenceTotalSegmentator sbg:x: 259.817138671875 @@ -310,10 +314,10 @@ steps: cwlVersion: v1.2 "$namespaces": sbg: https://sevenbridges.com - id: vamsikrishna14/idc/dicomsegandradiomicssr/1 + id: vamsikrishna14/idc/dicomsegandradiomicssr/2 baseCommand: - wget - - https://raw.githubusercontent.com/vkt1414/Cloud-Resources-Workflows/main/Notebooks/Totalsegmentator/dicomsegAndRadiomicsSR_Notebook.ipynb + - https://raw.githubusercontent.com/ImagingDataCommons/Cloud-Resources-Workflows/main/Notebooks/Totalsegmentator/dicomsegAndRadiomicsSR_Notebook.ipynb - "&&" - set - "-e" @@ -394,7 +398,7 @@ steps: - class: ShellCommandRequirement - class: LoadListingRequirement - class: DockerRequirement - dockerPull: vamsithiriveedhi/totalsegmentator:task3_v3 + dockerPull: imagingdatacommons/radiomics - class: InlineJavascriptRequirement hints: - class: sbg:AWSInstanceType @@ -409,13 +413,17 @@ steps: sbg:modifiedBy: vamsikrishna14 sbg:modifiedOn: 1685298787 sbg:revisionNotes: updated task3 + - sbg:revision: 2 + sbg:modifiedBy: vamsikrishna14 + sbg:modifiedOn: 1695396190 + sbg:revisionNotes: '' sbg:image_url: sbg:appVersion: - v1.2 - sbg:id: vamsikrishna14/idc/dicomsegandradiomicssr/1 - sbg:revision: 1 - sbg:revisionNotes: updated task3 - sbg:modifiedOn: 1685298787 + sbg:id: vamsikrishna14/idc/dicomsegandradiomicssr/2 + sbg:revision: 2 + sbg:revisionNotes: '' + sbg:modifiedOn: 1695396190 sbg:modifiedBy: vamsikrishna14 sbg:createdOn: 1685298038 sbg:createdBy: vamsikrishna14 @@ -424,9 +432,9 @@ steps: sbg:validationErrors: [] sbg:contributors: - vamsikrishna14 - sbg:latestRevision: 1 + sbg:latestRevision: 2 sbg:publisher: sbg - sbg:content_hash: a75556be18f1ecf2535f6d414adff727aa056f49a974989de22bce3da346ed857 + sbg:content_hash: a32120ab84bdb935639d78709618996d0108b5048e4eb87e3e5beeb31cb0dae64 sbg:workflowLanguage: CWL label: dicomsegAndRadiomicsSR sbg:x: 966.80322265625 @@ -456,14 +464,18 @@ sbg:revisionsInfo: sbg:modifiedBy: vamsikrishna14 sbg:modifiedOn: 1685301237 sbg:revisionNotes: '' -sbg:image_url: https://cgc.sbgenomics.com/ns/brood/images/vamsikrishna14/idc/totalsegmentatortwovmworkflow/4.png +- sbg:revision: 5 + sbg:modifiedBy: vamsikrishna14 + sbg:modifiedOn: 1695396447 + sbg:revisionNotes: '' +sbg:image_url: https://cgc.sbgenomics.com/ns/brood/images/vamsikrishna14/idc/totalsegmentatortwovmworkflow/5.png sbg:appVersion: - v1.2 -id: https://cgc-api.sbgenomics.com/v2/apps/vamsikrishna14/idc/totalsegmentatortwovmworkflow/4/raw/ -sbg:id: vamsikrishna14/idc/totalsegmentatortwovmworkflow/4 -sbg:revision: 4 +id: https://cgc-api.sbgenomics.com/v2/apps/vamsikrishna14/idc/totalsegmentatortwovmworkflow/5/raw/ +sbg:id: vamsikrishna14/idc/totalsegmentatortwovmworkflow/5 +sbg:revision: 5 sbg:revisionNotes: '' -sbg:modifiedOn: 1685301237 +sbg:modifiedOn: 1695396447 sbg:modifiedBy: vamsikrishna14 sbg:createdOn: 1685298940 sbg:createdBy: vamsikrishna14 @@ -472,7 +484,7 @@ sbg:sbgMaintained: false sbg:validationErrors: [] sbg:contributors: - vamsikrishna14 -sbg:latestRevision: 4 +sbg:latestRevision: 5 sbg:publisher: sbg -sbg:content_hash: aa5ee5d4291c7bb7fcb71652ee8126b3629d5f5493176b28f23df80d4f3cc9c07 +sbg:content_hash: a1b26965f8c6bee5d3d74583373e5bf6c031d759013fbaa383a60cb32911088ab sbg:workflowLanguage: CWL From 7470516cff28673df76a0ee1e51535448b0eb4d9 Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Fri, 22 Sep 2023 14:40:33 -0400 Subject: [PATCH 25/40] considate dev and main branch workflows to one --- .github/workflows/download_convert-dev.yml | 46 ---------------- .github/workflows/download_convert.yml | 45 ++++++++++++++-- ...ownload_convert_inference_totalseg-dev.yml | 49 ----------------- .../download_convert_inference_totalseg.yml | 52 +++++++++++++++++-- ...nvert_inference_totalseg_radiomics-dev.yml | 49 ----------------- ...d_convert_inference_totalseg_radiomics.yml | 50 ++++++++++++++++-- .github/workflows/inference_totalseg-dev.yml | 49 ----------------- .github/workflows/inference_totalseg.yml | 52 +++++++++++++++++-- ...er_frame_functional_group_sequence-dev.yml | 45 ---------------- .../per_frame_functional_group_sequence.yml | 46 ++++++++++++++-- .github/workflows/radiomics-dev.yml | 45 ---------------- .github/workflows/radiomics.yml | 44 ++++++++++++++-- 12 files changed, 264 insertions(+), 308 deletions(-) delete mode 100644 .github/workflows/download_convert-dev.yml delete mode 100644 .github/workflows/download_convert_inference_totalseg-dev.yml delete mode 100644 .github/workflows/download_convert_inference_totalseg_radiomics-dev.yml delete mode 100644 .github/workflows/inference_totalseg-dev.yml delete mode 100644 .github/workflows/per_frame_functional_group_sequence-dev.yml delete mode 100644 .github/workflows/radiomics-dev.yml diff --git a/.github/workflows/download_convert-dev.yml b/.github/workflows/download_convert-dev.yml deleted file mode 100644 index df4c176..0000000 --- a/.github/workflows/download_convert-dev.yml +++ /dev/null @@ -1,46 +0,0 @@ -name: dev-download_convert - -on: - push: - branches: - - dev - paths: - - 'Dockerfiles/download_convert/**' - - .github/workflows/download_convert-dev.yml - -jobs: - build-and-push: - runs-on: ubuntu-latest - steps: - - name: Checkout code - uses: actions/checkout@v4 - - - name: Set up Git - run: | - git config --global user.email "actions@github.com" - git config --global user.name "GitHub Actions" - - - name: Get Git Commit Hash - id: git-commit-hash - run: | - COMMIT_HASH=$(git rev-parse HEAD) - echo $COMMIT_HASH - echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - - - name: Login to Docker Hub - uses: docker/login-action@v3 - with: - username: ${{ secrets.DOCKER_USERNAME }} - password: ${{ secrets.DOCKER_PASSWORD }} - - - name: Build and push Docker image - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/download_convert/Dockerfile - push: true - tags: imagingdatacommons/download_convert:dev - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file diff --git a/.github/workflows/download_convert.yml b/.github/workflows/download_convert.yml index 5d1b33e..89c8262 100644 --- a/.github/workflows/download_convert.yml +++ b/.github/workflows/download_convert.yml @@ -3,13 +3,51 @@ name: download_convert on: push: branches: + - dev - main paths: - 'Dockerfiles/download_convert/**' - - .github/workflows/download_convert.yml + - '.github/workflows/download_convert.yml' jobs: - build-and-push: + build-and-push-dev: + if: github.ref == 'refs/heads/dev' + runs-on: ubuntu-latest + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Git + run: | + git config --global user.email "actions@github.com" + git config --global user.name "GitHub Actions" + + - name: Get Git Commit Hash + id: git-commit-hash + run: | + COMMIT_HASH=$(git rev-parse HEAD) + echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV + + - name: Login to Docker Hub + uses: docker/login-action@v3 + with: + username: ${{ secrets.DOCKER_USERNAME }} + password: ${{ secrets.DOCKER_PASSWORD }} + + - name: Build and push Docker image + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/download_convert/Dockerfile + push: true + tags: imagingdatacommons/download_convert:dev + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} + + build-and-push-prod: + if: github.ref == 'refs/heads/main' runs-on: ubuntu-latest steps: - name: Checkout code @@ -24,7 +62,6 @@ jobs: id: git-commit-hash run: | COMMIT_HASH=$(git rev-parse HEAD) - echo $COMMIT_HASH echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - name: Login to Docker Hub @@ -43,4 +80,4 @@ jobs: build-args: | GIT_HASH=${{ env.COMMIT_HASH }} env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file + COMMIT_HASH: ${{ env.COMMIT_HASH }} diff --git a/.github/workflows/download_convert_inference_totalseg-dev.yml b/.github/workflows/download_convert_inference_totalseg-dev.yml deleted file mode 100644 index c0b1c28..0000000 --- a/.github/workflows/download_convert_inference_totalseg-dev.yml +++ /dev/null @@ -1,49 +0,0 @@ -name: dev-download_convert_inference_totalseg - -on: - push: - branches: - - dev - paths: - - 'Dockerfiles/download_convert_inference_totalseg/**' - - .github/workflows/download_convert_inference_totalseg-dev.yml - -jobs: - build-and-push: - runs-on: ubuntu-latest - steps: - - name: Checkout code - uses: actions/checkout@v4 - - - name: Set up Git - run: | - git config --global user.email "actions@github.com" - git config --global user.name "GitHub Actions" - - - name: Get Git Commit Hash - id: git-commit-hash - run: | - COMMIT_HASH=$(git rev-parse HEAD) - echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - - - name: Copy additional files to build context - run: | - cp Dockerfiles/download_convert_inference_totalseg/weights_download.sh . - - - name: Login to Docker Hub - uses: docker/login-action@v3 - with: - username: ${{ secrets.DOCKER_USERNAME }} - password: ${{ secrets.DOCKER_PASSWORD }} - - - name: Build and push Docker image - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/download_convert_inference_totalseg/Dockerfile - push: true - tags: imagingdatacommons/download_convert_inference_totalseg:dev - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} diff --git a/.github/workflows/download_convert_inference_totalseg.yml b/.github/workflows/download_convert_inference_totalseg.yml index 31af54b..662ad60 100644 --- a/.github/workflows/download_convert_inference_totalseg.yml +++ b/.github/workflows/download_convert_inference_totalseg.yml @@ -3,13 +3,15 @@ name: download_convert_inference_totalseg on: push: branches: + - dev - main paths: - 'Dockerfiles/download_convert_inference_totalseg/**' - .github/workflows/download_convert_inference_totalseg.yml - + jobs: - build-and-push: + build-and-push-dev: + if: github.ref == 'refs/heads/dev' runs-on: ubuntu-latest steps: - name: Checkout code @@ -19,13 +21,53 @@ jobs: run: | git config --global user.email "actions@github.com" git config --global user.name "GitHub Actions" - + - name: Get Git Commit Hash id: git-commit-hash run: | COMMIT_HASH=$(git rev-parse HEAD) echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - + + - name: Copy additional files to build context + run: | + cp Dockerfiles/download_convert_inference_totalseg/weights_download.sh . + + - name: Login to Docker Hub + uses: docker/login-action@v3 + with: + username: ${{ secrets.DOCKER_USERNAME }} + password: ${{ secrets.DOCKER_PASSWORD }} + + - name: Build and push Docker image (dev) + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/download_convert_inference_totalseg/Dockerfile + push: true + tags: imagingdatacommons/download_convert_inference_totalseg:dev + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} + + build-and-push-prod: + if: github.ref == 'refs/heads/main' + runs-on: ubuntu-latest + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Git + run: | + git config --global user.email "actions@github.com" + git config --global user.name "GitHub Actions" + + - name: Get Git Commit Hash + id: git-commit-hash + run: | + COMMIT_HASH=$(git rev-parse HEAD) + echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV + - name: Copy additional files to build context run: | cp Dockerfiles/download_convert_inference_totalseg/weights_download.sh . @@ -36,7 +78,7 @@ jobs: username: ${{ secrets.DOCKER_USERNAME }} password: ${{ secrets.DOCKER_PASSWORD }} - - name: Build and push Docker image + - name: Build and push Docker image (main) uses: docker/build-push-action@v5 with: context: . diff --git a/.github/workflows/download_convert_inference_totalseg_radiomics-dev.yml b/.github/workflows/download_convert_inference_totalseg_radiomics-dev.yml deleted file mode 100644 index b028174..0000000 --- a/.github/workflows/download_convert_inference_totalseg_radiomics-dev.yml +++ /dev/null @@ -1,49 +0,0 @@ -name: dev-download_convert_inference_totalseg_radiomics - -on: - push: - branches: - - dev - paths: - - 'Dockerfiles/download_convert_inference_totalseg_radiomics/**' - - .github/workflows/download_convert_inference_totalseg_radiomics-dev.yml - -jobs: - build-and-push: - runs-on: ubuntu-latest - steps: - - name: Checkout code - uses: actions/checkout@v4 - - - name: Set up Git - run: | - git config --global user.email "actions@github.com" - git config --global user.name "GitHub Actions" - - - name: Get Git Commit Hash - id: git-commit-hash - run: | - COMMIT_HASH=$(git rev-parse HEAD) - echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - - - name: Copy additional files to build context - run: | - cp Dockerfiles/download_convert_inference_totalseg_radiomics/weights_download.sh . - - - name: Login to Docker Hub - uses: docker/login-action@v3 - with: - username: ${{ secrets.DOCKER_USERNAME }} - password: ${{ secrets.DOCKER_PASSWORD }} - - - name: Build and push Docker image - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile - push: true - tags: imagingdatacommons/download_convert_inference_totalseg_radiomics:dev - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} diff --git a/.github/workflows/download_convert_inference_totalseg_radiomics.yml b/.github/workflows/download_convert_inference_totalseg_radiomics.yml index 5a59193..c456f89 100644 --- a/.github/workflows/download_convert_inference_totalseg_radiomics.yml +++ b/.github/workflows/download_convert_inference_totalseg_radiomics.yml @@ -3,13 +3,15 @@ name: download_convert_inference_totalseg_radiomics on: push: branches: - - main + - dev + - main paths: - 'Dockerfiles/download_convert_inference_totalseg_radiomics/**' - .github/workflows/download_convert_inference_totalseg_radiomics.yml jobs: - build-and-push: + build-and-push-dev: + if: github.ref == 'refs/heads/dev' runs-on: ubuntu-latest steps: - name: Checkout code @@ -25,7 +27,47 @@ jobs: run: | COMMIT_HASH=$(git rev-parse HEAD) echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - + + - name: Copy additional files to build context + run: | + cp Dockerfiles/download_convert_inference_totalseg_radiomics/weights_download.sh . + + - name: Login to Docker Hub + uses: docker/login-action@v3 + with: + username: ${{ secrets.DOCKER_USERNAME }} + password: ${{ secrets.DOCKER_PASSWORD }} + + - name: Build and push Docker image (dev) + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile + push: true + tags: imagingdatacommons/download_convert_inference_totalseg_radiomics:dev + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} + + build-and-push-prod: + if: github.ref == 'refs/heads/main' + runs-on: ubuntu-latest + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Git + run: | + git config --global user.email "actions@github.com" + git config --global user.name "GitHub Actions" + + - name: Get Git Commit Hash + id: git-commit-hash + run: | + COMMIT_HASH=$(git rev-parse HEAD) + echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV + - name: Copy additional files to build context run: | cp Dockerfiles/download_convert_inference_totalseg_radiomics/weights_download.sh . @@ -36,7 +78,7 @@ jobs: username: ${{ secrets.DOCKER_USERNAME }} password: ${{ secrets.DOCKER_PASSWORD }} - - name: Build and push Docker image + - name: Build and push Docker image (main) uses: docker/build-push-action@v5 with: context: . diff --git a/.github/workflows/inference_totalseg-dev.yml b/.github/workflows/inference_totalseg-dev.yml deleted file mode 100644 index 0f95b54..0000000 --- a/.github/workflows/inference_totalseg-dev.yml +++ /dev/null @@ -1,49 +0,0 @@ -name: dev-inference_totalseg - -on: - push: - branches: - - dev - paths: - - 'Dockerfiles/inference_totalseg/**' - - .github/workflows/inference_totalseg-dev.yml - -jobs: - build-and-push: - runs-on: ubuntu-latest - steps: - - name: Checkout code - uses: actions/checkout@v4 - - - name: Set up Git - run: | - git config --global user.email "actions@github.com" - git config --global user.name "GitHub Actions" - - - name: Get Git Commit Hash - id: git-commit-hash - run: | - COMMIT_HASH=$(git rev-parse HEAD) - echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - - - name: Copy additional files to build context - run: | - cp Dockerfiles/inference_totalseg/weights_download.sh . - - - name: Login to Docker Hub - uses: docker/login-action@v3 - with: - username: ${{ secrets.DOCKER_USERNAME }} - password: ${{ secrets.DOCKER_PASSWORD }} - - - name: Build and push Docker image - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/inference_totalseg/Dockerfile - push: true - tags: imagingdatacommons/inference_totalseg:dev - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file diff --git a/.github/workflows/inference_totalseg.yml b/.github/workflows/inference_totalseg.yml index 51182f1..d61b7f1 100644 --- a/.github/workflows/inference_totalseg.yml +++ b/.github/workflows/inference_totalseg.yml @@ -3,13 +3,55 @@ name: inference_totalseg on: push: branches: - - main + - dev + - main paths: - 'Dockerfiles/inference_totalseg/**' - - .github/workflows/inference_totalseg.yml - + - .github/workflows/inference_totalseg.yml + jobs: - build-and-push: + build-and-push-dev: + if: github.ref == 'refs/heads/dev' + runs-on: ubuntu-latest + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Git + run: | + git config --global user.email "actions@github.com" + git config --global user.name "GitHub Actions" + + - name: Get Git Commit Hash + id: git-commit-hash + run: | + COMMIT_HASH=$(git rev-parse HEAD) + echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV + + - name: Copy additional files to build context + run: | + cp Dockerfiles/inference_totalseg/weights_download.sh . + + - name: Login to Docker Hub + uses: docker/login-action@v3 + with: + username: ${{ secrets.DOCKER_USERNAME }} + password: ${{ secrets.DOCKER_PASSWORD }} + + - name: Build and push Docker image + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/inference_totalseg/Dockerfile + push: true + tags: imagingdatacommons/inference_totalseg:dev + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} + + build-and-push-prod: + if: github.ref == 'refs/heads/main' runs-on: ubuntu-latest steps: - name: Checkout code @@ -46,4 +88,4 @@ jobs: build-args: | GIT_HASH=${{ env.COMMIT_HASH }} env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file + COMMIT_HASH: ${{ env.COMMIT_HASH }} diff --git a/.github/workflows/per_frame_functional_group_sequence-dev.yml b/.github/workflows/per_frame_functional_group_sequence-dev.yml deleted file mode 100644 index 468ef1d..0000000 --- a/.github/workflows/per_frame_functional_group_sequence-dev.yml +++ /dev/null @@ -1,45 +0,0 @@ -name: dev-per_frame_functional_group_sequence - -on: - push: - branches: - - dev - paths: - - 'Dockerfiles/per_frame_functional_group_sequence/**' - - .github/workflows/per_frame_functional_group_sequence-dev.yml - -jobs: - build-and-push: - runs-on: ubuntu-latest - steps: - - name: Checkout code - uses: actions/checkout@v4 - - - name: Set up Git - run: | - git config --global user.email "actions@github.com" - git config --global user.name "GitHub Actions" - - - name: Get Git Commit Hash - id: git-commit-hash - run: | - COMMIT_HASH=$(git rev-parse HEAD) - echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - - - name: Login to Docker Hub - uses: docker/login-action@v3 - with: - username: ${{ secrets.DOCKER_USERNAME }} - password: ${{ secrets.DOCKER_PASSWORD }} - - - name: Build and push Docker image - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/per_frame_functional_group_sequence/Dockerfile - push: true - tags: imagingdatacommons/per_frame_functional_group_sequence:dev - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file diff --git a/.github/workflows/per_frame_functional_group_sequence.yml b/.github/workflows/per_frame_functional_group_sequence.yml index 86ec423..4806a60 100644 --- a/.github/workflows/per_frame_functional_group_sequence.yml +++ b/.github/workflows/per_frame_functional_group_sequence.yml @@ -3,13 +3,51 @@ name: per_frame_functional_group_sequence on: push: branches: - - main + - dev + - main paths: - 'Dockerfiles/per_frame_functional_group_sequence/**' - - .github/workflows/per_frame_functional_group_sequence.yml + - .github/workflows/per_frame_functional_group_sequence.yml jobs: - build-and-push: + build-and-push-dev: + if: github.ref == 'refs/heads/dev' + runs-on: ubuntu-latest + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Git + run: | + git config --global user.email "actions@github.com" + git config --global user.name "GitHub Actions" + + - name: Get Git Commit Hash + id: git-commit-hash + run: | + COMMIT_HASH=$(git rev-parse HEAD) + echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV + + - name: Login to Docker Hub + uses: docker/login-action@v3 + with: + username: ${{ secrets.DOCKER_USERNAME }} + password: ${{ secrets.DOCKER_PASSWORD }} + + - name: Build and push Docker image + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/per_frame_functional_group_sequence/Dockerfile + push: true + tags: imagingdatacommons/per_frame_functional_group_sequence:dev + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} + + build-and-push-prod: + if: github.ref == 'refs/heads/main' runs-on: ubuntu-latest steps: - name: Checkout code @@ -42,4 +80,4 @@ jobs: build-args: | GIT_HASH=${{ env.COMMIT_HASH }} env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file + COMMIT_HASH: ${{ env.COMMIT_HASH }} diff --git a/.github/workflows/radiomics-dev.yml b/.github/workflows/radiomics-dev.yml deleted file mode 100644 index 8656520..0000000 --- a/.github/workflows/radiomics-dev.yml +++ /dev/null @@ -1,45 +0,0 @@ -name: dev-radiomics - -on: - push: - branches: - - dev - paths: - - 'Dockerfiles/radiomics/**' - - .github/workflows/radiomics-dev.yml - -jobs: - build-and-push: - runs-on: ubuntu-latest - steps: - - name: Checkout code - uses: actions/checkout@v4 - - - name: Set up Git - run: | - git config --global user.email "actions@github.com" - git config --global user.name "GitHub Actions" - - - name: Get Git Commit Hash - id: git-commit-hash - run: | - COMMIT_HASH=$(git rev-parse HEAD) - echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - - - name: Login to Docker Hub - uses: docker/login-action@v3 - with: - username: ${{ secrets.DOCKER_USERNAME }} - password: ${{ secrets.DOCKER_PASSWORD }} - - - name: Build and push Docker image - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/radiomics/Dockerfile - push: true - tags: imagingdatacommons/radiomics:dev - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file diff --git a/.github/workflows/radiomics.yml b/.github/workflows/radiomics.yml index e3068a8..6624120 100644 --- a/.github/workflows/radiomics.yml +++ b/.github/workflows/radiomics.yml @@ -3,13 +3,51 @@ name: radiomics on: push: branches: - - main + - dev + - main paths: - 'Dockerfiles/radiomics/**' - .github/workflows/radiomics.yml jobs: - build-and-push: + build-and-push-dev: + if: github.ref == 'refs/heads/dev' + runs-on: ubuntu-latest + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Git + run: | + git config --global user.email "actions@github.com" + git config --global user.name "GitHub Actions" + + - name: Get Git Commit Hash + id: git-commit-hash + run: | + COMMIT_HASH=$(git rev-parse HEAD) + echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV + + - name: Login to Docker Hub + uses: docker/login-action@v3 + with: + username: ${{ secrets.DOCKER_USERNAME }} + password: ${{ secrets.DOCKER_PASSWORD }} + + - name: Build and push Docker image + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/radiomics/Dockerfile + push: true + tags: imagingdatacommons/radiomics:dev + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} + + build-and-push-prod: + if: github.ref == 'refs/heads/main' runs-on: ubuntu-latest steps: - name: Checkout code @@ -42,4 +80,4 @@ jobs: build-args: | GIT_HASH=${{ env.COMMIT_HASH }} env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file + COMMIT_HASH: ${{ env.COMMIT_HASH }} From 5af3dac46d60a55d02c46e83ae00a29cdab3fece Mon Sep 17 00:00:00 2001 From: Vamsi Thiriveedhi <115020590+vkt1414@users.noreply.github.com> Date: Fri, 22 Sep 2023 19:11:29 -0400 Subject: [PATCH 26/40] Created using Colaboratory --- .../downloadDicomAndConvertNotebook.ipynb | 1187 ++++++++++------- 1 file changed, 726 insertions(+), 461 deletions(-) diff --git a/Notebooks/Totalsegmentator/downloadDicomAndConvertNotebook.ipynb b/Notebooks/Totalsegmentator/downloadDicomAndConvertNotebook.ipynb index 34d3de4..582d388 100644 --- a/Notebooks/Totalsegmentator/downloadDicomAndConvertNotebook.ipynb +++ b/Notebooks/Totalsegmentator/downloadDicomAndConvertNotebook.ipynb @@ -7,7 +7,7 @@ "colab_type": "text" }, "source": [ - "\"Open" + "\"Open" ] }, { @@ -16,7 +16,8 @@ "id": "rh8wdZYXnGby" }, "source": [ - "#**This Notebook does the first step in the split workflow on Terra**\n", + "#**This Notebook can download CT data from Imaging Data Commons and convert to NIfTI with dcm2niix or plastimatch**\n", + "\n", "DICOM files are downloaded from IDC and converted to NIFTI files with dcm2niix or plastimatch. Whenever there are multiple NIFTI files for a series, such series are prohibited from continuing to Inference. A CSV file is created with a list of such series.\n", "\n", "Please cite:\n", @@ -24,58 +25,133 @@ "Li X, Morgan PS, Ashburner J, Smith J, Rorden C. (2016) The first step for neuroimaging data analysis: DICOM to NIfTI conversion. J Neurosci Methods. 264:47-56.\n", "\n", "Shackleford, James A., Nagarajan Kandasamy and Gregory C. Sharp. “Plastimatch—An Open-Source Software for Radiotherapy Imaging.” (2014).\n", + "\n", + "Fedorov, A., Longabaugh, W. J. R., Pot, D., Clunie, D. A., Pieper, S., Aerts, H. J. W. L., Homeyer, A., Lewis, R., Akbarzadeh, A., Bontempi, D., Clifford, W., Herrmann, M. D., Höfener, H., Octaviano, I., Osborne, C., Paquette, S., Petts, J., Punzo, D., Reyes, M., Schacherer, D. P., … Kikinis, R. (2021). NCI Imaging Data Commons. Cancer research, 81(16), 4188–4193. https://doi.org/10.1158/0008-5472.CAN-21-0950\n", "\n" ] }, { "cell_type": "markdown", - "metadata": { - "id": "zVSZRlpTrXTe" - }, "source": [ - "###**Installing Packages**" - ] + "##**Ways to utilize this notebook**\n", + "\n", + "\n", + "* **Colab**\n", + "* **Jupyter Notebook/Lab**\n", + "* **DockerContainer/Terra/SB-CGC**\n", + "\n", + "\n", + "####**Colab**\n", + "* This notebook was initally developed and tested on Colab, and a working version is saved on github, however reproducibility may not be guaranteed as the run time environment changes with colab updates\n", + "* To run this notebook with Colab, Click 'Open In Colab' icon on top left ![image.png](data:image/png;base64,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)\n", + "*Uncomment all the cells under \"Installing Packages\"\n", + "*Provide the converter of your liking (between dcm2niix and plastimatch), and a path to csv manifest containing SeriesInstanceUID and s5cmd download urls (specific to gcp buckets) under \"Parameters for Papermill\"\n", + "* A sample manifest is provided for convenience can be downloaded by uncommenting and running the cells in \"For local testing\"\n", + "* Run each cell to install the packages and to download the data from IDC, convert to NIfTI saved in lz4 compressed format\n", + "\n", + "\n", + "####**JupyterNotebook/Lab**\n", + "\n", + "* Uncomment all the cells under \"Installing Packages\"\n", + "* Provide the converter of your liking (between dcm2niix and plastimatch), and a path to csv manifest containing SeriesInstanceUID and s5cmd download urls (specific to gcp buckets) under \"Parameters for Papermill\"\n", + "* A sample manifest is provided for convenience can be downloaded by uncommenting and running the cells in \"For local testing\"\n", + "* Run each cell to install the packages and to download the data from IDC, convert to NIfTI saved in lz4 compressed format\n", + "\n", + "####**Docker**\n", + "* This notebook is saved by default in a way that's amenable to be used on Terra/SB-CGC platforms using Docker\n", + "* Running this notebook in a docker container ensures reproduciblity, as we lock the run environment beginning from the base docker image to apt packages and pip packages in the docker image\n", + "\n", + "* Docker images can be found @ https://hub.docker.com/repository/docker/imagingdatacommons/download_convert/tags\n", + "* The link to dockerfile along with git commit hash used for building the docker image can be found in one of the layers called 'LABEL' ![image.png](data:image/png;base64,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)\n", + "* We use a python package called Papermill, that can run the notebook with out having to convert it to python script. This allows us maintain one copy of code instead of two.\n", + "* To use papermill, download this notebook and tag the cell under 'Parameters for Papermill\" as parameters using jupyternotebook or jupyterlab as instructed @ https://papermill.readthedocs.io/en/latest/usage-parameterize.html#designate-parameters-for-a-cell\n", + "* A sample papermill command is\n", + "
\n",
+        "papermill -p converterType 'dcm2niix' -p csvFilePath path_to_csv_manifest downloadDicomAndConvertNotebook.ipynb outputdownloadDicomAndConvertNotebook.ipynb\n",
+        "
\n", + "\n" + ], + "metadata": { + "id": "99a_FPoOpH_I" + } }, { - "cell_type": "code", - "execution_count": null, + "cell_type": "markdown", "metadata": { - "id": "hT_MQVJ_NbZU" + "id": "zVSZRlpTrXTe" }, - "outputs": [], "source": [ - "# %%capture\n", - "# #Installing dcm2niix and pigz\n", - "# !apt-get install dcm2niix pigz lz4" + "###**Installing Packages**" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": { - "id": "N2Z3udYNn7ur" + "id": "hT_MQVJ_NbZU", + "outputId": "1c228a71-211a-4fdf-e685-86efea9bb3c8", + "colab": { + "base_uri": "https://localhost:8080/" + } }, - "outputs": [], + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\r0% [Working]\r \rHit:1 http://security.ubuntu.com/ubuntu jammy-security InRelease\n", + "\r0% [Connecting to archive.ubuntu.com (91.189.91.82)] [Connected to cloud.r-proj\r \rHit:2 https://cloud.r-project.org/bin/linux/ubuntu jammy-cran40/ InRelease\n", + "\r0% [Connecting to archive.ubuntu.com (91.189.91.82)] [Connected to ppa.launchpa\r \rHit:3 https://ppa.launchpadcontent.net/c2d4u.team/c2d4u4.0+/ubuntu jammy InRelease\n", + "\r0% [Connecting to archive.ubuntu.com (91.189.91.82)] [Connecting to ppa.launchp\r \rHit:4 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64 InRelease\n", + "\r0% [Waiting for headers] [Connected to ppa.launchpadcontent.net (185.125.190.52\r \rHit:5 https://ppa.launchpadcontent.net/deadsnakes/ppa/ubuntu jammy InRelease\n", + "Hit:6 http://archive.ubuntu.com/ubuntu jammy InRelease\n", + "Hit:7 https://ppa.launchpadcontent.net/graphics-drivers/ppa/ubuntu jammy InRelease\n", + "Hit:8 http://archive.ubuntu.com/ubuntu jammy-updates InRelease\n", + "Hit:9 https://ppa.launchpadcontent.net/ubuntugis/ppa/ubuntu jammy InRelease\n", + "Hit:10 http://archive.ubuntu.com/ubuntu jammy-backports InRelease\n", + "Reading package lists... Done\n", + "Reading package lists... Done\n", + "Building dependency tree... Done\n", + "Reading state information... Done\n", + "Package plastimatch is not available, but is referred to by another package.\n", + "This may mean that the package is missing, has been obsoleted, or\n", + "is only available from another source\n", + "\n", + "E: Package 'plastimatch' has no installation candidate\n" + ] + } + ], "source": [ - "# %%capture\n", - "# #Installing plastimatch\n", - "# !apt-get install plastimatch " + "#Uncomment %%capture to hide the stdout from installing packages\n", + "#%%capture\n", + "\n", + "# #Install apt packages\n", + "# !apt-get update \\\n", + "# && apt-get install -y --no-install-recommends \\\n", + "# dcm2niix\\\n", + "# lz4\\\n", + "# pigz\\\n", + "# #plastimatch\\\n", + "# wget\\\n", + "# zip\\\n", + "# && rm -rf /var/lib/apt/lists/*" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": { "id": "cMi94BlAQrb5" }, "outputs": [], "source": [ + "# #Uncomment %%capture to hide the stdout from installing packages\n", "# %%capture\n", "# #install s5cmd\n", - "# !wget \"https://github.com/peak/s5cmd/releases/download/v2.0.0/s5cmd_2.0.0_Linux-64bit.tar.gz\"\n", - "# !tar -xvzf \"s5cmd_2.0.0_Linux-64bit.tar.gz\"\n", - "# !rm \"s5cmd_2.0.0_Linux-64bit.tar.gz\"\n", - "# !mv s5cmd /usr/local/bin/s5cmd" + "# !wget \"https://github.com/peak/s5cmd/releases/download/v2.0.0/s5cmd_2.0.0_Linux-64bit.tar.gz\"\\\n", + "# && tar -xvzf \"s5cmd_2.0.0_Linux-64bit.tar.gz\"\\\n", + "# && rm \"s5cmd_2.0.0_Linux-64bit.tar.gz\"\\\n", + "# && mv s5cmd /usr/local/bin/s5cmd" ] }, { @@ -89,23 +165,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "mWLvDAwIQcg1", - "outputId": "663f9297-b935-437e-e57e-b8184c7e7665" + "outputId": "71696ecd-3359-46df-e573-7032cb8bc9db" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ - "Tue Apr 18 16:24:28 2023\n", + "Fri Sep 22 22:37:51 2023\n", "\n", "Current directory :/content\n", - "Python version : 3.9.16 (main, Dec 7 2022, 01:11:51) \n" + "Python version : 3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0]\n" ] } ], @@ -123,6 +199,7 @@ "from datetime import datetime\n", "import psutil\n", "import matplotlib.pyplot as plt\n", + "import subprocess\n", "curr_dir = Path().absolute()\n", "\n", "print(time.asctime(time.localtime()))\n", @@ -141,7 +218,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": { "id": "gy6QqWR-jjdP", "tags": [ @@ -165,35 +242,35 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "zPptwqXbw0TD", - "outputId": "28fb5c64-f57b-4cb8-f695-eaac9c1fab2d" + "outputId": "7010ec2b-8328-4278-e87d-470c2a832739" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ - "--2023-04-18 16:24:39-- https://raw.githubusercontent.com/vkt1414/Cloud-Resources-Workflows/main/sampleManifests/batch_1.csv\n", - "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n", - "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\n", + "--2023-09-22 22:37:51-- https://raw.githubusercontent.com/ImagingDataCommons/Cloud-Resources-Workflows/main/sampleManifests/batch_1.csv\n", + "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.109.133, 185.199.111.133, 185.199.108.133, ...\n", + "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.109.133|:443... connected.\n", "HTTP request sent, awaiting response... 200 OK\n", "Length: 139861 (137K) [text/plain]\n", "Saving to: ‘batch_1.csv’\n", "\n", - "\rbatch_1.csv 0%[ ] 0 --.-KB/s \rbatch_1.csv 100%[===================>] 136.58K --.-KB/s in 0.02s \n", + "batch_1.csv 100%[===================>] 136.58K --.-KB/s in 0.01s \n", "\n", - "2023-04-18 16:24:39 (5.39 MB/s) - ‘batch_1.csv’ saved [139861/139861]\n", + "2023-09-22 22:37:51 (10.9 MB/s) - ‘batch_1.csv’ saved [139861/139861]\n", "\n" ] } ], "source": [ - "# !wget https://raw.githubusercontent.com/vkt1414/Cloud-Resources-Workflows/main/sampleManifests/batch_1.csv\n", + "# !wget https://raw.githubusercontent.com/ImagingDataCommons/Cloud-Resources-Workflows/main/sampleManifests/batch_1.csv\n", "# csvFilePath = glob.glob('*.csv')[0]\n" ] }, @@ -208,20 +285,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "LZMjMRsyQyCH", - "outputId": "d91cd934-8660-4c42-ecef-5d34e7b0b2ca" + "outputId": "a46b306e-c274-4404-ee13-0c3dba79f4b2" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ - "read in 0.016416072845458984 seconds\n" + "read in 0.016353845596313477 seconds\n" ] } ], @@ -234,7 +311,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": { "id": "jDxZvqDlR5Cc" }, @@ -254,7 +331,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": { "id": "lx_U7rRjtRYk" }, @@ -270,113 +347,133 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": { "id": "QFG0KcZ_QPyG" }, "outputs": [], "source": [ - "def download_dicom_data(series_id):\n", - "\n", + "def download_dicom_data(series_id: str) -> None:\n", " \"\"\"\n", " Download raw DICOM data into \"idc_data\" folder.\n", "\n", + " Args:\n", + " series_id: The DICOM Tag SeriesInstanceUID of the DICOM series to be converted.\n", " \"\"\"\n", + "\n", + " # Attempt to remove the directory for the series if it exists\n", " try:\n", " shutil.rmtree(f'idc_data/{series_id}')\n", " except OSError:\n", " pass\n", + "\n", + " # Access the global dataframe variable\n", " global cohort_df\n", + "\n", + " # Get the series data from the dataframe\n", " gs_file_path = \"s5cmd_manifest.txt\"\n", - " #when bigquery is used the following line could be used\n", - " #cohort_df = bq_client.query(selection_query).to_dataframe()\n", " series_df=cohort_df[cohort_df['SeriesInstanceUID']==series_id]\n", + "\n", + " # Write the URLs to a file\n", " series_df[\"s5cmdUrls\"].to_csv(gs_file_path, header = False, index = False)\n", - " #remove double quotes from the manifest file\n", - " !sed -i 's/\"//g' s5cmd_manifest.txt \n", "\n", + " # Remove double quotes from the manifest file\n", + " !sed -i 's/\"//g' s5cmd_manifest.txt\n", + "\n", + " # Start a timer for the download\n", " start_time = time.time()\n", " print(\"Copying files from IDC buckets..\")\n", "\n", - " !s5cmd --no-sign-request --endpoint-url https://storage.googleapis.com run s5cmd_manifest.txt >> /dev/null\n", + " # Download the files and suppress output\n", + " !s5cmd --no-sign-request --endpoint-url https://storage.googleapis.com run s5cmd_manifest.txt >> /dev/null\n", "\n", + " # Calculate and print elapsed time\n", " elapsed = time.time() - start_time\n", - " print(\"Done in %g seconds.\"%elapsed)" + " print(\"Done in %g seconds.\"%elapsed)\n" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": { "id": "s0SPIZ5RTxDb" }, "outputs": [], "source": [ - "def convert_dicom_to_nifti(series_id):\n", - " if converterType.lower()=='dcm2niix':\n", - " try:\n", - " shutil.rmtree(f'dcm2niix/{series_id}')\n", - " except OSError:\n", - " pass\n", - " os.mkdir(f'dcm2niix/{series_id}')\n", - "\n", - " !dcm2niix -z y -f %j_%p_%t_%s -b n -m y -o /{curr_dir}/dcm2niix/{series_id} /{curr_dir}/idc_data/\n", - " else:\n", - " try:\n", - " shutil.rmtree(f'plastimatch/{series_id}')\n", - " except OSError:\n", - " pass\n", - " os.mkdir(f'plastimatch/{series_id}')\n", - " \"\"\"\n", - " Make sure to check the s5cmd urls for the destination directory and \n", - " plastimatch input directory must be changed accordingly\n", - " dcm2niix, however, checks upto depth 5 to find DICOM files\n", + "def convert_dicom_to_nifti(series_id: str) -> None:\n", + " \"\"\"\n", + " Converts a DICOM series to a NIfTI file.\n", "\n", - " \"\"\"\n", - " !plastimatch convert --input /{curr_dir}/idc_data/{series_id} --output-img /{curr_dir}/plastimatch/{series_id}/{series_id}.nii.gz\n", + " Args:\n", + " series_id: The DICOM Tag SeriesInstanceUID of the DICOM series to be converted.\n", + " \"\"\"\n", "\n", + " # Determine which converter to use based on the converterType variable\n", + " converter = \"dcm2niix\" if converterType.lower() == \"dcm2niix\" else \"plastimatch\"\n", "\n", + " # Attempt to remove the directory for the series if it exists\n", " try:\n", - " shutil.rmtree('idc_data')\n", + " shutil.rmtree(f\"{converter}/{series_id}\")\n", " except OSError:\n", - " pass\n", - " os.mkdir('idc_data')" + " pass\n", + "\n", + " # Create a new directory for the series\n", + " os.mkdir(f\"{converter}/{series_id}\")\n", + "\n", + " # Run the appropriate converter command and capture the output\n", + " if converter == \"dcm2niix\":\n", + " result = subprocess.run(f\"dcm2niix -z y -f %j_%p_%t_%s -b n -m y -o {curr_dir}/dcm2niix/{series_id} {curr_dir}/idc_data/\", shell=True, capture_output=True, text=True)\n", + " print(result.stdout)\n", + " else:\n", + " subprocess.run(f\"plastimatch convert --input {curr_dir}/idc_data/{series_id} --output-img {curr_dir}/plastimatch/{series_id}/{series_id}.nii.gz\", shell=True)\n", + "\n", + " # Attempt to remove the input directory for the DICOM series if it exists\n", + " try:\n", + " shutil.rmtree(\"idc_data\")\n", + " except OSError:\n", + " pass\n", + "\n", + " # Create a new input directory for the DICOM series\n", + " os.mkdir(\"idc_data\")\n" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": { - "id": "fGX6gofuPhjf" + "id": "oKATbtgwPjX9" }, "outputs": [], "source": [ - "# class MemoryMonitor:\n", - "# def __init__(self):\n", - "# self.keep_measuring = True\n", - "\n", - "# def measure_usage(self):\n", - "# cpu_usage = []\n", - "# ram_usage_mb=[]\n", - "# disk_usage_all=[]\n", - "# time_stamps = []\n", - "# start_time = time.time()\n", - "# while self.keep_measuring:\n", - "# cpu = psutil.cpu_percent()\n", - "# ram = psutil.virtual_memory()\n", - "# disk_used= psutil.disk_usage('/').used/1024/1024/1024\n", - "# disk_total= psutil.disk_usage('/').total/1024/1024/1024\n", - "# ram_total_mb = psutil.virtual_memory().total / 1024 / 1024\n", - "# ram_mb = (ram.total - ram.available) / 1024 / 1024\n", - "\n", - "# cpu_usage.append(cpu)\n", - "# ram_usage_mb.append(ram_mb)\n", - "# disk_usage_all.append(disk_used)\n", - "\n", - "# time_stamps.append(time.time()- start_time)\n", - "# sleep(1)\n", - "\n", - "# return cpu_usage, ram_usage_mb, time_stamps, ram_total_mb, disk_usage_all, disk_total" + "def download_and_process_series(series_id: str) -> None:\n", + " \"\"\"Downloads and processes a DICOM series.\n", + "\n", + " Args:\n", + " series_id: The identifier of the DICOM series to be processed.\n", + " \"\"\"\n", + "\n", + " # Create a DataFrame to track the processing times.\n", + " log = pd.DataFrame({'SeriesInstanceUID': [series_id]})\n", + "\n", + " # Start the timer for downloading the DICOM series.\n", + " start_time = time.time()\n", + " download_dicom_data(series_id)\n", + " download_time = time.time() - start_time\n", + "\n", + " # Add the download time to the DataFrame.\n", + " log['download_time'] = download_time\n", + "\n", + " # Start the timer for converting the DICOM series to NIfTI.\n", + " start_time = time.time()\n", + " convert_dicom_to_nifti(series_id)\n", + " convert_dicom_to_nifti_time = time.time() - start_time\n", + "\n", + " # Add the conversion time to the DataFrame.\n", + " log['NiftiConverter_time'] = convert_dicom_to_nifti_time\n", + "\n", + " # Update the global runtime statistics DataFrame.\n", + " global runtime_stats\n", + " runtime_stats = pd.concat([runtime_stats, log], ignore_index=True, axis=0)\n" ] }, { @@ -384,76 +481,74 @@ "source": [ "class MemoryMonitor:\n", " def __init__(self):\n", + " # Flag to control the measurement loop\n", " self.keep_measuring = True\n", + " # Get the path of the working disk\n", " self.working_disk_path = self.get_working_disk_path()\n", "\n", " def get_working_disk_path(self):\n", + " # This code is specific to Terra/SB-CGC as multiple disks are mounted on the platforms\n", + "\n", + " # Get all disk partitions\n", " partitions = psutil.disk_partitions()\n", " for partition in partitions:\n", + " # If root partition, return root path\n", " if partition.mountpoint == '/':\n", " return '/'\n", + " # If cromwell_root is in mountpoint, return cromwell_root path\n", " elif '/cromwell_root' in partition.mountpoint:\n", " return '/cromwell_root'\n", - " return '/' # Default to root directory if no specific path is found\n", + " # Default to root directory if no specific path is found\n", + " return '/'\n", "\n", " def measure_usage(self):\n", + " # Initialize lists to store measurements\n", " cpu_usage = []\n", " ram_usage_mb = []\n", " disk_usage_all = []\n", " time_stamps = []\n", + "\n", + " # Record start time\n", " start_time = time.time()\n", + "\n", " while self.keep_measuring:\n", + " # Measure CPU usage\n", " cpu = psutil.cpu_percent()\n", + "\n", + " # Measure RAM usage\n", " ram = psutil.virtual_memory()\n", + "\n", + " # Measure disk usage\n", " disk_usage = psutil.disk_usage(self.working_disk_path)\n", + "\n", + " # Calculate used and total disk space in GB\n", " disk_used = disk_usage.used / 1024 / 1024 / 1024\n", " disk_total = disk_usage.total / 1024 / 1024 / 1024\n", + "\n", + " # Calculate total and used RAM in MB\n", " ram_total_mb = ram.total / 1024 / 1024\n", " ram_mb = (ram.total - ram.available) / 1024 / 1024\n", "\n", + " # Append measurements to lists\n", " cpu_usage.append(cpu)\n", " ram_usage_mb.append(ram_mb)\n", " disk_usage_all.append(disk_used)\n", "\n", + " # Record timestamp relative to start time\n", " time_stamps.append(time.time() - start_time)\n", + "\n", + " # Wait for a second before next measurement\n", " sleep(1)\n", "\n", + " # Return all measurements and totals\n", " return cpu_usage, ram_usage_mb, time_stamps, ram_total_mb, disk_usage_all, disk_total\n" ], "metadata": { "id": "aAQcXTtAGUfZ" }, - "execution_count": null, + "execution_count": 12, "outputs": [] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "oKATbtgwPjX9" - }, - "outputs": [], - "source": [ - "def download_and_process_series(series_id):\n", - " log = pd.DataFrame({'SeriesInstanceUID': [series_id]})\n", - "\n", - " start_time = time.time()\n", - " download_dicom_data( series_id)\n", - " download_time = time.time() - start_time\n", - "\n", - " log['download_time'] = download_time\n", - "\n", - " start_time = time.time()\n", - " convert_dicom_to_nifti(series_id)\n", - " convert_dicom_to_nifti_time = time.time() - start_time\n", - "\n", - " log['NiftiConverter_time'] = convert_dicom_to_nifti_time\n", - "\n", - " global runtime_stats\n", - " runtime_stats = pd.concat([runtime_stats, log], ignore_index=True, axis=0)\n", - "\n" - ] - }, { "cell_type": "markdown", "metadata": { @@ -465,14 +560,14 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "id": "ZTtOJ7CtQYkX", - "outputId": "b803de2e-c6d9-42b9-ce59-e34f82acd8ce" + "outputId": "6495a8a0-6ff4-4f6a-a8f7-974cc020616c" }, "outputs": [ { @@ -480,12 +575,13 @@ "name": "stdout", "text": [ "Copying files from IDC buckets..\n", - "Done in 0.622821 seconds.\n", - "Chris Rorden's dcm2niiX version v1.0.20181125 (JP2:OpenJPEG) GCC9.3.0 (64-bit Linux)\n", + "Done in 1.61305 seconds.\n", + "Chris Rorden's dcm2niiX version v1.0.20211006 (JP2:OpenJPEG) GCC11.2.0 x86-64 (64-bit Linux)\n", "Found 181 DICOM file(s)\n", - "Convert 181 DICOM as //content/dcm2niix/1.3.6.1.4.1.14519.5.2.1.7009.9004.118722452529394350711166589345/1.3.6.1.4.1.14519.5.2.1.7009.9004.11872245252939435071116658934_1_OPA_GE_LSPR16_STANDARD_330_2.5_120_80_58.2_1.4_20000102000000_2 (512x512x181x1)\n", - "compress: \"/usr/bin/pigz\" -n -f -6 \"//content/dcm2niix/1.3.6.1.4.1.14519.5.2.1.7009.9004.118722452529394350711166589345/1.3.6.1.4.1.14519.5.2.1.7009.9004.11872245252939435071116658934_1_OPA_GE_LSPR16_STANDARD_330_2.5_120_80_58.2_1.4_20000102000000_2.nii\"\n", - "Conversion required 6.255639 seconds (0.366965 for core code).\n" + "Convert 181 DICOM as /content/dcm2niix/1.3.6.1.4.1.14519.5.2.1.7009.9004.118722452529394350711166589345/1.3.6.1.4.1.14519.5.2.1.7009.9004.118722452529394350711166589345_1,OPA,GE,LSPR16,STANDARD,330,2.5,120,80,58.2,1.4_20000102000000_2 (512x512x181x1)\n", + "Compress: \"/usr/bin/pigz\" -b 960 -n -f -6 \"/content/dcm2niix/1.3.6.1.4.1.14519.5.2.1.7009.9004.118722452529394350711166589345/1.3.6.1.4.1.14519.5.2.1.7009.9004.118722452529394350711166589345_1,OPA,GE,LSPR16,STANDARD,330,2.5,120,80,58.2,1.4_20000102000000_2.nii\"\n", + "Conversion required 6.393267 seconds (0.340352 for core code).\n", + "\n" ] }, { @@ -494,7 +590,7 @@ "text/plain": [ "
" ], - "image/png": 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ql1bNQKvZ4QAAAAAAMkHRfgeK/euCVuw+IUka0LqyydEAAAAAALJC0X4Hmr3+F6WlG2pZ5S7VDfI1OxwAAAAAQBYo2u8wJxIv6tMdf0iSBvIsOwAAAAA4NYr2O0zU978qNc1QaIWSaljez+xwAAAAAAA3QNF+B4m3XdKy7cclSQPaMMoOAAAAAM6Oov0O8v7633T5Sroaliuh0AolzQ4HAAAAAHATFO13iD+TU7Rk6zFJ0oA2lWWxWEyOCAAAAABwMxTtd4i5P/ymS6npqlvWqpaVS5kdDgAAAAAgGyja7wBnz1/Wf2L+HmVvzSg7AAAAABQUFO13gHk/HtWFy2mqUcZHbaqXNjscAAAAAEA2UbQXckkXU7Xgx98lSQPbVGKUHQAAAAAKEIr2Qm7hpt91LuWKqvoXV9saAWaHAwAAAADIAacu2tPS0jR69GiFhITI29tbFStW1NixY2UYhr2PYRgaM2aMypQpI29vb4WFhenIkSMmRu08klOuaN6PRyVJka0rycWFUXYAAAAAKEicumh/6623NHv2bM2YMUM///yz3nrrLU2aNEnTp0+395k0aZKmTZumqKgobdmyRUWLFlV4eLguXbpkYuTO4T8xx5R4IVUV7iqqjrXLmB0OAAAAACCH3MwO4EY2bdqkhx9+WB07dpQklS9fXh999JG2bt0q6eoo+9SpUzVq1Cg9/PDDkqRFixbJ399fK1asULdu3TI9bkpKilJSUuzrNpstj68k/124fEUf/PCbJCmyVSW5MsoOAAAAAAWOU4+0N2vWTGvWrNHhw4clSXv27NHGjRvVvn17SdLRo0cVFxensLAw+z5Wq1VNmjRRTExMlsedMGGCrFarfQkKCsrbCzHBki2x+uv8ZQX7FdHD9QLNDgcAAAAAcAuceqT9pZdeks1mU7Vq1eTq6qq0tDS9+eabioiIkCTFxcVJkvz9/R328/f3t2/LzMiRIzV06FD7us1mK1SF+6XUNM3ZcHWU/flWFeXm6tS/zQAAAAAAsuDURfvHH3+sxYsXa8mSJapZs6Z2796twYMHKzAwUL169brl43p6esrT0zMXI3UuH28/rtPnUnS3r7c6NyhrdjgAAAAAgFvk1EX7iy++qJdeesn+bHrt2rV17NgxTZgwQb169VJAwNVXmMXHx6tMmf9NtBYfH6969eqZEbLpLl9JV9T3v0qSnr2vgjzcGGUHAAAAgILKqSu6CxcuyMXFMURXV1elp6dLkkJCQhQQEKA1a9bYt9tsNm3ZskWhoaH5Gquz+GznHzqZdEmli3vq0YaF55Z/AAAAALgTOfVI+4MPPqg333xTwcHBqlmzpnbt2qV3331XTz31lCTJYrFo8ODBGjdunCpXrqyQkBCNHj1agYGB6tSpk7nBmyA1LV0z1/0iSXrmvorycnc1OSIAAAAAwO1w6pH26dOn69///reef/55Va9eXcOGDdMzzzyjsWPH2vsMHz5cAwYMUL9+/dSoUSMlJydr1apV8vLyMjFyc6zYdUJ/nL2oUsU81KNxsNnhAHesDRs26MEHH1RgYKAsFotWrFjhsN0wDI0ZM0ZlypSRt7e3wsLCdOTIEYc+CQkJioiIkI+Pj3x9fdWnTx8lJyc79Nm7d6/uvfdeeXl5KSgoSJMmTcoQyyeffKJq1arJy8tLtWvX1tdff53r1wsAAIC849RFe/HixTV16lQdO3ZMFy9e1K+//qpx48bJw8PD3sdiseiNN95QXFycLl26pO+++05VqlQxMWpzpKUbmvX3s+xP31tB3h6MsgNmOX/+vOrWrauZM2dmun3SpEmaNm2aoqKitGXLFhUtWlTh4eG6dOmSvU9ERIR++uknRUdHa+XKldqwYYP69etn326z2dS2bVuVK1dOO3bs0Ntvv63XXntNc+bMsffZtGmTunfvrj59+mjXrl3q1KmTOnXqpP379+fdxQMAACBXWQzDMMwOwmw2m01Wq1VJSUny8fExO5xb8n+7T2jQ0t3yLeKujSNaq5inUz/5ABQqN8ohFotFy5cvtz+yYxiGAgMD9cILL2jYsGGSpKSkJPn7+2vBggXq1q2bfv75Z9WoUUPbtm1Tw4YNJUmrVq1Shw4d9McffygwMFCzZ8/WK6+8ori4OPsPmS+99JJWrFihgwcPSpIee+wxnT9/XitXrrTH07RpU9WrV09RUVG3fW0AcDOFOYcU5msDkD+ym0eceqQd2ZOebmjG2qvPsvdpHkLBDjixo0ePKi4uTmFhYfY2q9WqJk2aKCYmRpIUExMjX19fe8EuSWFhYXJxcdGWLVvsfVq2bOlw51F4eLgOHTqks2fP2vtcf55rfa6dJzMpKSmy2WwOCwAAAMxD0V4IrPopTkdOJ6u4l5t6NS9vdjgAbiAuLk6S5O/v79Du7+9v3xYXF6fSpUs7bHdzc5Ofn59Dn8yOcf05supzbXtmJkyYIKvVal+CgngLBQAAgJko2gs4wzA0/e9R9t7NQ+Tj5W5yRAAKspEjRyopKcm+HD9+3OyQAAAA7mgU7QWYYRiavf5X/XzKpqIernqKUXbA6QUEBEiS4uPjHdrj4+Pt2wICAnT69GmH7VeuXFFCQoJDn8yOcf05supzbXtmPD095ePj47AAAADAPBTtBdSVtHS9smK/Jq06JEmKbF1JvkU8brIXALOFhIQoICBAa9assbfZbDZt2bJFoaGhkqTQ0FAlJiZqx44d9j5r165Venq6mjRpYu+zYcMGpaam2vtER0eratWqKlGihL3P9ee51ufaeQAAAOD8KNoLoHOXUvXUwu1asiVWFos0qmN1PXdfRbPDAvC35ORk7d69W7t375Z0dfK53bt3KzY2VhaLRYMHD9a4ceP0xRdfaN++ferZs6cCAwPtM8xXr15d7dq1U9++fbV161b9+OOP6t+/v7p166bAwEBJUo8ePeTh4aE+ffrop59+0rJly/Tee+9p6NCh9jgGDRqkVatWafLkyTp48KBee+01bd++Xf3798/vjwQA8lVaWppGjx6tkJAQeXt7q2LFiho7dqyuf2mSYRgaM2aMypQpI29vb4WFhenIkSMmRg0AWTBgJCUlGZKMpKQks0O5qT/OXjDCp6w3yo1YaVQb9Y2xev8ps0MC7nj/zCHr1q0zJGVYevXqZRiGYaSnpxujR482/P39DU9PT6NNmzbGoUOHHI75119/Gd27dzeKFStm+Pj4GL179zbOnTvn0GfPnj1GixYtDE9PT+Puu+82Jk6cmCG2jz/+2KhSpYrh4eFh1KxZ0/jqq69u69oAICfMyiFvvvmmUbJkSWPlypXG0aNHjU8++cQoVqyY8d5779n7TJw40bBarcaKFSuMPXv2GA899JAREhJiXLx4MVvnID8CuF3ZzSO8p10F5z2be/9IVJ+F23XmXIruKu6peb0aqXZZq9lhAXe8gpJDbkVhvjYAec+sHPLAAw/I399fH374ob2tS5cu8vb21n//+18ZhqHAwEC98MILGjZsmCQpKSlJ/v7+WrBggbp163bTc5AfAdwu3tNeyKz+KU5d34/RmXMpqhZQXCsim1OwAwAAZKJZs2Zas2aNDh8+LEnas2ePNm7cqPbt20u6+thSXFycwsLC7PtYrVY1adJEMTExmR4zJSVFNpvNYQGA/OBmdgC4McMw9OHGo3rz659lGNJ9Ve7SjB71VZxXuwEAAGTqpZdeks1mU7Vq1eTq6qq0tDS9+eabioiIkCTFxcVJkvz9/R328/f3t2/7pwkTJuj111/P28ABIBOMtDuxK2npGrViv8Z9dbVgf7xpsD7s1ZCCHQAA4AY+/vhjLV68WEuWLNHOnTu1cOFCvfPOO1q4cOEtH3PkyJFKSkqyL8ePH8/FiAEga4y0O6lzl1LVf8kurT98RhaL9EqH6urTIkQWi8Xs0AAAAJzaiy++qJdeesn+bHrt2rV17NgxTZgwQb169VJAQIAkKT4+XmXKlLHvFx8fr3r16mV6TE9PT3l6euZ57ADwT4y0O6ETiRf1aFSM1h8+I293V0U9fo+evrcCBTsAAEA2XLhwQS4ujl9zXV1dlZ6eLkkKCQlRQECA1qxZY99us9m0ZcsWhYaG5musAHAzjLQ7mX1/JOmphdvsM8R/2Kuh6pT1NTssAACAAuPBBx/Um2++qeDgYNWsWVO7du3Su+++q6eeekqSZLFYNHjwYI0bN06VK1dWSEiIRo8ercDAQHXq1Mnc4AHgHyjanci3P8Vp0NLdupiapmoBxfXhk410t6+32WEBAAAUKNOnT9fo0aP1/PPP6/Tp0woMDNQzzzyjMWPG2PsMHz5c58+fV79+/ZSYmKgWLVpo1apV8vLyMjFyAMiI97TL/Pds/nOG+JZV7tJMZogHCgyzc0heKszXBiDvFeYcUpivDUD+yG4eYaTdZFfS0vXalz/pv5tjJUkRTYL1+kM15ebKdANAfkpJSdGWLVt07NgxXbhwQXfddZfq16+vkJAQs0MDAADAHYyi3UTMEA+Y78cff9R7772nL7/8UqmpqbJarfL29lZCQoJSUlJUoUIF9evXT88++6yKFy9udrgAAAC4wzCca5KT180Q7+XuwgzxgAkeeughPfbYYypfvry+/fZbnTt3Tn/99Zf++OMPXbhwQUeOHNGoUaO0Zs0aValSRdHR0WaHDAAAgDsMI+0m2PdHkvos3KbTzBAPmKpjx4767LPP5O6e+fwRFSpUUIUKFdSrVy8dOHBAp06dyucIAQAAcKejaM9n188QX9W/uOb1ZoZ4wCzPPPNMtvvWqFFDNWrUyMNoAAAAgIwo2vOJYRia9+PvGvfVARmGdG/lUpoV0YAZ4gEn9dtvv+nixYuqXr26XFx4kggAAADm4JtoPriSlq4x//eTxq68WrD3aBKs+U82omAHnEBqaqpeffVVPfjgg3rzzTeVlpam7t27q3LlyqpTp45q1aql33//3ewwAQAAcIeiaM9jySlX9PSi7frP5mP2GeLf7FSLV7oBTuKll17S7NmzFRAQoHnz5qlz587atWuXlixZoqVLl8rNzU2vvPKK2WECAADgDsXt8XnoZOJFPbVgmw7GnZOXu4umPlZf7WoFmB0WgOt8+umnWrBggTp06KDDhw+rWrVq+uqrr9S+fXtJUunSpRUREWFylAAAALhTUbTnkf0nkvTUgqszxJcqdnWG+LpBvmaHBeAfTp48qbp160qSqlSpIk9PT1WqVMm+vUqVKoqLizMrPAAAANzhKNrzQPSBeA38aJd9hvgPn2yosiWKmB0WgEykpaU5vPLNzc1Nrq6u9nUXFxcZhmFGaAAAAABFe24yDEPzf/xdY6+bIX5mRAP5MOEc4NRWr14tq9UqSUpPT9eaNWu0f/9+SVJiYqKJkQEAAOBOR9GeS66kpeuNlQe0KOaYpKszxL/+UE25M+Ec4PR69erlsP7P97dbLJb8DAcAAACwo2jPBckpV9R/yU59f+iMLBZpZPtq6ntvBb7oAwVAenq62SEAAAAAWaJov02nki6q9/zrZ4ivp3a1ypgdFgAAgNP4/ffftXv3bh07dkwXLlzQXXfdpfr16ys0NFReXl5mhwcATo2i/TYwQzxQ8G3YsCFb/Vq2bJnHkQBA4fPxxx9LkurVqyd/f38FBgbK29tbCQkJ+vXXX+Xl5aWIiAiNGDFC5cqVMzlaAHBOFO236LsD8Rrw9wzxVfyLad6TjZghHiiAWrVqZX+UJatZ4i0Wi9LS0vIzLAAo8OrXr29/G8f+/ftVo0YNh+0pKSmKiYnR0qVL1bBhQ82aNUuPPvqoGaECgFOjaM8hZogHCpcSJUqoePHievLJJ/XEE0+oVKlSZocEAIXCxIkTFRoaKqvVqrJly2bY7unpqVatWqlVq1Z688039fvvv+d/kABQADC1eQ799ud5jf/6ZxmG1L1xsOY92YiCHSjATp06pbfeeksxMTGqXbu2+vTpo02bNsnHx0dWq9W+AAByJjw8PNt9S5YsqXvuuScPowGAgitHI+3p6elav369fvjhhwwTiYSFhSkoKCiv4nQaFe8qpvGP1FbixcvMEA8UAh4eHnrsscf02GOPKTY2VgsWLFD//v2VkpKiXr166fXXX5ebGzclAUBuMQxD69at08WLF9WsWTOVKFHC7JAAwKlla6T94sWLGjdunIKCgtShQwd98803SkxMlKurq3755Re9+uqrCgkJUYcOHbR58+a8jtl0XRsFqV/LihTsQCETHBysMWPG6LvvvlOVKlU0ceJE2Ww2s8MCgAIrMTFRkhQaGqq+ffvKZrPp3nvvVVhYmB588EFVr15de/fuNTdIAHBy2Sraq1Spor1792ru3Lmy2WyKiYnRZ599pv/+97/6+uuvFRsbq19//VX33nuvunXrprlz5+Z13ACQq1JSUrRkyRKFhYWpVq1aKlWqlL766iv5+fmZHRoAFFijRo2SJHXu3Fn79u1Tu3btlJaWppiYGG3ZskXVq1fXK6+8YnKUAODcLEZW0yVf5+eff1b16tWzdcDU1FTFxsaqYsWKtx1cfrHZbLJarUpKSpKPj4/Z4QDIR1u3btX8+fO1dOlSlS9fXr1799bjjz+eo2K9MOeQwnxtAPJeYGCgTp06paSkJJ07d05BQUFau3atWrVqJelqDn7ooYcUFxdnbqC3gPwI4HZlN49k60HN7BbskuTu7l6gCnYAd7amTZsqODhYAwcOtE+CtHHjxgz9HnroofwODQAKvNOnT9v/vvvuu+Xl5eUwB1JwcLDOnDljRmgAUGDc8uxKV65c0fvvv6/vv/9eaWlpat68uSIjI+Xl5ZWb8QFAnouNjdXYsWOz3M572gHg1qSnpzusu7q6OswJxPxAAHBzt1y0Dxw4UIcPH1bnzp2VmpqqRYsWafv27froo49yMz4AyFP//EIJAMh9UVFR8vLy0pUrV7RgwQKVKlVKknTu3DmTIwMA55fton358uV65JFH7OvffvutDh06JFdXV0lX38XZtGnT3I8QAAAABVJQUJBiY2M1c+ZMubi4KCAgQP/5z38c+gQHB5sUHQAUDNku2ufNm6eFCxdq1qxZCgwMVIMGDfTss8+qS5cuSk1N1dy5c9WoUaO8jBUActXmzZuz/WPjhQsXdPToUdWsWTOPowKAwmPfvn2yWq3at28fk7UBwC3K1ivfJOnLL79U9+7d1apVK02fPl1z5syRj4+PXnnlFY0ePVpBQUFasmRJXsYKALnqiSeeUHh4uD755BOdP38+0z4HDhzQyy+/rIoVK2rHjh25ct60tDSNHj1aISEh8vb2VsWKFTV27Fhd/zIPwzA0ZswYlSlTRt7e3goLC9ORI0ccjpOQkKCIiAj5+PjI19dXffr0UXJyskOfvXv36t5777VP/jRp0qRcuQYAAADkjxw90/7YY48pPDxcw4cPV3h4uKKiojR58uS8ig0A8tSBAwc0e/ZsjRo1Sj169FCVKlUUGBgoLy8vnT17VgcPHlRycrIeeeQRffvtt6pdu3aunPett97S7NmztXDhQtWsWVPbt29X7969ZbVaNXDgQEnSpEmTNG3aNC1cuFAhISEaPXq0wsPDdeDAAfuEnxERETp16pSio6OVmpqq3r17q1+/fvYfUG02m9q2bauwsDBFRUVp3759euqpp+Tr66t+/frlyrUAwI1cvHjRYX3kyJFKSUmxr7u6umrs2LFMZAwAN5Ct97RnZsOGDYqMjFS7du0KfLLlPZsAtm/fro0bN+rYsWO6ePGiSpUqpfr16+v++++/6Tvbc5pDHnjgAfn7++vDDz+0t3Xp0kXe3t7673//K8MwFBgYqBdeeEHDhg2TJCUlJcnf318LFixQt27d9PPPP6tGjRratm2bGjZsKElatWqVOnTooD/++EOBgYGaPXu2XnnlFcXFxcnDw0OS9NJLL2nFihU6ePBgtj4X8iOA2zFlyhQNHTrUnkOKFy+umjVrytvbW5J08OBBDR8+XEOGDDE50pwjPwK4XdnNI9m+PT42NlZdu3ZV7dq1FRERocqVK2vHjh0qUqSI6tatq2+++SZXAgcAMzRs2FCDBw/WlClTFBUVpXHjxqlLly43LdhvRbNmzbRmzRodPnxYkrRnzx5t3LhR7du3lyQdPXpUcXFxCgsLs+9jtVrVpEkTxcTESJJiYmLk6+trL9glKSwsTC4uLtqyZYu9T8uWLe0Fu3R10tBDhw7p7NmzmcaWkpIim83msADArfrkk08ytC1ZskTr1q3TunXr9Pbbb+vjjz82ITIAKDiyXbT37NlTLi4uevvtt1W6dGk988wz8vDw0Ouvv64VK1ZowoQJ6tq1a17GCgCFwksvvaRu3bqpWrVqcnd3V/369TV48GBFRERIkuLi4iRJ/v7+Dvv5+/vbt8XFxal06dIO293c3OTn5+fQJ7NjXH+Of5owYYKsVqt9CQoKus2rBXAn++233xzWvby85OLyv6+fjRs31oEDB/I7LAAoULJdtG/fvl1vvvmm2rVrp3fffVd79+61b6tevbo2bNjgMCqUW06cOKHHH39cJUuWlLe3t2rXrq3t27fbt2dnsiYAcCYff/yxFi9erCVLlmjnzp1auHCh3nnnHS1cuNDs0DRy5EglJSXZl+PHj5sdEoACLCkpyWH9zJkzKl++vH09PT3d4Rl3AEBG2S7a77nnHo0ZM0bffvutRowYkemETLk9sdHZs2fVvHlzubu765tvvtGBAwc0efJklShRwt7n2mRNUVFR2rJli4oWLarw8HBdunQpV2MBgNzy4osv2kfba9eurSeeeEJDhgzRhAkTJEkBAQGSpPj4eIf94uPj7dsCAgJ0+vRph+1XrlxRQkKCQ5/MjnH9Of7J09NTPj4+DgsA3KrAwMAbbt+7d6/Kli2bT9EAQMGU7aJ90aJFSklJ0ZAhQ3TixAm9//77eRmXpKszLAcFBWn+/Plq3LixQkJC1LZtW1WsWFHS1VH2qVOnatSoUXr44YdVp04dLVq0SCdPntSKFSvyPD4AuBUXLlxwuD1UujqDcnp6uiQpJCREAQEBWrNmjX27zWbTli1bFBoaKkkKDQ1VYmKiw2vo1q5dq/T0dDVp0sTeZ8OGDUpNTbX3iY6OVtWqVR1+/ASAvNK2bVtJynQw5eLFi3r99dfVsWPH/A4LAAqUW549Pj/UqFFD4eHh+uOPP7R+/Xrdfffdev7559W3b19JV5+Tqlixonbt2qV69erZ97vvvvtUr149vffee5keNyUlxeFWLJvNpqCgIGb/BCDp6pfLnLwRI6czCD/55JP67rvv9P7776tmzZratWuX+vXrp6eeekpvvfWWpKs/Wk6cONHhlW979+51eOVb+/btFR8fr6ioKPsr3xo2bGh/5VtSUpKqVq2qtm3basSIEdq/f7+eeuopTZkyJdt3RjE7MoDb8csvv6hy5coKCgrSgAEDVKVKFUnSoUOHNGPGDF25ckW7du3KMP9GQUB+BHC7sp1HjGxITk7OTrdb7p8VT09Pw9PT0xg5cqSxc+dO4/333ze8vLyMBQsWGIZhGD/++KMhyTh58qTDfo8++qjRtWvXLI/76quvGpIyLElJSbkSN4CCJy0tzXjjjTeMwMBAw9XV1fj1118NwzCMUaNGGR988MEN901KSspRDrHZbMagQYOM4OBgw8vLy6hQoYLxyiuvGCkpKfY+6enpxujRow1/f3/D09PTaNOmjXHo0CGH4/z1119G9+7djWLFihk+Pj5G7969jXPnzjn02bNnj9GiRQvD09PTuPvuu42JEydmK8ZbvTYAuN61HNKmTRvDxcXFsFgshsViMVxcXIzw8HB7ri2IyI8Abld280i2RtrLlCmjQYMGqVevXipTpkxWxb++++47vfvuu2rZsqVGjhyZs58ZMuHh4aGGDRtq06ZN9raBAwdq27ZtiomJ0aZNm9S8eXOdPHnSIa6uXbvKYrFo2bJlmR6XkXYA//TGG29o4cKFeuONN9S3b1/t379fFSpU0LJlyzR16lT7q9YyU5hHWwrztQHIe9fnkCtXruiXX36RJFWqVClPXqmZn8iPAG5XdvOIW3YO9v333+vll1/Wa6+9prp166phw4YKDAyUl5eXzp49qwMHDigmJkZubm4aOXKknnnmmVy5iDJlyqhGjRoObdWrV9dnn30myXGypuuL9vj4eIfb5f/J09NTnp6euRIjgMJh0aJFmjNnjtq0aaNnn33W3l63bl0dPHjQxMgAoHDw8/NT48aNzQ4DAAqcbE1EV7VqVX322Wc6fPiwunbtqhMnTujTTz/V3Llz9f333+vuu+/W3Llz9fvvv+v555+Xq6trrgTXvHlzHTp0yKHt8OHDKleunKTsTdYEANlx4sQJVapUKUN7enq6w0RuAIDsefbZZ3XixIls9V22bJkWL16cxxEBQMGUrZH2a4KDg/XCCy/ohRdeyKt4HAwZMkTNmjXT+PHj1bVrV23dulVz5szRnDlzJEkWi0WDBw/WuHHjVLlyZftkTYGBgerUqVO+xAigcKhRo4Z++OEH+4+C13z66aeqX7++SVEBQMF11113qWnTppKkDz74QPfee2+GOzU3btyopUuXKjAw0P79DgDgKEdFe35r1KiRli9frpEjR+qNN95QSEiIpk6dqoiICHuf4cOH6/z58+rXr58SExPVokULrVq1KkczPwPAmDFj1KtXL504cULp6en6/PPPdejQIS1atEgrV640OzwAKHDGjh2rXr16qXLlyvrwww/14osvOmwvXry4wsLCNGfOHLVr186kKAHA+Tn1K9/yCxOJAJCkH374QW+88Yb27Nmj5ORkNWjQQGPGjLG/ZzgrhTmHFOZrA5D3rs8haWlpio2N1cWLF1WqVClVrFhRFovF7BBvGfkRwO3K1YnoAOBOcO+99yo6OtrsMACgUCpRooRKlChhdhgAUOBkayI6AAAAAACQ/yjaAUBXR4D8/PwyLCVLltTdd9+t++67T/Pnzzc7TABANp04cUKPP/64SpYsKW9vb9WuXVvbt2+3bzcMQ2PGjFGZMmXk7e2tsLAwHTlyxMSIASBzt1S0//DDD3r88ccVGhpqf5XHf/7zH23cuDFXgwOA/DJmzBi5uLioY8eOev311/X666+rY8eOcnFxUWRkpKpUqaLnnntOc+fONTtUAMBNnD17Vs2bN5e7u7u++eYbHThwQJMnT3a4PX/SpEmaNm2aoqKitGXLFhUtWlTh4eG6dOmSiZEDQEY5fqb9s88+0xNPPKGIiAjt2rVLKSkpkqSkpCSNHz9eX3/9da4HCQB5bePGjRo3bpyeffZZh/b3339f3377rT777DPVqVNH06ZNU9++fU2KEgCQHW+99ZaCgoIc7pAKCQmx/20YhqZOnapRo0bp4YcfliQtWrRI/v7+WrFihbp165bvMQNAVnI80j5u3DhFRUVp7ty5cnd3t7c3b95cO3fuzNXgACC/rF69WmFhYRna27Rpo9WrV0uSOnTooN9++y2/QwOAQuHKlSv67rvv9P777+vcuXOSpJMnTyo5OTnXz/XFF1+oYcOGevTRR1W6dGnVr1/f4U6po0ePKi4uziHvW61WNWnSRDExMZkeMyUlRTabzWEBgPyQ46L90KFDatmyZYZ2q9WqxMTE3IgJAPKdn5+fvvzyywztX375pfz8/CRJ58+fV/HixfM7NAAo8GJjY1W7dm09/PDDioyM1JkzZyRdHREfNmxYrp/vt99+0+zZs1W5cmWtXr1azz33nAYOHKiFCxdKkuLi4iRJ/v7+Dvv5+/vbt/3ThAkTZLVa7UtQUFCuxw0Amcnx7fEBAQH65ZdfVL58eYf2jRs3qkKFCrkVFwDkq9GjR+u5557TunXr1LhxY0nStm3b9PXXXysqKkqSFB0drfvuu8/MMAGgQHrppZfUsGFD7dmzRyVLlrS3P/LII3nyyFF6eroaNmyo8ePHS5Lq16+v/fv3KyoqSr169bqlY44cOVJDhw61r9tsNgp3APkix0V73759NWjQIM2bN08Wi0UnT55UTEyMhg0bptGjR+dFjACQ5/r27asaNWpoxowZ+vzzzyVJVatW1fr169WsWTNJ0gsvvGBmiABQYG3atEkxMTHy8PBwaC9fvrx9UuPcVKZMGdWoUcOhrXr16vrss88kXR2EkqT4+HiVKVPG3ic+Pl716tXL9Jienp7y9PTM9VgB4GZyXLS/9NJLSk9PV5s2bXThwgW1bNlSnp6eGjZsmAYMGJAXMQJAvmjevLmaN29udhgAUOikp6crLS0tQ/sff/yRJ48dNW/eXIcOHXJoO3z4sMqVKyfp6qR0AQEBWrNmjb1It9ls2rJli5577rlcjwcAbkeOn2m3WCx65ZVXlJCQoP3792vz5s06c+aMxo4dmxfxAUC+u3TpEpMNAUAuat26taZOnWpft1gsSk5O1quvvqoOHTrk+vmGDBmizZs3a/z48frll1+0ZMkSzZkzR5GRkfbzDx48WOPGjdMXX3yhffv2qWfPngoMDFSnTp1yPR4AuB05Hmm/xsPDI8NtRwBQUF24cEHDhw/Xxx9/rL/++ivD9sxGiAAA2fPmm2/q3//+t2rUqKFLly6pR48eOnLkiEqVKqWPPvoo18/XqFEjLV++XCNHjtQbb7yhkJAQTZ06VREREfY+w4cP1/nz59WvXz8lJiaqRYsWWrVqlby8vHI9HgC4HRbDMIyc7PDII4/IYrFkPJDFIi8vL1WqVEk9evRQ1apVcy3IvGaz2WS1WpWUlCQfHx+zwwFggsjISK1bt05jx47VE088oZkzZ+rEiRN6//33NXHiRIcvev9UmHNIYb42AHnv+hxSpEgRLV26VHv37lVycrIaNGigiIgIeXt7mx3mLSE/Arhd2c0jOR5pt1qtWrFihXx9fXXPPfdIknbu3KnExES1bdtWy5Yt01tvvaU1a9bwbCiAAuPLL7/UokWL1KpVK/Xu3Vv33nuvKlWqpHLlymnx4sU3LNoBADfn5uamxx9/3OwwAKDAuaVXvvXo0UMzZsyQi8vVR+LT09M1aNAgFS9eXEuXLtWzzz6rESNGaOPGjbkeMADkhYSEBPtrK318fJSQkCBJatGiBZMSAcBt+vrrr1WkSJEM7dffqRkSEmJCZADg/HJctH/44Yf68ccf7QW7JLm4uGjAgAFq1qyZxo8fr/79++vee+/N1UABIC9VqFBBR48eVXBwsKpVq6aPP/5YjRs31pdffilfX1+zwwOAAq1Hjx6yWCz651OZ19osFotatGihFStWqESJEiZFCQDOKcezx1+5ckUHDx7M0H7w4EH7RE1eXl6ZPvcOAM6qd+/e2rNnj6Srr7acOXOmvLy8NGTIEL344osmRwcABduKFSvUqFEjRUdHKykpSUlJSYqOjlaTJk20cuVKbdiwQX/99ZeGDRtmdqgA4HRyPNL+xBNPqE+fPnr55ZfVqFEjSdK2bds0fvx49ezZU5K0fv161axZM3cjBYA8NGTIEPvfYWFhOnjwoHbs2KFKlSqpTp06JkYGAAXfSy+9pA8++EDNmjWzt7Vp00ZeXl7q16+ffvrpJ02dOlVPPfWUiVECgHPKcdE+ZcoU+fv7a9KkSYqPj5ck+fv7a8iQIRoxYoQkqW3btmrXrl3uRgoA+ahcuXKyWq3cGg8AueDo0aOZzozs4+Oj3377TZJUuXJl/fnnn/kdGgA4vRzfHu/q6qpXXnlFp06dUmJiohITE3Xq1Cm9/PLLcnV1lSQFBwerbNmyuR4sAOSVt956S8uWLbOvd+3aVSVLltTdd99tv20eAHBr6tWrpxdffFFnzpyxt505c0bDhw+337l55MgRBQUFmRUiADitHBft1/Px8eG9lAAKhaioKPuXxejoaEVHR+ubb75R+/bteaYdAG7TjBkzdPToUZUtW1aVKlVSpUqVVLZsWf3+++/64IMPJEnJyckaNWqUyZECgPPJ8e3xkvTpp5/q448/VmxsrC5fvuywbefOnbkSGADkp7i4OHvRvnLlSnXt2lVt27ZV+fLl1aRJE5OjA4CCrXLlyjpw4IC+/fZbHT58WJJUtWpV/etf/7K/kahTp04mRggAzivHI+3Tpk1T79695e/vr127dqlx48YqWbKkfvvtN7Vv3z4vYgSAPFeiRAkdP35ckrRq1SqFhYVJkgzDsL8ZAwBw61xcXNSuXTsNHDhQAwcOVHh4uMMrhAEAmcvxSPusWbM0Z84cde/eXQsWLNDw4cNVoUIFjRkzRgkJCXkRIwDkuc6dO6tHjx6qXLmy/vrrL/uPkLt27VKlSpVMjg4ACr7z589r/fr1md6pOXDgQJOiAgDnl+OiPTY21v66Dm9vb507d07S1VfBNW3aVDNmzMjdCAEgH0yZMkXly5fX8ePHNWnSJBUrVkySdOrUKT3//PMmRwcABduePXvUtWtXXbhwQefPn5efn5/+/PNPFSlSRKVLl6ZoB4AbyHHRHhAQoISEBJUrV07BwcHavHmz6tatq6NHj8owjLyIEQDynLu7u4YNG5ah/fr3twMAbs3LL7+sBx98UFFRUbJardq8ebPc3d31+OOPa9CgQWaHBwBOLcdFe+vWrfXFF1+ofv366t27t4YMGaJPP/1U27dvV+fOnfMiRgDIc4sWLbrh9p49e+ZTJABQ+Ozbt08ffPCBXFxc5OrqqpSUFFWoUEGTJk1Sr169+A4JADeQ46J9zpw5Sk9PlyRFRkaqZMmS2rRpkx566CE988wzuR4gAOSHf470pKam6sKFC/Lw8FCRIkUo2gHgNri5udknnStdurRiY2NVvXp1Wa1W+ySgAIDM5bhod3FxcZjps1u3burWrVuuBgUA+e3s2bMZ2o4cOaLnnnuO97QDwG2qU6eOtm3bpsqVK+u+++7TmDFj9Oeff+o///mPatWqZXZ4AODUcvyejVWrVmnjxo329ZkzZ6pevXrq0aNHpl96AaCgqly5siZOnMjzlgBwm8aMGaMyZcpIkt58802VKFFCzz33nM6cOaM5c+aYHB0AOLccF+0vvviibDabpKvPJw0dOlQdOnTQ0aNHNXTo0FwPEADM5ObmppMnT5odBgAUaA0aNND9998v6ert8atWrZLNZtOOHTtUt25dk6MDAOeW49vjjx49qho1akiSPvvsMz344IMaP368du7cqQ4dOuR6gACQH7744guHdcMwdOrUKc2YMUPNmzc3KSoAKBwuXrwoNzc3FSlSRJJ07NgxLV++XDVq1FDbtm1Njg4AnFuOR9o9PDx04cIFSdJ3331nT7R+fn72EXgAKGg6derksHTu3Fmvvfaa6tSpo3nz5uX6+U6cOKHHH39cJUuWlLe3t2rXrq3t27fbtxuGYb+d1NvbW2FhYTpy5IjDMRISEhQRESEfHx/5+vqqT58+Sk5Oduizd+9e3XvvvfLy8lJQUJAmTZqU69cCADfTvXt3+1s6EhMT1bhxY02ePFkPP/ywZs+ebXJ0AODccly0t2jRQkOHDtXYsWO1detWdezYUZJ0+PBhlS1bNtcDBID8kJ6e7rCkpaUpLi5OS5YssT+HmVvOnj2r5s2by93dXd98840OHDigyZMnq0SJEvY+kyZN0rRp0xQVFaUtW7aoaNGiCg8P16VLl+x9IiIi9NNPPyk6OlorV67Uhg0b1K9fP/t2m82mtm3bqly5ctqxY4fefvttvfbaazw/CiDf7dmzR/fee68k6dNPP1VAQICOHTumRYsWadq0aSZHBwDOLce3x8+YMUPPP/+8Pv30U82ePVt33323JOmbb75Ru3btcj1AAChs3nrrLQUFBWn+/Pn2tpCQEPvfhmFo6tSpGjVqlB5++GFJV98j7+/vrxUrVqhbt276+eeftWrVKm3btk0NGzaUJE2fPl0dOnTQO++8o8DAQC1evFiXL1/WvHnz5OHhoZo1a2r37t169913HYr766WkpCglJcW+zh1UAHLDxYsXVbx4cUnSt99+q86dO8vFxUVNmzbVsWPHTI4OAJxbjkfag4ODtXLlSu3Zs0d9+vSxt0+ZMoVfSgEgG7744gs1bNhQjz76qEqXLq369etr7ty59u1Hjx5VXFycwsLC7G1Wq1VNmjRRTEyMJCkmJka+vr72gl2SwsLC5OLioi1bttj7tGzZUh4eHvY+4eHhOnToUJZv+5gwYYKsVqt9CQoKytVrB3BnqlChglasWKHjx49r9erV9scrT58+LR8fH5OjAwDnluOiPTY29oYLAODGfvvtN82ePVuVK1fW6tWr9dxzz2ngwIFauHChJCkuLk6S5O/v77Cfv7+/fVtcXJxKly7tsN3NzU1+fn4OfTI7xvXn+KeRI0cqKSnJvhw/fvw2rxYApOHDh2vYsGEqX768mjRpotDQUElXR93r169vcnQA4NxyfHt8+fLlZbFYstyelpZ2WwEBQGGXnp6uhg0bavz48ZKk+vXra//+/YqKilKvXr1Mjc3T01Oenp6mxgCg8OnUqZPatm2rU6dOObzirU2bNnrkkUdMjAwAnF+Oi/Zdu3Y5rKempmrXrl1699139eabb+ZaYABQWJUpU8b+6sxrqlevrs8++0ySFBAQIEmKj493mAQvPj5e9erVs/c5ffq0wzGuXLmihIQE+/4BAQGKj4936HNt/VofAMgvAQEBGXJP48aNTYoGAAqOHBft1/86ek3Dhg0VGBiot99+W507d86VwAAgP5UvX15PPfWUnnzySQUHB+fpuZo3b65Dhw45tB0+fFjlypWTdHVSuoCAAK1Zs8ZepNtsNm3ZskXPPfecJCk0NFSJiYnasWOH7rnnHknS2rVrlZ6eriZNmtj7vPLKK0pNTZW7u7skKTo6WlWrVnWYqR4A8toDDzwgN7esv3auXbs2H6MBgIIlx8+0Z6Vq1aratm1bbh0OAPLV4MGD9fnnn6tChQr617/+paVLlzrMop6bhgwZos2bN2v8+PH65ZdftGTJEs2ZM0eRkZGSJIvFosGDB2vcuHH64osvtG/fPvXs2VOBgYHq1KmTpKsj8+3atVPfvn21detW/fjjj+rfv7+6deumwMBASVKPHj3k4eGhPn366KefftKyZcv03nvvaejQoXlyXQCQldq1a6tu3br2pUaNGrp8+bJ27typ2rVrmx0eADg1i2EYRk52+OfrfwzD0KlTp/Taa6/p4MGD2r17d27Gly9sNpusVquSkpKYwRS4w+3cuVMLFizQRx99pLS0NPXo0UNPPfWUGjRokOU+t5JDVq5cqZEjR+rIkSMKCQnR0KFD1bdvX/t2wzD06quvas6cOUpMTFSLFi00a9YsValSxd4nISFB/fv315dffikXFxd16dJF06ZNU7Fixex99u7dq8jISG3btk2lSpXSgAEDNGLEiGx/HuRHALfjZjnktddeU3Jyst555x0Tors95EcAtyu7eSTHRbuLi0uGiegMw1BQUJCWLl1qnw20ICHpAvin1NRUzZo1SyNGjFBqaqpq166tgQMHqnfv3hlyYGHOIYX52gDkvZvlkF9++UWNGzdWQkKCCdHdHvIjgNuV3TyS42fa161b57Du4uKiu+66S5UqVbrhs0oAUBCkpqZq+fLlmj9/vqKjo9W0aVP16dNHf/zxh15++WV99913WrJkidlhAkChEBMTIy8vL7PDAACnluMq+7777suLOADAVDt37tT8+fP10UcfycXFRT179tSUKVNUrVo1e59HHnlEjRo1MjFKACiYIiIi7BNiSv97vHL79u0aPXq0iZEBgPNjaBwAJDVq1Ej/+te/NHv2bHXq1Mnhy+U1ISEh6tatmwnRAUDBZrVaHfKqi4uLqlatqjfeeENt27Y1MTIAcH4U7QDueGlpaZo3b54eeuihG74KrWjRopo/f34+RgYAhcOsWbN47hsAblGuvfINAAoqV1dXPfPMM0pMTDQ7FAAAAMABRTsASKpVq5Z+++03s8MAAAAAHGT79vh/vp/9mqJFi8rV1TXXAgIAM4wbN07Dhg3T2LFjdc8996ho0aIO27mtEwAAAGbIdtHu6+ub4d3E0tXbSkNCQjRs2DD17ds3V4MDgPzSoUMHSdJDDz3kkOsMw5DFYlFaWppZoQEAAOAOlu2i/Z/vZ78mMTFRO3bs0Isvvig3Nzf17t0714L7p4kTJ2rkyJEaNGiQpk6dKkm6dOmSXnjhBS1dulQpKSkKDw/XrFmz5O/vn2dxACh8sspxAIDbd+DAATVt2jTTbStWrFCnTp3yNyAAKECyXbTf6P3sDz/8sMqXL6/p06fnWdG+bds2vf/++6pTp45D+5AhQ/TVV1/pk08+kdVqVf/+/dW5c2f9+OOPeRIHgMLpRjkOAHB7rn03CwkJcWj/7LPP1LNnT50/f96kyADA+eXaRHT33Xeffvnll9w6nIPk5GRFRERo7ty5Dq9jSkpK0ocffqh3331XrVu31j333KP58+dr06ZN2rx5c57EAqDwSkxM1OTJk/X000/r6aef1pQpU5SUlGR2WABQ4PXs2VNhYWGKi4uzty1btkw9e/bUggULzAsMAAqAXCvak5KSZLVac+twDiIjI9WxY0eFhYU5tO/YsUOpqakO7dWqVVNwcLBiYmKyPF5KSopsNpvDAuDOtn37dlWsWFFTpkxRQkKCEhIS9O6776pixYrauXOn2eEBQIH28ssvq0OHDgoLC1NCQoKWLFmi3r17a9GiRXr00UfNDg8AnFq2b4+/kdTUVL399ttq0qRJbhzOwdKlS7Vz505t27Ytw7a4uDh5eHjI19fXod3f39/hl9x/mjBhgl5//fXcDhVAATZkyBA99NBDmjt3rtzcrqbGK1eu6Omnn9bgwYO1YcMGkyMEgIJt+vTpioiIUNOmTXXixAl99NFHevjhh80OCwCcXraL9s6dO2fanpSUpJ9++kkWi0U//PBDrgUmScePH9egQYMUHR0tLy+vXDvuyJEjNXToUPu6zWZTUFBQrh0fQMGzfft2h4Jdktzc3DR8+HA1bNjQxMgAoGD64osvdOHCBUnS119/rSJFiqhz58764Ycf1L17d1ksFn3xxReSrr65AwCQuWwX7Vnd+h4UFKQuXbooIiIi12+P37Fjh06fPq0GDRrY29LS0rRhwwbNmDFDq1ev1uXLl5WYmOgw2h4fH6+AgIAsj+vp6SlPT89cjRVAwebj46PY2FhVq1bNof348eMqXry4SVEBQMF1/YzwPXr0cNg2b948zZs3T5J4rSYA3ES2i/b58+fnZRyZatOmjfbt2+fQ1rt3b1WrVk0jRoxQUFCQ3N3dtWbNGnXp0kWSdOjQIcXGxio0NDTf4wVQcD322GPq06eP3nnnHTVr1kyS9OOPP+rFF19U9+7dTY4OAAqe9PR02Ww2Wa1WJSYmysfHx+yQAKBAytEz7Zs3b9aXX36py5cvq02bNmrXrl1exSVJKl68uGrVquXQVrRoUZUsWdLe3qdPHw0dOlR+fn7y8fHRgAEDFBoamuW7QAEgM++8844sFot69uypK1euSJLc3d313HPPaeLEiSZHBwCFzz/vlAQAZC7bs8d/+umnat68ud577z198MEH6tixo9555528jC1bpkyZogceeEBdunRRy5YtFRAQoM8//9zssAAUMB4eHnrvvfd09uxZ7d69W7t371ZCQoKmTJnC4zQAcJumTJmiZcuW2dcfffRR+fn56e6779aePXvy/PwTJ06UxWLR4MGD7W2XLl1SZGSkSpYsqWLFiqlLly6Kj4/P81gAIKcshmEY2el4zz33qFGjRpo5c6ZcXV01YcIEvf3220pISMjrGPPctVu3kpKSuHULQI4V5hxSmK8NQN67lkOCg4P10UcfqVmzZoqOjlbXrl21bNkyffzxx4qNjdW3336bZzFs27ZNXbt2lY+Pj+6//35NnTpVkvTcc8/pq6++0oIFC2S1WtW/f3+5uLjoxx9/zNG1kR8B3Krs5pFs3x5/6NAhLVu2TK6urpKkF154QWPGjNHp06dVunTp248YAEx06dIlTZ8+XevWrdPp06eVnp7usJ13tQPArTt9+rT9TT0rV65U165d1bZtW5UvXz5PXhl8TXJysiIiIjR37lyNGzfO3p6UlKQPP/xQS5YsUevWrSVdnb+pevXq2rx5c6aPWaakpCglJcW+brPZ8ixuALhetm+Pv3DhgkP17+HhIS8vLyUnJ+dJYACQn/r06aNJkyapXLlyeuCBB/Twww87LACAW+fr66vjx49LklatWqWwsDBJkmEYeTpzfGRkpDp27Gg/3zU7duxQamqqQ3u1atUUHBysmJiYTI81YcIEWa1W+8LrggHklxxNRPfBBx+oWLFi9vUrV65owYIFKlWqlL1t4MCBuRcdAOSTlStX6uuvv1bz5s3NDgUACp0HH3xQPXr0UOXKlfXXX3+pffv2kqRdu3apUqVKeXLOpUuXaufOndq2bVuGbXFxcfLw8MgwEZ6/v7/i4uIyPd7IkSM1dOhQ+7rNZqNwB5Avsl20BwcHa+7cuQ5tAQEB+s9//mNft1gsFO0ACqS7776b97EDQB6ZMGGCqlSpouPHj2vSpEn2QaBTp07p+eefz/XzHT9+XIMGDVJ0dLS8vLxy5Zienp5MTArAFNku2n///fc8DAMAzDV58mSNGDFCUVFRKleunNnhAECh4u7urmHDhmVoHzJkSJ6cb8eOHTp9+rQaNGhgb0tLS9OGDRs0Y8YMrV69WpcvX87w2rn4+HgFBATkSUwAcKtydHs8ABRWDRs21KVLl1ShQgUVKVJE7u7uDtsLw5syACA/ffHFF/ZHjr7++msVKVIky74PPfRQrp67TZs22rdvn0Nb7969Va1aNY0YMUJBQUFyd3fXmjVr1KVLF0lXJ12OjY1VaGhorsYCALcr20X72rVr1b9/f23evDnDdPRJSUlq1qyZZs+erZYtW+Z6kACQ17p3764TJ05o/Pjx8vf3l8ViMTskACjQOnXqpCNHjkiSevTokWU/i8WS65PRFS9eXLVq1XJoK1q0qEqWLGlv79Onj4YOHSo/Pz/5+PhowIABCg0NzXTmeAAwU7aL9qlTp6pv376Zvj/OarXqmWee0ZQpUyjaARRImzZtUkxMjOrWrWt2KABQKKSnp9tfi5aYmOh07zKfMmWKXFxc1KVLF6WkpCg8PFyzZs0yOywAyCDbRfuePXv01ltvZbm9bdu2euedd3IlKADIb9WqVdPFixfNDgMAkEe+//57h3UvLy/NnDlTM2fONCcgAMimbL+nPT4+PsMzntdzc3PTmTNnciUoAMhvEydO1AsvvKDvv/9ef/31l2w2m8MCALh1//nPf/TAAw+oVq1aql27th566CEtWrRIhmGYHRoAOL1sj7Tffffd2r9/f5bv0ty7d6/KlCmTa4EBQH5q166dpKuTF13PMIw8ed4SAO4E14ryAQMGqG7duqpdu7YMw9DPP/+sJ598Up9//rlWrFhhbpAA4OSyXbR36NBBo0ePVrt27TK87/LixYt69dVX9cADD+R6gACQH9atW2d2CABQ6CxevFjS1Znk//k9ce3aterUqZMWLVqknj17mhEeABQIFiOb9yXFx8erQYMGcnV1Vf/+/VW1alVJ0sGDBzVz5kylpaVp586d8vf3z9OA84LNZpPValVSUpLTTZICwPkV5hxSmK8NQN5r3bq11q1bl2UOGT9+vNavX6/Vq1ebEN3tIT8CuF3ZzSPZfqbd399fmzZtUq1atTRy5Eg98sgjeuSRR/Tyyy+rVq1a2rhxY4Es2AHgmh9++EGPP/64mjVrphMnTki6+hzmxo0bTY4MAAqmn3766Ybb27dvrz179uRTNABQMGW7aJekcuXK6euvv9aff/6pLVu2aPPmzfrzzz/19ddfKyQkJK9iBIA899lnnyk8PFze3t7auXOnUlJSJElJSUkaP368ydEBQMF09uzZG2739/e/aR8AuNPlqGi/pkSJEmrUqJEaN26sEiVK5HZMAJDvxo0bp6ioKM2dO9fhTRnNmzfXzp07TYwMAAqum03i6erqqitXruRTNABQMGV7IjoAKMwOHTqkli1bZmi3Wq1KTEzM/4AAoBC4NnVSREREpq8OvnZXEwAga7c00g4AhU1AQIB++eWXDO0bN25UhQoV8vTcEydOlMVi0eDBg+1tly5dUmRkpEqWLKlixYqpS5cuio+Pd9gvNjZWHTt2VJEiRVS6dGm9+OKLGUasvv/+ezVo0ECenp6qVKmSFixYkKfXAgDX69Gjh6SrP4BmtpQuXZqZ4wHgJhhpBwBJffv21aBBgzRv3jxZLBadPHlSMTExGjZsmEaPHp1n5922bZvef/991alTx6F9yJAh+uqrr/TJJ5/IarWqf//+6ty5s3788UdJV2857dixowICArRp0yadOnVKPXv2lLu7u/0Z/KNHj6pjx4569tlntXjxYq1Zs0ZPP/20ypQpo/Dw8Dy7JgC4ZtasWVq8eLFmzZrFDOsAcIso2gFA0ksvvaT09HS1adNGFy5cUMuWLeXp6alhw4ZpwIABeXLO5ORkRUREaO7cuRo3bpy9PSkpSR9++KGWLFmi1q1bS5Lmz5+v6tWra/PmzWratKm+/fZbHThwQN999538/f1Vr149jR07ViNGjNBrr70mDw8PRUVFKSQkRJMnT5YkVa9eXRs3btSUKVMo2gEAAAoIbo8HAEkWi0WvvPKKEhIStH//fm3evFlnzpzR2LFj8+yckZGR6tixo8LCwhzad+zYodTUVIf2atWqKTg4WDExMZKkmJgY1a5d2+FVm+Hh4bLZbPZXLMXExGQ4dnh4uP0YmUlJSZHNZnNYAAAAYB5G2gHgOh4eHqpRo0aen2fp0qXauXOntm3blmFbXFycPDw85Ovr69Du7++vuLg4e5/rC/Zr269tu1Efm82mixcvytvbO8O5J0yYoNdff/2WrwsAAAC5i6IdwB3tqaeeyla/efPm5do5jx8/rkGDBik6OlpeXl65dtzcMHLkSA0dOtS+brPZFBQUZGJEAAAAdzaKdgB3tAULFqhcuXKqX7++/dVEeW3Hjh06ffq0GjRoYG9LS0vThg0bNGPGDK1evVqXL19WYmKiw2h7fHy8AgICJF2d7X7r1q0Ox702u/z1ff4543x8fLx8fHwyHWWXJE9PT3l6et72NQIAACB3ULQDuKM999xz+uijj3T06FH17t1bjz/+uPz8/PL0nG3atNG+ffsc2nr37q1q1appxIgRCgoKkru7u9asWaMuXbpIuvoe+djYWIWGhkqSQkND9eabb+r06dMqXbq0JCk6Olo+Pj722/tDQ0P19ddfO5wnOjrafgwAAAA4PyaiA3BHmzlzpk6dOqXhw4fryy+/VFBQkLp27arVq1fn2ch78eLFVatWLYelaNGiKlmypGrVqiWr1ao+ffpo6NChWrdunXbs2KHevXsrNDRUTZs2lSS1bdtWNWrU0BNPPKE9e/Zo9erVGjVqlCIjI+0j5c8++6x+++03DR8+XAcPHtSsWbP08ccfa8iQIXlyXQAAAMh9FO0A7nienp7q3r27oqOjdeDAAdWsWVPPP/+8ypcvr+TkZFNimjJlih544AF16dJFLVu2VEBAgD7//HP7dldXV61cuVKurq4KDQ3V448/rp49e+qNN96w9wkJCdFXX32l6Oho1a1bV5MnT9YHH3zA694AAAAKEG6PB4DruLi4yGKxyDAMpaWl5dt5v//+e4d1Ly8vzZw5UzNnzsxyn3LlymW4/f2fWrVqpV27duVGiAAAADABI+0A7ngpKSn66KOP9K9//UtVqlTRvn37NGPGDMXGxqpYsWJmhwcAAIA7GCPtAO5ozz//vJYuXaqgoCA99dRT+uijj1SqVCmzwwIAAAAkUbQDuMNFRUUpODhYFSpU0Pr167V+/fpM+13/PDkAAACQXyjaAdzRevbsKYvFYnYYAAAAQKYo2gHc0RYsWGB2CAAAAECWmIgOAAAAAAAnRdEOAAAAAICTomgHAAAAAMBJUbQDAAAAAOCkKNoBAAAAAHBSFO0AAAAAADgpinYAAAAAAJwURTsAAAAAAE6Koh0AAAAAACdF0Q4AAAAAgJOiaAcAAAAAwElRtAMAAAAA4KQo2gEAAAAAcFIU7QAAAAAAOCk3swMAAAAACruLl9N04fIVpRuSYRhKN6R0w1C6YcgwJOO69Wt9DP3dli57v/Tr2u3HSf97HxnXHefqf/WPdcN+fMfzZ9bnWpv+sW5cF6d9//Tr1pWNPsb/YrZfr5H5Z5dVu3R1/yy33WC/q/veYFtWsWS2V5Z9szp25luy7p/Fhhvsc6Pz3Gy/m3W41c88L/53vNl13PjfQN6c84W2VVQz0HqTXjlD0Q4AAADksbk//KZ3ow+bHQaAPNanRUiuH5OiHQAAAMhjluv+drFILhaLXCwWyeK4bvn7b4u9TbJc+6+uW3e5bh/puv43Psa1dsvf+7m6WDL0vbp+bb+Mx/1nH5e/45GuW7ef8+82l0z21//6WP7+HDL97CxZbMjqs87qOMp8Q9b9c36OG53nZvvdSFafQVaHy+k1ZXn8W/hsbnSRZnymeXHOG22qVLrYjQO6BU5dtE+YMEGff/65Dh48KG9vbzVr1kxvvfWWqlatau9z6dIlvfDCC1q6dKlSUlIUHh6uWbNmyd/f38TIAQAAgP+JvL+S+reulOMCFACceiK69evXKzIyUps3b1Z0dLRSU1PVtm1bnT9/3t5nyJAh+vLLL/XJJ59o/fr1OnnypDp37mxi1AAAAICjqyPNFOwAcs6pR9pXrVrlsL5gwQKVLl1aO3bsUMuWLZWUlKQPP/xQS5YsUevWrSVJ8+fPV/Xq1bV582Y1bdrUjLABAAAAAMgVTj3S/k9JSUmSJD8/P0nSjh07lJqaqrCwMHufatWqKTg4WDExMVkeJyUlRTabzWEBAAAAAMDZFJiiPT09XYMHD1bz5s1Vq1YtSVJcXJw8PDzk6+vr0Nff319xcXFZHmvChAmyWq32JSgoKC9DBwAAAADglhSYoj0yMlL79+/X0qVLb/tYI0eOVFJSkn05fvx4LkQIAAAAZzBhwgQ1atRIxYsXV+nSpdWpUycdOnTIoc+lS5cUGRmpkiVLqlixYurSpYvi4+NNihgAslYgivb+/ftr5cqVWrduncqWLWtvDwgI0OXLl5WYmOjQPz4+XgEBAVkez9PTUz4+Pg4LAAAACgcmMwZQmDj1RHSGYWjAgAFavny5vv/+e4WEOL6o/p577pG7u7vWrFmjLl26SJIOHTqk2NhYhYaGmhEyAAAATMZkxgAKE6cu2iMjI7VkyRL93//9n4oXL25/Tt1qtcrb21tWq1V9+vTR0KFD5efnJx8fHw0YMEChoaEkWwAAAEjK+WTGmX2PTElJUUpKin2diYwB5Benvj1+9uzZSkpKUqtWrVSmTBn7smzZMnufKVOm6IEHHlCXLl3UsmVLBQQE6PPPPzcxagAAADiL3JrMmImMAZjFqUfaDcO4aR8vLy/NnDlTM2fOzIeIAAAAUJBcm8x448aNt3WckSNHaujQofZ1m81G4Q4gXzh10Q4AAADcqmuTGW/YsCHLyYyvH22/0WTGnp6e8vT0zOuQASADp749HgAAAMgpwzDUv39/LV++XGvXrr3hZMbXMJkxAGfFSDsAAAAKFSYzBlCYULQDAACgUJk9e7YkqVWrVg7t8+fP15NPPinp6mTGLi4u6tKli1JSUhQeHq5Zs2blc6QAcHPcHg8A+WzChAlq1KiRihcvrtKlS6tTp046dOiQQ59Lly4pMjJSJUuWVLFixdSlSxfFx8c79ImNjVXHjh1VpEgRlS5dWi+++KKuXLni0Of7779XgwYN5OnpqUqVKmnBggV5fXkAYDrDMDJdrhXs0v8mM05ISND58+f1+eefZ/k8OwCYiaIdAPLZ+vXrFRkZqc2bNys6Olqpqalq27atzp8/b+8zZMgQffnll/rkk0+0fv16nTx5Up07d7ZvT0tLU8eOHXX58mVt2rRJCxcu1IIFCzRmzBh7n6NHj6pjx466//77tXv3bg0ePFhPP/20Vq9ena/XCwAAgFtnMbLzXrVCzmazyWq1KikpST4+PmaHA6CAud0ccubMGZUuXVrr169Xy5YtlZSUpLvuuktLlizRv//9b0nSwYMHVb16dcXExKhp06b65ptv9MADD+jkyZPy9/eXJEVFRWnEiBE6c+aMPDw8NGLECH311Vfav3+//VzdunVTYmKiVq1alWksKSkpSklJcbi2oKAg8iOAW1KYv2MV5msDkD+ym0cYaQcAkyUlJUmS/Pz8JEk7duxQamqqwsLC7H2qVaum4OBgxcTESJJiYmJUu3Zte8EuSeHh4bLZbPrpp5/sfa4/xrU+146RmQkTJshqtdoX3kEMAABgLop2ADBRenq6Bg8erObNm6tWrVqSpLi4OHl4eDi8O1iS/P397TMgx8XFORTs17Zf23ajPjabTRcvXsw0npEjRyopKcm+HD9+/LavEQAAALeO2eMBwESRkZHav3+/Nm7caHYokiRPT095enqaHQYAAAD+xkg7AJikf//+WrlypdatW6eyZcva2wMCAnT58mUlJiY69I+Pj7fPbBwQEJBhNvlr6zfr4+PjI29v79y+HAAAAOQBinYAyGeGYah///5avny51q5dq5CQEIft99xzj9zd3bVmzRp726FDhxQbG6vQ0FBJUmhoqPbt26fTp0/b+0RHR8vHx0c1atSw97n+GNf6XDsGAAAAnB+3xwNAPouMjNSSJUv0f//3fypevLj9GXSr1Spvb29ZrVb16dNHQ4cOlZ+fn3x8fDRgwACFhoaqadOmkqS2bduqRo0aeuKJJzRp0iTFxcVp1KhRioyMtN/e/uyzz2rGjBkaPny4nnrqKa1du1Yff/yxvvrqK9OuHQAAADnDSDsA5LPZs2crKSlJrVq1UpkyZezLsmXL7H2mTJmiBx54QF26dFHLli0VEBCgzz//3L7d1dVVK1eulKurq0JDQ/X444+rZ8+eeuONN+x9QkJC9NVXXyk6Olp169bV5MmT9cEHHyg8PDxfrxcAAAC3jve0i/dsArg9hTmHFOZrA5D3CnMOKczXBiB/8J52AAAAAAAKOIp2AAAAAACcFEU7AAAAAABOiqIdAAAAAAAnRdEOAAAAAICTomgHAAAAAMBJUbQDAAAAAOCkKNoBAAAAAHBSFO0AAAAAADgpN7MDAADgdhmGoQuX03T2wmUlXkjV2QuXdfZCqpIuXFbKlXQZhmTIULoh+9+GcXW/q+tS+nV//6/96n/T//5bxj/7XV2/FkP6P/aR/Tz/63cjFssNtinrjTfc7wbbbiYbIWevj27eKTvHcTxmDvvndIdccjufv8NxculcN/p3lJPjjO1US+6ujP0AQH6gaAcAOJXUtHQlXkhV4t+F99VC/Foxfq398nV/pyrpQqoup6WbHTpwx3j94ZpmhwAAdwyKdgBAnjAMQ+dSrijx/LWR78tKupiqs+cdC+7rR8eTLqTqXMqVWz6nh6uLfIu4q0QRD1mLuKtEEXd5ubvKIsnFYpEsV0caXSxXRxMtssjFRZIsslh0tf3vvy2SLBbL//pd2+e6tgz7WCx/73f1fNf+vn6fTD+rLMaNczz6nMkOWR3DUC6O3ubScHJOD5OdUePbOb6zuNG/g5vdxXCrdxhk9m/peq4F9cMEgAKIoh0AkGteXr5PW48m2EfGr6TfWsVgsUg+XleLbt8iHvZC/Np/r7Vfa7vWXsTDNdcKSAAAAGdA0Q4AyDWnEi/ql9PJDm1e7i5/F9fXim13+9+Zt3vI6u0uVxeKbwAAAIp2AECuGRxWRX1bVpCvt4dKFL1alHu5u5odFgAAQIFF0Q4AyDV1g3zNDgEAAKBQ4V0dAAAAAAA4KYp2AAAAAACcFEU7AAAAAABOiqIdAAAAAAAnRdEOAAAAAICTomgHAAAAAMBJUbQDAAAAAOCkKNoBAAAAAHBSFO0AAAAAADgpinYAAAAAAJwURTsAAAAAAE6Koh0AAAAAACdF0Q4AAAAAgJOiaAcAAAAAwElRtAMAAAAA4KQo2gEAAAAAcFIU7QAAAAAAOCmKdgAAAAAAnBRFOwAAAAAAToqiHQAAAAAAJ1VoivaZM2eqfPny8vLyUpMmTbR161azQwIAp0B+BICskSMBOLtCUbQvW7ZMQ4cO1auvvqqdO3eqbt26Cg8P1+nTp80ODQBMRX4EgKyRIwEUBIWiaH/33XfVt29f9e7dWzVq1FBUVJSKFCmiefPmmR0aAJiK/AgAWSNHAigI3MwO4HZdvnxZO3bs0MiRI+1tLi4uCgsLU0xMTKb7pKSkKCUlxb6elJQkSbLZbHkbLIBC6VruMAzD5EgckR8BmM1Z86OU8xxJfgSQ27KbIwt80f7nn38qLS1N/v7+Du3+/v46ePBgpvtMmDBBr7/+eob2oKCgPIkRwJ3h3LlzslqtZodhR34E4CycLT9KOc+R5EcAeeVmObLAF+23YuTIkRo6dKh9PT09XQkJCSpZsqQsFstN97fZbAoKCtLx48fl4+OTl6EWOHw2WeOzyVpB/2wMw9C5c+cUGBhodii3jfyYd/hsssZnk7WC/tmQHx0V9P898xKfTeb4XLJWGD6b7ObIAl+0lypVSq6uroqPj3doj4+PV0BAQKb7eHp6ytPT06HN19c3x+f28fEpsP9A8hqfTdb4bLJWkD8bZxtBksiPzorPJmt8NlkryJ+NM+ZHKec5Mrfyo1Sw//fMa3w2meNzyVpB/2yykyML/ER0Hh4euueee7RmzRp7W3p6utasWaPQ0FATIwMAc5EfASBr5EgABUWBH2mXpKFDh6pXr15q2LChGjdurKlTp+r8+fPq3bu32aEBgKnIjwCQNXIkgIKgUBTtjz32mM6cOaMxY8YoLi5O9erV06pVqzJMLJJbPD099eqrr2a4RQp8NjfCZ5M1Ppu8Q350Hnw2WeOzyRqfTd4iRzoPPpvM8blk7U76bCyGM76DAwAAAAAAFPxn2gEAAAAAKKwo2gEAAAAAcFIU7QAAAAAAOCmKdgAAAAAAnBRF+y2YOXOmypcvLy8vLzVp0kRbt241OyTTTZgwQY0aNVLx4sVVunRpderUSYcOHTI7LKczceJEWSwWDR482OxQnMaJEyf0+OOPq2TJkvL29lbt2rW1fft2s8PCLSI/ZkR+zD5ypCPyY+FCfsyI/Jh95EdHd1p+pGjPoWXLlmno0KF69dVXtXPnTtWtW1fh4eE6ffq02aGZav369YqMjNTmzZsVHR2t1NRUtW3bVufPnzc7NKexbds2vf/++6pTp47ZoTiNs2fPqnnz5nJ3d9c333yjAwcOaPLkySpRooTZoeEWkB8zR37MHnKkI/Jj4UJ+zBz5MXvIj47uyPxoIEcaN25sREZG2tfT0tKMwMBAY8KECSZG5XxOnz5tSDLWr19vdihO4dy5c0blypWN6Oho47777jMGDRpkdkhOYcSIEUaLFi3MDgO5hPyYPeTHjMiRGZEfCxfyY/aQHzMiP2Z0J+ZHRtpz4PLly9qxY4fCwsLsbS4uLgoLC1NMTIyJkTmfpKQkSZKfn5/JkTiHyMhIdezY0eHfDqQvvvhCDRs21KOPPqrSpUurfv36mjt3rtlh4RaQH7OP/JgROTIj8mPhQX7MPvJjRuTHjO7E/EjRngN//vmn0tLS5O/v79Du7++vuLg4k6JyPunp6Ro8eLCaN2+uWrVqmR2O6ZYuXaqdO3dqwoQJZofidH777TfNnj1blStX1urVq/Xcc89p4MCBWrhwodmhIYfIj9lDfsyIHJk58mPhQX7MHvJjRuTHzN2J+dHN7ABQ+ERGRmr//v3auHGj2aGY7vjx4xo0aJCio6Pl5eVldjhOJz09XQ0bNtT48eMlSfXr19f+/fsVFRWlXr16mRwdkPvIj47IkVkjP+JOQ350RH7M2p2YHxlpz4FSpUrJ1dVV8fHxDu3x8fEKCAgwKSrn0r9/f61cuVLr1q1T2bJlzQ7HdDt27NDp06fVoEEDubm5yc3NTevXr9e0adPk5uamtLQ0s0M0VZkyZVSjRg2HturVqys2NtakiHCryI83R37MiByZNfJj4UF+vDnyY0bkx6zdifmRoj0HPDw8dM8992jNmjX2tvT0dK1Zs0ahoaEmRmY+wzDUv39/LV++XGvXrlVISIjZITmFNm3aaN++fdq9e7d9adiwoSIiIrR79265urqaHaKpmjdvnuHVLocPH1a5cuVMigi3ivyYNfJj1siRWSM/Fh7kx6yRH7NGfszanZgfuT0+h4YOHapevXqpYcOGaty4saZOnarz58+rd+/eZodmqsjISC1ZskT/93//p+LFi9uf0bJarfL29jY5OvMUL148w3NZRYsWVcmSJXleS9KQIUPUrFkzjR8/Xl27dtXWrVs1Z84czZkzx+zQcAvIj5kjP2aNHJk18mPhQn7MHPkxa+THrN2R+dHk2esLpOnTpxvBwcGGh4eH0bhxY2Pz5s1mh2Q6SZku8+fPNzs0p8PrOhx9+eWXRq1atQxPT0+jWrVqxpw5c8wOCbeB/JgR+TFnyJH/Q34sXMiPGZEfc4b8+D93Wn60GIZh5PcPBQAAAAAA4OZ4ph0AAAAAACdF0Q4AAAAAgJOiaAcAAAAAwElRtAMAAAAA4KQo2gEAAAAAcFIU7QAAAAAAOCmKdgAAAAAAnBRFOwAAAAAAToqiHYXWk08+qU6dOpl2/ieeeELjx4/PVt9u3bpp8uTJeRwRAFxFfgSArJEj4WwshmEYZgcB5JTFYrnh9ldffVVDhgyRYRjy9fXNn6Cus2fPHrVu3VrHjh1TsWLFbtp///79atmypY4ePSqr1ZoPEQIorMiPAJA1ciQKIop2FEhxcXH2v5ctW6YxY8bo0KFD9rZixYplK9Hllaefflpubm6KiorK9j6NGjXSk08+qcjIyDyMDEBhR34EgKyRI1EQcXs8CqSAgAD7YrVaZbFYHNqKFSuW4damVq1aacCAARo8eLBKlCghf39/zZ07V+fPn1fv3r1VvHhxVapUSd98843Dufbv36/27durWLFi8vf31xNPPKE///wzy9jS0tL06aef6sEHH3RonzVrlipXriwvLy/5+/vr3//+t8P2Bx98UEuXLr39DwfAHY38CABZI0eiIKJoxx1l4cKFKlWqlLZu3aoBAwboueee06OPPqpmzZpp586datu2rZ544glduHBBkpSYmKjWrVurfv362r59u1atWqX4+Hh17do1y3Ps3btXSUlJatiwob1t+/btGjhwoN544w0dOnRIq1atUsuWLR32a9y4sbZu3aqUlJS8uXgAuAHyIwBkjRwJUxlAATd//nzDarVmaO/Vq5fx8MMP29fvu+8+o0WLFvb1K1euGEWLFjWeeOIJe9upU6cMSUZMTIxhGIYxduxYo23btg7HPX78uCHJOHToUKbxLF++3HB1dTXS09PtbZ999pnh4+Nj2Gy2LK9jz549hiTj999/v+H1AkB2kR8BIGvkSBQUjLTjjlKnTh37366uripZsqRq165tb/P395cknT59WtLVyUDWrVtnf76pWLFiqlatmiTp119/zfQcFy9elKenp8NEJ//6179Urlw5VahQQU888YQWL15s/yX2Gm9vb0nK0A4A+YH8CABZI0fCTBTtuKO4u7s7rFssFoe2a0kyPT1dkpScnKwHH3xQu3fvdliOHDmS4daka0qVKqULFy7o8uXL9rbixYtr586d+uijj1SmTBmNGTNGdevWVWJior1PQkKCJOmuu+7KlWsFgJwgPwJA1siRMBNFO3ADDRo00E8//aTy5curUqVKDkvRokUz3adevXqSpAMHDji0u7m5KSwsTJMmTdLevXv1+++/a+3atfbt+/fvV9myZVWqVKk8ux4AyC3kRwDIGjkSuYmiHbiByMhIJSQkqHv37tq2bZt+/fVXrV69Wr1791ZaWlqm+9x1111q0KCBNm7caG9buXKlpk2bpt27d+vYsWNatGiR0tPTVbVqVXufH374QW3bts3zawKA3EB+BICskSORmyjagRsIDAzUjz/+qLS0NLVt21a1a9fW4MGD5evrKxeXrP/P5+mnn9bixYvt676+vvr888/VunVrVa9eXVFRUfroo49Us2ZNSdKlS5e0YsUK9e3bN8+vCQByA/kRALJGjkRushiGYZgdBFDYXLx4UVWrVtWyZcsUGhp60/6zZ8/W8uXL9e233+ZDdABgHvIjAGSNHInMMNIO5AFvb28tWrRIf/75Z7b6u7u7a/r06XkcFQCYj/wIAFkjRyIzjLQDAAAAAOCkGGkHAAAAAMBJUbQDAAAAAOCkKNoBAAAAAHBSFO0AAAAAADgpinYAAAAAAJwURTsAAAAAAE6Koh0AAAAAACdF0Q4AAAAAgJOiaAcAAAAAwEn9PxiD9FQymfflAAAAAElFTkSuQmCC\n" + "image/png": 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\n" }, "metadata": {} }, @@ -503,12 +599,13 @@ "name": "stdout", "text": [ "Copying files from IDC buckets..\n", - "Done in 0.521746 seconds.\n", - "Chris Rorden's dcm2niiX version v1.0.20181125 (JP2:OpenJPEG) GCC9.3.0 (64-bit Linux)\n", + "Done in 1.61487 seconds.\n", + "Chris Rorden's dcm2niiX version v1.0.20211006 (JP2:OpenJPEG) GCC11.2.0 x86-64 (64-bit Linux)\n", "Found 115 DICOM file(s)\n", - "Convert 115 DICOM as //content/dcm2niix/1.3.6.1.4.1.14519.5.2.1.7009.9004.431377773401197924485551006033/1.3.6.1.4.1.14519.5.2.1.7009.9004.43137777340119792448555100603_1_OPA_GE_LS16_STANDARD_339_2.5_120_40_29.1_1.4_20000102000000_2 (512x512x115x1)\n", - "compress: \"/usr/bin/pigz\" -n -f -6 \"//content/dcm2niix/1.3.6.1.4.1.14519.5.2.1.7009.9004.431377773401197924485551006033/1.3.6.1.4.1.14519.5.2.1.7009.9004.43137777340119792448555100603_1_OPA_GE_LS16_STANDARD_339_2.5_120_40_29.1_1.4_20000102000000_2.nii\"\n", - "Conversion required 5.236592 seconds (0.210617 for core code).\n" + "Convert 115 DICOM as /content/dcm2niix/1.3.6.1.4.1.14519.5.2.1.7009.9004.431377773401197924485551006033/1.3.6.1.4.1.14519.5.2.1.7009.9004.431377773401197924485551006033_1,OPA,GE,LS16,STANDARD,339,2.5,120,40,29.1,1.4_20000102000000_2 (512x512x115x1)\n", + "Compress: \"/usr/bin/pigz\" -b 960 -n -f -6 \"/content/dcm2niix/1.3.6.1.4.1.14519.5.2.1.7009.9004.431377773401197924485551006033/1.3.6.1.4.1.14519.5.2.1.7009.9004.431377773401197924485551006033_1,OPA,GE,LS16,STANDARD,339,2.5,120,40,29.1,1.4_20000102000000_2.nii\"\n", + "Conversion required 3.809751 seconds (0.226478 for core code).\n", + "\n" ] }, { @@ -517,7 +614,7 @@ "text/plain": [ "
" ], - "image/png": 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\n" + "image/png": 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idXZGXQJUtIuIiIiISPZS0S7ygH45ch6LBar5euDn6W50HBERERERyUdUtIs8oIi/b41vq6vsIiIiIiKSzVS0izyA6zfS2HDkAgBttdSbiIiIiIhkM7su2lNTUxk3bhwBAQG4u7tToUIFJkyYgMVisfaxWCyMHz8eX19f3N3dCQoK4tixYwamloJk+x+xXE6+QfHCLtQp7Wl0HBERERERyWfsumh///33mTVrFtOnT+fQoUO8//77TJ48mU8//dTaZ/LkyUybNo2wsDC2bNlC4cKFCQ4OJikpycDkUlCk3xr/SNVSODiYDE4jIiIiIiL5jZPRAe5m06ZNPP7443Tq1AmAcuXK8dVXX7F161bg5lX2qVOnMnbsWB5//HEAFixYgLe3N8uXL6dHjx4Z7jc5OZnk5GTr+4SEhBw+E8mv1up5dhERERERyUF2faW9WbNmREREcPToUQD27NnDxo0b6dChAwAnT54kOjqaoKAg62fMZjNNmjQhMjLyjvudNGkSZrPZ+vL398/ZE5F86cSFK5y8mIizo4kWlUoYHUdERERERPIhu77S/uqrr5KQkEDVqlVxdHQkNTWVd955h5CQEACio6MB8Pb2tvmct7e3dVtGxowZw4gRI6zvExISVLhLlqVfZW8SUJyibs4GpxERERERkfzIrov2r7/+moULF7Jo0SJq1KjB7t27GTZsGH5+fvTp0+e+9+vq6oqrq2s2JpWCKOLQzaK9jW6NFxERERGRHGLXRfsrr7zCq6++an02vVatWpw6dYpJkybRp08ffHx8AIiJicHX19f6uZiYGOrWrWtEZCkg4q+lsO2PWEBLvYmIiIiISM6x62far169ioODbURHR0fS0tIACAgIwMfHh4iICOv2hIQEtmzZQmBgYK5mlYLl12MXuJFmoWKpIpQtXtjoOCIiIiIikk/Z9ZX2zp07884771CmTBlq1KjBrl27+Pjjj3nuuecAMJlMDBs2jIkTJ1KpUiUCAgIYN24cfn5+dOnSxdjwkq+l3xqvWeNFRERERCQn2fWV9k8//ZR///vfvPTSS1SrVo2RI0fywgsvMGHCBGufUaNGMXjwYAYMGECjRo24cuUKq1evxs3NzcDkkp+lpllYd0TPs8udbdiwgc6dO+Pn54fJZGL58uU22y0WC+PHj8fX1xd3d3eCgoI4duyYTZ/Y2FhCQkLw8PDA09OTfv36ceXKFZs+e/fupWXLlri5ueHv78/kyZNvy/LNN99QtWpV3NzcqFWrFqtWrcr28xURERGRnGPXRXvRokWZOnUqp06d4tq1a/z+++9MnDgRFxcXax+TycTbb79NdHQ0SUlJ/Pzzz1SuXNnA1JLf7Yq6RNzVFDzcnGhQtpjRccQOJSYmUqdOHWbMmJHh9smTJzNt2jTCwsLYsmULhQsXJjg4mKSkJGufkJAQDhw4QHh4OCtXrmTDhg0MGDDAuj0hIYF27dpRtmxZduzYwQcffMCbb77J7NmzrX02bdpEz5496devH7t27aJLly506dKF/fv359zJi4iIiEi2MlksFovRIYyWkJCA2WwmPj4eDw8Po+OInXt/9WFm/fI7j9XxY1rPekbHETtwtzHEZDKxbNky6yM7FosFPz8/Xn75ZUaOHAlAfHw83t7ezJs3jx49enDo0CGqV6/Otm3baNiwIQCrV6+mY8eO/Pnnn/j5+TFr1ixef/11oqOjrT9kvvrqqyxfvpzDhw8D8NRTT5GYmMjKlSuteZo2bUrdunUJCwvL8FySk5NJTk62OTd/f3+NjyJyX/Lzd6z8fG4ikjsyO47Y9ZV2EXu0Nv15ds0aL/fh5MmTREdHExQUZG0zm800adKEyMhIACIjI/H09LQW7ABBQUE4ODiwZcsWa59WrVrZ3HkUHBzMkSNHuHTpkrXPrcdJ75N+nIxMmjQJs9lsffn7+z/4SYuIiIjIfVPRLpIFp2OvciTmMg4meLhySaPjSB4UHR0NgLe3t027t7e3dVt0dDSlStn+KOTk5ISXl5dNn4z2cesx7tQnfXtGxowZQ3x8vPV1+vTprJ6iiIiIiGQju549XsTepE9A17CsF56FXO7RWyTvcXV1xdXV1egYIiIiIvI3XWkXyYII3RovD8jHxweAmJgYm/aYmBjrNh8fH86fP2+z/caNG8TGxtr0yWgftx7jTn3St4uIiIiI/VPRLpJJick3iPz9L0BFu9y/gIAAfHx8iIiIsLYlJCSwZcsWAgMDAQgMDCQuLo4dO3ZY+6xdu5a0tDSaNGli7bNhwwZSUlKsfcLDw6lSpQrFihWz9rn1OOl90o8jIiIiIvZPRbtIJm08fpHrqWmU8SpEhZJFjI4jduzKlSvs3r2b3bt3Azcnn9u9ezdRUVGYTCaGDRvGxIkT+f7779m3bx+9e/fGz8/POsN8tWrVaN++Pf3792fr1q389ttvDBo0iB49euDn5wdAr169cHFxoV+/fhw4cIAlS5bwySefMGLECGuOoUOHsnr1aj766CMOHz7Mm2++yfbt2xk0aFBu/5WIiOSq1NRUxo0bR0BAAO7u7lSoUIEJEyZw66JJFouF8ePH4+vri7u7O0FBQRw7dszA1CIiGdMz7SKZlD5rfJuqpTCZTAanEXu2fft2HnnkEev79EK6T58+zJs3j1GjRpGYmMiAAQOIi4ujRYsWrF69Gjc3N+tnFi5cyKBBg2jbti0ODg5069aNadOmWbebzWZ++uknQkNDadCgASVKlGD8+PE2a7k3a9aMRYsWMXbsWF577TUqVarE8uXLqVmzZi78LYiIGOf9999n1qxZzJ8/nxo1arB9+3b69u2L2WxmyJAhAEyePJlp06Yxf/58AgICGDduHMHBwRw8eNBmPBYRMZrWaUfrbMq9paVZaDIpgguXk/lPv8a0rKSZ4+V/8vMYkp/PTURynlFjyKOPPoq3tzdffPGFta1bt264u7vzf//3f1gsFvz8/Hj55ZcZOXIkAPHx8Xh7ezNv3jx69Ohxz2NofBSRB6V12kWy0f6z8Vy4nExhF0caB3gZHUdERETuolmzZkRERHD06FEA9uzZw8aNG+nQoQNw87Gl6OhogoKCrJ8xm800adKEyMjIDPeZnJxMQkKCzUtEJDfo9niRTEifNb5lpZK4OjkanEZERETu5tVXXyUhIYGqVavi6OhIamoq77zzDiEhIQBER0cD4O3tbfM5b29v67Z/mjRpEm+99VbOBhcRyYCutItkwtrDfz/PrlnjRURE7N7XX3/NwoULWbRoETt37mT+/Pl8+OGHzJ8//773OWbMGOLj462v06dPZ2NiEZE705V2kXuISUhi35l4TCZ4pIqKdhEREXv3yiuv8Oqrr1qfTa9VqxanTp1i0qRJ9OnTBx8fHwBiYmLw9fW1fi4mJoa6detmuE9XV1dcXV1zPLuIyD/pSrvIPaRfZa9T2pOSRfV/1iIiIvbu6tWrODjYfs11dHQkLS0NgICAAHx8fIiIiLBuT0hIYMuWLQQGBuZqVhGRe9GVdpF7SH+evW1VXWUXERHJCzp37sw777xDmTJlqFGjBrt27eLjjz/mueeeA8BkMjFs2DAmTpxIpUqVrEu++fn50aVLF2PDi4j8g4r2+5CSmobFAi5OulEhv0tKSeW34xcBPc8uIiKSV3z66aeMGzeOl156ifPnz+Pn58cLL7zA+PHjrX1GjRpFYmIiAwYMIC4ujhYtWrB69Wqt0S4idkfrtJO1dTYtFgsjv9lLTEISs56uT1E351xKKUZYd+Q8feduw8fDjcgxbTCZTEZHEjuUn9fqzc/nJiI5Lz+PIfn53EQkd2R2HNGV9iw6eTGR1fvPkXg9lSfDIpn/XGO8PfSLbH619tD/Zo1XwZ6/JScns2XLFk6dOsXVq1cpWbIk9erVIyAgwOhoIiIiIlKAqWjPovIli7DkhUD6ztvG4ejLPDHjN+Y/15hK3kWNjibZzGKxWCeh0/Ps+ddvv/3GJ598wooVK0hJScFsNuPu7k5sbCzJycmUL1+eAQMG8OKLL1K0qP47FxEREZHcpYey70PNh8x8N7AZ5UsW5mx8Et1mbWLLib+MjiXZ7EjMZc7EXcPVyYFmFUoYHUdywGOPPcZTTz1FuXLl+Omnn7h8+TJ//fUXf/75J1evXuXYsWOMHTuWiIgIKleuTHh4uNGRRURERKSA0ZX2++TvVYilLzbj+QXb2XHqEs98sZWPn6rDo7X9jI4m2SR91vgWFUvg7uJocBrJCZ06dWLp0qU4O2c8N0X58uUpX748ffr04eDBg5w7dy6XE4qIiIhIQacr7Q+gWGEXFj7fhOAa3lxPTWPQol18/usJo2NJNok4FANo1vj87IUXXrhjwf5P1atXp23btjmcSERERETElor2B+Tm7MjMkAY826wcABN/OMTbKw6SllbgJ+XP0/66ksyu03EAtNHz7AXSiRMnOHDgAGlpaUZHEREREZECTEV7NnB0MPFG5+qM6VAVgC9/O8ngr3aRlJJqcDK5X78cuYDFAtV9PfA1uxsdR3JQSkoKb7zxBp07d+add94hNTWVnj17UqlSJWrXrk3NmjX5448/jI4pIiIiIgWUivZsYjKZeOHhCnzSoy7OjiZ+2HeO3l9uJf5qitHR5D5YZ43XrfH53quvvsqsWbPw8fHhyy+/pGvXruzatYtFixaxePFinJyceP31142OKSIiIiIFlCaiy2aP132IkkVdeWHBDraejKVb2CbmP9eYhzx1tTavuH4jjQ1HLwC6Nb4g+Pbbb5k3bx4dO3bk6NGjVK1alR9++IEOHToAUKpUKUJCQgxOKSIiIiIFla6054BmFUrwzcBAfDzcOH7+Ck/M+I0DZ+ONjiWZtP2PWC4n36B4YRfqlPY0Oo7ksLNnz1KnTh0AKleujKurKxUrVrRur1y5MtHR0UbFExEREZECTkV7Dqnq48Gy0GZU8S7K+cvJPPXZZn49dsHoWJIJEX/fGv9I1VI4OJgMTiM5LTU11WYGeScnJxwd/7fEn4ODAxaLJpYUEREREWPo9vgc5Gt25+sXA3nhP9vZfCKWvnO3Mfnftelav7TR0eQu0p9nD9Lz7AXGmjVrMJvNAKSlpREREcH+/fsBiIuLMzCZiIiIiBR0KtpzmNndmfnPNWbkN3tZsecsI77ew7n4JF5qXQGTSVdx7c2JC1c4eTERZ0cTLSqVNDqO5JI+ffrYvH/hhRds3uu/VRERERExim6PzwWuTo588lRdXmhVHoAP1hxh3H/3k6q13O1OxKGbV9mbli9OEVf9plUQpKWl3fOVmqrlG0VERETEGKpKcomDg4kxHavha3bjrZUH+b/NUUTHJ/Npz3q4uzjeeweSKyIOxwCaNV5ERCQ7/fHHH+zevZtTp05x9epVSpYsSb169QgMDMTNzc3oeCIidk1Fey57tnkA3h5uDF2ym58PxdDr88180acRXoVdjI5W4MVfS2HbH5cAFe0FyYYNGzLVr1WrVjmcREQk//n6668BqFu3Lt7e3vj5+eHu7k5sbCy///47bm5uhISEMHr0aMqWLWtwWhER+6Si3QAdavlSsqgr/eZvZ1dUHN1mbWJe30aULV7Y6GgF2oajF0hNs1CxVBH9b1GAtG7d2vrM+p1miTeZTLpFXkQki+rVq2ddjWP//v1Ur17dZntycjKRkZEsXryYhg0bMnPmTJ588kkjooqI2DU9026QhuW8WDqwGQ95unPyYiLdZm1iz+k4o2MVaOmzxrfVVfYCpVixYvj7+zNu3DiOHTvGpUuXbnvFxsYaHVNEJM957733WLt2LQClS9++co6rqyutW7cmLCyMw4cPU758+dyOKCKSJ6hoN1DFUkVYFtqMGn4eXLxynR6zN7P272eqJXelpllYd+Tvor2at8FpJDedO3eO999/n8jISGrVqkW/fv3YtGkTHh4emM1m60tERLImODg4032LFy9OgwYNcjCNiEjelaWiPS0tjXXr1vH222/Tr18/evbsyZAhQ5g7dy6nT5/OqYz5Wqmibix5IZBWlUtyLSWV/gt2sHhrlNGxCpxdUZeIu5qC2d2Z+mU8jY4jucjFxYWnnnqKNWvWcPjwYWrXrs2gQYPw9/fn9ddf58aNG0ZHFBHJVywWC2vXruWHH37g0qVLRscREbF7mSrar127xsSJE/H396djx478+OOPxMXF4ejoyPHjx3njjTcICAigY8eObN68Oacz5ztFXJ34ok9D/t2gNKlpFl79bh8fhx+94/O1kv0i/r41vnWVkjg56gaUgqpMmTKMHz+en3/+mcqVK/Pee++RkJBgdCwRkTwrLi4OgMDAQPr3709CQgItW7YkKCiIzp07U61aNfbu3WtsSBERO5ep6qRy5crs3buXOXPmkJCQQGRkJEuXLuX//u//WLVqFVFRUfz++++0bNmSHj16MGfOnJzOne84Ozrwwb9rM6RNRQCmRRxj1Ld7SUlNMzhZwRBxSEu9FXTJycksWrSIoKAgatasSYkSJfjhhx/w8vIyOpqISJ41duxYALp27cq+ffto3749qampREZGsmXLFqpVq8brr79ucEoREftmsmTicu6hQ4eoVq1apnaYkpJCVFQUFSpUeOBwuSUhIQGz2Ux8fDweHh5Gx2HRlijGLt9HmgUerlySmSH1Keyqif5zyunYq7ScvA5HBxM7xgbhWUjL7xUkW7duZe7cuSxevJhy5crRt29fnn766SwV6/Y2hmSn/HxuIpLz/Pz8OHfuHPHx8Vy+fBl/f3/Wrl1L69atgZtj8GOPPUZ0dLSxQe+DxkcReVCZHUcyVQlmtmAHcHZ2zlMFuz3q1aQM3h6uDFq0i/VHL/DU7Ei+fLYRpYq6GR0tX0qfNb5B2WIq2Augpk2bUqZMGYYMGWKdBGnjxo239XvsscdyO5qISJ53/vx5658feugh3Nzc8Pf3t7aVKVOGCxcuGBFNRCTPuO/Ltzdu3OCzzz7jl19+ITU1lebNmxMaGoqbmwrL7NC2mjdfDWhKv3nb2H8mga4zNzH/ucZUKFnE6Gj5ToSWeivwoqKimDBhwh23a512EZH7k5Zm+5ifo6MjJpPJ+v7WP4uISMbuu2gfMmQIR48epWvXrqSkpLBgwQK2b9/OV199lZ35CrS6/p4sHdiMZ+du5Y+/rtJt1ia+6NOQBmX1jG12SUy+webf/wKgbTUV7QXRP79QiohI9gsLC8PNzY0bN24wb948SpQoAcDly5cNTiYiYv8yXbQvW7aMJ554wvr+p59+4siRIzg6OgI31+Js2rRp9ics4MqVKMzSgc14bv529pyOo9ecLXzSox7ta/oYHS1f2Hj8ItdT0yhbvJDuYhAREclm/v7+REVFMWPGDBwcHPDx8eE///mPTZ8yZcoYlE5EJG/I9NpWX375JV26dOHs2bMA1K9fnxdffJHVq1ezYsUKRo0aRaNGjXIsaEFWvIgrX/VvQlC1UiTfSGPgwh3M3/SH0bHyhbWHbt4a36ZqKd2iVwBlZYnKq1evcuDAgRxMIyKS/+zbt8/6z5MnT97xJSIid5bpon3FihX07NmT1q1b8+mnnzJ79mw8PDx4/fXXGTduHP7+/ixatCgnsxZohVycCHu6Ab2alMFigTe+P8CkHw+Rlqa13O9XWpqFtUfSn2f3NjiNGOGZZ54hODiYb775hsTExAz7HDx4kNdee40KFSqwY8eObDluamoq48aNIyAgAHd3dypUqMCECRO4dTEPi8XC+PHj8fX1xd3dnaCgII4dO2azn9jYWEJCQvDw8MDT05N+/fpx5coVmz579+6lZcuW1smfJk+enC3nICIiIiK5I0vPtD/11FMEBwczatQogoODCQsL46OPPsqpbPIPTo4OvNOlJg95uvPBmiN8tv4E0fFJTP53bVydHI2Ol+fsOxPPhcvJFHZxpHGA5gkoiA4ePMisWbMYO3YsvXr1onLlyvj5+eHm5salS5c4fPgwV65c4YknnuCnn36iVq1a2XLc999/n1mzZjF//nxq1KjB9u3b6du3L2azmSFDhgAwefJkpk2bxvz58wkICGDcuHEEBwdz8OBB64SfISEhnDt3jvDwcFJSUujbty8DBgyw/oCakJBAu3btCAoKIiwsjH379vHcc8/h6enJgAEDsuVcRETu5tq1azbvx4wZQ3JysvW9o6MjEyZM0ETGIiJ3kal12jOyYcMGQkNDad++fZ4fbPPiOptLd/zJ6KV7uZFmIbB8cT7r3QAPN2ejY+UpH4cfZVrEMTrU9GHW0w2MjiMG2759Oxs3buTUqVNcu3aNEiVKUK9ePR555JF7rtme1THk0Ucfxdvbmy+++MLa1q1bN9zd3fm///s/LBYLfn5+vPzyy4wcORKA+Ph4vL29mTdvHj169ODQoUNUr16dbdu20bBhQwBWr15Nx44d+fPPP/Hz82PWrFm8/vrrREdH4+JycznDV199leXLl3P48OFM/b3kxfFRROzHlClTGDFihHUMKVq0KDVq1MDd3R2Aw4cPM2rUKIYPH25w0qzT+CgiDyqz40imb4+Pioqie/fu1KpVi5CQECpVqsSOHTsoVKgQderU4ccff8yW4JI53RqU5stnG1HYxZHIE3/RPSySc/HX7v1BsVp7OAa4+Ty7SMOGDRk2bBhTpkwhLCyMiRMn0q1bt3sW7PejWbNmREREcPToUQD27NnDxo0b6dChAwAnT54kOjqaoKAg62fMZjNNmjQhMjISgMjISDw9Pa0FO0BQUBAODg5s2bLF2qdVq1bWgh1uThp65MgRLl26lGG25ORkEhISbF4iIvfrm2++ua1t0aJFrFu3jnXr1vHBBx/w9ddfG5BMRCTvyHTR3rt3bxwcHPjggw8oVaoUL7zwAi4uLrz11lssX76cSZMm0b1795zMKv/QqnJJvn4xkJJFXTkcfZmuMzdxJFpLp2RGdHwS+88kYDJB6yoq2iV3vfrqq/To0YOqVavi7OxMvXr1GDZsGCEhIQBER0cD4O1tO9eCt7e3dVt0dDSlStn+u+vk5ISXl5dNn4z2cesx/mnSpEmYzWbry9/f/wHPVkQKshMnTti8d3Nzw8Hhf18/GzduzMGDB3M7lohInpLpon379u288847tG/fno8//pi9e/dat1WrVo0NGzbYXBXKLmfOnOHpp5+mePHiuLu7U6tWLbZv327dnpnJmvKzGn5mlr3UjAolC3MuPol/h21i0+8XjY5l99b9PQFdndKelCzqanAaKWi+/vprFi5cyKJFi9i5cyfz58/nww8/ZP78+UZHY8yYMcTHx1tfp0+fNjqSiORh8fHxNu8vXLhAuXLlrO/T0tJsnnEXEZHbZbpob9CgAePHj+enn35i9OjRGU7IlN0TG126dInmzZvj7OzMjz/+yMGDB/noo48oVqyYtU/6ZE1hYWFs2bKFwoULExwcTFJSUrZmsWelixVi6cBmNCpXjMtJN3j2y218v+es0bHsWsTfS70FVdNVdsl9r7zyivVqe61atXjmmWcYPnw4kyZNAsDHxweAmJgYm8/FxMRYt/n4+HD+/Hmb7Tdu3CA2NtamT0b7uPUY/+Tq6oqHh4fNS0Tkfvn5+d11+969eyldunQupRERyZsyXbQvWLCA5ORkhg8fzpkzZ/jss89yMhdwc4Zlf39/5s6dS+PGjQkICKBdu3ZUqFABuHmVferUqYwdO5bHH3+c2rVrs2DBAs6ePcvy5ctzPJ898Szkwn/6NaFDTR+up6Yx5KtdzN7wO/c5z2C+lpSSym/Hb96N0EZLvYkBrl69anN7KNycQTktLQ2AgIAAfHx8iIiIsG5PSEhgy5YtBAYGAhAYGEhcXJzNMnRr164lLS2NJk2aWPts2LCBlJQUa5/w8HCqVKli8+OniEhOadeuHUCGF1OuXbvGW2+9RadOnXI7lohInpLpor1s2bJ8++23HDhwgIULF97zl9Ps8P3339OwYUOefPJJSpUqRb169ZgzZ451e2Yma8pIfp1oyc3Zkem96tO3eTkA3l11mLdWHCRVa7nbiDzxF9dSUvE1u1HNt6jRccQO5fSdOp07d+add97hhx9+4I8//mDZsmV8/PHHPPHEEwCYTCaGDRvGxIkT+f7779m3bx+9e/fGz8+PLl26ADcfS2rfvj39+/dn69at/PbbbwwaNIgePXpYx+devXrh4uJCv379OHDgAEuWLOGTTz5hxIgROXp+IiLpXn75ZeDmZJ8ffPAB//3vf/nvf//L5MmTqVKlCpcuXeK1114zOKWIiH3L1DrtiYmJFC5cONM7zWr/Ozlx4gSzZs1ixIgRvPbaa2zbto0hQ4bg4uJCnz59MjVZU0YmTZrEW2+99cD57JGjg4k3OtfgIU93Jv5wiHmb/iAmIYkpT9XFzVlruQNEHPrfrPEmk8ngNGIv0tLSeOeddwgLCyMmJoajR49Svnx5xo0bR7ly5ejXr1+2HevTTz9l3LhxvPTSS5w/fx4/Pz9eeOEFxo8fb+0zatQoEhMTGTBgAHFxcbRo0YLVq1fbLK+5cOFCBg0aRNu2bXFwcKBbt25MmzbNut1sNvPTTz8RGhpKgwYNKFGiBOPHj9ca7SKSa9InzKxcuTKvvvqq9Q5Ak8nEv/71L2bOnHnb9zgREbGVqXXafX19GTp0KH369MHX1zfDPhaLhZ9//pmPP/6YVq1aMWbMmAcO5+LiQsOGDdm0aZO1bciQIWzbto3IyEg2bdpE8+bNOXv2rE2u7t27YzKZWLJkSYb7TU5Otpn0JCEhAX9//3y3zuaKPWd5+es9XE9No2HZYnzepyGehVzu/cF8zGKx0Py9tZyNT+LLZxvq9nixevvtt5k/fz5vv/02/fv3Z//+/ZQvX54lS5YwderUu969k5/X6s3P5yYiOe/WMeTGjRscP34cgIoVK+bIkpq5SeOjiDyozI4jmbrS/ssvv/Daa6/x5ptvUqdOHRo2bIifnx9ubm5cunSJgwcPEhkZiZOTE2PGjOGFF17IlpPw9fWlevXqNm3VqlVj6dKlgO1kTbcW7TExMdStW/eO+3V1dcXVNf/PGN65jh8lirgy4D/b2X7qEt1mbWJe38b4exUyOpphDkdf5mx8Em7ODjSrUMLoOGJHFixYwOzZs2nbti0vvviitb1OnTocPnzYwGQiIvmDl5cXjRs3NjqGiEiek6ln2qtUqcLSpUs5evQo3bt358yZM3z77bfMmTOHX375hYceeog5c+bwxx9/8NJLL+HomD23YTdv3pwjR47YtB09epSyZcsCmZusqaALrFCcpQOb4Wt24/cLiXSdtYn9Z+Lv/cF8au3hm7NtN69QQo8LiI0zZ85QsWLF29rT0tJsJnITEZHMefHFFzlz5kym+i5ZsoSFCxfmcCIRkbwpU1fa05UpU4aXX37ZOqlIThs+fDjNmjXj3XffpXv37mzdupXZs2cze/ZswHaypkqVKhEQEMC4ceNsJmsSqOxdlGUvNefZuVs5HH2Zpz6LZObTDXi4ckmjo+U66/PsWupN/qF69er8+uuv1h8F03377bfUq1fPoFQiInlXyZIladq0KQCff/45LVu2vO1OzY0bN7J48WL8/Pys3+9ERMRWlor23NaoUSOWLVvGmDFjePvttwkICGDq1KmEhIRY+2RmsiYBH7MbX78YyIv/2cGm3/+i37xtTOpaiycb+hsdLdf8dSWZXafjAGirZ9nlH8aPH0+fPn04c+YMaWlpfPfddxw5coQFCxawcuVKo+OJiOQ5EyZMoE+fPlSqVIkvvviCV155xWZ70aJFCQoKYvbs2bRv396glCIi9i9TE9HldwVpIpHrN9J45ds9/Hf3WQCGtK3E0LaVcHTI/7OoL93xJy9/s4cafh78MKSl0XHEDv3666+8/fbb7NmzhytXrlC/fn3Gjx9vXWf4TvLzGJKfz01Ect6tY0hqaipRUVFcu3aNEiVKUKFChTy9iovGRxF5UNk6EZ3kHy5ODkzpXhdfszth639nWsQxtv8Ry9Sn6lLKI3/fnZD+PHvbqro1XjLWsmVLwsPDjY4hIpIvFStWjGLFihkdQ0Qkz8nURHSSvzg4mHi1Q1U+erIOhVwc2fT7X3T45Fd+OXLe6Gg55vqNNDYcvQBAm2q6NV5ERERERPIGFe0FWLcGpVkxuAXVfD34K/E6z87dxqRVh0hJTTM6Wrbb9kcsl5NvUKKIC7UfMhsdR+xQsWLF8PLyuu1VvHhxHnroIR5++GHmzp1rdEwREcmkM2fO8PTTT1O8eHHc3d2pVasW27dvt263WCyMHz8eX19f3N3dCQoK4tixYwYmFhHJ2H0V7b/++itPP/00gYGB1qU8/vOf/7Bx48ZsDSc5r0LJIix7qRl9Am/OmP3ZhhM8GRbJ6dirBifLXhGHbt5F8EiVUjgUgOf3JevGjx+Pg4MDnTp14q233uKtt96iU6dOODg4EBoaSuXKlRk4cCBz5swxOqqIiNzDpUuXaN68Oc7Ozvz4448cPHiQjz76yOb2/MmTJzNt2jTCwsLYsmULhQsXJjg4mKSkJAOTi4jcLsvPtC9dupRnnnmGkJAQdu3aRXJyMgDx8fG8++67rFq1KttDSs5yc3bkrcdrElihBKO+3cPu03F0nPYr73erTcdavkbHe2AWi4WIwzeXemurpd7kDjZu3MjEiRN58cUXbdo/++wzfvrpJ5YuXUrt2rWZNm0a/fv3NyiliIhkxvvvv4+/v7/NHVIBAQHWP1ssFqZOncrYsWN5/PHHAViwYAHe3t4sX76cHj165HpmEZE7yfKV9okTJxIWFsacOXNwdna2tjdv3pydO3dmazjJXe1r+rBqaEvql/HkctINXlq4k9eX7SMpJdXoaA/kxMVETv11FRdHB1pUKnhr00vmrFmzhqCgoNva27Zty5o1awDo2LEjJ06cyO1oIiL5wo0bN/j555/57LPPuHz5MgBnz57lypUr2X6s77//noYNG/Lkk09SqlQp6tWrZ3On1MmTJ4mOjrYZ981mM02aNCEyMjLDfSYnJ5OQkGDzEhHJDVku2o8cOUKrVq1uazebzcTFxWVHJjFQ6WKFWPJCIC+1roDJBAu3RNFlxm8cP3/Z6Gj3be3ft8Y3Ke9FEVctmCAZ8/LyYsWKFbe1r1ixAi8vLwASExMpWrRobkcTEcnzoqKiqFWrFo8//jihoaFcuHBzctj333+fkSNHZvvxTpw4waxZs6hUqRJr1qxh4MCBDBkyhPnz5wMQHR0NgLe37eS03t7e1m3/NGnSJMxms/Xl7++f7blFRDKS5QrGx8eH48ePU65cOZv2jRs3Ur58+ezKJQZydnRgVPuqBFYozvAluzkcfZnOn/7GW4/V4MmGpfPcmqrWW+O11Jvcxbhx4xg4cCDr1q2jcePGAGzbto1Vq1YRFhYGQHh4OA8//LCRMUVE8qRXX32Vhg0bsmfPHooXL25tf+KJJ3LkkaO0tDQaNmzIu+++C0C9evXYv38/YWFh9OnT5772OWbMGEaMGGF9n5CQoMJdRHJFlq+09+/fn6FDh7JlyxZMJhNnz55l4cKFjBw5koEDB+ZERjFIy0olWTW0JS0rleBaSiqjlu5l2JLdXE5KMTpapsVfS2HbH5cAaFNVS73JnfXv35/169dTuHBhvvvuO7777jsKFSrE+vXr6devHwAvv/wyS5YsMTipiEjes2nTJsaOHYuLi4tNe7ly5ayTGmcnX19fqlevbtNWrVo1oqKigJsXoQBiYmJs+sTExFi3/ZOrqyseHh42LxGR3JDlK+2vvvoqaWlptG3blqtXr9KqVStcXV0ZOXIkgwcPzomMYqBSRd2Y37cxYRt+56OfjvLf3WfZczqOT3vWp1Zp+186bcPRC6SmWahUqghlihcyOo7YuebNm9O8eXOjY4iI5DtpaWmkpt4+R86ff/6ZI48dNW/enCNHjti0HT16lLJlb66WExAQgI+PDxEREdStWxe4eeV8y5YtugglInYny1faTSYTr7/+OrGxsezfv5/Nmzdz4cIFJkyYkBP5xA44OJh4qXVFvn6hKQ95uvPHX1fpOus3vth4EovFYnS8u4o4dPMX9DaaNV6yICkpSZMNiYhkozZt2jB16lTre5PJxJUrV3jjjTfo2LFjth9v+PDhbN68mXfffZfjx4+zaNEiZs+eTWhoqPX4w4YNY+LEiXz//ffs27eP3r174+fnR5cuXbI9j4jIg7jvWblcXFxuu+1I8rcGZb34YUgLRi/dy5oDMUxYeZDI3y/ywb/rUKywy713kMtupKbxy9GbE9201a3xcg9Xr15l1KhRfP311/z111+3bc/oCpGIiGTOO++8w7///W+qV69OUlISvXr14tixY5QoUYKvvvoq24/XqFEjli1bxpgxY3j77bcJCAhg6tSphISEWPuMGjWKxMREBgwYQFxcHC1atGD16tW4ubllex4RkQdhsmTxUukTTzyR4URkJpMJNzc3KlasSK9evahSpUq2hcxpCQkJmM1m4uPj9XxSJlgsFv6z+RQTVx7iemoaPh5uTOtZj8YBXkZHs7Htj1ieDIvE7O7MjrFBODlm+cYSKUBCQ0NZt24dEyZM4JlnnmHGjBmcOXOGzz77jPfee8/mi94/5ecxJD+fm4jkvFvHkEKFCrF48WL27t3LlStXqF+/PiEhIbi7uxsd875ofBSRB5XZcSTLV9rNZjPLly/H09OTBg0aALBz507i4uJo164dS5Ys4f333yciIkLPhuZTJpOJ3oHlaFC2GIMX7eLExUR6zI5kWFBlQh+piKODfcwuH/H3Um+PVCmpgl3uacWKFSxYsIDWrVvTt29fWrZsScWKFSlbtiwLFy68a9EuIiL35uTkxNNPP210DBGRPOe+lnzr1asX06dPx8HhZiGUlpbG0KFDKVq0KIsXL+bFF19k9OjRbNy4MdsDi/2o4WdmxeAWjPvvfr7beYaPw48S+ftfTO1RF28P428tW3s4/Xl23Rov9xYbG2tdttLDw4PY2FgAWrRooUmJREQe0KpVqyhU6PYJYW+9UzMgIMCAZCIi9i/LRfsXX3zBb7/9Zi3YARwcHBg8eDDNmjXj3XffZdCgQbRs2TJbg4p9KuzqxMfd69K8QgnG/Xc/kSf+ouMnv/Jh9zo8UsW4yd9Ox17laMwVHB1MPFyppGE5JO8oX748J0+epEyZMlStWpWvv/6axo0bs2LFCjw9PY2OJyKSp/Xq1QuTyXTbBLbpbSaTiRYtWrB8+XKKFStmUEoREfuU5XuGb9y4weHDh29rP3z4sHWiJjc3twyfe5f8q1uD0qwY3IJqvh78lXidvnO38e6qQ1y/kWZInrWHb94a37BsMcyFnA3JIHlL37592bNnD3BzacsZM2bg5ubG8OHDeeWVVwxOJyKSty1fvpxGjRoRHh5OfHw88fHxhIeH06RJE1auXMmGDRv466+/GDlypNFRRUTsTpavtD/zzDP069eP1157jUaNGgGwbds23n33XXr37g3A+vXrqVGjRvYmFbtXoWQRlr3UjEmrDjE/8hSzN5xgy8lYpvesh79X7q6RHvF30d5WS71JJg0fPtz656CgIA4fPsyOHTuoWLEitWvXNjCZiEje9+qrr/L555/TrFkza1vbtm1xc3NjwIABHDhwgKlTp/Lcc88ZmFJExD5luWifMmUK3t7eTJ48mZiYm88Me3t7M3z4cEaPHg1Au3btaN++ffYmlTzBzdmRtx6vSWCFEoz6dg97TsfR8ZNfea9bbTrV9s2VDFeSb7D595tLdrXRUm9yn8qWLYvZbNat8SIi2eDkyZMZzozs4eHBiRMnAKhUqRIXL17M7WgiInYvy7fHOzo68vrrr3Pu3Dni4uKIi4vj3LlzvPbaazg6OgJQpkwZSpcune1hJe9oX9OHVUNb0qBsMS4n3yB00U5eW7aPpJScX+t647GLXE9No2zxQlQoWTjHjyf5w/vvv8+SJUus77t3707x4sV56KGHrLfNi4jI/albty6vvPIKFy5csLZduHCBUaNGWe/cPHbsGP7+/kZFFBGxWw+0DpaHh4fWpZQ7Kl2sEIsHNCX0kQqYTLBoSxSPT/+NYzGXc/S41lnjq5bS3AqSaWFhYdYvi+Hh4YSHh/Pjjz/SoUMHPdMuIvKApk+fzsmTJyldujQVK1akYsWKlC5dmj/++IPPP/8cgCtXrjB27FiDk4qI2J8s3x4P8O233/L1118TFRXF9evXbbbt3LkzW4JJ/uDs6MArwVVpWr44w5fs4UjMZTpP38jbj9XkyYals72oTkuzsPbwzV/xg7TUm2RBdHS0tWhfuXIl3bt3p127dpQrV44mTZoYnE5EJG+rVKkSBw8e5KeffuLo0aMAVKlShX/961/WFYm6dOliYEIREfuV5Svt06ZNo2/fvnh7e7Nr1y4aN25M8eLFOXHiBB06dMiJjJIPtKxUkh+HtqRlpRIkpaQxaulehi3ZzeWklGw9zr4z8Vy8kkwRVycalfPK1n1L/lasWDFOnz4NwOrVqwkKCgLAYrFYV8YQEZH75+DgQPv27RkyZAhDhgwhODjYZglhERHJWJavtM+cOZPZs2fTs2dP5s2bx6hRoyhfvjzjx48nNjY2JzJKPlGyqCvz+zYmbMPvfPTTUf67+yy7T8cxvWd9apU2Z8sx0meNb1W5BC5O+iIgmde1a1d69epFpUqV+Ouvv6w/Qu7atYuKFSsanE5EJO9LTExk/fr1Gd6pOWTIEINSiYjYvywX7VFRUdblOtzd3bl8+ebzyc888wxNmzZl+vTp2ZtQ8hUHBxMvta5Ik4DiDPlqF6f+ukrXWb/xaodqPNe83APfLv+/59l1a7xkzZQpUyhXrhynT59m8uTJFClSBIBz587x0ksvGZxORCRv27NnD927d+fq1askJibi5eXFxYsXKVSoEKVKlVLRLiJyF1m+FOnj42O9ol6mTBk2b94M3FzKw2KxZG86ybcalC3GqiEtCa7hTUqqhQkrD/L8/O1cSrx+7w/fQXR8EvvPJGAyQesqJbMxrRQEzs7OjBw5kk8++YR69epZ24cPH87zzz9vYDIRkbzvtddeo3Pnzly6dAl3d3c2b97MqVOnaNCgAR9++KHR8URE7FqWr7S3adOG77//nnr16tG3b1+GDx/Ot99+y/bt2+natWtOZJR8ylzImbCnG/B/m08x4YdDRBw+T4dPfuWTHnVpUr54lve39u9b4+v6e1KiiGt2x5V8bsGCBXfd3rt371xKIiKS/+zbt4/PP/8cBwcHHB0dSU5Opnz58kyePJk+ffroO6SIyF1kuWifPXs2aWlpAISGhlK8eHE2bdrEY489xgsvvJDtASV/M5lMPBNYjvplizH4q12cuJBIzzmbGdq2MoPaVMTRIfO3y6ffGt+2aqmciiv52NChQ23ep6SkcPXqVVxcXChUqJCKdhGRB+Dk5GSddK5UqVJERUVRrVo1zGazdRJQERHJWJaLdgcHB5uZPnv06EGPHj2yNZQUPDX8zKwY1ILx/z3A0p1/MuXno2w+8RdTe9TF28Ptnp9PSkll4/GLgJ5nl/tz6dKl29qOHTvGwIEDtU67iMgDql27Ntu2baNSpUo8/PDDjB8/nosXL/Kf//yHmjVrGh1PRMSuZfmZ9tWrV7Nx40br+xkzZlC3bl169eqV4Zdekcwq7OrER93r8HH3OhRycSTyxF90+ORX1h05f8/PRv7+F0kpafiZ3ajmWzQX0kpBUKlSJd57773brsKLiEjWjB8/Hl9fXwDeeecdihUrxsCBA7lw4QKzZ882OJ2IiH3LctH+yiuvkJCQANx8PmnEiBF07NiRkydPMmLEiGwPKAVP1/qlWTm4BdV9PYhNvE7fudt4d9Uhrt9Iu+NnItJnja9W6oFnoBe5lZOTE2fPnjU6hohInla/fn0eeeQR4Obt8atXryYhIYEdO3ZQp04dg9OJiNi3LN8ef/LkSapXrw7A0qVL6dy5M++++y47d+6kY8eO2R5QCqbyJYvw3UvNmLTqEPMjTzF7wwm2nIzl0x71KFO8kE1fi8XC2kM3r8a31a3xcp++//57m/cWi4Vz584xffp0mjdvblAqEZH84dq1azg5OVGo0M3/Dz916hTLli2jevXqtGvXzuB0IiL2LctX2l1cXLh69SoAP//8s3Wg9fLysl6BF8kObs6OvPV4TT57pgFmd2f2nI6j07Rf+WHvOZt+h6MvczY+CTdnBwIrZH3WeRGALl262Ly6du3Km2++Se3atfnyyy+z/Xhnzpzh6aefpnjx4ri7u1OrVi22b99u3W6xWKy3k7q7uxMUFMSxY8ds9hEbG0tISAgeHh54enrSr18/rly5YtNn7969tGzZEjc3N/z9/Zk8eXK2n4uIyL307NnTukpHXFwcjRs35qOPPuLxxx9n1qxZBqcTEbFvWS7aW7RowYgRI5gwYQJbt26lU6dOABw9epTSpUtne0CR4Bo+rBrakgZli3E5+Qahi3Yy5rt9JKWkAv9b6q1FxRK4OTsaGVXysLS0NJtXamoq0dHRLFq0yPocZna5dOkSzZs3x9nZmR9//JGDBw/y0UcfUaxYMWufyZMnM23aNMLCwtiyZQuFCxcmODiYpKQka5+QkBAOHDhAeHg4K1euZMOGDQwYMMC6PSEhgXbt2lG2bFl27NjBBx98wJtvvqnnR0Uk1+3Zs4eWLVsC8O233+Lj48OpU6dYsGAB06ZNMzidiIh9y/Lt8dOnT+ell17i22+/ZdasWTz00EMA/Pjjj7Rv3z7bA4oAPOTpzpIBTZny81Fm/vI7X22NYuepS0zvVY+IQ38/z65b4yWPeP/99/H392fu3LnWtoCAAOufLRYLU6dOZezYsTz++OPAzXXkvb29Wb58OT169ODQoUOsXr2abdu20bBhQwA+/fRTOnbsyIcffoifnx8LFy7k+vXrfPnll7i4uFCjRg12797Nxx9/bFPc3yo5OZnk5GTre91BJSLZ4dq1axQtenOi2J9++omuXbvi4OBA06ZNOXXqlMHpRETsW5avtJcpU4aVK1eyZ88e+vXrZ22fMmWKfimVHOXk6MArwVX5z3NNKFHElSMxl+k8fSO7TscB0Ebrs0se8f3339OwYUOefPJJSpUqRb169ZgzZ451+8mTJ4mOjiYoKMjaZjabadKkCZGRkQBERkbi6elpLdgBgoKCcHBwYMuWLdY+rVq1wsXFxdonODiYI0eO3HG1j0mTJmE2m60vf3//bD13ESmYypcvz/Llyzl9+jRr1qyxPl55/vx5PDw8DE4nImLfsly0R0VF3fUlktNaVCrBj0Nb0rJSCZJS0rBYoIafBz7me6/nLmIPTpw4waxZs6hUqRJr1qxh4MCBDBkyhPnz5wMQHR0NgLe37d0j3t7e1m3R0dGUKmX7Q5WTkxNeXl42fTLax63H+KcxY8YQHx9vfZ0+ffoBz1ZEBEaNGsXIkSMpV64cTZo0ITAwELh51b1evXoGpxMRsW9Zvj2+XLlyd11SKzU19YECiWRGyaKuzO/bmLANvzN7wwn6NCtndCSRTEtLS6Nhw4a8++67ANSrV4/9+/cTFhZGnz59DM3m6uqKq6uroRlEJP/p0qUL7dq149y5czZLvLVt25YnnnjCwGQiIvYvy0X7rl27bN6npKSwa9cuPv74Y955551sCyZyLw4OJl5qXZGBD1fQ2uySp/j6+lqXzkxXrVo1li5dCoCPjw8AMTExNpPgxcTEULduXWuf8+fP2+zjxo0bxMbGWj/v4+NDTEyMTZ/09+l9RERyi4+Pz21jT+PGjQ1KIyKSd2S5aL/119F0DRs2xM/Pjw8++ICuXbtmSzCRzFLBLtmhXLlyPPfcczz77LOUKVMmR4/VvHlzjhw5YtN29OhRypYtC9yclM7Hx4eIiAhrkZ6QkMCWLVsYOHAgAIGBgcTFxbFjxw4aNGgAwNq1a0lLS6NJkybWPq+//jopKSk4OzsDEB4eTpUqVWxmqhcRyWmPPvooTk53/tq5du3aXEwjIpK3ZPmZ9jupUqUK27Zty67diYjkqmHDhvHdd99Rvnx5/vWvf7F48WKbWdSz0/Dhw9m8eTPvvvsux48fZ9GiRcyePZvQ0FDg5g9Rw4YNY+LEiXz//ffs27eP3r174+fnR5cuXYCbV+bbt29P//792bp1K7/99huDBg2iR48e+Pn5AdCrVy9cXFzo168fBw4cYMmSJXzyySeMGDEiR85LROROatWqRZ06dayv6tWrc/36dXbu3EmtWrWMjiciYtdMFovFkpUP/HP5H4vFwrlz53jzzTc5fPgwu3fvzs58uSIhIQGz2Ux8fLxmMBUp4Hbu3Mm8efP46quvSE1NpVevXjz33HPUr1//jp+5nzFk5cqVjBkzhmPHjhEQEMCIESPo37+/dbvFYuGNN95g9uzZxMXF0aJFC2bOnEnlypWtfWJjYxk0aBArVqzAwcGBbt26MW3aNIoUKWLts3fvXkJDQ9m2bRslSpRg8ODBjB49OtN/HxofReRB3GsMefPNN7ly5QoffvihAekejMZHEXlQmR1Hsly0Ozg43HY7ssViwd/fn8WLF1tnA81LNOiKyD+lpKQwc+ZMRo8eTUpKCrVq1WLIkCH07dv3tjEwP48h+fncRCTn3WsMOX78OI0bNyY2NtaAdA9G46OIPKjMjiNZfqZ93bp1Nu8dHBwoWbIkFStWvOuzSiIieUFKSgrLli1j7ty5hIeH07RpU/r168eff/7Ja6+9xs8//8yiRYuMjikiki9ERkbi5qYlW0VE7ibLVfbDDz+cEzlERAy1c+dO5s6dy1dffYWDgwO9e/dmypQpVK1a1drniSeeoFGjRgamFBHJm0JCQqwTYsL/Hq/cvn0748aNMzCZiIj906VxERGgUaNG/Otf/2LWrFl06dLF5stluoCAAHr06GFAOhGRvM1sNtuMqw4ODlSpUoW3336bdu3aGZhMRMT+qWgXkQIvNTWVL7/8kscee+yuS6EVLlyYuXPn5mIyEZH8YebMmXruW0TkPmXbkm8iInmVo6MjL7zwAnFxcUZHERERERGxoaJdRASoWbMmJ06cMDqGiIiIiIiNTN8e/8/12dMVLlwYR0fHbAskImKEiRMnMnLkSCZMmECDBg0oXLiwzXbd1ikiIiIiRsh00e7p6Xnb2sRw87bSgIAARo4cSf/+/bM1nIhIbunYsSMAjz32mM1YZ7FYMJlMpKamGhVNRERERAqwTBft/1yfPV1cXBw7duzglVdewcnJib59+2ZbuH967733GDNmDEOHDmXq1KkAJCUl8fLLL7N48WKSk5MJDg5m5syZeHt751gOEcl/7jTGiYjIgzt48CBNmzbNcNvy5cvp0qVL7gYSEclDMl2032199scff5xy5crx6aef5ljRvm3bNj777DNq165t0z58+HB++OEHvvnmG8xmM4MGDaJr16789ttvOZJDRPKnu41xIiLyYNK/mwUEBNi0L126lN69e5OYmGhQMhER+5dtE9E9/PDDHD9+PLt2Z+PKlSuEhIQwZ84cm+WY4uPj+eKLL/j4449p06YNDRo0YO7cuWzatInNmzfnSBYRyb/i4uL46KOPeP7553n++eeZMmUK8fHxRscSEcnzevfuTVBQENHR0da2JUuW0Lt3b+bNm2dcMBGRPCDbivb4+HjMZnN27c5GaGgonTp1IigoyKZ9x44dpKSk2LRXrVqVMmXKEBkZecf9JScnk5CQYPMSkYJt+/btVKhQgSlTphAbG0tsbCwff/wxFSpUYOfOnUbHExHJ01577TU6duxIUFAQsbGxLFq0iL59+7JgwQKefPJJo+OJiNi1TN8efzcpKSl88MEHNGnSJDt2Z2Px4sXs3LmTbdu23bYtOjoaFxcXPD09bdq9vb1tfsn9p0mTJvHWW29ld1QRycOGDx/OY489xpw5c3Byujk03rhxg+eff55hw4axYcMGgxOKiORtn376KSEhITRt2pQzZ87w1Vdf8fjjjxsdS0TE7mW6aO/atWuG7fHx8Rw4cACTycSvv/6abcEATp8+zdChQwkPD8fNzS3b9jtmzBhGjBhhfZ+QkIC/v3+27V9E8p7t27fbFOwATk5OjBo1ioYNGxqYTEQkb/r++++5evUqAKtWraJQoUJ07dqVX3/9lZ49e2Iymfj++++Bmyt3iIhIxjJdtN/p1nd/f3+6detGSEhItt8ev2PHDs6fP0/9+vWtbampqWzYsIHp06ezZs0arl+/TlxcnM3V9piYGHx8fO64X1dXV1xdXbM1q4jkbR4eHkRFRVG1alWb9tOnT1O0aFGDUomI5F23zgjfq1cvm21ffvklX375JYCW1RQRuYdMF+1z587NyRwZatu2Lfv27bNp69u3L1WrVmX06NH4+/vj7OxMREQE3bp1A+DIkSNERUURGBiY63lFJO966qmn6NevHx9++CHNmjUD4LfffuOVV16hZ8+eBqcTEcl70tLSSEhIwGw2ExcXh4eHh9GRRETypCw9075582ZWrFjB9evXadu2Le3bt8+pXAAULVqUmjVr2rQVLlyY4sWLW9v79evHiBEj8PLywsPDg8GDBxMYGHjHtUBFRDLy4YcfYjKZ6N27Nzdu3ADA2dmZgQMH8t577xmcTkQk//nnnZIiIpKxTM8e/+2339K8eXM++eQTPv/8czp16sSHH36Yk9kyZcqUKTz66KN069aNVq1a4ePjw3fffWd0LBHJY1xcXPjkk0+4dOkSu3fvZvfu3cTGxjJlyhQ9TiMi8oCmTJnCkiVLrO+ffPJJvLy8eOihh9izZ0+OH/+9997DZDIxbNgwa1tSUhKhoaEUL16cIkWK0K1bN2JiYnI8i4hIVpksFoslMx0bNGhAo0aNmDFjBo6OjkyaNIkPPviA2NjYnM6Y49Jv3YqPj9etWyKSZfl5DMnP5yYiOS99DClTpgxfffUVzZo1Izw8nO7du7NkyRK+/vproqKi+Omnn3Isw7Zt2+jevTseHh488sgjTJ06FYCBAwfyww8/MG/ePMxmM4MGDcLBwYHffvstS+em8VFE7ldmx5FM3x5/5MgRlixZgqOjIwAvv/wy48eP5/z585QqVerBE4uIGCgpKYlPP/2UdevWcf78edLS0my2a612EZH7d/78eetKPStXrqR79+60a9eOcuXK5ciSwemuXLlCSEgIc+bMYeLEidb2+Ph4vvjiCxYtWkSbNm2Am/M3VatWjc2bN2f4mGVycjLJycnW9wkJCTmWW0TkVpm+Pf7q1as21b+Liwtubm5cuXIlR4KJiOSmfv36MXnyZMqWLcujjz7K448/bvMSEZH75+npyenTpwFYvXo1QUFBAFgslhydOT40NJROnTpZj5dux44dpKSk2LRXrVqVMmXKEBkZmeG+Jk2ahNlstr60XLCI5JYsTUT3+eefU6RIEev7GzduMG/ePEqUKGFtGzJkSPalExHJJStXrmTVqlU0b97c6CgiIvlO586d6dWrF5UqVeKvv/6iQ4cOAOzatYuKFSvmyDEXL17Mzp072bZt223boqOjcXFxuW0iPG9vb6KjozPc35gxYxgxYoT1fUJCggp3EckVmS7ay5Qpw5w5c2zafHx8+M9//mN9bzKZVLSLSJ700EMPaT12EZEcMmnSJCpXrszp06eZPHmy9SLQuXPneOmll7L9eKdPn2bo0KGEh4fj5uaWLft0dXXVxKQiYohMF+1//PFHDsYQETHWRx99xOjRowkLC6Ns2bJGxxERyVecnZ0ZOXLkbe3Dhw/PkePt2LGD8+fPU79+fWtbamoqGzZsYPr06axZs4br16/ftuxcTEwMPj4+OZJJROR+Zen2eBGR/Kphw4YkJSVRvnx5ChUqhLOzs832/LBShohIbvr++++tjxytWrWKQoUK3bHvY489lq3Hbtu2Lfv27bNp69u3L1WrVmX06NH4+/vj7OxMREQE3bp1A25OuhwVFUVgYGC2ZhEReVCZLtrXrl3LoEGD2Lx5823T0cfHx9OsWTNmzZpFq1atsj2kiEhO69mzJ2fOnOHdd9/F29sbk8lkdCQRkTytS5cuHDt2DIBevXrdsZ/JZMr2yeiKFi1KzZo1bdoKFy5M8eLFre39+vVjxIgReHl54eHhweDBgwkMDMxw5ngRESNlumifOnUq/fv3z3D9OLPZzAsvvMCUKVNUtItInrRp0yYiIyOpU6eO0VFERPKFtLQ067JocXFxdreW+ZQpU3BwcKBbt24kJycTHBzMzJkzjY4lInKbTBfte/bs4f3337/j9nbt2vHhhx9mSygRkdxWtWpVrl27ZnQMERHJIb/88ovNezc3N2bMmMGMGTOMCSQikkmZXqc9Jibmtmc8b+Xk5MSFCxeyJZSISG577733ePnll/nll1/466+/SEhIsHmJiMj9+89//sOjjz5KzZo1qVWrFo899hgLFizAYrEYHU1ExO5l+kr7Qw89xP79+++4lubevXvx9fXNtmAiIrmpffv2wM3Ji25lsVhy5HlLEZGCIL0oHzx4MHXq1KFWrVpYLBYOHTrEs88+y3fffcfy5cuNDSkiYucyXbR37NiRcePG0b59+9vWu7x27RpvvPEGjz76aLYHFBHJDevWrTM6gohIvrNw4ULg5kzy//yeuHbtWrp06cKCBQvo3bu3EfFERPIEkyWT9yXFxMRQv359HB0dGTRoEFWqVAHg8OHDzJgxg9TUVHbu3Im3t3eOBs4JCQkJmM1m4uPj7W6SFBGxf/l5DMnP5yYiOa9NmzasW7fujmPIu+++y/r161mzZo0B6R6MxkcReVCZHUcy/Uy7t7c3mzZtombNmowZM4YnnniCJ554gtdee42aNWuycePGPFmwi4ik+/XXX3n66adp1qwZZ86cAW4+h7lx40aDk4mI5E0HDhy46/YOHTqwZ8+eXEojIpI3ZbpoByhbtiyrVq3i4sWLbNmyhc2bN3Px4kVWrVpFQEBATmUUEclxS5cuJTg4GHd3d3bu3ElycjIA8fHxvPvuuwanExHJmy5dunTX7d7e3vfsIyJS0GWpaE9XrFgxGjVqROPGjSlWrFh2ZxIRyXUTJ04kLCyMOXPm2KyU0bx5c3bu3GlgMhGRvOtek3g6Ojpy48aNXEojIpI3ZXoiOhGR/OzIkSO0atXqtnaz2UxcXFzuBxIRyQfSp04KCQnJcOng9LuaRETkzu7rSruISH7j4+PD8ePHb2vfuHEj5cuXz9Fjv/fee5hMJoYNG2ZtS0pKIjQ0lOLFi1OkSBG6detGTEyMzeeioqLo1KkThQoVolSpUrzyyiu3XbH65ZdfqF+/Pq6urlSsWJF58+bl6LmIiNyqV69ewM0fQDN6lSpVSjPHi4jcg660i4gA/fv3Z+jQoXz55ZeYTCbOnj1LZGQkI0eOZNy4cTl23G3btvHZZ59Ru3Ztm/bhw4fzww8/8M0332A2mxk0aBBdu3blt99+A27ectqpUyd8fHzYtGkT586do3fv3jg7O1ufwT958iSdOnXixRdfZOHChURERPD888/j6+tLcHBwjp2TiEi6mTNnsnDhQmbOnKkZ1kVE7pOKdhER4NVXXyUtLY22bdty9epVWrVqhaurKyNHjmTw4ME5cswrV64QEhLCnDlzmDhxorU9Pj6eL774gkWLFtGmTRsA5s6dS7Vq1di8eTNNmzblp59+4uDBg/z88894e3tTt25dJkyYwOjRo3nzzTdxcXEhLCyMgIAAPvroIwCqVavGxo0bmTJliop2ERERkTxCt8eLiAAmk4nXX3+d2NhY9u/fz+bNm7lw4QITJkzIsWOGhobSqVMngoKCbNp37NhBSkqKTXvVqlUpU6YMkZGRAERGRlKrVi2bpTaDg4NJSEiwLrEUGRl5276Dg4Ot+8hIcnIyCQkJNi8RERERMY6utIuI3MLFxYXq1avn+HEWL17Mzp072bZt223boqOjcXFxwdPT06bd29ub6Ohoa59bC/b07enb7tYnISGBa9eu4e7uftuxJ02axFtvvXXf5yUiIiIi2UtFu4gUaM8991ym+n355ZfZdszTp08zdOhQwsPDcXNzy7b9ZocxY8YwYsQI6/uEhAT8/f0NTCQiIiJSsKloF5ECbd68eZQtW5Z69epZlybKaTt27OD8+fPUr1/f2paamsqGDRuYPn06a9as4fr168TFxdlcbY+JicHHxwe4Odv91q1bbfabPrv8rX3+OeN8TEwMHh4eGV5lB3B1dcXV1fWBz1FEREREsoeKdhEp0AYOHMhXX33FyZMn6du3L08//TReXl45esy2bduyb98+m7a+fftStWpVRo8ejb+/P87OzkRERNCtWzfg5jryUVFRBAYGAhAYGMg777zD+fPnKVWqFADh4eF4eHhYb+8PDAxk1apVNscJDw+37kNERERE7J8mohORAm3GjBmcO3eOUaNGsWLFCvz9/enevTtr1qzJsSvvRYsWpWbNmjavwoULU7x4cWrWrInZbKZfv36MGDGCdevWsWPHDvr27UtgYCBNmzYFoF27dlSvXp1nnnmGPXv2sGbNGsaOHUtoaKj1SvmLL77IiRMnGDVqFIcPH2bmzJl8/fXXDB8+PEfOS0RERESyn4p2ESnwXF1d6dmzJ+Hh4Rw8eJAaNWrw0ksvUa5cOa5cuWJIpilTpvDoo4/SrVs3WrVqhY+PD9999511u6OjIytXrsTR0ZHAwECefvppevfuzdtvv23tExAQwA8//EB4eDh16tTho48+4vPPP9dybyIiIiJ5iG6PFxG5hYODAyaTCYvFQmpqaq4d95dffrF57+bmxowZM5gxY8YdP1O2bNnbbn//p9atW7Nr167siCgiIiIiBtCVdhEp8JKTk/nqq6/417/+ReXKldm3bx/Tp08nKiqKIkWKGB1PRERERAowXWkXkQLtpZdeYvHixfj7+/Pcc8/x1VdfUaJECaNjiYiIiIgAKtpFpIALCwujTJkylC9fnvXr17N+/foM+936PLmIiIiISG5R0S4iBVrv3r0xmUxGxxARERERyZCKdhEp0ObNm2d0BBERERGRO9JEdCIiIiIiIiJ2SkW7iIiIiIiIiJ1S0S4iIiIiIiJip1S0i4iIiIiIiNgpFe0iIiIiIiIidkpFu4iIiIiIiIid0pJvIiIiIiI5bN3h8/x0MCaLn7JkrXfWut//Z7CQZrn5WYvFggVIs1iwWP73TwsW0tJu75tm7f/3Z2/pm77Ncuu+/tH31uOQ4XEzaLP8nSGD3Hf/u7l7j3t/PhN/lw94jMz+K5LZ/5nvlSfr+8tkv3vsMVN/lw/cIXtyLHiuMc0qlrh3xyxQ0S4iIiIiksP2n4nnq61RRscQkRx2H7+D3ZOKdhERERGRHNakfHFG/Ktylj9nymr/rH4AMN3Hh0wmcDCZMPH3P0039+NgupnZweHmtpttpr/7gwnT/z5ryuizf//z77b0/Ts4/O+z6X3Tj2+6ZV8ZfdbmOPxjX1k430z0ysZ9ZSXbvXveq8e9dmG6xx7u59+7LGfIhfO8uY8HO1fPQs73PkgWqWgXEREREclhjQO8aBzgZXQMEcmDNBGdiIiIiIiIiJ1S0S4iIiIiIiJip1S0i4iIiIiIiNgpFe0iIiIiIiIidkpFu4iIiIiIiIidUtEuIiIiIiIiYqdUtIuIiIiIiIjYKbsu2idNmkSjRo0oWrQopUqVokuXLhw5csSmT1JSEqGhoRQvXpwiRYrQrVs3YmJiDEosIiIiIiIikn3sumhfv349oaGhbN68mfDwcFJSUmjXrh2JiYnWPsOHD2fFihV88803rF+/nrNnz9K1a1cDU4uIiIiIiIhkDyejA9zN6tWrbd7PmzePUqVKsWPHDlq1akV8fDxffPEFixYtok2bNgDMnTuXatWqsXnzZpo2bWpEbBEREREREZFsYddX2v8pPj4eAC8vLwB27NhBSkoKQUFB1j5Vq1alTJkyREZG3nE/ycnJJCQk2LxERERERERE7E2eKdrT0tIYNmwYzZs3p2bNmgBER0fj4uKCp6enTV9vb2+io6PvuK9JkyZhNputL39//5yMLiIiIiIiInJf8kzRHhoayv79+1m8ePED72vMmDHEx8dbX6dPn86GhCIiIiJiDzSZsYjkJ3miaB80aBArV65k3bp1lC5d2tru4+PD9evXiYuLs+kfExODj4/PHffn6uqKh4eHzUtERERE8gdNZiwi+YldT0RnsVgYPHgwy5Yt45dffiEgIMBme4MGDXB2diYiIoJu3boBcOTIEaKioggMDDQisoiIiIgYTJMZi0h+YtdFe2hoKIsWLeK///0vRYsWtT6nbjabcXd3x2w2069fP0aMGIGXlxceHh4MHjyYwMBADbYiIiIiAmR9MuOMvkcmJyeTnJxsfa+JjEUkt9j17fGzZs0iPj6e1q1b4+vra30tWbLE2mfKlCk8+uijdOvWjVatWuHj48N3331nYGoRERERsRfZNZmxJjIWEaPY9ZV2i8Vyzz5ubm7MmDGDGTNm5EIiEREREclL0icz3rhx4wPtZ8yYMYwYMcL6PiEhQYW7iOQKuy7aRURERETuV/pkxhs2bLjjZMa3Xm2/22TGrq6uuLq65nRkEZHb2PXt8SIiIiIiWWWxWBg0aBDLli1j7dq1d53MOJ0mMxYRe6Ur7SIiIiKSr2gyYxHJT1S0i4iIiEi+MmvWLABat25t0z537lyeffZZ4OZkxg4ODnTr1o3k5GSCg4OZOXNmLicVEbk33R4vIpLLJk2aRKNGjShatCilSpWiS5cuHDlyxKZPUlISoaGhFC9enCJFitCtWzdiYmJs+kRFRdGpUycKFSpEqVKleOWVV7hx44ZNn19++YX69evj6upKxYoVmTdvXk6fnoiI4SwWS4av9IId/jeZcWxsLImJiXz33Xd3fJ5dRMRIKtpFRHLZ+vXrCQ0NZfPmzYSHh5OSkkK7du1ITEy09hk+fDgrVqzgm2++Yf369Zw9e5auXbtat6emptKpUyeuX7/Opk2bmD9/PvPmzWP8+PHWPidPnqRTp0488sgj7N69m2HDhvH888+zZs2aXD1fEREREbl/Jktm1lXL5xISEjCbzcTHx+Ph4WF0HBHJYx50DLlw4QKlSpVi/fr1tGrVivj4eEqWLMmiRYv497//DcDhw4epVq0akZGRNG3alB9//JFHH32Us2fP4u3tDUBYWBijR4/mwoULuLi4MHr0aH744Qf2799vPVaPHj2Ii4tj9erVGWZJTk4mOTnZ5tz8/f01PorIfcnP37Hy87mJSO7I7DiiK+0iIgaLj48HwMvLC4AdO3aQkpJCUFCQtU/VqlUpU6YMkZGRAERGRlKrVi1rwQ4QHBxMQkICBw4csPa5dR/pfdL3kZFJkyZhNputL61BLCIiImIsFe0iIgZKS0tj2LBhNG/enJo1awIQHR2Ni4uLzdrBAN7e3tYZkKOjo20K9vTt6dvu1ichIYFr165lmGfMmDHEx8dbX6dPn37gcxQRERGR+6fZ40VEDBQaGsr+/fvZuHGj0VEAcHV1xdXV1egYIiIiIvI3XWkXETHIoEGDWLlyJevWraN06dLWdh8fH65fv05cXJxN/5iYGOvMxj4+PrfNJp/+/l59PDw8cHd3z+7TEREREZEcoKJdRCSXWSwWBg0axLJly1i7di0BAQE22xs0aICzszMRERHWtiNHjhAVFUVgYCAAgYGB7Nu3j/Pnz1v7hIeH4+HhQfXq1a19bt1Hep/0fYiIiIiI/dPt8SIiuSw0NJRFixbx3//+l6JFi1qfQTebzbi7u2M2m+nXrx8jRozAy8sLDw8PBg8eTGBgIE2bNgWgXbt2VK9enWeeeYbJkycTHR3N2LFjCQ0Ntd7e/uKLLzJ9+nRGjRrFc889x9q1a/n666/54YcfDDt3EREREckaXWkXEclls2bNIj4+ntatW+Pr62t9LVmyxNpnypQpPProo3Tr1o1WrVrh4+PDd999Z93u6OjIypUrcXR0JDAwkKeffprevXvz9ttvW/sEBATwww8/EB4eTp06dfjoo4/4/PPPCQ4OztXzFREREZH7p3Xa0TqbIvJg8vMYkp/PTURyXn4eQ/LzuYlI7tA67SIiIiIiIiJ5nIp2ERERERERETulol1ERERERETETqloFxEREREREbFTKtpFRERERERE7JSKdhERERERERE7paJdRERERERExE6paBcRERERERGxUyraRUREREREROyUinYRERERERERO+VkdAARERHJmhupaSTdSCMpJfXv180/J9/435/T/5lmsWAymQAwASbT3y9M/N18c5vJ9L/tf29Lf/93j1vaTDbb0j/DP7aTwf74x7Gt/W2OZ7rls7b7y8ssRgfIRrUfMuPgkB/+VxERsX8q2kVERB6AxWIh+YZtoZxkUzzf/PPNgvofRfUtbcl3+FzSjVSSb227kUZqWn4q/yQvOjKxPa4OjkbHEBEpEFS0i4hItnl/9WH2/RkPYHMV9+b7/13tTd9uuss2bmm59aqs7ft/bP9HO7d9LuPjZLT9RprFWiQnpaTeLKr/UWjfvLqddpe/kZzn6uSAm7Mjbs5//9Pp5p9dnR1xc3Yk/WKoxXLzSq/FYrnl/S1//vt9er/0y8K3tlkslr//ectVY5s2i3Vf6bv45/Fu/Wz6/vjH/m/rn49+o/jnfxciIiL3oqJdRESyzf4z8Ww8ftHoGIZxcjBZC2hXJ9t/uv1dRLs5O+Dm5Ph3UW1baN9afN/pc7Z9HKw/NIiIiEj+pKJdRESyzcCHK/DvBqVvudL6v6usNv8k/b3lliu2d/gM//xsxtvTG27rf6d2bLf/Yzc4OJgyLJT/V4j/o6h2csDJUfO7ioiISPZS0S4iItmmWcUSRkcQERERyVd0SUBERERERETETqloFxEREREREbFTKtpFRERERERE7JSKdhERERERERE7paJdRERERERExE6paBcRERERERGxUyraRUREREREROyUinYRERERERERO6WiXURERERERMROqWgXERERERERsVMq2kVERERERETslIp2ERERERERETulol1ERERERETETqloFxEREREREbFTKtpFRERERERE7JSKdhERERERERE7paJdRERERERExE6paBcRERERERGxUyraRUREREREROyUinYRERERERERO5VvivYZM2ZQrlw53NzcaNKkCVu3bjU6koiIXdD4KCJyZxojRcTe5YuifcmSJYwYMYI33niDnTt3UqdOHYKDgzl//rzR0UREDKXxUUTkzjRGikhekC+K9o8//pj+/fvTt29fqlevTlhYGIUKFeLLL780OpqIiKE0PoqI3JnGSBHJC5yMDvCgrl+/zo4dOxgzZoy1zcHBgaCgICIjIzP8THJyMsnJydb38fHxACQkJORsWBHJl9LHDovFYnASWxofRcRo9jo+QtbHSI2PIpLdMjtG5vmi/eLFi6SmpuLt7W3T7u3tzeHDhzP8zKRJk3jrrbdua/f398+RjCJSMFy+fBmz2Wx0DCuNjyJiL+xtfISsj5EaH0Ukp9xrjMzzRfv9GDNmDCNGjLC+T0tLIzY2luLFi2Myme75+YSEBPz9/Tl9+jQeHh45GTVH5YfzyA/nADoPe3I/52CxWLh8+TJ+fn45nC7naXy8SedhP/LDOUDBPQ+Nj/9TUP8dsFf54TzywzlAwT6PzI6Reb5oL1GiBI6OjsTExNi0x8TE4OPjk+FnXF1dcXV1tWnz9PTM8rE9PDzy9L9Y6fLDeeSHcwCdhz3J6jnY2xUk0PiYHXQe9iM/nAMUzPOwx/ERsj5Gany0pfOwH/nhHKDgnkdmxsg8PxGdi4sLDRo0ICIiwtqWlpZGREQEgYGBBiYTETGWxkcRkTvTGCkieUWev9IOMGLECPr06UPDhg1p3LgxU6dOJTExkb59+xodTUTEUBofRUTuTGOkiOQF+aJof+qpp7hw4QLjx48nOjqaunXrsnr16tsmFskurq6uvPHGG7fdIpXX5IfzyA/nADoPe5IfzuFWGh/vj87DfuSHcwCdh73KzTEyv/zd6TzsR344B9B5ZIbJYo9rcIiIiIiIiIhI3n+mXURERERERCS/UtEuIiIiIiIiYqdUtIuIiIiIiIjYKRXtIiIiIiIiInZKRft9mDFjBuXKlcPNzY0mTZqwdetWoyNlyYYNG+jcuTN+fn6YTCaWL19udKQsmzRpEo0aNaJo0aKUKlWKLl26cOTIEaNjZdmsWbOoXbs2Hh4eeHh4EBgYyI8//mh0rAfy3nvvYTKZGDZsmNFRsuTNN9/EZDLZvKpWrWp0rDxH46PxND7aL42PBZvGR+NpfLRfeXV8hNwZI1W0Z9GSJUsYMWIEb7zxBjt37qROnToEBwdz/vx5o6NlWmJiInXq1GHGjBlGR7lv69evJzQ0lM2bNxMeHk5KSgrt2rUjMTHR6GhZUrp0ad577z127NjB9u3badOmDY8//jgHDhwwOtp92bZtG5999hm1a9c2Osp9qVGjBufOnbO+Nm7caHSkPEXjo33Q+GifND4WbBof7YPGR/uU18dHyIUx0iJZ0rhxY0toaKj1fWpqqsXPz88yadIkA1PdP8CybNkyo2M8sPPnz1sAy/r1642O8sCKFStm+fzzz42OkWWXL1+2VKpUyRIeHm55+OGHLUOHDjU6Upa88cYbljp16hgdI0/T+GifND4aT+OjaHy0TxofjZfXx0eLJXfGSF1pz4Lr16+zY8cOgoKCrG0ODg4EBQURGRlpYDKJj48HwMvLy+Ak9y81NZXFixeTmJhIYGCg0XGyLDQ0lE6dOtn895HXHDt2DD8/P8qXL09ISAhRUVFGR8ozND7aL42PxtP4WLBpfLRfGh+Nlx/GR8j5MdIpW/eWz128eJHU1FS8vb1t2r29vTl8+LBBqSQtLY1hw4bRvHlzatasaXScLNu3bx+BgYEkJSVRpEgRli1bRvXq1Y2OlSWLFy9m586dbNu2zego961JkybMmzePKlWqcO7cOd566y1atmzJ/v37KVq0qNHx7J7GR/uk8dF4Gh9F46N90vhovPwwPkLujJEq2iXPCw0NZf/+/Xn2+boqVaqwe/du4uPj+fbbb+nTpw/r16/PMwPv6dOnGTp0KOHh4bi5uRkd57516NDB+ufatWvTpEkTypYty9dff02/fv0MTCZy/zQ+Gkvjo4j90vhorPwyPkLujJEq2rOgRIkSODo6EhMTY9MeExODj4+PQakKtkGDBrFy5Uo2bNhA6dKljY5zX1xcXKhYsSIADRo0YNu2bXzyySd89tlnBifLnB07dnD+/Hnq169vbUtNTWXDhg1Mnz6d5ORkHB0dDUx4fzw9PalcuTLHjx83OkqeoPHR/mh8NJ7GRwGNj/ZI46Px8uv4CDkzRuqZ9ixwcXGhQYMGREREWNvS0tKIiIjIk8+Q5GUWi4VBgwaxbNky1q5dS0BAgNGRsk1aWhrJyclGx8i0tm3bsm/fPnbv3m19NWzYkJCQEHbv3p1nB9wrV67w+++/4+vra3SUPEHjo/3Q+Gg/ND4KaHy0Jxof7Ud+HR8hZ8ZIXWnPohEjRtCnTx8aNmxI48aNmTp1KomJifTt29foaJl25coVm19+Tp48ye7du/Hy8qJMmTIGJsu80NBQFi1axH//+1+KFi1KdHQ0AGazGXd3d4PTZd6YMWPo0KEDZcqU4fLlyyxatIhffvmFNWvWGB0t04oWLXrbs2CFCxemePHieeoZsZEjR9K5c2fKli3L2bNneeONN3B0dKRnz55GR8szND7aB42P9kPjo6TT+GgfND7aj/wyPkIujZE5Ojd9PvXpp59aypQpY3FxcbE0btzYsnnzZqMjZcm6desswG2vPn36GB0t0zLKD1jmzp1rdLQsee655yxly5a1uLi4WEqWLGlp27at5aeffjI61gPLi0t2PPXUUxZfX1+Li4uL5aGHHrI89dRTluPHjxsdK8/R+Gg8jY/2TeNjwaXx0XgaH+1bXhwfLZbcGSNNFovFkn0/AYiIiIiIiIhIdtEz7SIiIiIiIiJ2SkW7iIiIiIiIiJ1S0S4iIiIiIiJip1S0i4iIiIiIiNgpFe0iIiIiIiIidkpFu4iIiIiIiIidUtEuIiIiIiIiYqdUtIuIiIiIiIjYKRXtkm89++yzdOnSxbDjP/PMM7z77ruZ6tujRw8++uijHE4kInKTxkcRkTvTGCn2xmSxWCxGhxDJKpPJdNftb7zxBsOHD8diseDp6Zk7oW6xZ88e2rRpw6lTpyhSpMg9++/fv59WrVpx8uRJzGZzLiQUkfxK46OIyJ1pjJS8SEW75EnR0dHWPy9ZsoTx48dz5MgRa1uRIkUyNdDllOeffx4nJyfCwsIy/ZlGjRrx7LPPEhoamoPJRCS/0/goInJnGiMlL9Lt8ZIn+fj4WF9msxmTyWTTVqRIkdtubWrdujWDBw9m2LBhFCtWDG9vb+bMmUNiYiJ9+/alaNGiVKxYkR9//NHmWPv376dDhw4UKVIEb29vnnnmGS5evHjHbKmpqXz77bd07tzZpn3mzJlUqlQJNzc3vL29+fe//22zvXPnzixevPjB/3JEpEDT+CgicmcaIyUvUtEuBcr8+fMpUaIEW7duZfDgwQwcOJAnn3ySZs2asXPnTtq1a8czzzzD1atXAYiLi6NNmzbUq1eP7du3s3r1amJiYujevfsdj7F3717i4+Np2LChtW379u0MGTKEt99+myNHjrB69WpatWpl87nGjRuzdetWkpOTc+bkRUTuQuOjiMidaYwUQ1lE8ri5c+dazGbzbe19+vSxPP7449b3Dz/8sKVFixbW9zdu3LAULlzY8swzz1jbzp07ZwEskZGRFovFYpkwYYKlXbt2Nvs9ffq0BbAcOXIkwzzLli2zODo6WtLS0qxtS5cutXh4eFgSEhLueB579uyxAJY//vjjrucrIpJZGh9FRO5MY6TkFbrSLgVK7dq1rX92dHSkePHi1KpVy9rm7e0NwPnz54Gbk4GsW7fO+nxTkSJFqFq1KgC///57hse4du0arq6uNhOd/Otf/6Js2bKUL1+eZ555hoULF1p/iU3n7u4OcFu7iEhu0PgoInJnGiPFSCrapUBxdna2eW8ymWza0gfJtLQ0AK5cuULnzp3ZvXu3zevYsWO33ZqUrkSJEly9epXr169b24oWLcrOnTv56quv8PX1Zfz48dSpU4e4uDhrn9jYWABKliyZLecqIpIVGh9FRO5MY6QYSUW7yF3Ur1+fAwcOUK5cOSpWrGjzKly4cIafqVu3LgAHDx60aXdyciIoKIjJkyezd+9e/vjjD9auXWvdvn//fkqXLk2JEiVy7HxERLKLxkcRkTvTGCnZSUW7yF2EhoYSGxtLz5492bZtG7///jtr1qyhb9++pKamZviZkiVLUr9+fTZu3GhtW7lyJdOmTWP37t2cOnWKBQsWkJaWRpUqVax9fv31V9q1a5fj5yQikh00PoqI3JnGSMlOKtpF7sLPz4/ffvuN1NRU2rVrR61atRg2bBienp44ONz5P5/nn3+ehQsXWt97enry3Xff0aZNG6pVq0ZYWBhfffUVNWrUACApKYnly5fTv3//HD8nEZHsoPFRROTONEZKdjJZLBaL0SFE8ptr165RpUoVlixZQmBg4D37z5o1i2XLlvHTTz/lQjoREeNofBQRuTONkZIRXWkXyQHu7u4sWLCAixcvZqq/s7Mzn376aQ6nEhExnsZHEZE70xgpGdGVdhERERERERE7pSvtIiIiIiIiInZKRbuIiIiIiIiInVLRLiIiIiIiImKnVLSLiIiIiIiI2CkV7SIiIiIiIiJ2SkW7iIiIiIiIiJ1S0S4iIiIiIiJip1S0i4iIiIiIiNgpFe0iIiIiIiIidur/ATh1NkW0Qv4HAAAAAElFTkSuQmCC\n" }, "metadata": {} }, @@ -526,12 +623,13 @@ "name": "stdout", "text": [ "Copying files from IDC buckets..\n", - "Done in 0.519958 seconds.\n", - "Chris Rorden's dcm2niiX version v1.0.20181125 (JP2:OpenJPEG) GCC9.3.0 (64-bit Linux)\n", + "Done in 1.51152 seconds.\n", + "Chris Rorden's dcm2niiX version v1.0.20211006 (JP2:OpenJPEG) GCC11.2.0 x86-64 (64-bit Linux)\n", "Found 135 DICOM file(s)\n", - "Convert 135 DICOM as //content/dcm2niix/1.2.840.113654.2.55.100875189782210690344207306235124901243/1.2.840.113654.2.55.100875189782210690344207306235124901243_0_OPA_GE_LSQX_STANDARD_360_2.5_120_na_na_na_19990102000000_2 (512x512x135x1)\n", - "compress: \"/usr/bin/pigz\" -n -f -6 \"//content/dcm2niix/1.2.840.113654.2.55.100875189782210690344207306235124901243/1.2.840.113654.2.55.100875189782210690344207306235124901243_0_OPA_GE_LSQX_STANDARD_360_2.5_120_na_na_na_19990102000000_2.nii\"\n", - "Conversion required 3.888236 seconds (0.251145 for core code).\n" + "Convert 135 DICOM as /content/dcm2niix/1.2.840.113654.2.55.100875189782210690344207306235124901243/1.2.840.113654.2.55.100875189782210690344207306235124901243_0,OPA,GE,LSQX,STANDARD,360,2.5,120,na,na,na_19990102000000_2 (512x512x135x1)\n", + "Compress: \"/usr/bin/pigz\" -b 960 -n -f -6 \"/content/dcm2niix/1.2.840.113654.2.55.100875189782210690344207306235124901243/1.2.840.113654.2.55.100875189782210690344207306235124901243_0,OPA,GE,LSQX,STANDARD,360,2.5,120,na,na,na_19990102000000_2.nii\"\n", + "Conversion required 4.873897 seconds (0.287424 for core code).\n", + "\n" ] }, { @@ -540,7 +638,7 @@ "text/plain": [ "
" ], - "image/png": 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\n" 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qoVQqhWOFQqHjO6HSoszOQWTe1PiGnBpPRERERESGTa9H2lu1aoWoqCjcvHkTAHDp0iWcPHkSXbp0AQDcvXsXcrkcPj4+wnukUim8vLwQHR1d6HnDw8MhlUqFl7Ozs25vhEpN3tR4mbU5mnFqPBERERERGTi9HmmfPHkyFAoF6tSpA2NjY+Tk5GDWrFkICAgAAMjlcgCATCbTeJ9MJhPqChIaGoqQkBDhWKFQMHEvI4RV4xs4cmo8EREREREZPL1O2jdv3ox169Zh/fr1qF+/Pi5evIixY8fCyckJQ4cOfevzmpubw9zcXIuRkj7g1HgiIiIiIipr9DppnzBhAiZPniw8m+7h4YH79+8jPDwcQ4cOhYODAwAgKSkJjo7/JmlJSUlo3LixGCGTiDg1noiIiIiIyhq9fqb9+fPnMDLSDNHY2BgqlQoA4ObmBgcHB0RFRQn1CoUCMTEx8Pb2LtVYSXycGk9ERERERGWNXo+09+jRA7NmzYKLiwvq16+PCxcu4KeffsInn3wCAJBIJBg7dixmzpwJd3d3uLm5YerUqXByckLv3r3FDZ5KFafGExERERFRWaTXI+2LFi3CBx98gC+++AJ169bF+PHj8dlnn2HGjBlCm4kTJ2LUqFEYMWIEmjdvjvT0dOzfvx8WFhYiRk6l7eQtTo0n/XH8+HH06NEDTk5OkEgk2LFjh0a9Wq1GWFgYHB0dYWlpCR8fH9y6dUujTUpKCgICAmBtbQ0bGxsEBgYiPT1do83ly5fRtm1bWFhYwNnZGXPmzMkXy5YtW1CnTh1YWFjAw8MDe/fu1fr9EhEREZHu6HXSbmVlhfnz5+P+/ft48eIF/vzzT8ycORNmZmZCG4lEgunTp0MulyMzMxOHDh1CrVq1RIyaxLDnMqfGk/7IyMhAo0aNsGTJkgLr58yZg4ULFyIiIgIxMTGoWLEi/Pz8kJmZKbQJCAjAtWvXEBkZid27d+P48eMYMWKEUK9QKODr64tq1aohNjYWP/zwA7799lssX75caHP69GkMGDAAgYGBuHDhAnr37o3evXvj6tWrurt5IiIiItIqiVqtVosdhNgUCgWkUinS0tJgbW0tdjhUTMrsHHjOOIRnymxs+dwbzV1txQ6JypnX9SESiQTbt28XHtlRq9VwcnLCl19+ifHjxwMA0tLSIJPJsHr1avTv3x9//PEH6tWrh3PnzsHT0xMAsH//fnTt2hV//fUXnJycsGzZMnz99deQy+XCD5mTJ0/Gjh07cOPGDQDARx99hIyMDOzevVuIp2XLlmjcuDEiIiIKvBelUgmlUqlxb87OzuwfieitlOXvWGX53oiodBS1H9HrkXaiouDUeDIkd+/ehVwuh4+Pj1AmlUrh5eWF6OhoAEB0dDRsbGyEhB0AfHx8YGRkhJiYGKFNu3btNGYe+fn5IT4+Hk+fPhXavHqdvDZ51ylIeHg4pFKp8HJ2di75TRMRERHRW2PSTgZvD1eNJwMil8sBADKZTKNcJpMJdXK5HPb29hr1JiYmsLW11WhT0DlevUZhbfLqCxIaGoq0tDThlZiYWNxbJCIiIiIt0uvV44neRJmdg8hruavGd/XgqvFEJWVubg5zc3OxwyAiIiKif3CknQxa3tR4eytzeFbj1HjSfw4ODgCApKQkjfKkpCShzsHBAcnJyRr12dnZSElJ0WhT0DlevUZhbfLqiYiIiEj/MWkng5Y3Nb6rB6fGk2Fwc3ODg4MDoqKihDKFQoGYmBh4e3sDALy9vZGamorY2FihzeHDh6FSqeDl5SW0OX78OLKysoQ2kZGRqF27NipXriy0efU6eW3yrkNERERE+o9JOxksZXYOIq9zajzpn/T0dFy8eBEXL14EkLv43MWLF5GQkACJRIKxY8di5syZ2LlzJ65cuYIhQ4bAyclJWGG+bt266Ny5M4YPH46zZ8/i1KlTCA4ORv/+/eHk5AQAGDhwIMzMzBAYGIhr165h06ZNWLBgAUJCQoQ4xowZg/3792Pu3Lm4ceMGvv32W5w/fx7BwcGl/ZEQEZWqnJwcTJ06FW5ubrC0tESNGjUwY8YMvLppklqtRlhYGBwdHWFpaQkfHx/cunVLxKiJiArGZ9rJYJ26/QTPMjk1nvTP+fPn8d577wnHeYn00KFDsXr1akycOBEZGRkYMWIEUlNT0aZNG+zfvx8WFhbCe9atW4fg4GB06tQJRkZG8Pf3x8KFC4V6qVSKgwcPIigoCM2aNUOVKlUQFhamsZd7q1atsH79ekyZMgVfffUV3N3dsWPHDjRo0KAUPgUiIvF8//33WLZsGdasWYP69evj/PnzGDZsGKRSKUaPHg0AmDNnDhYuXIg1a9bAzc0NU6dOhZ+fH65fv67RHxMRiY37tIP7bBqqkM0XsS3uAYZ6V8O0XkxCSDxluQ8py/dGRLonVh/SvXt3yGQy/Prrr0KZv78/LC0t8X//939Qq9VwcnLCl19+ifHjxwMA0tLSIJPJsHr1avTv3/+N12D/SEQlxX3aqUx7dWp8t4ZOIkdDRERE+qRVq1aIiorCzZs3AQCXLl3CyZMn0aVLFwC5jy3J5XL4+PgI75FKpfDy8kJ0dHSB51QqlVAoFBovIqLSwOnxZJA4NZ6IiIgKM3nyZCgUCtSpUwfGxsbIycnBrFmzEBAQAACQy+UAAJlMpvE+mUwm1P1XeHg4pk2bptvAiYgKwJF2Mkh7Luf+B7VLAweuGk9EREQaNm/ejHXr1mH9+vWIi4vDmjVr8OOPP2LNmjVvfc7Q0FCkpaUJr8TERC1GTERUOI60k8FRZufg4PXcpJ2rxhMREdF/TZgwAZMnTxaeTffw8MD9+/cRHh6OoUOHwsHBAQCQlJQER8d/v0skJSWhcePGBZ7T3Nwc5ubmOo+diOi/ONJOBkdjaryrrdjhEBERkZ55/vw5jIw0v+YaGxtDpVIBANzc3ODg4ICoqCihXqFQICYmBt7e3qUaKxHRm3CknQzOq1PjjTk1noiIiP6jR48emDVrFlxcXFC/fn1cuHABP/30Ez755BMAgEQiwdixYzFz5ky4u7sLW745OTmhd+/e4gZPRPQfTNrJoLzMVnFqPBEREb3WokWLMHXqVHzxxRdITk6Gk5MTPvvsM4SFhQltJk6ciIyMDIwYMQKpqalo06YN9u/fzz3aiUjvcJ92cJ9NQ3L4RhI+WX0e71iZ40xoJ460k14oy31IWb43ItK9styHlOV7I6LSUdR+hCPtZFDypsZ35dR40jKlUomYmBjcv38fz58/xzvvvIMmTZrAzc1N7NCIiIiIqBxj0k4G42W2CpGcGk9adurUKSxYsAC7du1CVlYWpFIpLC0tkZKSAqVSierVq2PEiBH4/PPPYWVlJXa4RERERFTOcPV4Mhinbj+BIjMb73DVeNKSnj174qOPPoKrqysOHjyIZ8+e4e+//8Zff/2F58+f49atW5gyZQqioqJQq1YtREZGih0yEREREZUzHGkng7H78iMAXDWetKdbt2747bffYGpqWmB99erVUb16dQwdOhTXr1/Ho0ePSjlCIiIiIirvmLSTQXh1anw3To0nLfnss8+K3LZevXqoV6+eDqMhIiIiIsqP0+PJIHBqPJW2O3fu4Nq1a1CpVGKHQkRERETlGJN2Mgh7rnBqPOlGVlYWvvnmG/To0QOzZs1CTk4OBgwYAHd3dzRs2BANGjTAvXv3xA6TiIiIiMopJu2k915mq3DwGleNJ92YPHkyli1bBgcHB6xcuRJ9+/bFhQsXsH79emzcuBEmJib4+uuvxQ6TiIiIiMopPtNOei9vanyVSuZozqnxpGVbt27F6tWr0bVrV9y8eRN16tTBnj170KVLFwCAvb09AgICRI6SiIiIiMorjrST3subGt/Vg1PjSfsePnyIRo0aAQBq1aoFc3Nz1KxZU6ivVasW5HK5WOERERERUTnHpJ30GqfGk67l5ORobPlmYmICY2Nj4djIyAhqtVqM0IiIiIiIOD2e9NupPzk1nnTvwIEDkEqlAACVSoWoqChcvXoVAJCamipiZERERERU3jFpJ7225zJXjSfdGzp0qMbxf/dvl0j4b4+IiIiIxMGknfTWq1PjuzXk1HjSDe7DTkRERET6jEk76S1OjSciIiob7t27h4sXL+L+/ft4/vw53nnnHTRp0gTe3t6wsLAQOzwiIr3GpJ301l5OjadScPz48SK1a9eunY4jISIqezZv3gwAaNy4MWQyGZycnGBpaYmUlBT8+eefsLCwQEBAACZNmoRq1aqJHC0RkX5i0k566WW2Cge4ajyVgg4dOgjPrBe2SrxEIkFOTk5phkVEZPCaNGki7MZx9epV1KtXT6NeqVQiOjoaGzduhKenJ5YuXYoPP/xQjFCJiPQak3bSS69OjW/hxqnxpDuVK1eGlZUVPv74YwwePBhVqlQROyQiojLhu+++g7e3N6RSKapWrZqv3tzcHB06dECHDh0wa9Ys3Lt3r/SDJCIyANynnfQSp8ZTaXn06BG+//57REdHw8PDA4GBgTh9+jSsra0hlUqFFxERFY+fn1+R29rZ2aFZs2Y6jIaIyHAVa6RdpVLh2LFjOHHiRL6FRHx8fODs7KyrOKkceZmtwsHrSQA4NZ50z8zMDB999BE++ugjJCQkYPXq1QgODoZSqcTQoUMxbdo0mJhwUhIRkbao1WocOXIEL168QKtWrVC5cmWxQyIi0mtFGml/8eIFZs6cCWdnZ3Tt2hX79u1DamoqjI2Ncfv2bXzzzTdwc3ND165dcebMGV3HTGXcqT+fIO1FFqfGU6lzcXFBWFgYDh06hFq1auG7776DQqEQOywiIoOVmpoKAPD29sbw4cOhUCjQtm1b+Pj4oEePHqhbty4uX74sbpBERHquSEl7rVq1cPnyZaxYsQIKhQLR0dH47bff8H//93/Yu3cvEhIS8Oeff6Jt27bo378/VqxYoeu4qQzLmxrfuYGMU+Op1CiVSqxfvx4+Pj5o0KABqlSpgj179sDWlj8cERG9rSlTpgAA+vbtiytXrqBz587IyclBdHQ0YmJiULduXXz99dciR0lEpN8k6sKWS37FH3/8gbp16xbphFlZWUhISECNGjVKHFxpUSgUkEqlSEtLg7W1tdjhlGtZOSp4zjyEtBdZ2DC8Jbxr2IkdEpVxZ8+exapVq7Bx40a4urpi2LBhGDRoULGS9bLch5TleyMi3XNycsKjR4+QlpaGZ8+ewdnZGYcPH0aHDh0A5PbBPXv2hFwuFzfQt8D+kYhKqqj9SJEe1Cxqwg4ApqamBpWwk345dZtT46l0tWzZEi4uLhg9erSwCNLJkyfztevZs2dph0ZEZPCSk5OFv7/77ruwsLDQWAPJxcUFjx8/FiM0IiKD8darK2VnZ+Pnn3/G0aNHkZOTg9atWyMoKAgWFhbajI/KmT2cGk8iSEhIwIwZMwqt5z7tRERvR6VSaRwbGxtDIvn3v++v/p2IiAr21kn76NGjcfPmTfTt2xdZWVlYu3Ytzp8/jw0bNmgzPipHsnK4ajyVvv9+oSQiIu2LiIiAhYUFsrOzsXr1alSpUgUA8OzZM5EjIyLSf0VO2rdv344+ffoIxwcPHkR8fDyMjY0B5O7F2bJlS+1HSOXGv1PjzeDlxmfZiYiIDJ2zszMSEhKwZMkSGBkZwcHBAf/73/802ri4uIgUHRGRYShy0r5y5UqsWbMGS5cuhZOTE5o2bYrPP/8c/v7+yMrKwooVK9C8eXNdxkpl3N4reVPjHTg1nkrFmTNnivxj4/Pnz3H37l3Ur19fx1EREZUdV65cgVQqxZUrV7hYGxHRWyrSlm8AsGvXLgwYMAAdOnTAokWLsHz5clhbW+Prr7/G1KlT4ezsjPXr1+syVirDsnJUOHCNU+OpdA0ePBh+fn7YsmULMjIyCmxz/fp1fPXVV6hRowZiY2O1ct2cnBxMnToVbm5usLS0RI0aNTBjxgy8upmHWq1GWFgYHB0dYWlpCR8fH9y6dUvjPCkpKQgICIC1tTVsbGwQGBiI9PR0jTaXL19G27ZthcWf5syZo5V7ICIiIqLSUaxn2j/66CP4+flh4sSJ8PPzQ0REBObOnaur2Kgc4dR4EsP169exbNkyTJkyBQMHDkStWrXg5OQECwsLPH36FDdu3EB6ejr69OmDgwcPwsPDQyvX/f7777Fs2TKsWbMG9evXx/nz5zFs2DBIpVKMHj0aADBnzhwsXLgQa9asgZubG6ZOnQo/Pz9cv35dWPAzICAAjx49QmRkJLKysjBs2DCMGDFC+AFVoVDA19cXPj4+iIiIwJUrV/DJJ5/AxsYGI0aM0Mq9EBG9zosXLzSOQ0NDoVQqhWNjY2PMmDGDCxkTEb1GkfZpL8jx48cRFBSEzp07G3xny302xTdx6yVsPv8XBrV0wcze2kmMiIrj/PnzOHnyJO7fv48XL16gSpUqaNKkCd5777037tle3D6ke/fukMlk+PXXX4Uyf39/WFpa4v/+7/+gVqvh5OSEL7/8EuPHjwcApKWlQSaTYfXq1ejfvz/++OMP1KtXD+fOnYOnpycAYP/+/ejatSv++usvODk5YdmyZfj6668hl8thZmYGAJg8eTJ27NiBGzduFOlzYf9IRCUxb948hISECH2IlZUV6tevD0tLSwDAjRs3MHHiRIwbN07kSIuP/SMRlVRR+5EiT49PSEhAv3794OHhgYCAALi7uyM2NhYVKlRAo0aNsG/fPq0ETuUPV40nfeDp6YmxY8di3rx5iIiIwMyZM+Hv7//GhP1ttGrVClFRUbh58yYA4NKlSzh58iS6dOkCALh79y7kcjl8fHyE90ilUnh5eSE6OhoAEB0dDRsbGyFhBwAfHx8YGRkhJiZGaNOuXTshYQdyFw2Nj4/H06dPC4xNqVRCoVBovIiI3taWLVvyla1fvx5HjhzBkSNH8MMPP2Dz5s0iREZEZDiKnLQPGTIERkZG+OGHH2Bvb4/PPvsMZmZmmDZtGnbs2IHw8HD069dPl7FSGXX6z7+R+pxT46n8mDx5Mvr37486derA1NQUTZo0wdixYxEQEAAAkMvlAACZTKbxPplMJtTJ5XLY29tr1JuYmMDW1lajTUHnePUa/xUeHg6pVCq8nJ2dS3i3RFSe3blzR+PYwsICRkb/fv1s0aIFrl+/XtphEREZlCIn7efPn8esWbPQuXNn/PTTT7h8+bJQV7duXRw/flxjVEhbHjx4gEGDBsHOzg6Wlpbw8PDA+fPnhfqiLNZE+m3P5YcAAL/6XDWeyofNmzdj3bp1WL9+PeLi4rBmzRr8+OOPWLNmjdihITQ0FGlpacIrMTFR7JCIyIClpaVpHD9+/Biurq7CsUql0njGnYiI8ity0t6sWTOEhYXh4MGDmDRpUoELMml7YaOnT5+idevWMDU1xb59+3D9+nXMnTsXlStXFtrkLdYUERGBmJgYVKxYEX5+fsjMzNRqLKQbr06N79aQU+OpfJgwYYIw2u7h4YHBgwdj3LhxCA8PBwA4ODgAAJKSkjTel5SUJNQ5ODggOTlZoz47OxspKSkabQo6x6vX+C9zc3NYW1trvIiI3paTk9Nr6y9fvoyqVauWUjRERIapyEn72rVroVQqMW7cODx48AA///yzLuMCkLvCsrOzM1atWoUWLVrAzc0Nvr6+qFGjBoDcUfb58+djypQp6NWrFxo2bIi1a9fi4cOH2LFjh87jo5Lj1Hgqj54/f64xPRTIXUFZpVIBANzc3ODg4ICoqCihXqFQICYmBt7e3gAAb29vpKamamxDd/jwYahUKnh5eQltjh8/jqysLKFNZGQkateurfHjJxGRrvj6+gJAgYMpL168wLRp09CtW7fSDouIyKAUOWmvVq0atm7dimvXrmHdunVv/OVUG3bu3AlPT098+OGHsLe3R5MmTbBixQqhviiLNRWECy3pj72XHwHg1HjSL7qeqdOjRw/MmjULe/bswb1797B9+3b89NNP6NOnDwBAIpFg7NixmDlzJnbu3IkrV65gyJAhcHJyQu/evQHkPpbUuXNnDB8+HGfPnsWpU6cQHByM/v37C/3zwIEDYWZmhsDAQFy7dg2bNm3CggULEBISotP7IyLK8+WXXwLIXezzhx9+wO+//47ff/8dc+bMQe3atfH06VN89dVXIkdJRKTfirRPe0ZGBipWrFjkkxa3fWHu3LmDZcuWISQkBF999RXOnTuH0aNHw8zMDEOHDi3SYk0FCQ8Px7Rp00ocH5XMy2wVDlzP/d+pG1eNJ5GpVCrMmjULERERSEpKws2bN1G9enVMnToVrq6uCAwM1Nq1Fi1ahKlTp+KLL75AcnIynJyc8NlnnyEsLExoM3HiRGRkZGDEiBFITU1FmzZtsH//fo3tNdetW4fg4GB06tQJRkZG8Pf3x8KFC4V6qVSKgwcPIigoCM2aNUOVKlUQFhbGPdqJqNTkLZhZq1YtTJ48GXk7DUskErz//vtYunRpvu9xRESkqUj7tDs6OmLMmDEYOnQoHB0LTq7UajUOHTqEn376Ce3atUNoaGiJgzMzM4OnpydOnz4tlI0ePRrnzp1DdHQ0Tp8+jdatW+Phw4cacfXr1w8SiQSbNm0q8LxKpVJj0ROFQgFnZ2fus1nKNp9LxMTfLsPeyhynJ3eEiXGRJ34Qad306dOxZs0aTJ8+HcOHD8fVq1dRvXp1bNq0CfPnz3/t7J2yvFdvWb43ItK9V/uQ7Oxs3L59GwBQs2ZNnWypWZrYPxJRSRW1HynSSPvRo0fx1Vdf4dtvv0WjRo3g6ekJJycnWFhY4OnTp7h+/Tqio6NhYmKC0NBQfPbZZ1q5CUdHR9SrV0+jrG7duvjtt98AaC7W9GrSnpSUhMaNGxd6XnNzc5ibm5cotsysHFiYGpfoHOVZjkqNZcf+BAB82taNCTuJbu3atVi+fDk6deqEzz//XChv1KgRbty4IWJkRERlg62tLVq0aCF2GEREBqdImVLt2rXx22+/4ebNm+jXrx8ePHiArVu3YsWKFTh69CjeffddrFixAvfu3cMXX3wBY2PtJLOtW7dGfHy8RtnNmzdRrVo1AEVbrEnbnqQrMXbjBXRZcAJZOSqdXKM82HvlEe4+yYDU0hQDvaqJHQ4RHjx4gJo1a+YrV6lUGgu5ERFR0Xz++ed48OBBkdpu2rQJ69at03FERESGqUgj7XlcXFzw5ZdfCouK6Nq4cePQqlUrzJ49G/369cPZs2exfPlyLF++HIDmYk3u7u5wc3PD1KlTNRZr0raKZiY4efsJnqS/xPYLD9DP01kn1ynL1Go1lhzJnR43rLUrKpkX658hkU7Uq1cPJ06cEH4UzLN161Y0adJEpKiIiAzXO++8g5YtWwIAfvnlF7Rt2zbfTM2TJ09i48aNcHJyEr7fERGRJr3Olpo3b47t27cjNDQU06dPh5ubG+bPn4+AgAChTVEWa9ImSzNjjGhXHbP33sCSI7fRt8m7nNpdTIdvJOOG/Bkqmhnj41auYodDBAAICwvD0KFD8eDBA6hUKmzbtg3x8fFYu3Ytdu/eLXZ4REQGZ8aMGRg6dCjc3d3x66+/YsKECRr1VlZW8PHxwfLly9G5c2eRoiQi0n9FWoiurCvuQiLPX2aj7fdH8HfGS/z4YSN80KxqKURZNqjVavRddhoXElLxWbvqCO1aV+yQiAQnTpzA9OnTcenSJaSnp6Np06YICwsT9hkuTFlejKgs3xsR6d6rfUhOTg4SEhLw4sULVKlSBTVq1IBEYrjbvbJ/JKKS0upCdKSpgpkJRrSrjvB9N7D48C30buzE0fYiir7zNy4kpMLMxAiBbd3EDodIQ9u2bREZGSl2GEREZVLlypVRuXJlscMgIjI4zDTf0mDvarCtaIZ7fz/HzksPxQ7HYOQ9y/6RpzPsrXTzCAMREREREVFZwaT9LVUwM8HwttUBAIsP30aOqtw/ZfBGFxKe4tTtv2FiJMFn7auLHQ6RhsqVK8PW1jbfy87ODu+++y7at2+PVatWiR0mEREV0YMHDzBo0CDY2dnB0tISHh4eOH/+vFCvVqsRFhYGR0dHWFpawsfHB7du3RIxYiKigr1V0n7ixAkMGjQI3t7ewlYe//vf/3Dy5EmtBqfvhnhXQ+UKprjzJAO7ONr+RkuO5O7L3qvxu6hauYLI0RBpCgsLg5GREbp164Zp06Zh2rRp6NatG4yMjBAUFIRatWph5MiRWLFihdihEhHRGzx9+hStW7eGqakp9u3bh+vXr2Pu3Lka0/PnzJmDhQsXIiIiAjExMahYsSL8/PyQmZkpYuRERPkV+5n23377DYMHD0ZAQAAuXLgApVIJAEhLS8Ps2bOxd+9erQepryqam+DTttXxw4F4LDx8Cz0aOcHYyHAXVNGlG3IFDv2RBIkEGNmhhtjhEOVz8uRJzJw5E59//rlG+c8//4yDBw/it99+Q8OGDbFw4UIMHz5cpCiJiKgovv/+ezg7O2vMkHJz+3ctHbVajfnz52PKlCno1asXAGDt2rWQyWTYsWMH+vfvX+oxExEVptgj7TNnzkRERARWrFgBU1NTobx169aIi4vTanCGYGgrV9hUMMWdxxnYfZmj7YVZ+s8oe5cGDqhpX0nkaIjyO3DgAHx8fPKVd+rUCQcOHAAAdO3aFXfu3Cnt0IiIyoTs7GwcOnQIP//8M549ewYAePjwIdLT07V+rZ07d8LT0xMffvgh7O3t0aRJE42ZUnfv3oVcLtfo96VSKby8vBAdHV3gOZVKJRQKhcaLiKg0FDtpj4+PR7t27fKVS6VSpKamaiMmg1LJ3ASftsn95XZh1C0+216Ae0/+/UHjiw41RY6GqGC2trbYtWtXvvJdu3bB1tYWAJCRkQErK6vSDo2IyOAlJCTAw8MDvXr1QlBQEB4/fgwgd0R8/PjxWr/enTt3sGzZMri7u+PAgQMYOXIkRo8ejTVr1gAA5HI5AEAmk2m8TyaTCXX/FR4eDqlUKrycnZ21HjcRUUGKPT3ewcEBt2/fhqurq0b5yZMnUb16+VxcbGgrV6w4cRd/Ps7AniuP0LORk9gh6ZWIY39CpQY61H4HDd6Vih0OUYGmTp2KkSNH4siRI2jRogUA4Ny5c9i7dy8iIiIAAJGRkWjfvr2YYRIRGaTJkyfD09MTly5dgp2dnVDep08fnTxypFKp4OnpidmzZwMAmjRpgqtXryIiIgJDhw59q3OGhoYiJCREOFYoFEzciahUFHukffjw4RgzZgxiYmIgkUjw8OFDrFu3DuPHj8fIkSN1EaPes7IwReA/o+2Lom5BxdF2wcPUF/gt7i8AQPB7HGUn/TV8+HAcO3YMFStWxLZt27Bt2zZUqFABx44dQ2BgIADgyy+/xKZNm0SOlIjI8Jw+fRpTpkyBmZmZRrmrq6uwqLE2OTo6ol69ehpldevWRUJCAoDcQSgASEpK0miTlJQk1P2Xubk5rK2tNV5ERKWh2CPtkydPhkqlQqdOnfD8+XO0a9cO5ubmGD9+PEaNGqWLGA3Cx61d8cuJO7iVnI69Vx+he0OOtgPAihN3kJWjRgs3W3i62oodDtFrtW7dGq1btxY7DCKiMkelUiEnJydf+V9//aWTx45at26N+Ph4jbKbN2+iWrVqAHIXpXNwcEBUVBQaN24MIHfkPCYmptwOQhGR/ir2SLtEIsHXX3+NlJQUXL16FWfOnMHjx48xY8YMXcRnMKwtTPHJK8+2c7QdeJKuxIazub9oc5SdDElmZiYXGyIi0qKOHTti/vz5wrFEIkF6ejq++eYbdO3aVevXGzduHM6cOYPZs2fj9u3bWL9+PZYvX46goCDh+mPHjsXMmTOxc+dOXLlyBUOGDIGTkxN69+6t9XiIiEqi2CPteczMzPJNOyrvhrV2w68n7+JmUjr2X5Ojq4ej2CGJatWpu8jMUqFhVSnaulcROxyi13r+/DkmTpyIzZs34++//85XX9AIERERFc2sWbPwwQcfoF69esjMzMTAgQNx69YtVKlSBRs2bND69Zo3b47t27cjNDQU06dPh5ubG+bPn4+AgAChzcSJE5GRkYERI0YgNTUVbdq0wf79+2FhYaH1eIiISkKiVquLNSTcp08fSCT59yKXSCSwsLBAzZo1MXDgQNSuXVtrQeqaQqGAVCpFWlpaiZ9P+inyJhZG3UIdByvsHd0WRuV03/a0F1lo891hPFNmI2JQM3RuUPDzYUT6IigoCEeOHMGMGTMwePBgLFmyBA8ePMDPP/+M7777TuOL3n9psw/RN2X53ohI917tQypUqICNGzfi8uXLSE9PR9OmTREQEABLS0uxw3wr7B+JqKSK2o8Ue6RdKpVix44dsLGxQbNmzQAAcXFxSE1Nha+vLzZt2oTvv/8eUVFR5fLZ0MDWblh18i5uyJ/h4HU5Ojcon6Pt/3fmPp4ps+FuXwm+9WRvfgORyHbt2oW1a9eiQ4cOGDZsGNq2bYuaNWuiWrVqWLdu3WuTdiIiejMTExMMGjRI7DCIiAzOW235NnDgQCxevBhGRrmPxKtUKowZMwZWVlbYuHEjPv/8c0yaNAknT57UesD6TlrBFB+3dsWiw7exIOo2fOs5lLvR9ucvs/HrybsAgC/eq1Hu7p8MU0pKirBtpbW1NVJSUgAAbdq04aJEREQltHfvXlSoUCFf+aszNd3c3ESIjIhI/xU7af/1119x6tQpIWEHACMjI4waNQqtWrXC7NmzERwcjLZt22o1UEMS2MYNq07dwx+PFIj8Iwl+9cvX1PANZxORkvESzraW6MFV9MlAVK9eHXfv3oWLiwvq1KmDzZs3o0WLFti1axdsbGzEDo+IyKANHDgQEokE/30qM69MIpGgTZs22LFjBypXrixSlERE+qnYq8dnZ2fjxo0b+cpv3LghLNRkYWFR4HPv5YVNBTN83MoVQO5K8sVcNsCgKbNzsOL4HQDA5+1rwMS42P/EiEQxbNgwXLp0CUDu1pZLliyBhYUFxo0bhwkTJogcHRGRYduxYweaN2+OyMhIpKWlIS0tDZGRkfDy8sLu3btx/Phx/P333xg/frzYoRIR6Z1ij7QPHjwYgYGB+Oqrr9C8eXMAwLlz5zB79mwMGTIEAHDs2DHUr19fu5EamNzR9ru49lCBQ38k4/1y8lz3trgHkCsyYW9ljg+aVRU7HKIiGzdunPB3Hx8f3LhxA7GxsahZsyYaNmwoYmRERIZv8uTJ+OWXX9CqVSuhrFOnTrCwsMCIESNw7do1zJ8/H5988omIURIR6adiJ+3z5s2DTCbDnDlzkJSUBACQyWQYN24cJk2aBADw9fVF586dtRupgalc0QxDW7li6dE/sSDqJnzq2pf52QfZOSpEHPsTADCiXXWYmxiLHBHR26tWrRqkUimnxhMRacHdu3cLXBnZ2toad+7kztBzd3fHkydPSjs0IiK9V+y5y8bGxvj666/x6NEjpKamIjU1FY8ePcJXX30FY+PcJM3FxQVVq3KU9dO21VHBzBhXHyhw+Eay2OHo3J4rj3D/7+eoXMEUA71cxA6HqFi+//57bNq0STju168f7Ozs8O677wrT5omI6O00btwYEyZMwOPHj4Wyx48fY+LEicLMzVu3bsHZ2VmsEImI9FaJHji2trbmvpSvYVvRDEO8XQEAC8r4s+0qlRpLj+SOsn/S2g0VzIo9iYNIVBEREcKXxcjISERGRmLfvn3o0qULn2knIiqhxYsX4+7du6hatSpq1qyJmjVromrVqrh37x5++eUXAEB6ejqmTJkicqRERPrnrTKrrVu3YvPmzUhISMDLly816uLi4rQSWFkxvK0b1py+h8t/peFIfDI61imbz7Yf+iMJ8UnPUMncRPihgsiQyOVyIWnfvXs3+vXrB19fX7i6usLLy0vk6IiIDJu7uzuuX7+OgwcP4ubNmwCA2rVr4/333xd2JOrdu7eIERIR6a9ij7QvXLgQw4YNg0wmw4ULF9CiRQvY2dnhzp076NKliy5iNGh2lcwxxLsaAGDBobI52q5Wq7HkaO4o+2DvapBWMBU5IqLiq1y5MhITEwEA+/fvh4+PD4Dcf995O2MQEdHbMzIyQufOnTF69GiMHj0afn5+GlsIExFRwYo90r506VIsX74cAwYMwOrVqzFx4kRUr14dYWFhSElJ0UWMBm94u+pYG30fl/5Kw9Gbj/FebXuxQ9KqU7f/xqXEVJibGOGT1m5ih0P0Vvr27YuBAwfC3d0df//9t/Aj5IULF1CzZk2RoyMiMnwZGRk4duxYgTM1R48eLVJURET6r9hJe0JCgrBdh6WlJZ49ewYgdyu4li1bYvHixdqNsAyoUskcg1q6YMWJu1hw6BY61HqnTK0kv+TIbQDAgBYueMfKXORoiN7OvHnz4OrqisTERMyZMweVKlUCADx69AhffPGFyNERERm2S5cuoV+/fnj+/DkyMjJga2uLJ0+eoEKFCrC3t2fSTkT0GsWek+Tg4CCMqLu4uODMmTMAcrfyKItTv7VlRLsasDA1wsXEVBy/VXa2M4m9/xTRd/6GiZEEw9tVFzscordmamqK8ePHY8GCBWjSpIlQPm7cOHz66aciRkZEZPi++uor9OjRA0+fPoWlpSXOnDmD+/fvo1mzZvjxxx/FDo+ISK8Ve6S9Y8eO2LlzJ5o0aYJhw4Zh3Lhx2Lp1K86fP4++ffvqIsYy4R0rcwR4VcOvJ+9iwaGbaOdepUyMti/9Z5S9b9N38a6NpcjREL29tWvXvrZ+yJAhpRQJEVHZc+XKFfzyyy8wMjKCsbExlEolqlevjjlz5mDo0KH8DklE9BrFTtqXL18OlUoFAAgKCoKdnR1Onz6Nnj174rPPPtN6gGXJZ+2r4//O3EdcQipO3n6Ctu7viB1SiVx/qEDUjWQYSYDP29cQOxyiEhkzZozGcVZWFp4/fw4zMzNUqFCBSTsRUQmYmJgIi87Z29sjISEBdevWhVQqFRYBJSKighU7aTcyMtJY6bN///7o37+/VoMqq+ytLDDQywWrTt3DgkO30KamYY+2Lz2aO8re1cMR1d+pJHI0RCXz9OnTfGW3bt3CyJEjuU87EVEJNWzYEOfOnYO7uzvat2+PsLAwPHnyBP/73//QoEEDscMjItJrxX6mff/+/Th58qRwvGTJEjRu3BgDBw4s8Esvafq8fQ2YmRjh/P2nOP3n32KH89buPE7HniuPAABfdODK2lQ2ubu747vvvss3Ck9ERMUTFhYGR0dHAMCsWbNQuXJljBw5Eo8fP8by5ctFjo6ISL8VO2mfMGECFAoFgNznk0JCQtC1a1fcvXsXISEhWg+wrJFZW2BgCxcAhr1v+7Kjf0KtBjrVsUc9J2uxwyHSGRMTEzx8+FDsMIiIDFrTpk3x3nvvAcidHr9//34oFArExsaiUaNGIkdHRKTfij09/u7du6hXrx4A4LfffkOPHj0we/ZsxMXFoWvXrloPsCz6vH0NrD+bgLP3UhB952+0qlFF7JCK5UHqC2y/8AAAENSRo+xUNuzcuVPjWK1W49GjR1i8eDFat24tUlRERGXDixcvYGJiggoVKgAA7t+/j+3bt6NevXrw9fUVOToiIv1W7JF2MzMzPH/+HABw6NAhoaO1tbUVRuDp9RykFhjQ3BlA7mi7oVl+7E9kq9Twrm6Hpi6VxQ6HSCt69+6t8erbty++/fZbNGzYECtXrtT69R48eIBBgwbBzs4OlpaW8PDwwPnz54V6tVotTCe1tLSEj48Pbt3S7C9SUlIQEBAAa2tr2NjYIDAwEOnp6RptLl++jLZt28LCwgLOzs6YM2eO1u+FiOhNBgwYIOzSkZqaihYtWmDu3Lno1asXli1bJnJ0RET6rdhJe5s2bRASEoIZM2bg7Nmz6NatGwDg5s2bqFq1qtYDLKs+71ADZsZGiLmbgjN3DOfZ9sfPlNh4LneV12COslMZolKpNF45OTmQy+VYv3698Bymtjx9+hStW7eGqakp9u3bh+vXr2Pu3LmoXPnfH8HmzJmDhQsXIiIiAjExMahYsSL8/PyQmZkptAkICMC1a9cQGRmJ3bt34/jx4xgxYoRQr1Ao4Ovri2rVqiE2NhY//PADvv32Wz4/SkSl7tKlS2jbti0AYOvWrXBwcMD9+/exdu1aLFy4UOToiIj0W7GT9sWLF8PExARbt27FsmXL8O677wIA9u3bh86dO2s9wLLKUWqJjwxwtP3Xk3ehzFahkbMNWtWwEzscIoP0/fffw9nZGatWrUKLFi3g5uYGX19f1KiRu3WiWq3G/PnzMWXKFPTq1QsNGzbE2rVr8fDhQ+zYsQMA8Mcff2D//v345Zdf4OXlhTZt2mDRokXYuHGj8Az+unXr8PLlS6xcuRL169dH//79MXr0aPz000+FxqZUKqFQKDReREQl9eLFC1hZWQEADh48iL59+8LIyAgtW7bE/fv3RY6OiEi/FTtpd3Fxwe7du3Hp0iUEBgYK5fPmzeMvpcU0skMNmBpLEH3nb8QYwGh72vMs/N+Z3P+wBr9X06C3qyMS086dO+Hp6YkPP/wQ9vb2aNKkCVasWCHU3717F3K5HD4+PkKZVCqFl5cXoqOjAQDR0dGwsbGBp6en0MbHxwdGRkaIiYkR2rRr1w5mZmZCGz8/P8THxxe620d4eDikUqnwcnZ21uq9E1H5VL16dezYsQOJiYk4cOCA8HhlcnIyrK25oC0R0esUO2lPSEh47YuKzsnGEv08/xltj9L/0fY10feQrsxGbZkVOtWxFzscIoN1584dLFu2DO7u7jhw4ABGjhyJ0aNHY82aNQAAuVwOAJDJZBrvk8lkQp1cLoe9veb/D01MTGBra6vRpqBzvHqN/woNDUVaWprwSkxMLOHdEhEBEydOxPjx4+Hq6govLy94e3sDyB11b9KkicjRERHpt2KvHu/q6vraEdacnJwSBVTefPFeTWw+n4jTf/6Nc/dS0NzVVuyQCpShzMbKU3cBAF+8VwNGRhxlJ3pbKpUKnp6emD17NgCgSZMmuHr1KiIiIjB06FBRYzM3N4e5ubmoMRBR2dO7d2/4+vri0aNHGlu8derUCX369BExMiIi/VfskfYLFy4gLi5OeMXExCAiIgK1atXCli1bdBFjmfaujSU+aKb/z7ZvOJuA1OdZqGZXAd08tLsoF1F54+joKGydmadu3brCbCUHBwcAQFJSkkabpKQkoc7BwQHJycka9dnZ2UhJSdFoU9A5Xr0GEVFpcXBwQJMmTWBk9O/XzxYtWqBOnToiRkVEpP+KPdL+6q+jeTw9PeHk5IQffvgBffv21Upg5ckXHWpgy/lEnLz9BLH3U9Csmn6Ntiuzc7D8+B0AwMj2NWBiXOzfeoj0nqurKz755BN8/PHHcHFx0em1Wrdujfj4eI2ymzdvolq1agAANzc3ODg4ICoqCo0bNwaQuxJ8TEwMRo4cCQDw9vZGamoqYmNj0axZMwDA4cOHoVKp4OXlJbT5+uuvkZWVBVNTUwBAZGQkateurbFSPRGRrnXv3h0mJoV/7Tx8+HApRkNEZFi0ln3Vrl0b586d09bpyhVn2wr4oFnudnnz9XC0fWvsX0h+poSDtQX6NH1X7HCIdGLs2LHYtm0bqlevjvfffx8bN26EUqnUybXGjRuHM2fOYPbs2bh9+zbWr1+P5cuXIygoCAAgkUgwduxYzJw5Ezt37sSVK1cwZMgQODk5oXfv3gByR+Y7d+6M4cOH4+zZszh16hSCg4PRv39/ODk5AQAGDhwIMzMzBAYG4tq1a9i0aRMWLFiAkJAQndwXEVFhPDw80KhRI+FVr149vHz5EnFxcfDw8BA7PCIivSZRq9Xq4rzhv9v/qNVqPHr0CN9++y1u3LiBixcvajO+UqFQKCCVSpGWlibaCqaJKc/x3o9Hka1SY9sXrdDURT9GwbJzVHhv7lEkprxAWPd6+KSNm9ghEelUXFwcVq9ejQ0bNiAnJwcDBw7EJ598gqZNmxb6nrfpQ3bv3o3Q0FDcunULbm5uCAkJwfDhw4V6tVqNb775BsuXL0dqairatGmDpUuXolatWkKblJQUBAcHY9euXTAyMoK/vz8WLlyISpUqCW0uX76MoKAgnDt3DlWqVMGoUaMwadKkIn8e+tA/EpHhelMf8u233yI9PR0//vijCNGVDPtHIiqpovYjxU7ajYyM8i1Ep1ar4ezsjI0bNwqrgRoSfel0J269hM3n/0L7Wu9gzSctRIvjVdsv/IVxmy7BtqIZTk3qCEszY7FDIioVWVlZWLp0KSZNmoSsrCx4eHhg9OjRGDZsWL4+UF/6EF0oy/dGRLr3pj7k9u3baNGiBVJSUkSIrmTYPxJRSRW1Hyn2M+1HjhzRODYyMsI777yDmjVrvvZZJXqz4Pfc8VvcAxy7+RgXE1PR2NlG1HhUKjWWHvkTABDYxo0JO5ULWVlZ2L59O1atWoXIyEi0bNkSgYGB+Ouvv/DVV1/h0KFDWL9+vdhhEhGVCdHR0bCwsBA7DCIivVbsLLt9+/a6iIMAuNhVQJ8m72Jr7F9YcOgmVg0Td7T94PUk3EpOh5W5CQZ7VxM1FiJdi4uLw6pVq7BhwwYYGRlhyJAhmDdvnsaqxn369EHz5s1FjJKIyDAFBAQIC2IC/z5eef78eUydOlXEyIiI9B+HxvVM8Hs1sf3CAxyJf4xLialoJNJou1qtxpIjtwEAQ1pVg7WF6RveQWTYmjdvjvfffx/Lli1D7969Nb5c5nFzc0P//v1FiI6IyLBJpVKNftXIyAi1a9fG9OnT4evrK2JkRET6j0m7nnGtUhG9GjthW9wDLIy6hV8/FmdU78StJ7jyIA0Wpkb4pDUXn6OyLScnBytXrkTPnj1fuxVaxYoVsWrVqlKMjIiobFi6dCmf+yYiekvccFsPjeroDiMJEHUjGVf+ShMlhsX/jLIPaOECu0rmosRAVFqMjY3x2WefITU1VexQiIiIiIg0MGnXQ25VKqJ349z90BdElf6+7efupeDs3RSYGkswol31Ur8+kRgaNGiAO3fuiB0GEREREZGGIiftCoWiwFdOTo4u4yu3gjvWhJEEOPRHEq4+KN3R9rxn2f2bVoWj1LJUr00klpkzZ2L8+PHYvXs3Hj16lK+vIyIiIiISQ5GTdhsbG1SuXDnfy9LSErVr18aKFSt0GWe5U/2dSujZyAkAsLAUR9uvPkjD0fjHMJIAn7evUWrXJRJb165dcenSJfTs2RNVq1YV+ri8vo+IiIiISAxFXojuv/uz50lNTUVsbCwmTJgAExMTDBs2TGvB/dd3332H0NBQjBkzBvPnzwcAZGZm4ssvv8TGjRuhVCrh5+eHpUuXQiaT6SyO0hLc0R2/X3qIg9eTcO1hGuo7SXV+zaVHc0fZuzd0gmuVijq/HpG+KKyPIyKikrt+/TpatmxZYN2OHTvQu3fv0g2IiMiAFDlpf93+7L169YKrqysWLVqks6T93Llz+Pnnn9GwYUON8nHjxmHPnj3YsmULpFIpgoOD0bdvX5w6dUoncZSmmvaV0KOhE3ZeeoiFUbfw82BPnV7vdnI69l2VAwCC3qup02sR6ZvX9XFERFQyed/N3Nw0d6T57bffMGTIEGRkZIgUGRGR/tPaQnTt27fH7du3tXU6Denp6QgICMCKFSs0pqmmpaXh119/xU8//YSOHTuiWbNmWLVqFU6fPo0zZ87oJJbSNrpTTUgkwIFrSfjjkW6fq1129E+o1cD79WSo7WCl02sR6aPU1FTMnTsXn376KT799FPMmzcPaWni7OBARFSWDBkyBD4+PpDL5ULZpk2bMGTIEKxevVq8wIiIDIDWkva0tDRIpbqZvh0UFIRu3brBx8dHozw2NhZZWVka5XXq1IGLiwuio6MLPZ9SqTSYRaZq2luhm4cjAN0+256Y8hw7Lj4AwFF2Kp/Onz+PGjVqYN68eUhJSUFKSgp++ukn1KhRA3FxcWKHR0Rk0L766it07doVPj4+SElJwfr16zFs2DCsXbsWH374odjhERHptSJPj3+drKws/PDDD/Dy8tLG6TRs3LgRcXFxOHfuXL46uVwOMzMz2NjYaJTLZDKNX3L/Kzw8HNOmTdN2qDozupM79lx5hH1X5bghV6COg7XWr7H8+B3kqNRoU7MKGjvbaP38RPpu3Lhx6NmzJ1asWAETk9yuMTs7G59++inGjh2L48ePixwhEZFhW7RoEQICAtCyZUs8ePAAGzZsQK9evcQOi4hI7xU5ae/bt2+B5Wlpabh27RokEglOnDihtcAAIDExEWPGjEFkZCQsLCy0dt7Q0FCEhIQIxwqFAs7Ozlo7v7bVklmhawNH7LnyCIuibmNJQFOtnj9ZkYlN5xMBAF+8xxXjqXw6f/68RsIOACYmJpg4cSI8PXW7ngQRUVm0c+dOPH/+HACwd+9eVKhQAX379sWJEycwYMAASCQS7Ny5EwDQs2dPMUMlItJrRU7aC5v67uzsDH9/fwQEBGh9enxsbCySk5PRtOm/SWpOTg6OHz+OxYsX48CBA3j58iVSU1M1RtuTkpLg4OBQ6HnNzc1hbm6u1Vh1bVSnmthz5RH2Xn2Em0nPUEumvWfOfz15Fy+zVWjqYgPv6nZaOy+RIbG2tkZCQgLq1KmjUZ6YmAgrK67xQERUXK+uCD9w4ECNupUrV2LlypUAAIlEgpycnNIMjYjIoBQ5aV+1apUu4yhQp06dcOXKFY2yYcOGoU6dOpg0aRKcnZ1hamqKqKgo+Pv7AwDi4+ORkJAAb2/vUo9Xl+o4WKNLAwfsuyrHwqhbWDxQO6Ptqc9f4v/O3AeQ+yy7RCLRynmJDM1HH32EwMBA/Pjjj2jVqhUA4NSpU5gwYQIGDBggcnRERIZHpVJBoVBAKpUiNTUV1tbaf7yPiKg8KNYz7WfOnMGuXbvw8uVLdOrUCZ07d9ZVXAAAKysrNGjQQKOsYsWKsLOzE8oDAwMREhICW1tbWFtbY9SoUfD29i50L1BDNrqTO/ZdlWPPlUcYk/QM7loYbV99+h4yXuagjoMVOtax10KURIbpxx9/hEQiwZAhQ5CdnQ0AMDU1xciRI/Hdd9+JHB0RUdnz35mSRERUsCKvHr9161a0bt0aCxYswC+//IJu3brhxx9/1GVsRTJv3jx0794d/v7+aNeuHRwcHLBt2zaxw9KJuo7W8Ksvg1oNLDpc8u310pXZWHXqHgCOshOZmZlhwYIFePr0KS5evIiLFy8iJSUF8+bNM7jHaYiI9M28efOwadMm4fjDDz+Era0t3n33XVy6dEnn1//uu+8gkUgwduxYoSwzMxNBQUGws7NDpUqV4O/vj6SkJJ3HQkRUXEVO2sPDwzF8+HCkpaXh6dOnmDlzJmbPnq3L2Ap09OhRzJ8/Xzi2sLDAkiVLkJKSgoyMDGzbtu21z7MbutGd3AEAuy4/xO3k9BKda33MfaS9yIJblYro+s+2ckTlXYUKFeDh4QEPDw9UqFBB7HCIiMqElStXCov+RkZG4tChQ9i/fz+6dOmCCRMm6PTa586dw88//4yGDRtqlI8bNw67du3Cli1bcOzYMTx8+LDQhZeJiMRU5Onx8fHx2LRpE4yNjQEAX375JcLCwpCcnAx7e06rLi31naTwrSfDwetJWHz4Fub3b/JW58nMysGKE3cBACPb14CxEUfZqXzLzMzEokWLcOTIESQnJ0OlUmnUc692IqK3l5ycLCTtu3fvRr9+/eDr6wtXV1edbBmcJz09HQEBAVixYgVmzpwplKelpeHXX3/F+vXr0bFjRwC56zfVrVsXZ86cKfAxS6VSCaVSKRwrFAqdxU1E9Koij7Q/f/5cYwERMzMzWFhYID29ZKO9VHx5o+07Lz3Encdv9/lvif0Lj58p4SS1QO8m72ozPCKDFBgYiDlz5qBatWro3r07evXqpfEiIqK3Z2Njg8TE3O1l9+/fDx8fHwCAWq3W6crxQUFB6Natm3C9PLGxscjKytIor1OnDlxcXBAdHV3gucLDwyGVSoWXPm8XTERlS7EWovvll19QqVIl4Tg7OxurV69GlSpVhLLRo0drLzoqUIN3pfCpK8OhP5Kw+PBt/PRR42K9PytHhYijfwIAPmtfA2YmRf7thqjM2r17N/bu3YvWrVuLHQoRUZnTo0cPDBw4EO7u7vj777/RpUsXAMCFCxdQs2ZNnVxz48aNiIuLw7lz5/LVyeVymJmZ5VsITyaTQS6XF3i+0NBQhISECMcKhYKJOxGViiIn7S4uLlixYoVGmYODA/73v/8JxxKJhEl7KRnTyR2H/kjCjosPMKqTO9yqVCzye3defIgHqS9QpZIZPmrO/9gQAcC7777L/diJiHQkPDwctWrVQmJiIubMmSMMAj169AhffPGF1q+XmJiIMWPGIDIyEhYWFlo5p7m5ORcmJSJRFDlpv3fvng7DoOLyqCpFpzr2iLqRjEWHb+Gnfo2L9D6VSo2lR3NXng9sUx0WpsY6jJLIcMydOxeTJk1CREQEqlWrJnY4RERliqmpKcaPH5+vfNy4cTq5XmxsLJKTk9G0aVOhLCcnB8ePH8fixYtx4MABvHz5Mt+2c0lJSWV6QWMiMkzFmh5P+mWMjzuibiTj94sPMbqjO1yLMNp+4Jocfz7OgLWFCQa1dCmFKIkMg6enJzIzM1G9enVUqFABpqamGvUpKSkiRUZEZJh27twpPHK0d+/e1+7I0bNnT61eu1OnTrhy5YpG2bBhw1CnTh1MmjQJzs7OMDU1RVRUFPz9/QHkLrqckJAAb29vrcZCRFRSRU7aDx8+jODgYJw5c0ZjQTogdwXOVq1aYdmyZWjXrp3Wg6SCNaxqg/dqv4Mj8Y+x+Mht/Phho9e2V6vVWHwkd5T941ausLIwfW17ovJkwIABePDgAWbPng2ZTAaJhDsqEBGVRO/evXHr1i0AwMCBAwttJ5FItL4YnZWVFRo0aKBRVrFiRdjZ2QnlgYGBCAkJga2tLaytrTFq1Ch4e3sXuHI8EZGYipy0z58/H8OHD8+XsAOAVCrFZ599hnnz5jFpL2VjfGrhSPxjbL/wAKM61kQ1u8JH24/dfIxrDxWwNDXGx63dSjFKIv13+vRpREdHo1Gj1//4RURERaNSqYRt0VJTUwv8DimmefPmwcjICP7+/lAqlfDz88PSpUvFDouIKJ8iLxt+6dIldO7cudB6X19fxMbGaiUoKrrGzjZoX+sd5KjUWPLPKHph8uoDvFxgW9GsNMIjMhh16tTBixcvxA6DiIh05OjRo5g/f75wbGFhgSVLliAlJQUZGRnYtm0bn2cnIr1U5KQ9KSkp3zOerzIxMcHjx4+1EhQVzxif3H3bt8U9QGLK8wLbxNz5G+fuPYWZsRGGt6temuERGYTvvvsOX375JY4ePYq///4bCoVC40VERG/vf//7H7p3744GDRrAw8MDPXv2xNq1a6FWq8UOjYhI7xU5aX/33Xdx9erVQusvX74MR0dHrQRFxdPUpTLauldB9mtG25f8sy/7B55VIbPWztYnRGVJ586dER0djU6dOsHe3h6VK1dG5cqVYWNjg8qVK4sdHhGRQcpLykeNGoUHDx7Aw8MD9evXx/379/Hxxx+jT58+IkdIRKT/ivxMe9euXTF16lR07tw5336XL168wDfffIPu3btrPUAqmrE+7jhx6wm2xv6FoPdqwtn23xVaL/+ViuM3H8PYSILP29UQMUoi/XXkyBGxQyAiKnPWrVsHIHcl+f9+Tzx8+DB69+6NtWvXYsiQIWKER0RkEIqctE+ZMgXbtm1DrVq1EBwcjNq1awMAbty4gSVLliAnJwdff/21zgKl12tWzRZtalbBydtPsPTonwjv6yHULT2SO8res5ETXOwK326FqDxr37692CEQEZU5W7duBYACFyru2LEjJk+ejHXr1jFpJyJ6jSJPj5fJZDh9+jQaNGiA0NBQ9OnTB3369MFXX32FBg0a4OTJk5DJZLqMld4g79n2rbGJeJCau6DWraRn2H9NDgD4ogNH2Yle58SJExg0aBBatWqFBw8eAMh9DvPkyZMiR0ZEZJiuXbv22vouXbrg0qVLpRQNEZFhKnLSDgDVqlXD3r178eTJE8TExODMmTN48uQJ9u7dCzc3biEmtuautmhVww5ZOWos/efZ9mX/PMvuV18Gd5mVmOER6bXffvsNfn5+sLS0RFxcHJRKJQAgLS0Ns2fPFjk6IiLD9PTp09fWy2SyN7YhIirvipW056lcuTKaN2+OFi1acIEmPTOmU+5o++bziYi58zd+v/QQABD0Xk0xwyLSezNnzkRERARWrFihsVNG69atERcXJ2JkRESGKycn57X1xsbGyM7OLqVoiIgMU5GfaSfD4FXdDt7V7RB95298svocclRqtHWvgoZVbcQOjUivxcfHF/jMpVQqRWpqaukHRERUBuStHh8QEFDg1sF5s5qIiKhwbzXSTvot79n2jJe5v24Hc5Sd6I0cHBxw+3b+LRNPnjyJ6tWr6/Ta3333HSQSCcaOHSuUZWZmIigoCHZ2dqhUqRL8/f2RlJSk8b6EhAR069YNFSpUgL29PSZMmJBvxOro0aNo2rQpzM3NUbNmTaxevVqn90JE9KqBAwcCyP0BtKCXvb09F6EjInoDjrSXQS2r28HLzRYxd1PgWa0yWrjZih0Skd4bPnw4xowZg5UrV0IikeDhw4eIjo7G+PHjMXXqVJ1d99y5c/j555/RsGFDjfJx48Zhz5492LJlC6RSKYKDg9G3b1+cOnUKQO6U027dusHBwQGnT5/Go0ePMGTIEJiamgrP4N+9exfdunXD559/jnXr1iEqKgqffvopHB0d4efnp7N7IiLKs3TpUqxbtw5Lly6FtbW12OEQERkkJu1l1Kw+Hph36CZGd3SHRCIROxwivTd58mSoVCp06tQJz58/R7t27WBubo7x48dj1KhROrlmeno6AgICsGLFCsycOVMoT0tLw6+//or169ejY8eOAIBVq1ahbt26OHPmDFq2bImDBw/i+vXrOHToEGQyGRo3bowZM2Zg0qRJ+Pbbb2FmZoaIiAi4ublh7ty5AIC6devi5MmTmDdvHpN2IiIiIgPB6fFlVE37SlgysClqO3DFeKKikEgk+Prrr5GSkoKrV6/izJkzePz4MWbMmKGzawYFBaFbt27w8fHRKI+NjUVWVpZGeZ06deDi4oLo6GgAQHR0NDw8PDS22vTz84NCoRC2WIqOjs53bj8/P+EcBVEqlVAoFBovIiIiIhIPR9qJiF5hZmaGevXq6fw6GzduRFxcHM6dO5evTi6Xw8zMDDY2NhrlMpkMcrlcaPNqwp5Xn1f3ujYKhQIvXryApaVlvmuHh4dj2rRpb31fRERERKRdTNqJqFz75JNPitRu5cqVWrtmYmIixowZg8jISFhYWGjtvNoQGhqKkJAQ4VihUMDZ2VnEiIiIiIjKNybtRFSurV69GtWqVUOTJk2ErYl0LTY2FsnJyWjatKlQlpOTg+PHj2Px4sU4cOAAXr58idTUVI3R9qSkJDg4OADIXe3+7NmzGufNW13+1Tb/XXE+KSkJ1tbWBY6yA4C5uTnMzc1LfI9EREREpB1M2omoXBs5ciQ2bNiAu3fvYtiwYRg0aBBsbXW740KnTp1w5coVjbJhw4ahTp06mDRpEpydnWFqaoqoqCj4+/sDyN1HPiEhAd7e3gAAb29vzJo1C8nJybC3twcAREZGwtraWpje7+3tjb1792pcJzIyUjgHEREREek/LkRHROXakiVL8OjRI0ycOBG7du2Cs7Mz+vXrhwMHDuhs5N3KygoNGjTQeFWsWBF2dnZo0KABpFIpAgMDERISgiNHjiA2NhbDhg2Dt7c3WrZsCQDw9fVFvXr1MHjwYFy6dAkHDhzAlClTEBQUJIyUf/7557hz5w4mTpyIGzduYOnSpdi8eTPGjRunk/siIiIiIu1j0k5E5Z65uTkGDBiAyMhIXL9+HfXr18cXX3wBV1dXpKenixLTvHnz0L17d/j7+6Ndu3ZwcHDAtm3bhHpjY2Ps3r0bxsbG8Pb2xqBBgzBkyBBMnz5daOPm5oY9e/YgMjISjRo1wty5c/HLL79wuzciIiIiA8Lp8URErzAyMoJEIoFarUZOTk6pXffo0aMaxxYWFliyZAmWLFlS6HuqVauWb/r7f3Xo0AEXLlzQRohEREREJAKOtBNRuadUKrFhwwa8//77qFWrFq5cuYLFixcjISEBlSpVEjs8IiIiIirHONJOROXaF198gY0bN8LZ2RmffPIJNmzYgCpVqogdFhERERERACbtRFTORUREwMXFBdWrV8exY8dw7NixAtu9+jw5EREREVFpYdJOROXakCFDIJFIxA6DiIiIiKhATNqJqFxbvXq12CEQERERERWKC9ERERERERER6Skm7URERERERER6ikk7ERERERERkZ5i0k5ERERERESkp5i0ExEREREREekprh5PRERERER6Sa1WQ60GVGo1VMKfuX8vrH2B5YWev7CKworzVxR2jsKvWcA5CmxXtOsXsah453zDe4pyLc1zlOwab6sk533T51IYeysLWJoZv/2FC8CknYiIiIhIx/ZeeYRdlx4Kx0VJnv7b5r9vyX+ONyeU+c+hzleflyT/myznJsnqVxNn1atJdF7dv2V5781Rvfk8ajWQU0i9rpI5Il1Z96kXWtesotVzMmknIiIiItKxP5PTse+qXOwwyEBJJIWUF9q+4JrC27/h+oW+8w0nLkaTEsdQjHNpnreo5yxaS6PiXLyImLQTEREREelY+9rvwKaimUZZQV/t//t9/7+JSv7617+/oHO84RBGEgmMjHL/lEgkMJL8UybBP8f/lBm98neJBBKh3attAeN/2hVWL5QZvb5e8k+98T/nKkzhCW4hiawWEuLiJsNFTQCJACbtREREREQ617CqDRpWtRE7DCIyQFw9noiIiIiIiEhPMWknIiIiIiIi0lNM2omIiIiIiIj0FJN2IiIiIiIiIj3FpJ2IiIiIiIhITzFpJyIiIiIiItJTTNqJiIiIiIiI9JReJ+3h4eFo3rw5rKysYG9vj969eyM+Pl6jTWZmJoKCgmBnZ4dKlSrB398fSUlJIkVMREREREREpD16nbQfO3YMQUFBOHPmDCIjI5GVlQVfX19kZGQIbcaNG4ddu3Zhy5YtOHbsGB4+fIi+ffuKGDURERERERGRdpiIHcDr7N+/X+N49erVsLe3R2xsLNq1a4e0tDT8+uuvWL9+PTp27AgAWLVqFerWrYszZ86gZcuWYoRNREREREREpBV6PdL+X2lpaQAAW1tbAEBsbCyysrLg4+MjtKlTpw5cXFwQHR1d6HmUSiUUCoXGi4iIiIiIiEjfGEzSrlKpMHbsWLRu3RoNGjQAAMjlcpiZmcHGxkajrUwmg1wuL/Rc4eHhkEqlwsvZ2VmXoRMRERERERG9FYNJ2oOCgnD16lVs3LixxOcKDQ1FWlqa8EpMTNRChERERESkD7iYMRGVJQaRtAcHB2P37t04cuQIqlatKpQ7ODjg5cuXSE1N1WiflJQEBweHQs9nbm4Oa2trjRcRERERlQ1czJiIyhK9XohOrVZj1KhR2L59O44ePQo3NzeN+mbNmsHU1BRRUVHw9/cHAMTHxyMhIQHe3t5ihExEREREIuNixkRUluh10h4UFIT169fj999/h5WVlfCculQqhaWlJaRSKQIDAxESEgJbW1tYW1tj1KhR8Pb2ZmdLRERERACKv5hxQd8jlUollEqlcMyFjImotOj19Phly5YhLS0NHTp0gKOjo/DatGmT0GbevHno3r07/P390a5dOzg4OGDbtm0iRk1ERERE+kJbixlzIWMiEotej7Sr1eo3trGwsMCSJUuwZMmSUoiIiIiIiAxJ3mLGJ0+eLNF5QkNDERISIhwrFAom7kRUKvQ6aSciIiIielt5ixkfP3680MWMXx1tf91ixubm5jA3N9d1yERE+ej19HgiIiIiouJSq9UIDg7G9u3bcfjw4dcuZpyHixkTkb7iSDsRERERlSlczJiIyhIm7URERERUpixbtgwA0KFDB43yVatW4eOPPwaQu5ixkZER/P39oVQq4efnh6VLl5ZypEREb8bp8UREpSw8PBzNmzeHlZUV7O3t0bt3b8THx2u0yczMRFBQEOzs7FCpUiX4+/sjKSlJo01CQgK6deuGChUqwN7eHhMmTEB2drZGm6NHj6Jp06YwNzdHzZo1sXr1al3fHhGR6NRqdYGvvIQd+Hcx45SUFGRkZGDbtm2FPs9ORCQmJu1ERKXs2LFjCAoKwpkzZxAZGYmsrCz4+voiIyNDaDNu3Djs2rULW7ZswbFjx/Dw4UP07dtXqM/JyUG3bt3w8uVLnD59GmvWrMHq1asRFhYmtLl79y66deuG9957DxcvXsTYsWPx6aef4sCBA6V6v0RERET09iTqouyrVsYpFApIpVKkpaXB2tpa7HCIyMCUtA95/Pgx7O3tcezYMbRr1w5paWl45513sH79enzwwQcAgBs3bqBu3bqIjo5Gy5YtsW/fPnTv3h0PHz6ETCYDAERERGDSpEl4/PgxzMzMMGnSJOzZswdXr14VrtW/f3+kpqZi//79BcaiVCqhVCo17s3Z2Zn9IxG9lbL8Hass3xsRlY6i9iMcaSciEllaWhoAwNbWFgAQGxuLrKws+Pj4CG3q1KkDFxcXREdHAwCio6Ph4eEhJOwA4OfnB4VCgWvXrgltXj1HXpu8cxQkPDwcUqlUeHEPYiIiIiJxMWknIhKRSqXC2LFj0bp1azRo0AAAIJfLYWZmprF3MADIZDJhBWS5XK6RsOfV59W9ro1CocCLFy8KjCc0NBRpaWnCKzExscT3SERERERvj6vHExGJKCgoCFevXsXJkyfFDgUAYG5uDnNzc7HDICIiIqJ/cKSdiEgkwcHB2L17N44cOYKqVasK5Q4ODnj58iVSU1M12iclJQkrGzs4OORbTT7v+E1trK2tYWlpqe3bISIiIiIdYNJORFTK1Go1goODsX37dhw+fBhubm4a9c2aNYOpqSmioqKEsvj4eCQkJMDb2xsA4O3tjStXriA5OVloExkZCWtra9SrV09o8+o58trknYOIiIiI9B+nxxMRlbKgoCCsX78ev//+O6ysrIRn0KVSKSwtLSGVShEYGIiQkBDY2trC2toao0aNgre3N1q2bAkA8PX1Rb169TB48GDMmTMHcrkcU6ZMQVBQkDC9/fPPP8fixYsxceJEfPLJJzh8+DA2b96MPXv2iHbvRERERFQ8HGknIiply5YtQ1paGjp06ABHR0fhtWnTJqHNvHnz0L17d/j7+6Ndu3ZwcHDAtm3bhHpjY2Ps3r0bxsbG8Pb2xqBBgzBkyBBMnz5daOPm5oY9e/YgMjISjRo1wty5c/HLL7/Az8+vVO+XiIiIiN4e92kH99kkopIpy31IWb43ItK9styHlOV7I6LSwX3aiYiIiIiIiAwck3YiIiIiIiIiPcWknYiIiIiIiEhPMWknIiIiIiIi0lNM2omIiIiIiIj0FJN2IiIiIiIiIj3FpJ2IiIiIiIhITzFpJyIiIiIiItJTTNqJiIiIiIiI9BSTdiIiIiIiIiI9ZSJ2AEREROWBWq1GZpYKz19m4/nLHLzIysHzlzl4/jIbmcLfc/BC+DMbyhzVP29+5TyvnC/3z4LqXi3L3+7VmP5zeqGd+pXSf8vytzMcaqhUQI5aDZVaDbUaUKnVUP3zp1qdW59Xpv6n3b/1eXWv1hfQXpW/ff5rFX6uV0le/btEUkh5we94tbyw9pIitde4gODI+A4wM+HYDxFRaWDSTkRE9I+sHNUriXM2XmT9m0TnJtrZmol11r9tXy1/npWbdD9/mSMk5C+ycgww0SUiIiKxMWknIiKt2XA2AX8mp0MNCKOJwL8jiWrkjSwCeSOfr5apkTsK+W/73L+/WvfvSGXuOYQyQBi1BDRHNNX/OZdKrYYyW/VKQp6boGfllE5WbW5ihApmxqhgZgJLM2NUMDOGpamxRpmlqTHMTYyEEdACR1rz6goYMS1odPW17Qo4f0GjsoWNyBoCIyMJjCQSGEkAYyMJJP/8Pa8s9/jfMklenVHecRHba9TnXbco7YF/P9X8Mx00SwueUZGvvAhtXlXU9iZGhva/PhGR4WLSTkREWrP3yiOcuPVE7DBKzNhIggqmxv8m1GYm/yTUxrAQkmtjWJqa/FP/SpmZiZCAC+Wmmsm5ERMeIiIiKiIm7UREpDXdPBxRz9EayBtJxL8jihLkjjRKXqmTSPKX5bUHNEcj33iOAtrnOwf+Hc20MDVCBTPNpNvyn0TdzNio0Gd5iYiIiEoTk3YiItKa/i1cxA6BiIiIqEzhsp9EREREREREeopJOxEREREREZGeYtJOREREREREpKeYtBMRERERERHpKSbtRERERERERHqKSTsRERERERGRnmLSTkRERERERKSnmLQTERERERER6Skm7URERERERER6ikk7ERERERERkZ5i0k5ERERERESkp5i0ExEREREREekpJu1EREREREREeopJOxEREREREZGeYtJOREREREREpKeYtBMRERERERHpKSbtRERERERERHqKSTsRERERERGRnmLSTkRERERERKSnmLQTERERERER6akyk7QvWbIErq6usLCwgJeXF86ePSt2SEREeoH9IxFR4dhHEpG+KxNJ+6ZNmxASEoJvvvkGcXFxaNSoEfz8/JCcnCx2aEREomL/SERUOPaRRGQIykTS/tNPP2H48OEYNmwY6tWrh4iICFSoUAErV64UOzQiIlGxfyQiKhz7SCIyBCZiB1BSL1++RGxsLEJDQ4UyIyMj+Pj4IDo6usD3KJVKKJVK4TgtLQ0AoFAodBssEZVJeX2HWq0WORJN7B+JSGz62j8Cxe8j2T8SkbYVtY80+KT9yZMnyMnJgUwm0yiXyWS4ceNGge8JDw/HtGnT8pU7OzvrJEYiKh+ePXsGqVQqdhgC9o9EpC/0rX8Eit9Hsn8kIl15Ux9p8En72wgNDUVISIhwrFKpkJKSAjs7O0gkkje+X6FQwNnZGYmJibC2ttZlqGUeP0vt4WepHW/zOarVajx79gxOTk46jk732D/qD36W2sPPUnuK+1myf9TEf4vawc9Re/hZao8uv0MafNJepUoVGBsbIykpSaM8KSkJDg4OBb7H3Nwc5ubmGmU2NjbFvra1tTX/cWsJP0vt4WepHcX9HPVtBAlg/1hW8LPUHn6W2lOcz1If+0eg+H2ktvpHgP8WtYWfo/bws9QeXXyHNPiF6MzMzNCsWTNERUUJZSqVClFRUfD29hYxMiIicbF/JCIqHPtIIjIUBj/SDgAhISEYOnQoPD090aJFC8yfPx8ZGRkYNmyY2KEREYmK/SMRUeHYRxKRISgTSftHH32Ex48fIywsDHK5HI0bN8b+/fvzLSyiLebm5vjmm2/yTZGi4uNnqT38LLWjrH2O7B8NFz9L7eFnqT1l7bNkH2mY+DlqDz9L7dHlZylR6+MeHERERERERERk+M+0ExEREREREZVVTNqJiIiIiIiI9BSTdiIiIiIiIiI9xaSdiIiIiIiISE8xaX8LS5YsgaurKywsLODl5YWzZ8+KHZJBCQ8PR/PmzWFlZQV7e3v07t0b8fHxYodVJnz33XeQSCQYO3as2KEYpAcPHmDQoEGws7ODpaUlPDw8cP78ebHDMijsH0uOfaRusH8sGfaPJcf+seTYP+oG+8eSKY3+kUl7MW3atAkhISH45ptvEBcXh0aNGsHPzw/Jyclih2Ywjh07hqCgIJw5cwaRkZHIysqCr68vMjIyxA7NoJ07dw4///wzGjZsKHYoBunp06do3bo1TE1NsW/fPly/fh1z585F5cqVxQ7NYLB/1A72kdrH/rFk2D+WHPtH7WD/qH3sH0um1PpHNRVLixYt1EFBQcJxTk6O2snJSR0eHi5iVIYtOTlZDUB97NgxsUMxWM+ePVO7u7urIyMj1e3bt1ePGTNG7JAMzqRJk9Rt2rQROwyDxv5RN9hHlgz7x5Jj/1hy7B91g/1jybB/LLnS6h850l4ML1++RGxsLHx8fIQyIyMj+Pj4IDo6WsTIDFtaWhoAwNbWVuRIDFdQUBC6deum8W+Timfnzp3w9PTEhx9+CHt7ezRp0gQrVqwQOyyDwf5Rd9hHlgz7x5Jj/1gy7B91h/1jybB/LLnS6h+ZtBfDkydPkJOTA5lMplEuk8kgl8tFisqwqVQqjB07Fq1bt0aDBg3EDscgbdy4EXFxcQgPDxc7FIN2584dLFu2DO7u7jhw4ABGjhyJ0aNHY82aNWKHZhDYP+oG+8iSYf+oHewfS4b9o26wfywZ9o/aUVr9o4lWz0ZUTEFBQbh69SpOnjwpdigGKTExEWPGjEFkZCQsLCzEDsegqVQqeHp6Yvbs2QCAJk2a4OrVq4iIiMDQoUNFjo7KK/aRb4/9o/awfyR9xP7x7bF/1J7S6h850l4MVapUgbGxMZKSkjTKk5KS4ODgIFJUhis4OBi7d+/GkSNHULVqVbHDMUixsbFITk5G06ZNYWJiAhMTExw7dgwLFy6EiYkJcnJyxA7RYDg6OqJevXoaZXXr1kVCQoJIERkW9o/axz6yZNg/ag/7x5Jh/6h97B9Lhv2j9pRW/8ikvRjMzMzQrFkzREVFCWUqlQpRUVHw9vYWMTLDolarERwcjO3bt+Pw4cNwc3MTOySD1alTJ1y5cgUXL14UXp6enggICMDFixdhbGwsdogGo3Xr1vm2jbl58yaqVasmUkSGhf2j9rCP1A72j9rD/rFk2D9qD/tH7WD/qD2l1T9yenwxhYSEYOjQofD09ESLFi0wf/58ZGRkYNiwYWKHZjCCgoKwfv16/P7777CyshKe55JKpbC0tBQ5OsNiZWWV7zmuihUrws7Ojs93FdO4cePQqlUrzJ49G/369cPZs2exfPlyLF++XOzQDAb7R+1gH6kd7B+1h/1jybF/1A72j9rB/lF7Sq1/1Pn69GXQokWL1C4uLmozMzN1ixYt1GfOnBE7JIMCoMDXqlWrxA6tTOCWHW9v165d6gYNGqjNzc3VderUUS9fvlzskAwO+8eSYx+pO+wf3x77x5Jj/1hy7B91h/3j2yuN/lGiVqvV2v0ZgIiIiIiIiIi0gc+0ExEREREREekpJu1EREREREREeopJOxEREREREZGeYtJOREREREREpKeYtBMRERERERHpKSbtRERERERERHqKSTsRERERERGRnmLSTkRERERERKSnmLRTmfXxxx+jd+/eol1/8ODBmD17dpHa9u/fH3PnztVxREREudg/EhEVjn0k6RuJWq1Wix0EUXFJJJLX1n/zzTcYN24c1Go1bGxsSieoV1y6dAkdO3bE/fv3UalSpTe2v3r1Ktq1a4e7d+9CKpWWQoREVFaxfyQiKhz7SDJETNrJIMnlcuHvmzZtQlhYGOLj44WySpUqFamj05VPP/0UJiYmiIiIKPJ7mjdvjo8//hhBQUE6jIyIyjr2j0REhWMfSYaI0+PJIDk4OAgvqVQKiUSiUVapUqV8U5s6dOiAUaNGYezYsahcuTJkMhlWrFiBjIwMDBs2DFZWVqhZsyb27dunca2rV6+iS5cuqFSpEmQyGQYPHownT54UGltOTg62bt2KHj16aJQvXboU7u7usLCwgEwmwwcffKBR36NHD2zcuLHkHw4RlWvsH4mICsc+kgwRk3YqV9asWYMqVarg7NmzGDVqFEaOHIkPP/wQrVq1QlxcHHx9fTF48GA8f/4cAJCamoqOHTuiSZMmOH/+PPbv34+kpCT069ev0GtcvnwZaWlp8PT0FMrOnz+P0aNHY/r06YiPj8f+/fvRrl07jfe1aNECZ8+ehVKp1M3NExG9BvtHIqLCsY8kUamJDNyqVavUUqk0X/nQoUPVvXr1Eo7bt2+vbtOmjXCcnZ2trlixonrw4MFC2aNHj9QA1NHR0Wq1Wq2eMWOG2tfXV+O8iYmJagDq+Pj4AuPZvn272tjYWK1SqYSy3377TW1tba1WKBSF3selS5fUANT37t177f0SERUV+0ciosKxjyRDwZF2KlcaNmwo/N3Y2Bh2dnbw8PAQymQyGQAgOTkZQO5iIEeOHBGeb6pUqRLq1KkDAPjzzz8LvMaLFy9gbm6usdDJ+++/j2rVqqF69eoYPHgw1q1bJ/wSm8fS0hIA8pUTEZUG9o9ERIVjH0liYtJO5YqpqanGsUQi0SjL6yRVKhUAID09HT169MDFixc1Xrdu3co3NSlPlSpV8Pz5c7x8+VIos7KyQlxcHDZs2ABHR0eEhYWhUaNGSE1NFdqkpKQAAN555x2t3CsRUXGwfyQiKhz7SBITk3ai12jatCmuXbsGV1dX1KxZU+NVsWLFAt/TuHFjAMD169c1yk1MTODj44M5c+bg8uXLuHfvHg4fPizUX716FVWrVkWVKlV0dj9ERNrC/pGIqHDsI0mbmLQTvUZQUBBSUlIwYMAAnDt3Dn/++ScOHDiAYcOGIScnp8D3vPPOO2jatClOnjwplO3evRsLFy7ExYsXcf/+faxduxYqlQq1a9cW2pw4cQK+vr46vyciIm1g/0hEVDj2kaRNTNqJXsPJyQmnTp1CTk4OfH194eHhgbFjx8LGxgZGRoX/3+fTTz/FunXrhGMbGxts27YNHTt2RN26dREREYENGzagfv36AIDMzEzs2LEDw4cP1/k9ERFpA/tHIqLCsY8kbZKo1Wq12EEQlTUvXrxA7dq1sWnTJnh7e7+x/bJly7B9+3YcPHiwFKIjIhIP+0ciosKxj6SCcKSdSAcsLS2xdu1aPHnypEjtTU1NsWjRIh1HRUQkPvaPRESFYx9JBeFIOxEREREREZGe4kg7ERERERERkZ5i0k5ERERERESkp5i0ExEREREREekpJu1EREREREREeopJOxEREREREZGeYtJOREREREREpKeYtBMRERERERHpKSbtRERERERERHqKSTsRERERERGRnvp/r3L+nITHKuIAAAAASUVORK5CYII=\n" }, "metadata": {} }, @@ -549,12 +647,13 @@ "name": "stdout", "text": [ "Copying files from IDC buckets..\n", - "Done in 0.820563 seconds.\n", - "Chris Rorden's dcm2niiX version v1.0.20181125 (JP2:OpenJPEG) GCC9.3.0 (64-bit Linux)\n", + "Done in 2.01734 seconds.\n", + "Chris Rorden's dcm2niiX version v1.0.20211006 (JP2:OpenJPEG) GCC11.2.0 x86-64 (64-bit Linux)\n", "Found 191 DICOM file(s)\n", - "Convert 191 DICOM as //content/dcm2niix/1.2.840.113654.2.55.113040386178547843571271236478024341696/1.2.840.113654.2.55.113040386178547843571271236478024341696_0_OPA_GE_LSQX_STANDARD_352_2.5_120_64_0.1_1.5_19990102000000_2 (512x512x191x1)\n", - "compress: \"/usr/bin/pigz\" -n -f -6 \"//content/dcm2niix/1.2.840.113654.2.55.113040386178547843571271236478024341696/1.2.840.113654.2.55.113040386178547843571271236478024341696_0_OPA_GE_LSQX_STANDARD_352_2.5_120_64_0.1_1.5_19990102000000_2.nii\"\n", - "Conversion required 7.032374 seconds (0.352415 for core code).\n" + "Convert 191 DICOM as /content/dcm2niix/1.2.840.113654.2.55.113040386178547843571271236478024341696/1.2.840.113654.2.55.113040386178547843571271236478024341696_0,OPA,GE,LSQX,STANDARD,352,2.5,120,64,0.1,1.5_19990102000000_2 (512x512x191x1)\n", + "Compress: \"/usr/bin/pigz\" -b 960 -n -f -6 \"/content/dcm2niix/1.2.840.113654.2.55.113040386178547843571271236478024341696/1.2.840.113654.2.55.113040386178547843571271236478024341696_0,OPA,GE,LSQX,STANDARD,352,2.5,120,64,0.1,1.5_19990102000000_2.nii\"\n", + "Conversion required 5.459414 seconds (0.344534 for core code).\n", + "\n" ] }, { @@ -563,7 +662,7 @@ "text/plain": [ "
" ], - "image/png": 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\n" 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\n" }, "metadata": {} }, @@ -572,12 +671,13 @@ "name": "stdout", "text": [ "Copying files from IDC buckets..\n", - "Done in 0.622624 seconds.\n", - "Chris Rorden's dcm2niiX version v1.0.20181125 (JP2:OpenJPEG) GCC9.3.0 (64-bit Linux)\n", + "Done in 1.7216 seconds.\n", + "Chris Rorden's dcm2niiX version v1.0.20211006 (JP2:OpenJPEG) GCC11.2.0 x86-64 (64-bit Linux)\n", "Found 128 DICOM file(s)\n", - "Convert 128 DICOM as //content/dcm2niix/1.2.840.113654.2.55.142419057730651121165090739113900499978/1.2.840.113654.2.55.142419057730651121165090739113900499978_2_OPA_GE_LSQX_BONE_360_2.5_120_72_0.1_1.5_20010102000000_3 (512x512x128x1)\n", - "compress: \"/usr/bin/pigz\" -n -f -6 \"//content/dcm2niix/1.2.840.113654.2.55.142419057730651121165090739113900499978/1.2.840.113654.2.55.142419057730651121165090739113900499978_2_OPA_GE_LSQX_BONE_360_2.5_120_72_0.1_1.5_20010102000000_3.nii\"\n", - "Conversion required 3.556607 seconds (0.236975 for core code).\n" + "Convert 128 DICOM as /content/dcm2niix/1.2.840.113654.2.55.142419057730651121165090739113900499978/1.2.840.113654.2.55.142419057730651121165090739113900499978_2,OPA,GE,LSQX,BONE,360,2.5,120,72,0.1,1.5_20010102000000_3 (512x512x128x1)\n", + "Compress: \"/usr/bin/pigz\" -b 960 -n -f -6 \"/content/dcm2niix/1.2.840.113654.2.55.142419057730651121165090739113900499978/1.2.840.113654.2.55.142419057730651121165090739113900499978_2,OPA,GE,LSQX,BONE,360,2.5,120,72,0.1,1.5_20010102000000_3.nii\"\n", + "Conversion required 4.308476 seconds (0.277552 for core code).\n", + "\n" ] }, { @@ -586,7 +686,7 @@ "text/plain": [ "
" ], - "image/png": 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JRbvkO6cTLjHu2yuPxQ9tU52QMkUNTiQiIiIiIuIcKtolX7HZbIxcspek1HQaBJegT/MQoyOJiIiIiIg4jYp2yVe+2vEH6w6fw8vDjUmP1MNdj8WLiIiIiEgBpqJd8o3YxBTGrDgAwOAHqlGlbDGDE4mIiIiIiDiXinbJF2w2G68u3cuFlHTqBZXg6RZ6LF5ERERERAo+Fe2SLyz95RRrDp7Fy92N9x6pi4e7/umKiIiIiEjBp8pHXN5ZSwpvLb/yWPzL4VWp6l/c4EQiIiIiIiJ5Q0W7uDSbzcbry/aReCmNOuX9eKZlZaMjiYiIiIiI5BkV7eLSlu85ww8H4vB0N/HuI/Xw1GPxIiIiIiJSiKgCEpd17kIqb/xvHwAD/lOVmuX8DE4kIiIiIiKSt1S0i8t645t9nL+YRs1yfrzwnzuNjiMiIiIiIpLnVLSLS/p2zxm+2xuLh5uJ9x6tq8fiRURERESkUFIlJC7nr6RURv/9WPwL991J7UCzwYlERERERESMoaJdXM6byw/wV/JlqvsXZ8D9VY2OIyIiIiIiYhgV7eJSVu6LZfnu07i7mXj30bp4eeifqIiIiIiIFF6qiMRlnE++zOvLrjwW/2zLytStUMLYQCIiIiIiIgZz6aI9IyODUaNGERISgq+vL3feeSdjxozBZrPZ29hsNkaPHk25cuXw9fUlPDycI0eOGJhabtXbKw7wZ1IqVcoW46VWeixeRERERETEpYv2d955h5kzZzJt2jR+/fVX3nnnHSZNmsRHH31kbzNp0iSmTp1KZGQkW7ZsoWjRorRp04aUlBQDk0tO/XggjqW/nMLNBO8+UhcfT3ejI4mIiIiIiBjOw+gAN7Jp0yYeeughOnToAEClSpX44osv2Lp1K3DlLvuUKVN4/fXXeeihhwCYN28e/v7+LFu2jG7dumV63NTUVFJTU+3LFovFyVciN5J4MY1Xl+4FoP89lakfXNLgRCIiIiIiIq7Bpe+0N2vWjNWrV3P48GEAdu/ezYYNG2jXrh0Ax44dIzY2lvDwcPs+ZrOZJk2aEB0dneVxJ0yYgNlstn+CgoKceyFyQ2O+PcDZC6lULlOUQQ9UMzqOiIiIiIiIy3DpO+0jRozAYrFQo0YN3N3dycjIYNy4cfTs2ROA2NhYAPz9/R328/f3t2/LzMiRIxk8eLB92WKxqHA3yNpDZ1m84w9MJnj3UT0WLyIiIiIici2XLtq//PJL5s+fz4IFC6hduza7du1i4MCBBAYG0rt371s+rre3N97e3rmYVG6FJSWNV5dceSy+b/MQGlYsZXAiERERERER1+LSRfvQoUMZMWKE/d300NBQTpw4wYQJE+jduzcBAQEAxMXFUa5cOft+cXFx3HXXXUZElhwY/+2vnElMoVLpIgxpXd3oOCIiIiIiIi7Hpd9pv3jxIm5ujhHd3d2xWq0AhISEEBAQwOrVq+3bLRYLW7ZsISwsLE+zSs78fOQcC7edBOCdrnXx9dJj8SIiIiIiIv/m0nfaO3XqxLhx4wgODqZ27dr88ssvfPDBB/Tt2xcAk8nEwIEDGTt2LFWrViUkJIRRo0YRGBhI586djQ0vWUpKTWfE11cei3+qWSWaVC5tcCIRERERERHX5NJ32j/66CMeeeQRXnjhBWrWrMmQIUN49tlnGTNmjL3NsGHDePHFF3nmmWe4++67SUpKYuXKlfj4+BiYXG5kwne/cirhEkGlfBnWVo/FS8Gzfv16OnXqRGBgICaTiWXLljlst9lsjB49mnLlyuHr60t4eDhHjhxxaBMfH0/Pnj3x8/OjRIkS9OvXj6SkJIc2e/bs4Z577sHHx4egoCAmTZp0XZavvvqKGjVq4OPjQ2hoKN99912uX6+IiIiIOI9LF+3FixdnypQpnDhxgkuXLvHbb78xduxYvLy87G1MJhNvv/02sbGxpKSk8OOPP1KtmqYNc1Wbjv7J/C0xwJXH4ot4ufTDHiK3JDk5mXr16jF9+vRMt0+aNImpU6cSGRnJli1bKFq0KG3atCElJcXepmfPnuzfv5+oqChWrFjB+vXreeaZZ+zbLRYLrVu3pmLFiuzYsYN3332XN998k08++cTeZtOmTXTv3p1+/frxyy+/0LlzZzp37sy+ffucd/EiIiIikqtMNpvNZnQIo1ksFsxmM4mJifj5+Rkdp8BKTk2n7YfrORl/iSeaBjO2c6jRkURyxY36EJPJxNKlS+2v7NhsNgIDA3nllVcYMmQIAImJifj7+zN37ly6devGr7/+Sq1atdi2bRuNGjUCYOXKlbRv354//viDwMBAZs6cyWuvvUZsbKz9F5kjRoxg2bJlHDx4EIDHH3+c5ORkVqxYYc/TtGlT7rrrLiIjI2/72kREbqYg9yEF+dpEJG9ktx9x6TvtUrBMWnmQk/GXKF/ClxHtahodR8QQx44dIzY2lvDwcPs6s9lMkyZNiI6OBiA6OpoSJUrYC3aA8PBw3Nzc2LJli71Ny5YtHZ48atOmDYcOHeL8+fP2Ntee52qbq+fJTGpqKhaLxeEjIiIiIsZR0S55Ysvvf/F59AkAJnYNpZi3HouXwik2NhYAf39/h/X+/v72bbGxsZQtW9Zhu4eHB6VKlXJok9kxrj1HVm2ubs/MhAkTMJvN9k9QUFBOL1FEREREcpGKdnG6S5czGPb1HgC6Nw7inqp3GJxIRLIycuRIEhMT7Z+TJ08aHUlERESkUFPRLk737qpDnPjrIuXMPoxsr8fipXALCAgAIC4uzmF9XFycfVtAQABnz5512J6enk58fLxDm8yOce05smpzdXtmvL298fPzc/iIiIiIiHFUtItTbT8ez5xNxwCY0CUUPx9PgxOJGCskJISAgABWr15tX2exWNiyZQthYWEAhIWFkZCQwI4dO+xt1qxZg9VqpUmTJvY269evJy0tzd4mKiqK6tWrU7JkSXuba89ztc3V84iIiIiI61PRLk6TkpbBsMV7sNng0YYVuK962ZvvJFIAJCUlsWvXLnbt2gVcGXxu165dxMTEYDKZGDhwIGPHjuWbb75h79699OrVi8DAQPsI8zVr1qRt27b079+frVu3snHjRgYMGEC3bt0IDAwEoEePHnh5edGvXz/279/PokWL+PDDDxk8eLA9x8svv8zKlSt5//33OXjwIG+++Sbbt29nwIABef1HIiKSpzIyMhg1ahQhISH4+vpy5513MmbMGK6dNMlmszF69GjKlSuHr68v4eHhHDlyxMDUIiJZsIktMTHRBtgSExONjlKgjP/2gK3i8BW2xuOibAkXLxsdR8Rp/t2HrF271gZc9+ndu7fNZrPZrFarbdSoUTZ/f3+bt7e3rVWrVrZDhw45HPOvv/6yde/e3VasWDGbn5+frU+fPrYLFy44tNm9e7etRYsWNm9vb1v58uVtEydOvC7bl19+aatWrZrNy8vLVrt2bdu33357W9cmIpITRvUh48aNs5UuXdq2YsUK27Fjx2xfffWVrVixYrYPP/zQ3mbixIk2s9lsW7ZsmW337t22Bx980BYSEmK7dOlSts6h/lFEbld2+xHN047m2XSGX2LO03XmJqw2+Kx3I1rV9L/5TiL5VEHuQwrytYmI8xnVh3Ts2BF/f38+++wz+7quXbvi6+vL//3f/2Gz2QgMDOSVV15hyJAhACQmJuLv78/cuXPp1q3bTc+h/lFEbpfmaRfDpKRlMHTxHqw2eLh+eRXsIiIikqeaNWvG6tWrOXz4MAC7d+9mw4YNtGvXDrjy2lJsbCzh4eH2fcxmM02aNCE6OjrTY6ampmKxWBw+IiJ5QZNlS66buvoIR88mUaaYN290qmV0HBERESlkRowYgcVioUaNGri7u5ORkcG4cePo2bMnALGxsQD4+zveWPD397dv+7cJEybw1ltvOTe4iEgmdKddctWePxL4eP3vAIx7uA4lingZnEhEREQKmy+//JL58+ezYMECdu7cyeeff857773H559/fsvHHDlyJImJifbPyZMnczGxiEjWdKddck1qegZDv9pDhtVGp3qBtKmd9VzQIiIiIs4ydOhQRowYYX83PTQ0lBMnTjBhwgR69+5NQMCV7yhxcXGUK1fOvl9cXBx33XVXpsf09vbG29vb6dlFRP5Nd9ol10xfc5RDcRcoXdSLtx6sbXQcERERKaQuXryIm5vj11x3d3esVisAISEhBAQEsHr1avt2i8XCli1bCAsLy9OsIiI3ozvtkiv2nUpk+k+/ATCmcx1KFdVj8SIiImKMTp06MW7cOIKDg6lduza//PILH3zwAX379gXAZDIxcOBAxo4dS9WqVQkJCWHUqFEEBgbSuXNnY8OLiPyLina5bZfTrQxdfOWx+PahAbQPLXfznURERESc5KOPPmLUqFG88MILnD17lsDAQJ599llGjx5tbzNs2DCSk5N55plnSEhIoEWLFqxcuRIfHx8Dk4uIXE/ztKN5Nm/Xhz8eYfKPhylZxJOowfdSppje95LCpSD3IQX52kTE+QpyH1KQr01E8kZ2+xHdaZfb8usZCx+tOQLAWw/VUcEu+VZqaipbtmzhxIkTXLx4kTvuuIP69esTEhJidDQRERERKcRUtMstS8uwMnTxbtKtNlrX8qdTXT0WL/nPxo0b+fDDD1m+fDlpaWmYzWZ8fX2Jj48nNTWVypUr88wzz/Dcc89RvHhxo+OKiIiISCGj0ePlln2y/nf2nbJg9vVk7MN1MJlMRkcSyZEHH3yQxx9/nEqVKvHDDz9w4cIF/vrrL/744w8uXrzIkSNHeP3111m9ejXVqlUjKirK6MgiIiIiUsjoTrvcksNxF/jwxyuPxb/5YC3KFtegLZL/dOjQga+//hpPT89Mt1euXJnKlSvTu3dvDhw4wJkzZ/I4oYiIiIgUdiraJcfSM6wM/Wo3lzOstKpRls53lTc6ksgtefbZZ7PdtlatWtSqVcuJaURERERErqfH4yXHPt1wjN1/JOLn48H4LqF6LF4KpN9//539+/djtVqNjiIiIiIihZiKdsmRo2eT+CDqMACjOtbC30+PxUv+lpaWxhtvvEGnTp0YN24cGRkZdO/enapVq1K3bl3q1KnD8ePHjY4pIiIiIoWUinbJtgyrjaGLd3M53cp91e/gkYYVjI4kcttGjBjBzJkzCQgIYPbs2XTp0oVffvmFBQsWsHDhQjw8PHjttdeMjikiIiIihZTeaZds+3zTcX6JSaCYtwfjH9Zj8VIwLF68mLlz59K+fXsOHz5MjRo1+Pbbb2nXrh0AZcuWpWfPnganFBEREZHCSnfaJVtS0zOY8dNvAIxsX4PAEr4GJxLJHadPn6ZevXoAVKtWDW9vb6pUqWLfXq1aNWJjY42KJyIiIiKFnIp2yZYVu8/wZ1IqAX4+PNYoyOg4IrkmIyPDYco3Dw8P3N3d7ctubm7YbDYjoomIiIiI6PF4uTmbzcbsjccAeDKsIp7u+l2PFCyrVq3CbDYDYLVaWb16Nfv27QMgISHBwGQiIiIiUtipaJeb2nb8PPtPW/D2cKNH42Cj44jkut69ezss/3v+do3fICIiIiJGUdEuNzV7w5W77F0alKdkUS+D04jkLs3DLiIiIiKuTEW73NDJ+Iv8cODKIFxPNQsxOI2IiIjkR8ePH2fXrl2cOHGCixcvcscdd1C/fn3CwsLw8fExOp6IiEtT0S43NC/6OFYbtKhShuoBxY2OI5Lr1q9fn612LVu2dHISEZGC58svvwTgrrvuwt/fn8DAQHx9fYmPj+e3337Dx8eHnj17Mnz4cCpWrGhwWhER16SiXbKUnJrOwm0nAejTvJKxYUSc5L777rO/s57VKPEmk4mMjIy8jCUiku/Vr1/fPhvHvn37qFWrlsP21NRUoqOjWbhwIY0aNWLGjBk8+uijRkQVEXFpKtolS1/v/IMLKelUKl2E/1Qva3QcEacoWbIkxYsX56mnnuLJJ5+kTJkyRkcSESkQJk6cSFhYGGazmQoVKly33dvbm/vuu4/77ruPcePGcfz48bwPKSKSD2juLsmU1Wpj7sbjADzVrBJubho9WwqmM2fO8M477xAdHU1oaCj9+vVj06ZN+Pn5YTab7R8REcmZNm3aZLtt6dKladiwoRPTiIjkXzm60261Wlm3bh0///zzdQOJhIeHExQU5KycksfWHT7H738mU9zbg0ca6e9VCi4vLy8ef/xxHn/8cWJiYpg7dy4DBgwgNTWV3r1789Zbb+HhoYeSRERyi81mY+3atVy6dIlmzZpRsmRJoyOJiLi0bN1pv3TpEmPHjiUoKIj27dvz/fffk5CQgLu7O0ePHuWNN94gJCSE9u3bs3nzZmdnljwwe+OVad4euzuIYt4qWKRwCA4OZvTo0fz4449Uq1aNiRMnYrFYjI4lIpJvJSQkABAWFkb//v2xWCzcc889hIeH06lTJ2rWrMmePXuMDSki4uKyVbRXq1aNPXv2MGvWLCwWC9HR0Xz99df83//9H9999x0xMTH89ttv3HPPPXTr1o1Zs2Y5O7c40ZG4C/x85E/cTFcejRcpDFJTU1mwYAHh4eHUqVOHMmXK8O2331KqVCmjo4mI5Fuvv/46AF26dGHv3r20bduWjIwMoqOj2bJlCzVr1uS1114zOKWIiGsz2bIaLvkav/76KzVr1szWAdPS0oiJieHOO++87XB5xWKxYDabSUxMxM/Pz+g4hnt16V4WbImhdS1/PunVyOg4Ik61detW5syZw8KFC6lUqRJ9+vThiSeeyFGxXpD7kIJ8bSLifIGBgZw5c4bExEQuXLhAUFAQa9as4b777gOu9MEPPvggsbGxxga9BeofReR2ZbcfydZzz9kt2AE8PT3zVcEujhIuXmbJzj8A6NsixOA0Is7XtGlTgoODeemll+yDIG3YsOG6dg8++GBeRxMRyffOnj1r/7l8+fL4+Pg4jIEUHBzMuXPnjIgmIpJv3PLLyunp6Xz88cf89NNPZGRk0Lx5cyIiIvDx8cnNfJLHvth6kpQ0KzXL+dEkRI8FS+EQExPDmDFjstyuedpFRG6N1Wp1WHZ3d8dk+mdGmmt/FhGRzN1y0f7SSy9x+PBhunTpQlpaGvPmzWP79u188cUXuZlP8lBahpV50ccB6Nu8kv4fqRQK//5CKSIiuS8yMhIfHx/S09OZO3cuZcqUAeDChQsGJxMRcX3ZLtqXLl3Kww8/bF/+4YcfOHToEO7u7sCVuTibNm2a+wklz6zaH8uZxBRKF/WiU71Ao+OIiIhIPhcUFERMTAzTp0/Hzc2NgIAA/vvf/zq0CQ4ONiidiEj+kO2iffbs2Xz++efMmDGDwMBAGjRowHPPPUfXrl1JS0tj1qxZ3H333c7MKk42e8OVad56Nq2Ij6e7wWlEnG/z5s3Z/mXjxYsXOXbsGLVr13ZyKhGRgmPv3r2YzWb27t2rwdpERG5RtqZ8A1i+fDndu3fnvvvu46OPPuKTTz7Bz8+P1157jVGjRhEUFMSCBQucmVWcaNfJBHbGJODpbuKJpvqNtxQOTz75JG3atOGrr74iOTk50zYHDhzg1Vdf5c4772THjh25ct6MjAxGjRpFSEgIvr6+3HnnnYwZM4ZrJ/Ow2WyMHj2acuXK4evrS3h4OEeOHHE4Tnx8PD179sTPz48SJUrQr18/kpKSHNrs2bOHe+65xz7406RJk3LlGkREREQkb+TonfbHH3+cNm3aMGzYMNq0aUNkZCTvv/++s7JJHpqz8cpd9k51AylbXIMJSuFw4MABZs6cyeuvv06PHj2oVq0agYGB+Pj4cP78eQ4ePEhSUhIPP/wwP/zwA6Ghobly3nfeeYeZM2fy+eefU7t2bbZv306fPn0wm8289NJLAEyaNImpU6fy+eefExISwqhRo2jTpg0HDhywD/jZs2dPzpw5Q1RUFGlpafTp04dnnnnG/gtUi8VC69atCQ8PJzIykr1799K3b19KlCjBM888kyvXIiJyI5cuXXJYHjlyJKmpqfZld3d3xowZo4GMRURuIFvztGdm/fr1RERE0LZt23zf2Rb2eTbjLCk0n7iGdKuN5QNaEFrBbHQkkTy3fft2NmzYwIkTJ7h06RJlypShfv36/Oc//7npnO057UM6duyIv78/n332mX1d165d8fX15f/+7/+w2WwEBgbyyiuvMGTIEAASExPx9/dn7ty5dOvWjV9//ZVatWqxbds2GjVqBMDKlStp3749f/zxB4GBgcycOZPXXnuN2NhYvLy8ABgxYgTLli3j4MGD2fpzKez9o4jcnsmTJzN48GB7H1K8eHFq166Nr68vAAcPHmTYsGEMGjTI4KQ5p/5RRG5XdvuRbD8eHxMTw2OPPUZoaCg9e/akatWq7NixgyJFilCvXj2+//77XAkuee+/0SdIt9q4u1JJFexSaDVq1IiBAwcyefJkIiMjGTt2LF27dr1pwX4rmjVrxurVqzl8+DAAu3fvZsOGDbRr1w6AY8eOERsbS3h4uH0fs9lMkyZNiI6OBiA6OpoSJUrYC3aA8PBw3Nzc2LJli71Ny5Yt7QU7XBk09NChQ5w/fz7TbKmpqVgsFoePiMit+uqrr65bt2DBAtauXcvatWt59913+fLLLw1IJiKSf2S7aO/Vqxdubm68++67lC1blmeffRYvLy/eeustli1bxoQJE3jsscecmVWcICUtgwVbYwDo0zzE4DQihcOIESPo1q0bNWrUwNPTk/r16zNw4EB69uwJQGxsLAD+/v4O+/n7+9u3xcbGUrZsWYftHh4elCpVyqFNZse49hz/NmHCBMxms/0TFBR0m1crIoXZ77//7rDs4+ODm9s/Xz8bN27MgQMH8jqWiEi+ku2iffv27YwbN462bdvywQcfsGfPHvu2mjVrsn79eoe7Qrnl1KlTPPHEE5QuXRpfX19CQ0PZvn27fXt2BmuSrP1v1yniky9TvoQvrWv533wHEbltX375JfPnz2fBggXs3LmTzz//nPfee4/PP//c6GiMHDmSxMRE++fkyZNGRxKRfCwxMdFh+dy5c1SqVMm+bLVaHd5xFxGR62W7aG/YsCGjR4/mhx9+YPjw4ZkOyJTbAxudP3+e5s2b4+npyffff8+BAwd4//33KVmypL3N1cGaIiMj2bJlC0WLFqVNmzakpKTkapaCyGazMWfjcQB6N6uIh3u2/zmIyG0YOnSo/W57aGgoTz75JIMGDWLChAkABAQEABAXF+ewX1xcnH1bQEAAZ8+eddienp5OfHy8Q5vMjnHtOf7N29sbPz8/h4+IyK0KDAy84fY9e/ZQoUKFPEojIpI/ZbtKmzdvHqmpqQwaNIhTp07x8ccfOzMXcGWE5aCgIObMmUPjxo0JCQmhdevW3HnnncCVonPKlCm8/vrrPPTQQ9StW5d58+Zx+vRpli1b5vR8+V30b39xMPYCvp7uPN5I07yJ5JWLFy86PB4KV0ZQtlqtAISEhBAQEMDq1avt2y0WC1u2bCEsLAyAsLAwEhISHKahW7NmDVarlSZNmtjbrF+/nrS0NHubqKgoqlev7vDLTxERZ2ndujVApjdTLl26xFtvvUWHDh3yOpaISL6S7aK9YsWKLF68mP379zN//vyb/uY0N3zzzTc0atSIRx99lLJly1K/fn1mzZpl356dwZoyo4GWrpj99132RxpWwFzE09gwIi7E2U/qdOrUiXHjxvHtt99y/Phxli5dygcffMDDDz8MgMlkYuDAgYwdO5ZvvvmGvXv30qtXLwIDA+ncuTNw5bWktm3b0r9/f7Zu3crGjRsZMGAA3bp1s/fPPXr0wMvLi379+rF//34WLVrEhx9+yODBg516fSIiV73yyivAlcE+3333Xf73v//xv//9j0mTJlG9enXOnz/Pq6++anBKERHXlq152pOTkylatGi2D5rT9ln5/fffmTlzJoMHD+bVV19l27ZtvPTSS3h5edG7d+9sDdaUmQkTJvDWW2/ddr787MRfyaw+eOUx2aeaVzI2jIgLsFqtjBs3jsjISOLi4jh8+DCVK1dm1KhRVKpUiX79+uXauT766CNGjRrFCy+8wNmzZwkMDOTZZ59l9OjR9jbDhg0jOTmZZ555hoSEBFq0aMHKlSsdptecP38+AwYMoFWrVri5udG1a1emTp1q3242m/nhhx+IiIigYcOGlClThtGjR2uOdhHJM1cHzKxWrRojRozg6kzDJpOJBx54gBkzZlz3PU5ERBxla572cuXK8fLLL9O7d2/KlSuXaRubzcaPP/7IBx98QMuWLRk5cuRth/Py8qJRo0Zs2rTJvu6ll15i27ZtREdHs2nTJpo3b87p06cdcj322GOYTCYWLVqU6XFTU1MdBj2xWCwEBQUVqnk231q+nzkbj3Nf9TuY26ex0XFEDPf222/z+eef8/bbb9O/f3/27dtH5cqVWbRoEVOmTLnh0zsFea7egnxtIuJ81/Yh6enpHD16FIAqVao4ZUrNvKT+UURuV3b7kWzdaf/pp5949dVXefPNN6lXrx6NGjUiMDAQHx8fzp8/z4EDB4iOjsbDw4ORI0fy7LPP5spFlCtXjlq1ajmsq1mzJl9//TXgOFjTtUV7XFwcd911V5bH9fb2xtvbO1cy5kcXUtL4avsfgKZ5E7lq3rx5fPLJJ7Rq1YrnnnvOvr5evXocPHjQwGQiIgVDqVKlaNxYNwpERHIqW++0V69ena+//prDhw/z2GOPcerUKRYvXsysWbP46aefKF++PLNmzeL48eO88MILuLu750q45s2bc+jQIYd1hw8fpmLFikD2BmuS6321/Q+SUtOpUrYYLauWMTqOiEs4deoUVapUuW691Wp1GMhNRESy57nnnuPUqVPZarto0SLmz5/v5EQiIvlTtu60XxUcHMwrr7xiH1TE2QYNGkSzZs0YP348jz32GFu3buWTTz7hk08+ARwHa6patSohISGMGjXKYbAmcZRhtTF303EAnmpWCZPJZGwgERdRq1Ytfv75Z/svBa9avHgx9evXNyiViEj+dccdd9C0aVMAPv30U+65557rntTcsGEDCxcuJDAw0P79TkREHOWoaM9rd999N0uXLmXkyJG8/fbbhISEMGXKFHr27Glvk53BmuQfaw6eJSb+ImZfT7o0KG90HBGXMXr0aHr37s2pU6ewWq0sWbKEQ4cOMW/ePFasWGF0PBGRfGfMmDH07t2bqlWr8tlnnzF06FCH7cWLFyc8PJxPPvmEtm3bGpRSRMT1ZWsguoKuMA0k0v2TzUT//hfP3luZke1qGh1HxKX8/PPPvP322+zevZukpCQaNGjA6NGj7fMMZ6Ug9yEF+dpExPmu7UMyMjKIiYnh0qVLlClThjvvvDNfP/Gn/lFEbleuDkQnBcOvZyxE//4X7m4meoVVMjqOiMu55557iIqKMjqGiEiBVLJkSUqWLGl0DBGRfCdbA9FJwTBn4zEA2tYOoHwJX4PTiIiIiIiIyM2oaC8k/kpKZdmu0wD0bVHJ2DAiLqhkyZKUKlXquk/p0qUpX7489957L3PmzDE6poiIZNOpU6d44oknKF26NL6+voSGhrJ9+3b7dpvNxujRoylXrhy+vr6Eh4dz5MgRAxOLiGTulor2n3/+mSeeeIKwsDD7VB7//e9/2bBhQ66Gk9yzYEsMl9Ot1K1gpkGwHk0T+bfRo0fj5uZGhw4deOutt3jrrbfo0KEDbm5uREREUK1aNZ5//nlmzZpldFQREbmJ8+fP07x5czw9Pfn+++85cOAA77//vsPj+ZMmTWLq1KlERkayZcsWihYtSps2bUhJSTEwuYjI9XL8TvvXX3/Nk08+Sc+ePfnll19ITU0FIDExkfHjx/Pdd9/leki5PZfTrfx38wkA+jYPydeDvog4y4YNGxg7dizPPfecw/qPP/6YH374ga+//pq6desydepU+vfvb1BKERHJjnfeeYegoCCHJ6RCQkLsP9tsNqZMmcLrr7/OQw89BMC8efPw9/dn2bJldOvWLc8zi4hkJcd32seOHUtkZCSzZs3C09PTvr558+bs3LkzV8NJ7vhu7xnOXkilbHFv2oeWMzqOiEtatWoV4eHh161v1aoVq1atAqB9+/b8/vvveR1NRKRASE9P58cff+Tjjz/mwoULAJw+fZqkpKRcP9c333xDo0aNePTRRylbtiz169d3eFLq2LFjxMbGOvT7ZrOZJk2aEB0dnekxU1NTsVgsDh8RkbyQ46L90KFDtGzZ8rr1ZrOZhISE3MgkuchmszH77wHonmxaES8PDWMgkplSpUqxfPny69YvX76cUqVKAZCcnEzx4sXzOpqISL4XExNDaGgoDz30EBEREZw7dw64ckd8yJAhuX6+33//nZkzZ1K1alVWrVrF888/z0svvcTnn38OQGxsLAD+/v4O+/n7+9u3/duECRMwm832T1BQUK7nFhHJTI4fjw8ICODo0aNUqlTJYf2GDRuoXLlybuWSXLIz5jx7/kjEy8ONHk2CjY4j4rJGjRrF888/z9q1a2ncuDEA27Zt47vvviMyMhKAqKgo7r33XiNjiojkSyNGjKBRo0bs3r2b0qVL29c//PDDTnnlyGq10qhRI8aPHw9A/fr12bdvH5GRkfTu3fuWjjly5EgGDx5sX7ZYLCrcRSRP5Lho79+/Py+//DKzZ8/GZDJx+vRpoqOjGTJkCKNGjXJGRrkNszceB6DzXYGULuZtbBgRF9a/f39q1arFtGnTWLJkCQDVq1dn3bp1NGvWDIBXXnnFyIgiIvnWpk2biI6OxsvLy2F9pUqV7IMa56Zy5cpRq1Yth3U1a9bk66+/Bq7chAKIi4ujXLl/Xh2Mi4vjrrvuyvSY3t7eeHvru5SI5L0cF+0jRozAarXSqlUrLl68SMuWLfH29mbIkCG8+OKLzsgot+hUwiVW7rvyiFef5iE3aS0izZs3p3nz5kbHEBEpcKxWKxkZGdet/+OPP5zy2lHz5s05dOiQw7rDhw9TsWJF4MqgdAEBAaxevdpepFssFrZs2cLzzz+f63lERG5Hjl9wNplMvPbaa8THx7Nv3z42b97MuXPnGDNmjDPyyW2YF32cDKuNsMqlqVnOz+g4IvlGSkqKBhsSEclF999/P1OmTLEvm0wmkpKSeOONN2jfvn2un2/QoEFs3ryZ8ePHc/ToURYsWMAnn3xCRESE/fwDBw5k7NixfPPNN+zdu5devXoRGBhI586dcz2PiMjtyPGd9qu8vLyue+xIXMfFy+ks3HoSgD7NKxkbRiQfuHjxIsOGDePLL7/kr7/+um57ZneIREQke8aNG8cjjzxCrVq1SElJoUePHhw5coQyZcrwxRdf5Pr57r77bpYuXcrIkSN5++23CQkJYcqUKfTs2dPeZtiwYSQnJ/PMM8+QkJBAixYtWLlyJT4+PrmeR0TkduS4aH/44YcznefbZDLh4+NDlSpV6NGjB9WrV8+VgHJrluw8ReKlNIJLFaFVTf+b7yBSyA0dOpS1a9cyc+ZMnnzySaZPn86pU6f4+OOPmThxotHxRETytfLly7N7924WLlzInj17SEpKol+/fvTs2RNfX1+nnLNjx4507Ngxy+0mk4m3336bt99+2ynnFxHJLTku2s1mM8uWLaNEiRI0bNgQgJ07d5KQkEDr1q1ZtGgR77zzDqtXr9a7oQaxWm3M+Xuat97NKuHudv0vWUTE0fLly5k3bx733Xcfffr04Z577qFKlSpUrFiR+fPnO9ydERGRnPPw8OCJJ54wOoaISL5zS1O+9ejRg2nTpuHmduWVeKvVyssvv0zx4sVZuHAhzz33HMOHD2fDhg25Hlhu7uejf/LbuWSKeXvwWKMKRscRyRfi4+Pt01b6+fkRHx8PQIsWLTQokYjIbfruu+8oUqTIdeuvfVIzJESD5oqIZCbHRftnn33Gxo0b7QU7gJubGy+++CLNmjVj/PjxDBgwgHvuuSdXg0r2Xb3L/kjDChT38TQ4jUj+ULlyZY4dO0ZwcDA1atTgyy+/pHHjxixfvpwSJUoYHU9EJF/r0aMHJpMJm83msP7qOpPJRIsWLVi2bBklS5Y0KKWIiGvK8ejx6enpHDx48Lr1Bw8etA/U5OPjk+l77+J8R88m8dOhc5hM8FSzSkbHEck3+vTpw+7du4ErU1tOnz4dHx8fBg0axNChQw1OJyKSvy1btoy7776bqKgoEhMTSUxMJCoqiiZNmrBixQrWr1/PX3/9xZAhQ4yOKiLicnJ8p/3JJ5+kX79+vPrqq9x9990AbNu2jfHjx9OrVy8A1q1bR+3atXM3qWTL55uOA9CqRlkqlSlqbBiRfGTQoEH2n8PDwzl48CA7duygSpUq1K1b18BkIiL534gRI/j0009p1qyZfV2rVq3w8fHhmWeeYf/+/UyZMoW+ffsamFJExDXluGifPHky/v7+TJo0ibi4OAD8/f0ZNGgQw4cPB6B169a0bds2d5PKTSVeTGPxjj8A6Ntc74WJ3I6KFStiNpv1aLyISC44duwYfn5+16338/Pj999/B6Bq1ar8+eefeR1NRMTl5fjxeHd3d1577TXOnDlDQkICCQkJnDlzhldffRV3d3cAgoODqVBBA6DltUXbY7iUlkGNgOKE3Vna6Dgi+co777zDokWL7MuPPfYYpUuXtk9TJCIit+6uu+5i6NChnDt3zr7u3LlzDBs2zP7k5pEjRwgKCjIqooiIy8px0X4tPz+/TH9rKnkvPcPK55tOANCneSWNKSCSQ5GRkfYvi1FRUURFRfH999/Trl07vdMuInKbpk2bxrFjx6hQoQJVqlShSpUqVKhQgePHj/Ppp58CkJSUxOuvv25wUhER15Pjx+MBFi9ezJdffklMTAyXL1922LZz585cCSY5E3UgjlMJlyhV1IuH7ipvdByRfCc2NtZetK9YsYLHHnuM1q1bU6lSJZo0aWJwOhGR/K1q1aocOHCAH374gcOHDwNQvXp1HnjgAfuMRJ07dzYwoYiI68rxnfapU6fSp08f/P39+eWXX2jcuDGlS5fm999/p127ds7IKNkw++9p3no0DsbH093gNCL5T8mSJTl58iQAK1euJDw8HACbzWafGUNERG6dm5sbbdu25aWXXuKll16iTZs2DlMIi4hI5nJ8p33GjBl88skndO/enblz5zJs2DAqV67M6NGjiY+Pd0ZGuYm9fySy7fh5PNxMPBlW0eg4IvlSly5d6NGjB1WrVuWvv/6y/xLyl19+oUqVKganExHJ/5KTk1m3bl2mT2q+9NJLBqUSEXF9OS7aY2Ji7NN1+Pr6cuHCBeDKVHBNmzZl2rRpuZtQbmrO33fZO9Qth7+fj8FpRPKnyZMnU6lSJU6ePMmkSZMoVqwYAGfOnOGFF14wOJ2ISP62e/duHnvsMS5evEhycjKlSpXizz//pEiRIpQtW1ZFu4jIDeS4aA8ICCA+Pp6KFSsSHBzM5s2bqVevHseOHcNmszkjo9zA2QspLN9zGoA+muZN5JZ5enoyZMiQ69ZfO3+7iIjcmldffZVOnToRGRmJ2Wxm8+bNeHp68sQTT/Dyyy8bHU9ExKXluGi///77+eabb6hfvz59+vRh0KBBLF68mO3bt9OlSxdnZJQb+L/NMaRl2GgQXIK7gkoYHUck35o3b94Nt/fq1SuPkoiIFDx79+7l008/xc3NDXd3d1JTU6lcuTKTJk2id+/e+g4pInIDOS7aP/nkE6xWKwARERGULl2aTZs28eCDD/Lss8/mekDJWkpaBgu2XJnmrW8L3WUXuR3/vtOTlpbGxYsX8fLyokiRIiraRURug4eHh33QubJlyxITE0PNmjUxm832QUBFRCRzOS7a3dzcHEb67NatG926dcvVUJI9y3ef5s+ky5Qz+9CmdoDRcUTytfPnz1+37siRIzz//POap11E5DbVrVuXbdu2UbVqVe69915Gjx7Nn3/+yX//+1/q1KljdDwREZeW43k2Vq5cyYYNG+zL06dP56677qJHjx6ZfukV57DZbMzZeByAXmGV8HTXlCkiua1q1apMnDhR71uKiNym0aNHU65cOQDGjRtHyZIlef755zl37hyffPKJwelERFxbjiu9oUOHYrFYgCvvJw0ePJj27dtz7NgxBg8enOsBJXNbjsVz4IwFH083ujcOMjqOSIHl4eHB6dOnjY4hIpKvNWjQgP/85z/AlcfjV65cicViYceOHdSrV8/gdCIiri3Hj8cfO3aMWrVqAfD111/TqVMnxo8fz86dO2nfvn2uB5TMXZ3mrUuDCpQo4mVwGpH875tvvnFYttlsnDlzhmnTptG8eXODUomIFAyXLl3Cw8ODIkWKAHDixAmWLl1KrVq1aN26tcHpRERcW47vtHt5eXHx4kUAfvzxR3tHW6pUKfsdeHGuk/EX+eFAHAB9mlUyNoxIAdG5c2eHT5cuXXjzzTepW7cus2fPzvXznTp1iieeeILSpUvj6+tLaGgo27dvt2+32Wz2x0l9fX0JDw/nyJEjDseIj4+nZ8+e+Pn5UaJECfr160dSUpJDmz179nDPPffg4+NDUFAQkyZNyvVrERG5me7du9tn6UhISKBx48a8//77PPTQQ8ycOdPgdCIiri3HRXuLFi0YPHgwY8aMYevWrXTo0AGAw4cPU6FChVwPKNf7fNNxbDa4p2oZqvoXNzqOSIFgtVodPhkZGcTGxrJgwQL7e5i55fz58zRv3hxPT0++//57Dhw4wPvvv0/JkiXtbSZNmsTUqVOJjIxky5YtFC1alDZt2pCSkmJv07NnT/bv309UVBQrVqxg/fr1PPPMM/btFouF1q1bU7FiRXbs2MG7777Lm2++qfdHRSTP7d69m3vuuQeAxYsXExAQwIkTJ5g3bx5Tp041OJ2IiGvL8ePx06ZN44UXXmDx4sXMnDmT8uXLA/D999/Ttm3bXA8ojpJS01m07crUKH2ba5o3kfzonXfeISgoiDlz5tjXhYT889+zzWZjypQpvP766zz00EPAlXnk/f39WbZsGd26dePXX39l5cqVbNu2jUaNGgHw0Ucf0b59e9577z0CAwOZP38+ly9fZvbs2Xh5eVG7dm127drFBx984FDcXys1NZXU1FT7sp6gEpHccOnSJYoXv3Kj4YcffqBLly64ubnRtGlTTpw4YXA6ERHXluM77cHBwaxYsYLdu3fTr18/+/rJkyfrN6V54Osdf3AhNZ3KZYpyb7U7jI4jIrfgm2++oVGjRjz66KOULVuW+vXrM2vWLPv2Y8eOERsbS3h4uH2d2WymSZMmREdHAxAdHU2JEiXsBTtAeHg4bm5ubNmyxd6mZcuWeHn9M+5FmzZtOHToUJazfUyYMAGz2Wz/BAVpoEsRuX2VK1dm2bJlnDx5klWrVtlfrzx79ix+fn4GpxMRcW05LtpjYmJu+BHnsVptzN10HICnmlfCzc1kbCARuSW///47M2fOpGrVqqxatYrnn3+el156ic8//xyA2NhYAPz9/R328/f3t2+LjY2lbNmyDts9PDwoVaqUQ5vMjnHtOf5t5MiRJCYm2j8nT568zasVEYFhw4YxZMgQKlWqRJMmTQgLCwOu3HWvX7++welERFxbjh+Pr1SpEiZT1sViRkbGbQWSrP10+CzH/kymuI8HXRto/ACR/MpqtdKoUSPGjx8PQP369dm3bx+RkZH07t3b0Gze3t54e3sbmkFECp7OnTvTunVrzpw54zDFW6tWrXj44YcNTCYi4vpyXLT/8ssvDstpaWn88ssvfPDBB4wbNy7Xgsn1Zm84DkC3u4Mo6p3jvzoRcRHlypWzT515Vc2aNfn6668BCAgIACAuLs5hELy4uDjuuusue5uzZ886HCM9PZ34+Hj7/gEBAcTFxTm0ubp8tY2ISF4JCAi4ru9p3LixQWlERPKPHFd+1/529KpGjRoRGBjIu+++S5cuXXIlmDg6HHeBDUf/xM0EvcIqGR1HpMCpVKkSffv25amnniI4ONip52revDmHDh1yWHf48GEqVqwIXBmULiAggNWrV9uLdIvFwpYtW3j++ecBCAsLIyEhgR07dtCwYUMA1qxZg9VqpUmTJvY2r732GmlpaXh6egIQFRVF9erVHUaqFxFxto4dO+LhkfXXzjVr1uRhGhGR/CXH77RnpXr16mzbti23Dif/MmfjMQBa1wogqFQRg9OIFDwDBw5kyZIlVK5cmQceeICFCxc6jKKemwYNGsTmzZsZP348R48eZcGCBXzyySdEREQAYDKZGDhwIGPHjuWbb75h79699OrVi8DAQDp37gxcuTPftm1b+vfvz9atW9m4cSMDBgygW7duBAYGAtCjRw+8vLzo168f+/fvZ9GiRXz44YcMHjzYKdclIpKV0NBQ6tWrZ//UqlWLy5cvs3PnTkJDQ42OJyLi0kw2m82Wkx3+Pf2PzWbjzJkzvPnmmxw8eJBdu3blZr48YbFYMJvNJCYmuuQIpueTL9N0wmpS0618+WwYjUNKGR1JpMDauXMnc+fO5YsvviAjI4MePXrQt29fGjRokOU+t9KHrFixgpEjR3LkyBFCQkIYPHgw/fv3t2+32Wy88cYbfPLJJyQkJNCiRQtmzJhBtWrV7G3i4+MZMGAAy5cvx83Nja5duzJ16lSKFStmb7Nnzx4iIiLYtm0bZcqU4cUXX2T48OHZ/vNw9f5RRFzbzfqQN998k6SkJN577z0D0t0e9Y8icruy24/kuGh3c3O7biA6m81GUFAQCxcutI8Gmp+4eqc7fe1R3l11iNqBfqx4scUNBwIUkdyRlpbGjBkzGD58OGlpaYSGhvLSSy/Rp0+f6/4bdPU+5HYU5GsTEee7WR9y9OhRGjduTHx8vAHpbo/6RxG5XdntR3L8TvvatWsdlt3c3LjjjjuoUqXKDd9VkluTlmHlv9EnAOjbPEQFu4iTpaWlsXTpUubMmUNUVBRNmzalX79+/PHHH7z66qv8+OOPLFiwwOiYIiIFQnR0ND4+PkbHEBFxaTmusu+9915n5JAsfL8vllhLCmWKedOxXrmb7yAit2Tnzp3MmTOHL774Ajc3N3r16sXkyZOpUaOGvc3DDz/M3XffbWBKEZH8qWfPnvYBMeGf1yu3b9/OqFGjDEwmIuL6dGvcxV0dgO6JpsF4e7gbnEak4Lr77rt54IEHmDlzJp07d3b4cnlVSEgI3bp1MyCdiEj+ZjabHfpVNzc3qlevzttvv03r1q0NTCYi4vpUtLuwX2LO80tMAl7ubvRsUtHoOCIFVkZGBrNnz+bBBx+84VRoRYsWZc6cOXmYTESkYJgxY4be+xYRuUW5NuWb5L45G48D0KleIHcU9zY2jEgB5u7uzrPPPktCQoLRUUREREREHKhod1FnEi/x3d4zAPRpXsnYMCKFQJ06dfj999+NjiEiIiIi4iDbj8f/e372q4oWLYq7u961zm3/jT5ButVG45BS1ClvNjqOSIE3duxYhgwZwpgxY2jYsCFFixZ12K7HOkVERETECNku2kuUKJHpdGPu7u6EhIQwZMgQ+vfvn6vhCqtLlzP4YmsMcGWaNxFxvvbt2wPw4IMPOvR1NpsNk8lERkaGUdFEREREpBDLdtH+7/nZr0pISGDHjh0MHToUDw8P+vTpk2vh/m3ixImMHDmSl19+mSlTpgCQkpLCK6+8wsKFC0lNTaVNmzbMmDEDf39/p+VwtmW7TnH+YhoVSvryQK38ex0i+UlWfZyIiNy+AwcO0LRp00y3LVu2jM6dO+dtIBGRfCTbRfuN5md/6KGHqFSpEh999JHTivZt27bx8ccfU7duXYf1gwYN4ttvv+Wrr77CbDYzYMAAunTpwsaNG52Sw9lsNpt9mrenmlXC3e36pxtEJPfdqI8TEZHbc/W7WUiI4xOEX3/9Nb169SI5OdmgZCIiri/XBqK79957OXr0aG4dzkFSUhI9e/Zk1qxZDtMxJSYm8tlnn/HBBx9w//3307BhQ+bMmcOmTZvYvHmzU7I428ajf3E4LokiXu482ijI6DgihUpCQgLvv/8+Tz/9NE8//TSTJ08mMTHR6FgiIvler169CA8PJzY21r5u0aJF9OrVi7lz5xoXTEQkH8i1oj0xMRGz2TkDpkVERNChQwfCw8Md1u/YsYO0tDSH9TVq1CA4OJjo6Ogsj5eamorFYnH4uIqrd9kfbVgBs6+nwWlECo/t27dz5513MnnyZOLj44mPj+eDDz7gzjvvZOfOnUbHExHJ11599VXat29PeHg48fHxLFiwgD59+jBv3jweffRRo+OJiLi0bD8efyNpaWm8++67NGnSJDcO52DhwoXs3LmTbdu2XbctNjYWLy8vSpQo4bDe39/f4Te5/zZhwgTeeuut3I562479mczqg2cB6N2skrFhRAqZQYMG8eCDDzJr1iw8PK50jenp6Tz99NMMHDiQ9evXG5xQRCR/++ijj+jZsydNmzbl1KlTfPHFFzz00ENGxxIRcXnZLtq7dOmS6frExET279+PyWTi559/zrVgACdPnuTll18mKioKHx+fXDvuyJEjGTx4sH3ZYrEQFGT8o+ifbzoOwP01ylL5jmLGhhEpZLZv3+5QsAN4eHgwbNgwGjVqZGAyEZH86ZtvvuHixYsAfPfddxQpUoQuXbrw888/0717d0wmE9988w1wZeYOERHJXLaL9qwefQ8KCqJr16707Nkz1x+P37FjB2fPnqVBgwb2dRkZGaxfv55p06axatUqLl++TEJCgsPd9ri4OAICArI8rre3N97e3rma9XZZUtL4avtJAPo0r2RsGJFCyM/Pj5iYGGrUqOGw/uTJkxQvXtygVCIi+de1I8L36NHDYdvs2bOZPXs2gKbVFBG5iWwX7XPmzHFmjky1atWKvXv3Oqzr06cPNWrUYPjw4QQFBeHp6cnq1avp2rUrAIcOHSImJoawsLA8z3s7vtx2kuTLGVQtW4wWVcoYHUek0Hn88cfp168f7733Hs2aNQNg48aNDB06lO7duxucTkQk/7FarVgsFsxmMwkJCfj5+RkdSUQkX8rRO+2bN29m+fLlXL58mVatWtG2bVtn5QKgePHi1KlTx2Fd0aJFKV26tH19v379GDx4MKVKlcLPz48XX3yRsLCwLOcCdUUZVhtz/340vk/zEEwmTfMmktfee+89TCYTvXr1Ij09HQBPT0+ef/55Jk6caHA6EZGC599PSoqISOayPXr84sWLad68OR9++CGffvopHTp04L333nNmtmyZPHkyHTt2pGvXrrRs2ZKAgACWLFlidKwc+fHXOP44f4kSRTx5uH55o+OIFEpeXl58+OGHnD9/nl27drFr1y7i4+OZPHmyy71OIyKS30yePJlFixbZlx999FFKlSpF+fLl2b17t9PPP3HiREwmEwMHDrSvS0lJISIigtKlS1OsWDG6du1KXFyc07OIiORUtov2CRMm0L9/fxITEzl//jxjx45l/PjxzsyWqZ9++okpU6bYl318fJg+fTrx8fEkJyezZMmSG77P7opmb7gyzVv3xsH4erkbnEakcCtSpAihoaGEhoZSpEgRo+OIiBQIs2fPtg/6GxUVxY8//sjKlStp164dQ4cOdeq5t23bxscff0zdunUd1g8aNIjly5fz1VdfsW7dOk6fPp3lwMsiIkbK9uPxhw4dYtGiRbi7XykqX3nlFUaPHs3Zs2cpW7as0wIWdPtPJ7LlWDzubiZ6hVU0Oo5IoZWSksJHH33E2rVrOXv2LFar1WG75moXEbl1Z8+etRftK1as4LHHHqN169ZUqlTJKVMGX5WUlETPnj2ZNWsWY8eOta9PTEzks88+Y8GCBdx///3AlfGbatasyebNmzN9zTI1NZXU1FT7ssVicVpuEZFrZftO+8WLFx0GEPHy8sLHx4ekpCSnBCss5mw8DkC7OgGUM/saG0akEOvXrx+TJk2iYsWKdOzYkYceesjhIyIit65EiRKcPHlllpyVK1cSHh4OgM1mc+rI8REREXTo0MF+vqt27NhBWlqaw/oaNWoQHBxMdHR0pseaMGECZrPZ/nGF6YJFpHDI0UB0n376KcWK/TN/eHp6OnPnzqVMmX9GO3/ppZdyL10B92dSKt/sOg1A3xYhBqcRKdxWrFjBd999R/PmzY2OIiJS4HTq1IkePXpQtWpV/vrrL9q1awfAL7/8QpUqVZxyzoULF7Jz5062bdt23bbY2Fi8vLyuGwjP39+f2NjYTI83cuRIBg8ebF+2WCwq3EUkT2S7aA8ODmbWrFkO6wICAvjvf/9rXzaZTCrac2D+5hguZ1ipF1SCBsEljY4jUqiVL19e87GLiDjJhAkTqFatGidPnmTSpEn2m0BnzpzhhRdeyPXznTx5kpdffpmoqCh8fHxy5Zje3t4amFREDJHtov348eNOjFH4pKZn8H9bTgDQt3klY8OICO+//z7Dhw8nMjKSihU1voSISG7y9PRkyJAh160fNGiQU863Y8cOzp49S4MGDezrMjIyWL9+PdOmTWPVqlVcvnz5umnn4uLi8t2AxiJS8OXo8XjJPd/uOcO5C6n4+3nTPrSc0XFECr1GjRqRkpJC5cqVKVKkCJ6eng7b4+PjDUomIpI/ffPNN/ZXjr777rsbzsjx4IMP5uq5W7Vqxd69ex3W9enThxo1ajB8+HCCgoLw9PRk9erVdO3aFbgy6HJMTAxhYWG5mkVE5HZlu2hfs2YNAwYMYPPmzQ4D0sGVETibNWvGzJkzadmyZa6HLGhsNhuzN16Z5q1XWCU83bM9HqCIOEn37t05deoU48ePx9/fH5PJZHQkEZF8rXPnzhw5cgSAHj16ZNnOZDLl+mB0xYsXp06dOg7rihYtSunSpe3r+/Xrx+DBgylVqhR+fn68+OKLhIWFZTpyvIiIkbJdtE+ZMoX+/ftfV7ADmM1mnn32WSZPnqyiPRu2nzjPvlMWvD3c6N442Og4IgJs2rSJ6Oho6tWrZ3QUEZECwWq12qdFS0hIyPQ7pJEmT56Mm5sbXbt2JTU1lTZt2jBjxgyjY4mIXCfbRfvu3bt55513stzeunVr3nvvvVwJVdDN+fsu+8P1y1OqqJfBaUQErkz1c+nSJaNjiIiIk/z0008Oyz4+PkyfPp3p06cbE0hEJJuy/Vx2XFzcde94XsvDw4Nz587lSqiC7I/zF1m578pUIk9pADoRlzFx4kReeeUVfvrpJ/766y8sFovDR0REbt1///tfOnbsSJ06dQgNDeXBBx9k3rx52Gw2o6OJiLi8bN9pL1++PPv27ctyLs09e/ZQrpwGVLuZ/0afwGqD5lVKUyPAtR4TEynM2rZtC1wZvOhaNpvNKe9biogUBleL8hdffJF69eoRGhqKzWbj119/5amnnmLJkiUsW7bM2JAiIi4u20V7+/btGTVqFG3btr1uvstLly7xxhtv0LFjx1wPWJBcvJzOF1tjAOjTLMTgNCJyrbVr1xodQUSkwJk/fz5wZST5f39PXLNmDZ07d2bevHn06tXLiHgiIvlCtov2119/nSVLllCtWjUGDBhA9erVATh48CDTp08nIyOD1157zWlBC4Kvd57CkpJOxdJFuL9GWaPjiMg17r33XqMjiIgUOIsXLwbIdKDi+++/nxEjRjB//nwV7SIiN5Dtd9r9/f3ZtGkTderUYeTIkTz88MM8/PDDvPrqq9SpU4cNGzbg7+/vzKz5mtVqsw9A91SzSri5aTopEVfz888/88QTT9CsWTNOnToFXHkPc8OGDQYnExHJn/bv33/D7e3atWP37t15lEZEJH/K0QThFStW5LvvvuPPP/9ky5YtbN68mT///JPvvvuOkBA97n0j64+c4/dzyRT39uDRRkFGxxGRf/n6669p06YNvr6+7Ny5k9TUVAASExMZP368welERPKn8+fP33C7v7//TduIiBR2OSrarypZsiR33303jRs3pmTJkrmdqUCavfE4AI82CqKYd7bfShCRPDJ27FgiIyOZNWuWw0wZzZs3Z+fOnQYmExHJv242iKe7uzvp6el5lEZEJH9S9ZgHjp69wPrD5zCZrjwaLyKu59ChQ5m+c2k2m0lISMj7QCIiBcDV0eN79uyZ6dTBV59qEhGRrN3SnXbJmTl/32V/oKY/waWLGBtGRDIVEBDA0aNHr1u/YcMGKleu7NRzT5w4EZPJxMCBA+3rUlJSiIiIoHTp0hQrVoyuXbsSFxfnsF9MTAwdOnSgSJEilC1blqFDh153x+qnn36iQYMGeHt7U6VKFebOnevUaxERuVaPHj2AK78AzexTtmxZDUInInITutPuZAkXL7Nk55UBrfo013v/Iq6qf//+vPzyy8yePRuTycTp06eJjo5myJAhjBo1ymnn3bZtGx9//DF169Z1WD9o0CC+/fZbvvrqK8xmMwMGDKBLly5s3LgRuPLIaYcOHQgICGDTpk2cOXOGXr164enpaX8H/9ixY3To0IHnnnuO+fPns3r1ap5++mnKlStHmzZtnHZNIiJXzZgxg/nz5zNjxgz8/PyMjiMiki+paHeyhdtOciktg5rl/GhauZTRcUQkCyNGjMBqtdKqVSsuXrxIy5Yt8fb2ZsiQIbz44otOOWdSUhI9e/Zk1qxZjB071r4+MTGRzz77jAULFnD//fcDMGfOHGrWrMnmzZtp2rQpP/zwAwcOHODHH3/E39+fu+66izFjxjB8+HDefPNNvLy8iIyMJCQkhPfffx+AmjVrsmHDBiZPnqyiXURERCSf0OPxTpSeYWXepuMA9GleCZNJ07yJuCqTycRrr71GfHw8+/btY/PmzZw7d44xY8Y47ZwRERF06NCB8PBwh/U7duwgLS3NYX2NGjUIDg4mOjoagOjoaEJDQx2m2mzTpg0Wi8U+xVJ0dPR1x27Tpo39GJlJTU3FYrE4fERERETEOLrT7kSr9sdxOjGF0kW9eLBeoNFxRCQbvLy8qFWrltPPs3DhQnbu3Mm2bduu2xYbG4uXlxclSpRwWO/v709sbKy9zbUF+9XtV7fdqI3FYuHSpUv4+vped+4JEybw1ltv3fJ1iYiIiEjuUtHuRHM2HgOgZ5NgfDzdDU4jIpnp27dvttrNnj0718558uRJXn75ZaKiovDx8cm14+aGkSNHMnjwYPuyxWIhKCjIwEQiIiIihZuKdifZ80cC20+cx9PdxBNNKxodR0SyMHfuXCpWrEj9+vXtUxM5244dOzh79iwNGjSwr8vIyGD9+vVMmzaNVatWcfnyZRISEhzutsfFxREQEABcGe1+69atDse9Orr8tW3+PeJ8XFwcfn5+md5lB/D29sbb2/u2r1FEREREcoeKdie5Os1bx7qBlPVzrTtpIvKP559/ni+++IJjx47Rp08fnnjiCUqVcu6gka1atWLv3r0O6/r06UONGjUYPnw4QUFBeHp6snr1arp27QpcmUc+JiaGsLAwAMLCwhg3bhxnz56lbNmyAERFReHn52d/vD8sLIzvvvvO4TxRUVH2Y4iIiIiI69NAdE4QZ0lhxZ7TAPTVNG8iLm369OmcOXOGYcOGsXz5coKCgnjsscdYtWqV0+68Fy9enDp16jh8ihYtSunSpalTpw5ms5l+/foxePBg1q5dy44dO+jTpw9hYWE0bdoUgNatW1OrVi2efPJJdu/ezapVq3j99deJiIiw3yl/7rnn+P333xk2bBgHDx5kxowZfPnllwwaNMgp1yUiIiIiuU9FuxP83+YTpGXYaFSxJKEVzEbHEZGb8Pb2pnv37kRFRXHgwAFq167NCy+8QKVKlUhKSjIk0+TJk+nYsSNdu3alZcuWBAQEsGTJEvt2d3d3VqxYgbu7O2FhYTzxxBP06tWLt99+294mJCSEb7/9lqioKOrVq8f777/Pp59+quneRERERPIRPR6fy1LSMpi/JQaAvi10l10kv3Fzc8NkMmGz2cjIyMiz8/70008Oyz4+PkyfPp3p06dnuU/FihWve/z93+677z5++eWX3IgoIiIiIgbQnfZc9s2u08QnX6Z8CV9a1/K/+Q4iYrjU1FS++OILHnjgAapVq8bevXuZNm0aMTExFCtWzOh4IiIiIlKI6U57LrLZbMz+e5q3XmEV8XDX70REXN0LL7zAwoULCQoKom/fvnzxxReUKVPG6FgiIiIiIoCK9lwV/ftfHIy9gK+nO93uDjY6johkQ2RkJMHBwVSuXJl169axbt26TNtd+z65iIiIiEheUdGei65O89a1YXnMRTyNDSMi2dKrVy9MJpPRMUREREREMqWiPZec+CuZH3+NA+CpZhqATiS/mDt3rtERRERERESypJeuc8nnm05gs8G91e6gSlkNXCUiIiIiIiK3T0V7LriQksaX208C0Kd5JWPDiIiIiIiISIGhoj0XLN7xB0mp6dx5R1FaVr3D6DgiIiIiIiJSQKhov00ZVhtzNx0H4KnmIbi5aUArERERERERyR0q2m/T2oNnOfHXRfx8POjaoLzRcURERERERKQAUdF+m2ZvPAZA98bBFPHSYPwiIiIiIiKSe1S034aDsRY2/fYX7m4mejWrZHQcERERERERKWBUtN+GORuOA9Cmtj/lS/gaG0ZEREREREQKHBXtt+ivpFSW7joFQN/mIQanERERERERkYJIRfst+mJrDJfTrYSWN9OwYkmj44iIiIiIiEgBpKL9FlxOt/LfzScA6NuiEiaTpnkTERERERGR3Kei/RZ8v+8McZZU7ijuTYfQQKPjiIiIiIiISAGloj2HbDYbszdcmebtyaYV8fLQH6GIiIiIiIg4hyrOHDqTmMJv55LxcnejR5Ngo+OIiIiIiIhIAeZhdID8JrCEL9Ej72fXyQTKFPM2Oo6IiIiI5AObf/+LTb/9BTYbVhvYsGGzYf/57//DarVhA2zXtLHZrqyz2v5evrrdvvz3Ma85ltX2z3Gu/szVttZrjs21x/n3OWwOOa7d5niOq9d05YQOx7nmWJm5dvXfKTNZf217W6bryWn77J4789hZHjerY16/f5abbrDXjfe70Z63fr4bHPOG+93aMW923Ow0uNn+t3v+m+zOZ081otmdZW5ylJxR0X4Livt4ck/VO4yOISIiIiL5xNZj8UxdfcToGCLiZDcr6m+FinYREREREScLrWDmyaYVcTNhn3nIzWTCZAITYDJdWcYEJkx/L//zs8lksrczYfr7OH+vv7bdNce9/hxX9uOaY7lde1z7z1f+183t5ufH/rMpk+u45ljXzLb074mXTFksmMh8n2vbm7I4rmObLM+WveNm2T7ra7rZ+n/vn6P9nHHMrDfdcL8b7ZmdCbayMwdXdmbqyt5xstEmG0e62XHuKJ77T2O7dNE+YcIElixZwsGDB/H19aVZs2a88847VK9e3d4mJSWFV155hYULF5KamkqbNm2YMWMG/v7+BiYXEREREfnHf6qX5T/VyxodQ0TyIZceiG7dunVERESwefNmoqKiSEtLo3Xr1iQnJ9vbDBo0iOXLl/PVV1+xbt06Tp8+TZcuXQxMLSIiIiIiIpI7XPpO+8qVKx2W586dS9myZdmxYwctW7YkMTGRzz77jAULFnD//fcDMGfOHGrWrMnmzZtp2rSpEbFFREREREREcoVL32n/t8TERABKlSoFwI4dO0hLSyM8PNzepkaNGgQHBxMdHZ3lcVJTU7FYLA4fEREREREREVeTb4p2q9XKwIEDad68OXXq1AEgNjYWLy8vSpQo4dDW39+f2NjYLI81YcIEzGaz/RMUFOTM6CIiIiIiIiK3JN8U7REREezbt4+FCxfe9rFGjhxJYmKi/XPy5MlcSCgiIiIirmDChAncfffdFC9enLJly9K5c2cOHTrk0CYlJYWIiAhKly5NsWLF6Nq1K3FxcQYlFhHJWr4o2gcMGMCKFStYu3YtFSpUsK8PCAjg8uXLJCQkOLSPi4sjICAgy+N5e3vj5+fn8BERERGRgkGDGYtIQeLSA9HZbDZefPFFli5dyk8//URISIjD9oYNG+Lp6cnq1avp2rUrAIcOHSImJoawsDAjIouIiIiIwTSYsYgUJC5dtEdERLBgwQL+97//Ubx4cft76mazGV9fX8xmM/369WPw4MGUKlUKPz8/XnzxRcLCwtTZioiIiAiQ88GMM/semZqaSmpqqn1ZAxmLSF5x6cfjZ86cSWJiIvfddx/lypWzfxYtWmRvM3nyZDp27EjXrl1p2bIlAQEBLFmyxMDUIiIiIuIqcmswYw1kLCJGcek77Tab7aZtfHx8mD59OtOnT8+DRCIiIiKSn1wdzHjDhg23dZyRI0cyePBg+7LFYlHhLiJ5wqWLdhERERGRW3V1MOP169dnOZjxtXfbbzSYsbe3N97e3s6OLCJyHZd+PF5EREREJKdsNhsDBgxg6dKlrFmz5oaDGV+lwYxFxFXpTruIiIiIFCgazFhEChIV7SIiIiJSoMycOROA++67z2H9nDlzeOqpp4Argxm7ubnRtWtXUlNTadOmDTNmzMjjpCIiN6fH40VE8tiECRO4++67KV68OGXLlqVz584cOnTIoU1KSgoRERGULl2aYsWK0bVrV+Li4hzaxMTE0KFDB4oUKULZsmUZOnQo6enpDm1++uknGjRogLe3N1WqVGHu3LnOvjwREcPZbLZMP1cLdvhnMOP4+HiSk5NZsmRJlu+zi4gYSUW7iEgeW7duHREREWzevJmoqCjS0tJo3bo1ycnJ9jaDBg1i+fLlfPXVV6xbt47Tp0/TpUsX+/aMjAw6dOjA5cuX2bRpE59//jlz585l9OjR9jbHjh2jQ4cO/Oc//2HXrl0MHDiQp59+mlWrVuXp9YqIiIjIrTPZsjOvWgFnsVgwm80kJibi5+dndBwRyWdutw85d+4cZcuWZd26dbRs2ZLExETuuOMOFixYwCOPPALAwYMHqVmzJtHR0TRt2pTvv/+ejh07cvr0afz9/QGIjIxk+PDhnDt3Di8vL4YPH863337Lvn377Ofq1q0bCQkJrFy5MtMsqamppKamOlxbUFCQ+kcRuSUF+TtWQb42Eckb2e1HdKddRMRgiYmJAJQqVQqAHTt2kJaWRnh4uL1NjRo1CA4OJjo6GoDo6GhCQ0PtBTtAmzZtsFgs7N+/397m2mNcbXP1GJmZMGECZrPZ/tEcxCIiIiLGUtEuImIgq9XKwIEDad68OXXq1AEgNjYWLy8vh7mDAfz9/e0jIMfGxjoU7Fe3X912ozYWi4VLly5lmmfkyJEkJibaPydPnrztaxQRERGRW6fR40VEDBQREcG+ffvYsGGD0VEA8Pb2xtvb2+gYIiIiIvI33WkXETHIgAEDWLFiBWvXrqVChQr29QEBAVy+fJmEhASH9nFxcfaRjQMCAq4bTf7q8s3a+Pn54evrm9uXIyIiIiJOoKJdRCSP2Ww2BgwYwNKlS1mzZg0hISEO2xs2bIinpyerV6+2rzt06BAxMTGEhYUBEBYWxt69ezl79qy9TVRUFH5+ftSqVcve5tpjXG1z9RgiIiIi4vr0eLyISB6LiIhgwYIF/O9//6N48eL2d9DNZjO+vr6YzWb69evH4MGDKVWqFH5+frz44ouEhYXRtGlTAFq3bk2tWrV48sknmTRpErGxsbz++utERETYH29/7rnnmDZtGsOGDaNv376sWbOGL7/8km+//dawaxcRERGRnNGddhGRPDZz5kwSExO57777KFeunP2zaNEie5vJkyfTsWNHunbtSsuWLQkICGDJkiX27e7u7qxYsQJ3d3fCwsJ44okn6NWrF2+//ba9TUhICN9++y1RUVHUq1eP999/n08//ZQ2bdrk6fWKiIiIyK3TPO1onk0RuT0FuQ8pyNcmIs5XkPuQgnxtIpI3NE+7iIiIiIiISD6nol1ERERERETERaloFxEREREREXFRKtpFREREREREXJSKdhEREREREREXpaJdRERERERExEWpaBcRERERERFxUSraRURERERERFyUinYRERERERERF+VhdAAREZH8wmq1cTnDeuWT/s8nNd1KWoYVm+2ftjZsDvvaHBf/tfVqG9sN2/z7GP9ucbNzXL9/zs/57+vK9EJukxMOmem139bxnJIy/2h+Zxnc3ExGxxARKRRUtIuIiMtK/1eBnJr+r4L5RtvSMxy3Z1hJTbu+4P53m8z2vdouLaNwF2oiVx0a2xZvN3ejY4iIFAoq2kVEJNf8b9cpjv95kcsZGQ7FbmoWRXJmRXdq2j8Fs9XFa2RPdxNe7m54eVz5uJkc7zz++z6kyXTjO5P/3nztsulfR7uu7U3Odd2Zc7D/9dv+vW/u33G9yR+VS7jZ32dB5oy/cxERyZyKdhERyTWLd/zBz0f+dMqxTSbsBbK3h5tDsezlsOyOl/uVNt6Zbv9n2XG7+3VtvW+wr5e7mx4PFhEREadT0S4iIrnmvuplqVCyiEOx61AYZ1oQZ69Y9nAzFeo7myIiIlI4qWgXEZFc069FiNERRERERAoUTfkmIiIiIiIi4qJUtIuIiIiIiIi4KBXtIiIiIiIiIi5KRbuIiIiIiIiIi1LRLiIiIiIiIuKiVLSLiIiIiIiIuCgV7SIiIiIiIiIuSkW7iIiIiIiIiItS0S4iIiIiIiLiolS0i4iIiIiIiLgoFe0iIiIiIiIiLkpFu4iIiIiIiIiLUtEuIiIiIiIi4qJUtIuIiIiIiIi4KBXtIiIiIiIiIi5KRbuIiIiIiIiIi1LRLiIiIiIiIuKiVLSLiIiIiIiIuCgV7SIiIiIiIiIuSkW7iIiIiIiIiItS0S4iIiIiIiLiogpM0T59+nQqVaqEj48PTZo0YevWrUZHEhFxCeofRUSypj5SRFxdgSjaFy1axODBg3njjTfYuXMn9erVo02bNpw9e9boaCIihlL/KCKSNfWRIpIfFIii/YMPPqB///706dOHWrVqERkZSZEiRZg9e7bR0UREDKX+UUQka+ojRSQ/8DA6wO26fPkyO3bsYOTIkfZ1bm5uhIeHEx0dnek+qamppKam2pcTExMBsFgszg0rIgXS1b7DZrMZnMSR+kcRMZqr9o+Q8z5S/aOI5Lbs9pH5vmj/888/ycjIwN/f32G9v78/Bw8ezHSfCRMm8NZbb123PigoyCkZRaRwuHDhAmaz2egYduofRcRVuFr/CDnvI9U/ioiz3KyPzPdF+60YOXIkgwcPti9brVbi4+MpXbo0JpPppvtbLBaCgoI4efIkfn5+zozqUnTduu7C4Fau22azceHCBQIDA52czvnUP94aXXfhum4ovNee0+tW/+hI/2503YWBrjv3v0Pm+6K9TJkyuLu7ExcX57A+Li6OgICATPfx9vbG29vbYV2JEiVyfG4/P79C9Q/xKl134aLrzh5Xu4ME6h+NoOsufArrtefkul2xf4Sc95G51T+C/t0UNrruwsUZ3yHz/UB0Xl5eNGzYkNWrV9vXWa1WVq9eTVhYmIHJRESMpf5RRCRr6iNFJL/I93faAQYPHkzv3r1p1KgRjRs3ZsqUKSQnJ9OnTx+jo4mIGEr9o4hI1tRHikh+UCCK9scff5xz584xevRoYmNjueuuu1i5cuV1A4vkFm9vb954443rHpEq6HTduu7CoKBdt/rHvKHrLlzXDYX32gvadauPzBu6bl13YeDM6zbZXHEODhERERERERHJ/++0i4iIiIiIiBRUKtpFREREREREXJSKdhEREREREREXpaJdRERERERExEWpaL8F06dPp1KlSvj4+NCkSRO2bt1qdCSnWr9+PZ06dSIwMBCTycSyZcuMjpQnJkyYwN13303x4sUpW7YsnTt35tChQ0bHcrqZM2dSt25d/Pz88PPzIywsjO+//97oWHlu4sSJmEwmBg4caHSUfEX94zKjI+UJ9Y/qH9U/5lxh6x+hcPaR6h/VPzqjf1TRnkOLFi1i8ODBvPHGG+zcuZN69erRpk0bzp49a3Q0p0lOTqZevXpMnz7d6Ch5at26dURERLB582aioqJIS0ujdevWJCcnGx3NqSpUqMDEiRPZsWMH27dv5/777+ehhx5i//79RkfLM9u2bePjjz+mbt26RkfJV9Q/Fh7qH9U/qn/MmcLYP0Lh7CPVP6p/dEr/aJMcady4sS0iIsK+nJGRYQsMDLRNmDDBwFR5B7AtXbrU6BiGOHv2rA2wrVu3zugoea5kyZK2Tz/91OgYeeLChQu2qlWr2qKiomz33nuv7eWXXzY6Ur6h/lH9o/rHgk39460r7P2jzVZ4+0j1j+ofc4PutOfA5cuX2bFjB+Hh4fZ1bm5uhIeHEx0dbWAyyQuJiYkAlCpVyuAkeScjI4OFCxeSnJxMWFiY0XHyREREBB06dHD471xuTv1j4ab+Uf2jZE39Y+Gm/lH9Y27wcMpRC6g///yTjIwM/P39Hdb7+/tz8OBBg1JJXrBarQwcOJDmzZtTp04do+M43d69ewkLCyMlJYVixYqxdOlSatWqZXQsp1u4cCE7d+5k27ZtRkfJd9Q/Fl7qH9U/yo2pfyy81D+qf8wtKtpFsiEiIoJ9+/axYcMGo6PkierVq7Nr1y4SExNZvHgxvXv3Zt26dQW64z158iQvv/wyUVFR+Pj4GB1HJN9Q/6j+UUQyp/5R/WNuUdGeA2XKlMHd3Z24uDiH9XFxcQQEBBiUSpxtwIABrFixgvXr11OhQgWj4+QJLy8vqlSpAkDDhg3Ztm0bH374IR9//LHByZxnx44dnD17lgYNGtjXZWRksH79eqZNm0Zqairu7u4GJnRt6h8LJ/WP6h/VP96c+sfCSf2j+sfc7B/1TnsOeHl50bBhQ1avXm1fZ7VaWb16daF5X6MwsdlsDBgwgKVLl7JmzRpCQkKMjmQYq9VKamqq0TGcqlWrVuzdu5ddu3bZP40aNaJnz57s2rVLX0hvQv1j4aL+8R/qH9U/3oz6x8JF/eM/1D/mXv+oO+05NHjwYHr37k2jRo1o3LgxU6ZMITk5mT59+hgdzWmSkpI4evSoffnYsWPs2rWLUqVKERwcbGAy54qIiGDBggX873//o3jx4sTGxgJgNpvx9fU1OJ3zjBw5knbt2hEcHMyFCxdYsGABP/30E6tWrTI6mlMVL178uvfNihYtSunSpQvFe2i5Qf2j+kf1jwWT+sfbVxj7RyicfaT6R/WPTukfc3Us+kLio48+sgUHB9u8vLxsjRs3tm3evNnoSE61du1aG3Ddp3fv3kZHc6rMrhmwzZkzx+hoTtW3b19bxYoVbV5eXrY77rjD1qpVK9sPP/xgdCxDaEqjnFP/qP6xIFP/+A/1jzlX2PpHm61w9pHqH9U/OqN/NNlsNlvu/QpARERERERERHKL3mkXERERERERcVEq2kVERERERERclIp2ERERERERERelol1ERERERETERaloFxEREREREXFRKtpFREREREREXJSKdhEREREREREXpaJdRERERERExEWpaJcC66mnnqJz586Gnf/JJ59k/Pjx2WrbrVs33n//fScnEhG5Qv2jiEjW1EeKqzHZbDab0SFEcspkMt1w+xtvvMGgQYOw2WyUKFEib0JdY/fu3dx///2cOHGCYsWK3bT9vn37aNmyJceOHcNsNudBQhEpqNQ/iohkTX2k5Ecq2iVfio2Ntf+8aNEiRo8ezaFDh+zrihUrlq2OzlmefvppPDw8iIyMzPY+d999N0899RQRERFOTCYiBZ36RxGRrKmPlPxIj8dLvhQQEGD/mM1mTCaTw7pixYpd92jTfffdx4svvsjAgQMpWbIk/v7+zJo1i+TkZPr06UPx4sWpUqUK33//vcO59u3bR7t27ShWrBj+/v48+eST/Pnnn1lmy8jIYPHixXTq1Mlh/YwZM6hatSo+Pj74+/vzyCOPOGzv1KkTCxcuvP0/HBEp1NQ/iohkTX2k5Ecq2qVQ+fzzzylTpgxbt27lxRdf5Pnnn+fRRx+lWbNm7Ny5k9atW/Pkk09y8eJFABISErj//vupX78+27dvZ+XKlcTFxfHYY49leY49e/aQmJhIo0aN7Ou2b9/OSy+9xNtvv82hQ4dYuXIlLVu2dNivcePGbN26ldTUVOdcvIjIDah/FBHJmvpIMZRNJJ+bM2eOzWw2X7e+d+/etoceesi+fO+999patGhhX05PT7cVLVrU9uSTT9rXnTlzxgbYoqOjbTabzTZmzBhb69atHY578uRJG2A7dOhQpnmWLl1qc3d3t1mtVvu6r7/+2ubn52ezWCxZXsfu3bttgO348eM3vF4RkexS/ygikjX1kZJf6E67FCp169a1/+zu7k7p0qUJDQ21r/P39wfg7NmzwJXBQNauXWt/v6lYsWLUqFEDgN9++y3Tc1y6dAlvb2+HgU4eeOABKlasSOXKlXnyySeZP3++/TexV/n6+gJct15EJC+ofxQRyZr6SDGSinYpVDw9PR2WTSaTw7qrnaTVagUgKSmJTp06sWvXLofPkSNHrns06aoyZcpw8eJFLl++bF9XvHhxdu7cyRdffEG5cuUYPXo09erVIyEhwd4mPj4egDvuuCNXrlVEJCfUP4qIZE19pBhJRbvIDTRo0ID9+/dTqVIlqlSp4vApWrRopvvcddddABw4cMBhvYeHB+Hh4UyaNIk9e/Zw/Phx1qxZY9++b98+KlSoQJkyZZx2PSIiuUX9o4hI1tRHSm5S0S5yAxEREcTHx9O9e3e2bdvGb7/9xqpVq+jTpw8ZGRmZ7nPHHXfQoEEDNmzYYF+3YsUKpk6dyq5duzhx4gTz5s3DarVSvXp1e5uff/6Z1q1bO/2aRERyg/pHEZGsqY+U3KSiXeQGAgMD2bhxIxkZGbRu3ZrQ0FAGDhxIiRIlcHPL+j+fp59+mvnz59uXS5QowZIlS7j//vupWbMmkZGRfPHFF9SuXRuAlJQUli1bRv/+/Z1+TSIiuUH9o4hI1tRHSm4y2Ww2m9EhRAqaS5cuUb16dRYtWkRYWNhN28+cOZOlS5fyww8/5EE6ERHjqH8UEcma+kjJjO60iziBr68v8+bN488//8xWe09PTz766CMnpxIRMZ76RxGRrKmPlMzoTruIiIiIiIiIi9KddhEREREREREXpaJdRERERERExEWpaBcRERERERFxUSraRURERERERFyUinYRERERERERF6WiXURERERERMRFqWgXERERERERcVEq2kVERERERERclIp2ERERERERERf1/7wYncgV2iCHAAAAAElFTkSuQmCC\n" + "image/png": 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\n" }, "metadata": {} }, @@ -595,12 +695,13 @@ "name": "stdout", "text": [ "Copying files from IDC buckets..\n", - "Done in 0.626405 seconds.\n", - "Chris Rorden's dcm2niiX version v1.0.20181125 (JP2:OpenJPEG) GCC9.3.0 (64-bit Linux)\n", + "Done in 1.5122 seconds.\n", + "Chris Rorden's dcm2niiX version v1.0.20211006 (JP2:OpenJPEG) GCC11.2.0 x86-64 (64-bit Linux)\n", "Found 122 DICOM file(s)\n", - "Convert 122 DICOM as //content/dcm2niix/1.2.840.113654.2.55.14382674871619950799472325766084940706/1.2.840.113654.2.55.14382674871619950799472325766084940706_0_OPA_GE_LSQX_STANDARD_350_2.5_120_na_na_na_19990102000000_2 (512x512x122x1)\n", - "compress: \"/usr/bin/pigz\" -n -f -6 \"//content/dcm2niix/1.2.840.113654.2.55.14382674871619950799472325766084940706/1.2.840.113654.2.55.14382674871619950799472325766084940706_0_OPA_GE_LSQX_STANDARD_350_2.5_120_na_na_na_19990102000000_2.nii\"\n", - "Conversion required 4.526357 seconds (0.258052 for core code).\n" + "Convert 122 DICOM as /content/dcm2niix/1.2.840.113654.2.55.14382674871619950799472325766084940706/1.2.840.113654.2.55.14382674871619950799472325766084940706_0,OPA,GE,LSQX,STANDARD,350,2.5,120,na,na,na_19990102000000_2 (512x512x122x1)\n", + "Compress: \"/usr/bin/pigz\" -b 960 -n -f -6 \"/content/dcm2niix/1.2.840.113654.2.55.14382674871619950799472325766084940706/1.2.840.113654.2.55.14382674871619950799472325766084940706_0,OPA,GE,LSQX,STANDARD,350,2.5,120,na,na,na_19990102000000_2.nii\"\n", + "Conversion required 3.423908 seconds (0.250755 for core code).\n", + "\n" ] }, { @@ -609,7 +710,7 @@ "text/plain": [ "
" ], - "image/png": 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\n" + "image/png": 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\n" }, "metadata": {} }, @@ -618,12 +719,13 @@ "name": "stdout", "text": [ "Copying files from IDC buckets..\n", - "Done in 0.624464 seconds.\n", - "Chris Rorden's dcm2niiX version v1.0.20181125 (JP2:OpenJPEG) GCC9.3.0 (64-bit Linux)\n", + "Done in 1.61606 seconds.\n", + "Chris Rorden's dcm2niiX version v1.0.20211006 (JP2:OpenJPEG) GCC11.2.0 x86-64 (64-bit Linux)\n", "Found 139 DICOM file(s)\n", - "Convert 139 DICOM as //content/dcm2niix/1.2.840.113654.2.55.146601594654322994982630019583270053397/1.2.840.113654.2.55.146601594654322994982630019583270053397_1_OPA_GE_LSQX_STANDARD_360_2.5_140_40_0_1.5_20000102000000_2 (512x512x139x1)\n", - "compress: \"/usr/bin/pigz\" -n -f -6 \"//content/dcm2niix/1.2.840.113654.2.55.146601594654322994982630019583270053397/1.2.840.113654.2.55.146601594654322994982630019583270053397_1_OPA_GE_LSQX_STANDARD_360_2.5_140_40_0_1.5_20000102000000_2.nii\"\n", - "Conversion required 4.197984 seconds (0.253758 for core code).\n" + "Convert 139 DICOM as /content/dcm2niix/1.2.840.113654.2.55.146601594654322994982630019583270053397/1.2.840.113654.2.55.146601594654322994982630019583270053397_1,OPA,GE,LSQX,STANDARD,360,2.5,140,40,0,1.5_20000102000000_2 (512x512x139x1)\n", + "Compress: \"/usr/bin/pigz\" -b 960 -n -f -6 \"/content/dcm2niix/1.2.840.113654.2.55.146601594654322994982630019583270053397/1.2.840.113654.2.55.146601594654322994982630019583270053397_1,OPA,GE,LSQX,STANDARD,360,2.5,140,40,0,1.5_20000102000000_2.nii\"\n", + "Conversion required 4.696904 seconds (0.252671 for core code).\n", + "\n" ] }, { @@ -632,7 +734,7 @@ "text/plain": [ "
" ], - "image/png": 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aunRp5s+ff8M+9erV4+eff75hn0cffZRHH330pscTEREREeeke9rFMEf/SmXBr5dXph7ZvgYmk8ngRCIiIiIiIs5FRbsY5r2V+7lktdGm+h00q1zm5h8QEREREREpYlS0iyF2n0hm6c5TmEwwIqKG0XFERERERESckop2McQ7y/cB8HD9IGoFafEWERERERGR7KholwK34dBf/HzwLzzdTQx7oLrRcURERERERJyWinYpUDabzX6WvWfTEELKFDM4kYiIiIiIiPNS0S4FavnueHb8mUwxL3cG3l/V6DgiIiIiIiJOTUW7FJhLmVbeXbkfgKdaVeaOkt4GJxIREREREXFuKtqlwHy19U8On0mldHEv+rcKNTqOiIiIiIiI01PRLgXiwsVMpvx4AICB91WhpI+nwYlEREREREScn4p2KRBzNhwlwZLOnf6+RDYPMTqOiIiIiIiIS1DRLvku+XwGM386BMCwB6rh7eFucCIRERERERHXoKJd8t3MtX9gSbtE9YCSdGlwp9FxREREREREXIaKdslX8clpzP7lCAAj2lfH3c1kcCIRERERERHXoaJd8tUHqw6QfslK44qluL9GOaPjiIiIiIiIuBQV7ZJv/jiTwpdb/gTgpQ41MJl0ll1ERERERCQ3VLRLvpm0cj+ZVhvhNcvRuFJpo+OIiIiIiIi4HBXtki92HE9i2a54TCZ4MaKG0XFERERERERckop2yXM2m413lu8D4JEGd1I9sKTBiURERERERFyTinbJc+sP/cWGP/7Gy92NYQ9UMzqOiIiIiIiIy1LRLnnKav3nLPsTzStSoVQxgxOJiIiIiIi4LhXtkqe+33WK3ScslPD2IOq+u4yOIyIiIiIi4tJUtEueyci0MmnlfgD6t6pMmRLeBicSERERERFxbSraJc8s3Hyco3+fp2wJL55qFWp0HBEREREREZenol3yxPmLl/hg1UEABt1fleLeHgYnEhERERERcX0q2iVPzP7lKGfOpRNc2pfHm4YYHUdERERERKRQUNEut+1s6kWif/oDgBceqI6Xh/61EhERERERyQuqruS2zVz7B+fSL1GzvB8P1Q8yOo6IiIiIiEih4dRFe2ZmJqNHjyY0NBRfX1/uuusuxo4di81ms/ex2WyMGTOG8uXL4+vrS3h4OAcPHjQwddFyMukCczYcBWBE++q4uZmMDSQiIiIiIlKIOHXR/s477zBz5kymTZvG77//zjvvvMPEiRP58MMP7X0mTpzI1KlTiY6OZtOmTRQvXpyIiAjS0tIMTF50TPnxABcvWWkWWpo21e4wOo6IiIiIiEih4tRLfG/YsIGHH36YTp06AVCpUiW++OILfv31V+DyWfYpU6bw6quv8vDDDwMwd+5cAgICWLJkCT169Mh2v+np6aSnp9vfWyyWfB5J4XQw4Rxfb/0TgJEdamAy6Sy7iIiIiIhIXnLqM+0tWrRg1apVHDhwAIAdO3awfv16OnToAMCRI0eIj48nPDzc/hmz2UyzZs2IjY297n4nTJiA2Wy2v4KDg/N3IIXUeyv3Y7VBu1oBNAwpZXQcERERERGRQsepz7S/9NJLWCwWatSogbu7O5mZmYwfP57IyEgA4uPjAQgICHD4XEBAgH1bdkaNGsWwYcPs7y0Wiwr3XNoWd5YVexJwM12+l11ERERERETynlMX7V9++SXz5s1j/vz51K5dm+3btzNkyBCCgoLo06fPLe/X29sbb2/vPExatNhsNt75YR8A/2pUgSrlShqcSEREREREpHBy6qL9xRdf5KWXXrLfm163bl2OHTvGhAkT6NOnD4GBgQAkJCRQvnx5++cSEhK4++67jYhcJPx04AybjiTi5eHGkPBqRscREREREREptJz6nvbz58/j5uYY0d3dHavVCkBoaCiBgYGsWrXKvt1isbBp0ybCwsIKNGtRYbXamLh8PwB9wioS5O9rcCIREREREZHCy6nPtHfu3Jnx48cTEhJC7dq1+e2333j//fd58sknATCZTAwZMoRx48ZRtWpVQkNDGT16NEFBQXTp0sXY8IXUdztP8vspCyW9PXiuTRWj44iIiIiIiBRqTn2m/cMPP+Rf//oXzz33HDVr1mT48OE8/fTTjB071t5nxIgRDBo0iAEDBtCkSRNSUlJYvnw5Pj4+BiYvnC5esjJp5eWV/J9pcxelinsZnEjEOa1bt47OnTsTFBSEyWRiyZIlDtttNhtjxoyhfPny+Pr6Eh4ezsGDBx36JCYmEhkZiZ+fH/7+/vTr14+UlBSHPjt37qRVq1b4+PgQHBzMxIkTr8ny1VdfUaNGDXx8fKhbty7Lli3L8/GKiIiISP5x6qK9ZMmSTJkyhWPHjnHhwgX++OMPxo0bh5fXP8WiyWTizTffJD4+nrS0NH788UeqVdN91vnhi1/jiEs8zx0lvenbspLRcUScVmpqKvXr12f69OnZbp84cSJTp04lOjqaTZs2Ubx4cSIiIkhLS7P3iYyMZM+ePcTExLB06VLWrVvHgAED7NstFgvt2rWjYsWKbN26lXfffZfXX3+djz/+2N5nw4YNPP744/Tr14/ffvuNLl260KVLF3bv3p1/gxcRERGRPGWy2Ww2o0MYzWKxYDabSU5Oxs/Pz+g4Tik1/RL3vruGv1IuMrZLHXo1r2h0JBGncaM5xGQysXjxYvstOzabjaCgIF544QWGDx8OQHJyMgEBAcyZM4cePXrw+++/U6tWLTZv3kzjxo0BWL58OR07duTPP/8kKCiImTNn8sorrxAfH2//IfOll15iyZIl7Nt3+ekOjz32GKmpqSxdutSep3nz5tx9991ER0ff9thERG6mMM8hhXlsIlIwcjqPOPWZdnEen64/wl8pF6lUphg9muiZ9iK36siRI8THxxMeHm5vM5vNNGvWjNjYWABiY2Px9/e3F+wA4eHhuLm5sWnTJnuf1q1bO1x5FBERwf79+zl79qy9z5XHyeqTdZzspKenY7FYHF4iIiIiYhwV7XJTf6ek8/G6wwC80K46nu7610bkVsXHxwMQEBDg0B4QEGDfFh8fT7ly5Ry2e3h4ULp0aYc+2e3jymNcr0/W9uxMmDABs9lsfwUH60c6ERERESOp+pKbmr7mD1LSL1HnTj861S1vdBwRyUejRo0iOTnZ/jp+/LjRkURERESKNBXtckN/nj3P/208BsCIiBq4uZkMTiTi2gIDAwFISEhwaE9ISLBvCwwM5PTp0w7bL126RGJiokOf7PZx5TGu1ydre3a8vb3x8/NzeImIiIiIcVS0yw1NjjnIxUwrLe4qQ6uqZY2OI+LyQkNDCQwMZNWqVfY2i8XCpk2bCAsLAyAsLIykpCS2bt1q77N69WqsVivNmjWz91m3bh0ZGRn2PjExMVSvXp1SpUrZ+1x5nKw+WccREREREeenol2ua3/8ORb99icAI9vXwGTSWXaRnEhJSWH79u1s374duLz43Pbt24mLi8NkMjFkyBDGjRvHt99+y65du+jduzdBQUH2FeZr1qxJ+/bt6d+/P7/++iu//PILAwcOpEePHgQFBQHQs2dPvLy86NevH3v27GHhwoV88MEHDBs2zJ7j+eefZ/ny5UyaNIl9+/bx+uuvs2XLFgYOHFjQfyUiIgUqMzOT0aNHExoaiq+vL3fddRdjx47lyocm2Ww2xowZQ/ny5fH19SU8PJyDBw8amFpEJHseRgcQ5/Xuin3YbNCxbiD1g/2NjiPiMrZs2cJ9991nf59VSPfp04c5c+YwYsQIUlNTGTBgAElJSdxzzz0sX74cHx8f+2fmzZvHwIEDadu2LW5ubnTr1o2pU6fat5vNZlauXElUVBSNGjWibNmyjBkzxuFZ7i1atGD+/Pm8+uqrvPzyy1StWpUlS5ZQp06dAvhbEBExzjvvvMPMmTP5/PPPqV27Nlu2bKFv376YzWYGDx4MwMSJE5k6dSqff/45oaGhjB49moiICPbu3eswH4uIGE3PaUfP2czO5qOJPBodi7ubiZVDW3PXHSWMjiTitArzHFKYxyYi+c+oOeTBBx8kICCATz/91N7WrVs3fH19+b//+z9sNhtBQUG88MILDB8+HIDk5GQCAgKYM2cOPXr0uOkxND+KyO3Sc9rlltlsNt75YR8A3RtXUMEuIiIiLqVFixasWrWKAwcOALBjxw7Wr19Phw4dgMu3LcXHxxMeHm7/jNlsplmzZsTGxma7z/T0dCwWi8NLRKQg6PJ4ucbqfafZcuws3h5uPN+2mtFxRERERHLlpZdewmKxUKNGDdzd3cnMzGT8+PFERkYCEB8fD0BAQIDD5wICAuzbrjZhwgTeeOON/A0uIpINnWkXB5lWGxOX7wegb8tQAs26p0tERERcy5dffsm8efOYP38+27Zt4/PPP+e9997j888/v+V9jho1iuTkZPvr+PHjeZhYROT6dKZdHCz57QT7E87h5+PBs/feZXQcERERkVx78cUXeemll+z3ptetW5djx44xYcIE+vTpQ2BgIAAJCQmUL1/e/rmEhATuvvvubPfp7e2Nt7d3vmcXEbmazrSLXfqlTN6PuXzv17NtqmAu5mlwIhEREZHcO3/+PG5ujl9z3d3dsVqtAISGhhIYGMiqVavs2y0WC5s2bSIsLKxAs4qI3IzOtIvdvI1xnEi6QICfN/9uUcnoOCIiIiK3pHPnzowfP56QkBBq167Nb7/9xvvvv8+TTz4JgMlkYsiQIYwbN46qVavaH/kWFBREly5djA0vInIVFe0CwLm0DKatOQTAkPBq+Hq5G5xIRERE5NZ8+OGHjB49mueee47Tp08TFBTE008/zZgxY+x9RowYQWpqKgMGDCApKYl77rmH5cuX6xntIuJ09Jx29JxNgPdjDjB11UEqly3OyqGt8XDXnRMiOVWY55DCPDYRyX+FeQ4pzGMTkYKR03lEZ9qFv1LS+eTnwwAMj6iugl2KpPT0dDZt2sSxY8c4f/48d9xxBw0aNCA0NNToaCIiIiJShKloF6atPsT5i5nUr2CmQ51Ao+OIFKhffvmFDz74gO+++46MjAzMZjO+vr4kJiaSnp5O5cqVGTBgAM888wwlS5Y0Oq6IiIiIFDE6pVrExf19nnmbjgEwsn0NTCaTwYlECs5DDz3EY489RqVKlVi5ciXnzp3j77//5s8//+T8+fMcPHiQV199lVWrVlGtWjViYmKMjiwiIiIiRYzOtBdx78fsJyPTRquqZWlRpazRcUQKVKdOnfjmm2/w9Mz+8YaVK1emcuXK9OnTh71793Lq1KkCTigiIiIiRZ2K9iJs70kL/91xErh8ll2kqHn66adz3LdWrVrUqlUrH9OIiIiIiFxLl8cXYe+u2IfNBg/WK0+dO81GxxFxKocPH2bPnj1YrVajo4iIiIhIEaaivYj6+eAZ1uw/g4ebieHtqhsdR8QwGRkZvPbaa3Tu3Jnx48eTmZnJ448/TtWqValXrx516tTh6NGjRscUERERkSJKRXsRdOFiJq8s3g1Ar7CKVCpb3OBEIsZ56aWXmDlzJoGBgXz22Wd07dqV3377jfnz57NgwQI8PDx45ZVXjI4pIiIiIkWU7mkvgj5YdZC4xPOUN/vwgs6ySxH39ddfM2fOHDp27MiBAweoUaMG33//PR06dACgXLlyREZGGpxSRERERIoqnWkvYn4/ZWHWz4cBGPtwHUp463cbKdpOnjxJ/fr1AahWrRre3t5UqVLFvr1atWrEx8cbFU9EREREijgV7UVIptXGS4t2kWm10aFOIOG1AoyOJGK4zMxMh0e+eXh44O7ubn/v5uaGzWYzIpqIiIiIiC6PL0r+b+MxdhxPoqS3B68/VNvoOCJOY8WKFZjNl5+gYLVaWbVqFbt3X173ISkpycBkIiIiIlLUqWgvIk4lX2Di8n0AjOhQgwA/H4MTiTiPPn36OLy/+vntJpOpIOOIiIiIiNipaC8iXvvvHlIvZtIwxJ/IpiFGxxFxGnoOu4iIiIg4MxXtRcDy3fGs3JuAh5uJCV3r4eams4YiIiJScI4ePcr27ds5duwY58+f54477qBBgwaEhYXh46Or/0REbkRFeyF3Li2D17/dA8DT91amemBJgxOJOJd169blqF/r1q3zOYmISOHz5ZdfAnD33XcTEBBAUFAQvr6+JCYm8scff+Dj40NkZCQjR46kYsWKBqcVEXFOKtoLufdW7CfekkalMsUYdH9Vo+OIOJ02bdrY71m/3irxJpOJzMzMgowlIuLyGjRoYH8ax+7du6lVq5bD9vT0dGJjY1mwYAGNGzdmxowZPProo0ZEFRFxairaC7FtcWeZu/EYAOMfqYuPp/tNPiFS9JQqVYqSJUvy73//m169elG2bFmjI4mIFApvv/02YWFhmM1mKlSocM12b29v2rRpQ5s2bRg/fjxHjx4t+JAiIi5Az2kvpDIyrby8aBc2G3RrWIGWVVSIiGTn1KlTvPPOO8TGxlK3bl369evHhg0b8PPzw2w2218iIpI7EREROe5bpkwZGjVqlI9pRERcV67OtFutVtauXcvPP/98zUIi4eHhBAcH51dOyaVZPx9mX/w5ShXz5JVONY2OI+K0vLy8eOyxx3jssceIi4tjzpw5DBw4kPT0dPr06cMbb7yBh4cuShIRySs2m401a9Zw4cIFWrRoQalSpYyOJCLi1HJ0pv3ChQuMGzeO4OBgOnbsyA8//EBSUhLu7u4cOnSI1157jdDQUDp27MjGjRvzO7PcxLG/U/ngx4MAjH6wFqWLexmcSMQ1hISEMGbMGH788UeqVavG22+/jcViMTqWiIjLSkpKAiAsLIz+/ftjsVho1aoV4eHhdO7cmZo1a7Jz505jQ4qIOLkcFe3VqlVj586dzJo1C4vFQmxsLN988w3/93//x7Jly4iLi+OPP/6gVatW9OjRg1mzZuV3brkOm83GK4t3k37JSssqZXikwZ1GRxJxCenp6cyfP5/w8HDq1KlD2bJl+f777yldurTR0UREXNarr74KQNeuXdm1axft27cnMzOT2NhYNm3aRM2aNXnllVcMTiki4txMtustl3yF33//nZo1c3aJdUZGBnFxcdx11123Ha6gWCwWzGYzycnJ+Pn5GR3ntiz+7U+GLtyBt4cbK4a0plLZ4kZHEnFqv/76K7Nnz2bBggVUqlSJvn378sQTT+SqWC9Mc8jVCvPYRCT/BQUFcerUKZKTkzl37hzBwcGsXr2aNm3aAJfn4Iceeoj4+Hhjg94CzY8icrtyOo/k6EbNnBbsAJ6eni5VsBcmiakXGbv0dwAGt62qgl0kB5o3b05ISAiDBw+2L4K0fv36a/o99NBDBR1NRMTlnT592v7nO++8Ex8fH4c1kEJCQjhz5owR0UREXMYtr6506dIlPvroI3766ScyMzNp2bIlUVFR+Pj45GU+yYW3lv1OYupFqgeUZEDrykbHEXEZcXFxjB079rrb9Zx2EZFbY7VaHd67u7tjMpns76/8s4iIZO+Wi/bBgwdz4MABunbtSkZGBnPnzmXLli188cUXeZlPcmjDob/4euufmEzwVte6eLrraX4iOXH1F0oREcl70dHR+Pj4cOnSJebMmUPZspcfRXvu3DmDk4mIOL8cF+2LFy/mkUcesb9fuXIl+/fvx93dHbj8LM7mzZvnfUK5qbSMTF5evAuAJ5pVpFFFPTpFREREjBccHExcXBzTp0/Hzc2NwMBA/vOf/zj0CQkJMSidiIhryHHR/tlnn/H5558zY8YMgoKCaNiwIc888wzdunUjIyODWbNm0aRJk/zMKtcxbfUhjv59ngA/b15sX93oOCIuY+PGjTn+sfH8+fMcOXKE2rVr53MqEZHCY9euXZjNZnbt2qXF2kREblGOr6H+7rvvePzxx2nTpg0ffvghH3/8MX5+frzyyiuMHj2a4OBg5s+fn59ZJRv7488RvfYPAN54qDZ+Pp4GJxJxHb169SIiIoKvvvqK1NTUbPvs3buXl19+mbvuuoutW7fmyXEzMzMZPXo0oaGh+Pr6ctdddzF27FiufJiHzWZjzJgxlC9fHl9fX8LDwzl48KDDfhITE4mMjMTPzw9/f3/69etHSkqKQ5+dO3fSqlUr++JPEydOzJMxiIiIiEjByNU97Y899hgRERGMGDGCiIgIoqOjmTRpUn5lk5uwWm28vHgXl6w2HqgVQETtQKMjibiUvXv3MnPmTF599VV69uxJtWrVCAoKwsfHh7Nnz7Jv3z5SUlJ45JFHWLlyJXXr1s2T477zzjvMnDmTzz//nNq1a7Nlyxb69u2L2Wxm8ODBAEycOJGpU6fy+eefExoayujRo4mIiGDv3r32BT8jIyM5deoUMTExZGRk0LdvXwYMGGD/AdVisdCuXTvCw8OJjo5m165dPPnkk/j7+zNgwIA8GYuIyI1cuHDB4f2oUaNIT0+3v3d3d2fs2LFayFhE5AZy9Jz27Kxbt46oqCjat2/v8pOtqz5n8/82HuPVJbsp7uVOzLB7CfL3NTqSiMvasmUL69ev59ixY1y4cIGyZcvSoEED7rvvvps+sz23c8iDDz5IQEAAn376qb2tW7du+Pr68n//93/YbDaCgoJ44YUXGD58OADJyckEBAQwZ84cevTowe+//06tWrXYvHkzjRs3BmD58uV07NiRP//8k6CgIGbOnMkrr7xCfHw8Xl5eALz00kssWbKEffv25ejvxVXnRxFxDpMnT2bYsGH2OaRkyZLUrl0bX9/L31n27dvHiBEjGDp0qMFJc0/zo4jcrpzOIzm+PD4uLo7u3btTt25dIiMjqVq1Klu3bqVYsWLUr1+fH374IU+CS84kWNJ454fLX7pfjKiugl3kNjVu3JghQ4YwefJkoqOjGTduHN26dbtpwX4rWrRowapVqzhw4AAAO3bsYP369XTo0AGAI0eOEB8fT3h4uP0zZrOZZs2aERsbC0BsbCz+/v72gh0gPDwcNzc3Nm3aZO/TunVre8EOlxcN3b9/P2fPns02W3p6OhaLxeElInKrvvrqq2va5s+fz5o1a1izZg3vvvsuX375pQHJRERcR46L9t69e+Pm5sa7775LuXLlePrpp/Hy8uKNN95gyZIlTJgwge7du+dnVrnCG9/t4Vz6JeoH+9MrrJLRcUQkF1566SV69OhBjRo18PT0pEGDBgwZMoTIyEgA4uPjAQgICHD4XEBAgH1bfHw85cqVc9ju4eFB6dKlHfpkt48rj3G1CRMmYDab7a/g4ODbHK2IFGWHDx92eO/j44Ob2z9fP5s2bcrevXsLOpaIiEvJcdG+ZcsWxo8fT/v27Xn//ffZuXOnfVvNmjVZt26dw1mhvHLixAmeeOIJypQpg6+vL3Xr1mXLli327TlZrKmw+XFvAst2xePuZmLCI3VxdzMZHUlEcuHLL79k3rx5zJ8/n23btvH555/z3nvv8fnnnxsdjVGjRpGcnGx/HT9+3OhIIuLCkpOTHd6fOXOGSpUq2d9brVaHe9xFRORaOS7aGzVqxJgxY1i5ciUjR47MdkGmvF7Y6OzZs7Rs2RJPT09++OEH9u7dy6RJkyhV6p/nkGct1hQdHc2mTZsoXrw4ERERpKWl5WkWZ5Gafokx/90NwFOtQqkVpHuoRFzNiy++aD/bXrduXXr16sXQoUOZMGECAIGBlxeVTEhIcPhcQkKCfVtgYCCnT5922H7p0iUSExMd+mS3jyuPcTVvb2/8/PwcXiIityooKOiG23fu3EmFChUKKI2IiGvKcdE+d+5c0tPTGTp0KCdOnOCjjz7Kz1zA5RWWg4ODmT17Nk2bNiU0NJR27dpx1113AZfPsk+ZMoVXX32Vhx9+mHr16jF37lxOnjzJkiVL8j2fESatPMDJ5DSCS/sypG01o+OIyC04f/68w+WhcHkFZavVCkBoaCiBgYGsWrXKvt1isbBp0ybCwsIACAsLIykpyeExdKtXr8ZqtdKsWTN7n3Xr1pGRkWHvExMTQ/Xq1R1+/BQRyS/t2rUDyPZkyoULF3jjjTfo1KlTQccSEXEpOS7aK1asyNdff82ePXuYN2/eTX85zQvffvstjRs35tFHH6VcuXI0aNCAWbNm2bfnZLGm7LjqQks7/0xizoYjAIzrUhdfL3eDE4kUTvl9pU7nzp0ZP34833//PUePHmXx4sW8//77PPLIIwCYTCaGDBnCuHHj+Pbbb9m1axe9e/cmKCiILl26AJdvS2rfvj39+/fn119/5ZdffmHgwIH06NHDPj/37NkTLy8v+vXrx549e1i4cCEffPABw4YNy9fxiYhkeeGFF4DLi32+++67/Pe//+W///0vEydOpHr16pw9e5aXX37Z4JQiIs4tR89pT01NpXjx4jneaW77X8/hw4eZOXMmw4YN4+WXX2bz5s0MHjwYLy8v+vTpk6PFmrIzYcIE3njjjdvOV5AuZVp56ZtdWG3w8N1B3FvtDqMjiRQqVquV8ePHEx0dTUJCAgcOHKBy5cqMHj2aSpUq0a9fvzw71ocffsjo0aN57rnnOH36NEFBQTz99NOMGTPG3mfEiBGkpqYyYMAAkpKSuOeee1i+fLnD4zXnzZvHwIEDadu2LW5ubnTr1o2pU6fat5vNZlauXElUVBSNGjWibNmyjBkzRs9oF5ECk7VgZrVq1XjppZfIetKwyWTigQceYMaMGdd8jxMREUc5ek57+fLlef755+nTpw/ly5fPto/NZuPHH3/k/fffp3Xr1owaNeq2w3l5edG4cWM2bNhgbxs8eDCbN28mNjaWDRs20LJlS06ePOmQq3v37phMJhYuXJjtftPT0x0WPbFYLAQHBzv1czY/XvcHby3bh9nXk1Uv3EvZEt5GRxIpVN58800+//xz3nzzTfr378/u3bupXLkyCxcuZMqUKTe8eqcwP6u3MI9NRPLflXPIpUuXOHToEABVqlTJl0dqFiTNjyJyu3I6j+ToTPtPP/3Eyy+/zOuvv079+vVp3LgxQUFB+Pj4cPbsWfbu3UtsbCweHh6MGjWKp59+Ok8GUb58eWrVquXQVrNmTb755hvAcbGmK4v2hIQE7r777uvu19vbG29v1yl6jyeeZ3LM5RXxX+lYUwW7SD6YO3cuH3/8MW3btuWZZ56xt9evX599+/YZmExEpHAoXbo0TZs2NTqGiIjLydE97dWrV+ebb77hwIEDdO/enRMnTvD1118za9YsfvrpJ+68805mzZrF0aNHee6553B3z5t7rVu2bMn+/fsd2g4cOEDFihWBnC3W5OpsNhuvLtnNhYxMmlcuzaONtcKqSH44ceIEVapUuabdarU6LOQmIiI588wzz3DixIkc9V24cCHz5s3L50QiIq4pR2fas4SEhPDCCy/YFxXJb0OHDqVFixa89dZbdO/enV9//ZWPP/6Yjz/+GHBcrKlq1aqEhoYyevRoh8WaXN13O0+x9sAZvNzdGP9IXUwmPZNdJD/UqlWLn3/+2f6jYJavv/6aBg0aGJRKRMR13XHHHTRv3hyATz75hFatWl1zpeb69etZsGABQUFB9u93IiLiKFdFe0Fr0qQJixcvZtSoUbz55puEhoYyZcoUIiMj7X1ysliTq0o6f5E3v9sDwMD7q3DXHSUMTiRSeI0ZM4Y+ffpw4sQJrFYrixYtYv/+/cydO5elS5caHU9ExOWMHTuWPn36ULVqVT799FNefPFFh+0lS5YkPDycjz/+mPbt2xuUUkTE+eVoIbrCzlkXEnnpm50s2HycKuVKsGxwK7w8cvyEPhG5BT///DNvvvkmO3bsICUlhYYNGzJmzBj7c4avx1nnkLxQmMcmIvnvyjkkMzOTuLg4Lly4QNmyZbnrrrtc+gpCzY8icrvydCE6KXibDv/Ngs3HAZjQta4KdpEC0KpVK2JiYoyOISJSKJUqVYpSpUoZHUNExOWoEnRC6ZcyGbV4FwCPNw2hSSXXfiSKiIiIiIiI3BoV7U5o5k9/cPhMKmVLePNS+xpGxxEpEkqVKkXp0qWveZUpU4Y777yTe++9l9mzZxsdU0REcujEiRM88cQTlClTBl9fX+rWrcuWLVvs2202G2PGjKF8+fL4+voSHh7OwYMHDUwsIpK9Wyraf/75Z5544gnCwsLsj/L4z3/+w/r16/M0XFF06HQKM9b8AcDrD9XCXMzT4EQiRcOYMWNwc3OjU6dOvPHGG7zxxht06tQJNzc3oqKiqFatGs8++yyzZs0yOqqIiNzE2bNnadmyJZ6envzwww/s3buXSZMmOVyeP3HiRKZOnUp0dDSbNm2iePHiREREkJaWZmByEZFr5fqe9m+++YZevXoRGRnJb7/9Rnp6OgDJycm89dZbLFu2LM9DFhVWq42XF+3iYqaV+6rfQae65Y2OJFJkrF+/nnHjxvHMM884tH/00UesXLmSb775hnr16jF16lT69+9vUEoREcmJd955h+DgYIcrpEJDQ+1/ttlsTJkyhVdffZWHH34YgLlz5xIQEMCSJUvo0aNHgWcWEbmeXJ9pHzduHNHR0cyaNQtPz3/OArds2ZJt27blabii5sstx/n1aCK+nu6M7VLHpVdUFXE1K1asIDw8/Jr2tm3bsmLFCgA6duzI4cOHCzqaiEihcOnSJX788Uc++ugjzp07B8DJkydJSUnJ82N9++23NG7cmEcffZRy5crRoEEDhyuljhw5Qnx8vMO8bzabadasGbGxsdnuMz09HYvF4vASESkIuS7a9+/fT+vWra9pN5vNJCUl5UWmIunMuXTeWvY7AC+0q0aFUsUMTiRStJQuXZrvvvvumvbvvvuO0qUvLwaZmppKyZIlCzqaiIjLi4uLo27dujz88MNERUVx5swZ4PIZ8eHDh+f58Q4fPszMmTOpWrUqK1as4Nlnn2Xw4MF8/vnnAMTHxwMQEBDg8LmAgAD7tqtNmDABs9lsfwUHB+d5bhGR7OT68vjAwEAOHTpEpUqVHNrXr19P5cqV8ypXkfPm0r1Y0i5R504//t2iktFxRIqc0aNH8+yzz7JmzRqaNm0KwObNm1m2bBnR0dEAxMTEcO+99xoZU0TEJb300ks0btyYHTt2UKZMGXv7I488ki+3HFmtVho3bsxbb70FQIMGDdi9ezfR0dH06dPnlvY5atQohg0bZn9vsVhUuItIgch10d6/f3+ef/55PvvsM0wmEydPniQ2Npbhw4czevTo/MhY6K3Zf5rvdpzEzQRvd62Hh7sW9RcpaP3796dWrVpMmzaNRYsWAVC9enXWrl1LixYtAHjhhReMjCgi4rI2bNhAbGwsXl5eDu2VKlWyL2qcl8qXL0+tWrUc2mrWrMk333wDXD4JBZCQkED58v+sIZSQkMDdd9+d7T69vb3x9vbO86wiIjeT66L9pZdewmq10rZtW86fP0/r1q3x9vZm+PDhDBo0KD8yFmrnL17i1cW7AXiyZSh17jQbnEik6GrZsiUtW7Y0OoaISKFjtVrJzMy8pv3PP//Ml9uOWrZsyf79+x3aDhw4QMWKFYHLi9IFBgayatUqe5FusVjYtGkTzz77bJ7nERG5Hbk+pWsymXjllVdITExk9+7dbNy4kTNnzjB27Nj8yFfoTfnxICeSLnCnvy9DH6hmdBwRAdLS0rTYkIhIHrr//vuZMmWK/b3JZCIlJYXXXnuNjh075vnxhg4dysaNG3nrrbc4dOgQ8+fP5+OPPyYqKsp+/CFDhjBu3Di+/fZbdu3aRe/evQkKCqJLly55nkdE5Hbk+kx7Fi8vr2suO5Lc2X0imU/XHwFgXJc6FPe+5f85ROQ2nT9/nhEjRvDll1/y999/X7M9uzNEIiKSM+PHj+df//oXtWrVIi0tjZ49e3Lw4EHKli3LF198kefHa9KkCYsXL2bUqFG8+eabhIaGMmXKFCIjI+19RowYQWpqKgMGDCApKYl77rmH5cuX4+Pjk+d5RERuh8lms9ly84FHHnkk20eRmUwmfHx8qFKlCj179qR69ep5FjK/WSwWzGYzycnJ+Pn5FcgxM602ukz/hV0nkulUrzzTezYskOOKSPaioqJYs2YNY8eOpVevXkyfPp0TJ07w0Ucf8fbbbzt80buaEXNIQSnMYxOR/HflHFKsWDEWLFjAzp07SUlJoWHDhkRGRuLr62t0zFui+VFEbldO55Fcn9o1m80sWbIEf39/GjVqBMC2bdtISkqiXbt2LFy4kHfeeYdVq1bp3tAbmLPhKLtOJFPSx4PXOuuKBRGjfffdd8ydO5c2bdrQt29fWrVqRZUqVahYsSLz5s27YdEuIiI35+HhwRNPPGF0DBERl3NLj3zr2bMn06ZNw83t8i3xVquV559/npIlS7JgwQKeeeYZRo4cyfr16/M8cGFwIukCk1ZeXhxlVIealCupy7BEjJaYmGh/bKWfnx+JiYkA3HPPPVqUSETkNi1btoxixYpd037llZqhoaEGJBMRcX65Lto//fRTfvnlF3vBDuDm5sagQYNo0aIFb731FgMHDqRVq1Z5GrSwsNlsjFmym/MXM2lcsRQ9muj5niLOoHLlyhw5coSQkBBq1KjBl19+SdOmTfnuu+/w9/c3Op6IiEvr2bMnJpOJq+/KzGozmUzcc889LFmyhFKlShmUUkTEOeV69fhLly6xb9++a9r37dtnX6jJx8cn2/veBX7YHc+qfafxdDcxoWtd3Nz09yTiDPr27cuOHTuAy4+2nD59Oj4+PgwdOpQXX3zR4HQiIq5tyZIlNGnShJiYGJKTk0lOTiYmJoZmzZqxdOlS1q1bx99//83w4cONjioi4nRyfaa9V69e9OvXj5dffpkmTZoAsHnzZt566y169+4NwNq1a6ldu3beJi0Eki9k8Pq3ewB49t67qBqQ988lFZFbM3ToUPufw8PD2bdvH1u3bqVKlSrUq1fPwGQiIq7vpZde4pNPPqFFixb2trZt2+Lj48OAAQPYs2cPU6ZM4cknnzQwpYiIc8p10T558mQCAgKYOHEiCQkJAAQEBDB06FBGjhwJQLt27Wjfvn3eJi0EJi7fx+lz6VQuW5zn7qtidBwRuYGKFStiNpt1abyISB44cuRItisj+/n5cfjwYQCqVq3KX3/9VdDRREScXq4vj3d3d+eVV17h1KlTJCUlkZSUxKlTp3j55Zdxd3cHICQkhAoVKuR5WFe25Wgi8zbFATD+kbr4eLobnEhErvTOO++wcOFC+/vu3btTpkwZ7rzzTvtl8yIicmvuvvtuXnzxRc6cOWNvO3PmDCNGjLBfuXnw4EGCg7XWj4jI1XJdtF/Jz89Pz6XMgYuXrIxatAuA7o0rEHZXGYMTicjVoqOj7V8WY2JiiImJ4YcffqBDhw66p11E5DZNmzaNI0eOUKFCBapUqUKVKlWoUKECR48e5ZNPPgEgJSWFV1991eCkIiLOJ9eXxwN8/fXXfPnll8TFxXHx4kWHbdu2bcuTYIXJx+v+4ODpFMoU9+LljjWNjiMi2YiPj7cX7UuXLqV79+60a9eOSpUq0axZM4PTiYi4tqpVq7J3715WrlzJgQMHAKhevToPPPCA/YlEXbp0MTChiIjzyvWZ9qlTp9K3b18CAgL47bffaNq0KWXKlOHw4cN06NAhPzK6tMNnUpi6+hAAYzrXwr+Yl8GJRCQ7pUqV4vjx4wAsX76c8PBw4PJjGrOejCEiIrfOzc2N9u3bM3jwYAYPHkxERITDI4RFRCR7uT7TPmPGDD7++GMef/xx5syZw4gRI6hcuTJjxowhMTExPzK6LJvNxiuLd3PxkpVWVcvyUP0goyOJyHV07dqVnj17UrVqVf7++2/7j5C//fYbVapo4UgRkduVmprK2rVrs71Sc/DgwQalEhFxfrku2uPi4uyP6/D19eXcuXPA5UfBNW/enGnTpuVtQhf29dY/iT38Nz6ebozvUlfPrhdxYpMnT6ZSpUocP36ciRMnUqJECQBOnTrFc889Z3A6ERHXtmPHDrp378758+dJTU2ldOnS/PXXXxQrVoxy5cqpaBcRuYFcF+2BgYEkJiZSsWJFQkJC2LhxI/Xr1+fIkSPYbLb8yOiS/k5JZ/yy3wEYEl6NkDLFDE4kIjfi6enJ8OHDr2m/8vntIiJya15++WU6d+5MdHQ0ZrOZjRs34unpyRNPPMHzzz9vdDwREaeW66L9/vvv59tvv6VBgwb07duXoUOH8vXXX7Nlyxa6du2aHxld0rjvfyfpfAY1AkvS755Qo+OIyE3MnTv3htt79+5dQElERAqfXbt28cknn+Dm5oa7uzvp6elUrlyZiRMn0qdPH32HFBG5gVwX7R9//DFWqxWAqKgoypQpw4YNG3jooYd4+umn8zygK/r54BkW/3YCkwne7lYPT3ctsiLi7K4+05ORkcH58+fx8vKiWLFiKtpFRG6Dh4eHfdG5cuXKERcXR82aNTGbzfZFQEVEJHu5Ltrd3NwcVvrs0aMHPXr0yNNQruzCxUxeWbwbgD5hlbg72N/YQCKSI2fPnr2m7eDBgzz77LN6TruIyG2qV68emzdvpmrVqtx7772MGTOGv/76i//85z/UqVPH6HgiIk4t16eAly9fzvr16+3vp0+fzt13303Pnj2z/dJb1ExdfZC4xPOUN/swPKK60XFE5DZUrVqVt99+W/dbiojcpjFjxlC+fHkAxo8fT6lSpXj22Wc5c+YMH3/8scHpREScW66L9hdffBGLxQJcvj9p2LBhdOzYkSNHjjBs2LA8D+hKfj9lYda6wwC88VBtSnjn+kIGEXEyHh4enDx50ugYIiIurWHDhtx3333A5cvjly9fjsViYevWrdSvX9/gdCIizi3XVeWRI0eoVasWAN988w2dO3fmrbfeYtu2bXTs2DHPA7qKTKuNUYt2cclqo33tQNrVDjQ6kojkwrfffuvw3mazcerUKaZNm0bLli0NSiUiUjhcuHABDw8PihW7/DSdY8eOsXjxYmrVqkW7du0MTici4txyfabdy8uL8+fPA/Djjz/aJ9rSpUvbz8AXRfM2HWP78SRKeHvw+kO1jY4jIrnUpUsXh1fXrl15/fXXqVevHp999lmeH+/EiRM88cQTlClTBl9fX+rWrcuWLVvs2202m/1yUl9fX8LDwzl48KDDPhITE4mMjMTPzw9/f3/69etHSkqKQ5+dO3fSqlUrfHx8CA4OZuLEiXk+FhGRm3n88cftT+lISkqiadOmTJo0iYcffpiZM2canE5ExLnlumi/5557GDZsGGPHjuXXX3+lU6dOABw4cIAKFSrkeUBXEJ+cxsTl+wEY2b46gWYfgxOJSG5ZrVaHV2ZmJvHx8cyfP99+H2ZeOXv2LC1btsTT05MffviBvXv3MmnSJEqVKmXvM3HiRKZOnUp0dDSbNm2iePHiREREkJaWZu8TGRnJnj17iImJYenSpaxbt44BAwbYt1ssFtq1a0fFihXZunUr7777Lq+//rruHxWRArdjxw5atWoFwNdff01gYCDHjh1j7ty5TJ061eB0IiLOLdeXx0+bNo3nnnuOr7/+mpkzZ3LnnXcC8MMPP9C+ffs8D+gKXvt2Nynpl2gQ4k9ks4pGxxERJ/fOO+8QHBzM7Nmz7W2hoaH2P9tsNqZMmcKrr77Kww8/DFx+jnxAQABLliyhR48e/P777yxfvpzNmzfTuHFjAD788EM6duzIe++9R1BQEPPmzePixYt89tlneHl5Ubt2bbZv387777/vUNxfKT09nfT0dPv7onwFlYjknQsXLlCyZEkAVq5cSdeuXXFzc6N58+YcO3bM4HQiIs4t12faQ0JCWLp0KTt27KBfv3729smTJxfJX0pX7IlnxZ4EPNxMTOhaFzc3k9GRRMTJffvttzRu3JhHH32UcuXK0aBBA2bNmmXffuTIEeLj4wkPD7e3mc1mmjVrRmxsLACxsbH4+/vbC3aA8PBw3Nzc2LRpk71P69at8fLysveJiIhg//79133ax4QJEzCbzfZXcHBwno5dRIqmypUrs2TJEo4fP86KFSvst1eePn0aPz8/g9OJiDi3XBftcXFxN3wVJefSMnjtv3sAGNC6MjUC9X86InJzhw8fZubMmVStWpUVK1bw7LPPMnjwYD7//HMA4uPjAQgICHD4XEBAgH1bfHw85cqVc9ju4eFB6dKlHfpkt48rj3G1UaNGkZycbH8dP378NkcrIgIjRoxg+PDhVKpUiWbNmhEWFgZcPuveoEEDg9OJiDi3XF8eX6lSJUym659NzszMvK1AruS9FfuJt6RRsUwxBretanQcEXERVquVxo0b89ZbbwHQoEEDdu/eTXR0NH369DE0m7e3N97e3oZmEJHCp0uXLrRr145Tp045POKtbdu2PPLIIwYmExFxfrku2n/77TeH9xkZGfz222+8//77jB8/Ps+CObvf4s4yd+Ple7DGd6mLj6e7wYlExFWUL1/e/ujMLDVr1uSbb74BIDDw8iMjExISHBbBS0hI4O6777b3OX36tMM+Ll26RGJiov3zgYGBJCQkOPTJep/VR0SkoAQGBl4z9zRt2tSgNCIiriPXRfuVv45mady4MUFBQbz77rt07do1T4I5s4xMK6MW7cJmg64N7uSeqmWNjiQit6lSpUo8+eST/Pvf/yYkJCRfj9WyZUv279/v0HbgwAEqVry8kGVoaCiBgYGsWrXKXqRbLBY2bdrEs88+C0BYWBhJSUls3bqVRo0aAbB69WqsVivNmjWz93nllVfIyMjA09MTgJiYGKpXr+6wUr2ISH578MEH8fC4/tfO1atXF2AaERHXkut72q+nevXqbN68Oa9259Q++fkI++LPUaqYJ690qml0HBHJA0OGDGHRokVUrlyZBx54gAULFjisop6Xhg4dysaNG3nrrbc4dOgQ8+fP5+OPPyYqKgoAk8nEkCFDGDduHN9++y27du2id+/eBAUF0aVLF+Dymfn27dvTv39/fv31V3755RcGDhxIjx49CAoKAqBnz554eXnRr18/9uzZw8KFC/nggw8YNmxYvoxLROR66tatS/369e2vWrVqcfHiRbZt20bdunWNjici4tRMNpvNlpsPXP34H5vNxqlTp3j99dfZt28f27dvz8t8BcJisWA2m0lOTr7pCqbHE88T/v5a0i9Zee/R+vyrUdF8Nr1IYbVt2zbmzJnDF198QWZmJj179uTJJ5+kYcOG1/1MbuaQLEuXLmXUqFEcPHiQ0NBQhg0bRv/+/e3bbTYbr732Gh9//DFJSUncc889zJgxg2rVqtn7JCYmMnDgQL777jvc3Nzo1q0bU6dOpUSJEvY+O3fuJCoqis2bN1O2bFkGDRrEyJEjc/z3cStjExHJcrM55PXXXyclJYX33nvPgHS3R/OjiNyunM4juS7a3dzcrlmIzmazERwczIIFC+yrgbqS3Ey6lzKtzP7lKJuO/M2s3o1vuCifiLiujIwMZsyYwciRI8nIyKBu3boMHjyYvn37XvPffWH+4laYxyYi+e9mc8ihQ4do2rQpiYmJBqS7PZofReR25XQeyfU97WvWrHF47+bmxh133EGVKlVueK9SYeHh7kb/1pV5qlWoCnaRQigjI4PFixcze/ZsYmJiaN68Of369ePPP//k5Zdf5scff2T+/PlGxxQRKRRiY2Px8fExOoaIiFPLdZV977335kcOl6OCXaRw2bZtG7Nnz+aLL77Azc2N3r17M3nyZGrUqGHv88gjj9CkSRMDU4qIuKbIyEj7gpjwz+2VW7ZsYfTo0QYmExFxfoX/1LiISA40adKEBx54gJkzZ9KlSxeHL5dZQkND6dGjhwHpRERcm9lsdphX3dzcqF69Om+++Sbt2rUzMJmIiPNT0S4iRV5mZiafffYZDz300A0fhVa8eHFmz55dgMlERAqHGTNm6L5vEZFblGePfBMRcVXu7u48/fTTJCUlGR1FRERERMSBinYREaBOnTocPnzY6BgiIiIiIg5yfHn81c9nz1K8eHHc3d3zLJCIiBHGjRvH8OHDGTt2LI0aNaJ48eIO23VZp4iIiIgYIcdFu7+/f7Yrpru7uxMaGsrw4cPp379/noYTESkoHTt2BOChhx5ymOtsNhsmk4nMzEyjoomIiIhIEZbjov3q57NnSUpKYuvWrbz44ot4eHjQt2/fPAt3tbfffptRo0bx/PPPM2XKFADS0tJ44YUXWLBgAenp6URERDBjxgwCAgLyLYeIFD7Xm+NEROT27d27l+bNm2e7bcmSJXTp0qVgA4mIuJAcF+03ej77ww8/TKVKlfjwww/zrWjfvHkzH330EfXq1XNoHzp0KN9//z1fffUVZrOZgQMH0rVrV3755Zd8ySEihdON5jgREbk9Wd/NQkNDHdq/+eYbevfuTWpqqkHJREScX54tRHfvvfdy6NChvNqdg5SUFCIjI5k1a5bD45iSk5P59NNPef/997n//vtp1KgRs2fPZsOGDWzcuDFfsohI4ZWUlMSkSZN46qmneOqpp5g8eTLJyclGxxIRcXm9e/cmPDyc+Ph4e9vChQvp3bs3c+bMMS6YiIgLyLOiPTk5GbPZnFe7cxAVFUWnTp0IDw93aN+6dSsZGRkO7TVq1CAkJITY2Njr7i89PR2LxeLwEpGibcuWLdx1111MnjyZxMREEhMTef/997nrrrvYtm2b0fFERFzayy+/TMeOHQkPDycxMZH58+fTt29f5s6dy6OPPmp0PBERp5bjy+NvJCMjg3fffZdmzZrlxe4cLFiwgG3btrF58+ZrtsXHx+Pl5YW/v79De0BAgMMvuVebMGECb7zxRl5HFREXNnToUB566CFmzZqFh8flqfHSpUs89dRTDBkyhHXr1hmcUETEtX344YdERkbSvHlzTpw4wRdffMHDDz9sdCwREaeX46K9a9eu2bYnJyezZ88eTCYTP//8c54FAzh+/DjPP/88MTEx+Pj45Nl+R40axbBhw+zvLRYLwcHBebZ/EXE9W7ZscSjYATw8PBgxYgSNGzc2MJmIiGv69ttvOX/+PADLli2jWLFidO3alZ9//pnHH38ck8nEt99+C1x+coeIiGQvx0X79S59Dw4Oplu3bkRGRub55fFbt27l9OnTNGzY0N6WmZnJunXrmDZtGitWrODixYskJSU5nG1PSEggMDDwuvv19vbG29s7T7OKiGvz8/MjLi6OGjVqOLQfP36ckiVLGpRKRMR1XbkifM+ePR22ffbZZ3z22WcAeqymiMhN5Lhonz17dn7myFbbtm3ZtWuXQ1vfvn2pUaMGI0eOJDg4GE9PT1atWkW3bt0A2L9/P3FxcYSFhRV4XhFxXY899hj9+vXjvffeo0WLFgD88ssvvPjiizz++OMGpxMRcT1WqxWLxYLZbCYpKQk/Pz+jI4mIuKRc3dO+ceNGvvvuOy5evEjbtm1p3759fuUCoGTJktSpU8ehrXjx4pQpU8be3q9fP4YNG0bp0qXx8/Nj0KBBhIWFXfdZoCIi2XnvvfcwmUz07t2bS5cuAeDp6cmzzz7L22+/bXA6EZHC5+orJUVEJHs5Xj3+66+/pmXLlnzwwQd88skndOrUiffeey8/s+XI5MmTefDBB+nWrRutW7cmMDCQRYsWGR1LRFyMl5cXH3zwAWfPnmX79u1s376dxMREJk+erNtpRERu0+TJk1m4cKH9/aOPPkrp0qW588472bFjR74f/+2338ZkMjFkyBB7W1paGlFRUZQpU4YSJUrQrVs3EhIS8j2LiEhumWw2my0nHRs1akSTJk2YPn067u7uTJgwgXfffZfExMT8zpjvsi7dSk5O1qVbIpJrhXkOKcxjE5H8lzWHhISE8MUXX9CiRQtiYmLo3r07Cxcu5MsvvyQuLo6VK1fmW4bNmzfTvXt3/Pz8uO+++5gyZQoAzz77LN9//z1z5szBbDYzcOBA3Nzc+OWXX3I1Ns2PInKrcjqP5Pjy+P3797Nw4ULc3d0BeOGFFxgzZgynT5+mXLlyt59YRMRAaWlpfPjhh6xZs4bTp09jtVodtutZ7SIit+706dP2J/UsXbqU7t27065dOypVqpQvjwzOkpKSQmRkJLNmzWLcuHH29uTkZD799FPmz5/P/fffD1xev6lmzZps3Lgx29ss09PTSU9Pt7+3WCz5lltE5Eo5vjz+/PnzDtW/l5cXPj4+pKSk5EswEZGC1K9fPyZOnEjFihV58MEHefjhhx1eIiJy6/z9/Tl+/DgAy5cvJzw8HACbzZavK8dHRUXRqVMn+/GybN26lYyMDIf2GjVqEBISQmxsbLb7mjBhAmaz2f7S44JFpKDkaiG6Tz75hBIlStjfX7p0iTlz5lC2bFl72+DBg/MunYhIAVm6dCnLli2jZcuWRkcRESl0OnfuTM+ePalatSp///03HTp0AOC3336jSpUq+XLMBQsWsG3bNjZv3nzNtvj4eLy8vK5ZCC8gIID4+Phs9zdq1CiGDRtmf2+xWFS4i0iByHHRHhISwqxZsxzaAgMD+c9//mN/bzKZVLSLiEu688479Tx2EZF8MmHCBKpVq8bx48eZOHGi/STQqVOneO655/L8eMePH+f5558nJiYGHx+fPNmnt7e3FiYVEUPkuGg/evRoPsYQETHWpEmTGDlyJNHR0VSsWNHoOCIihYqnpyfDhw+/pn3o0KH5crytW7dy+vRpGjZsaG/LzMxk3bp1TJs2jRUrVnDx4sVrHjuXkJBAYGBgvmQSEblVubo8XkSksGrcuDFpaWlUrlyZYsWK4enp6bC9MDwpQ0SkIH377bf2W46WLVtGsWLFrtv3oYceytNjt23bll27djm09e3blxo1ajBy5EiCg4Px9PRk1apVdOvWDbi86HJcXBxhYWF5mkVE5HbluGhfvXo1AwcOZOPGjdcsR5+cnEyLFi2YOXMmrVu3zvOQIiL57fHHH+fEiRO89dZbBAQEYDKZjI4kIuLSunTpwsGDBwHo2bPndfuZTKY8X4yuZMmS1KlTx6GtePHilClTxt7er18/hg0bRunSpfHz82PQoEGEhYVlu3K8iIiRcly0T5kyhf79+2f7/Diz2czTTz/N5MmTVbSLiEvasGEDsbGx1K9f3+goIiKFgtVqtT8WLSkpyemeZT558mTc3Nzo1q0b6enpREREMGPGDKNjiYhcI8dF+44dO3jnnXeuu71du3a89957eRJKRKSg1ahRgwsXLhgdQ0RE8slPP/3k8N7Hx4fp06czffp0YwKJiORQjp/TnpCQcM09nlfy8PDgzJkzeRJKRKSgvf3227zwwgv89NNP/P3331gsFoeXiIjcuv/85z88+OCD1KlTh7p16/LQQw8xd+5cbDab0dFERJxejs+033nnnezevfu6z9LcuXMn5cuXz7NgIiIFqX379sDlxYuuZLPZ8uV+SxGRoiCrKB80aBD169enbt262Gw2fv/9d/7973+zaNEilixZYmxIEREnl+OivWPHjowePZr27dtf87zLCxcu8Nprr/Hggw/meUARkYKwZs0aoyOIiBQ68+bNAy6vJH/198TVq1fTpUsX5s6dS+/evY2IJyLiEky2HF6XlJCQQMOGDXF3d2fgwIFUr14dgH379jF9+nQyMzPZtm0bAQEB+Ro4P1gsFsxmM8nJyU63SIqIOL/CPIcU5rGJSP67//77WbNmzXXnkLfeeou1a9eyYsUKA9LdHs2PInK7cjqP5Pie9oCAADZs2ECdOnUYNWoUjzzyCI888ggvv/wyderUYf369S5ZsIuIZPn555954oknaNGiBSdOnAAu34e5fv16g5OJiLimPXv23HB7hw4d2LFjRwGlERFxTTku2gEqVqzIsmXL+Ouvv9i0aRMbN27kr7/+YtmyZYSGhuZXRhGRfPfNN98QERGBr68v27ZtIz09HYDk5GTeeustg9OJiLims2fP3nB7QEDATfuIiBR1uSras5QqVYomTZrQtGlTSpUqldeZREQK3Lhx44iOjmbWrFkOT8po2bIl27ZtMzCZiIjrutkinu7u7ly6dKmA0oiIuKYcL0QnIlKY7d+/n9atW1/TbjabSUpKKvhAIiKFQNbSSZGRkdk+OjjrqiYREbm+WzrTLiJS2AQGBnLo0KFr2tevX0/lypXz9dhvv/02JpOJIUOG2NvS0tKIioqiTJkylChRgm7dupGQkODwubi4ODp16kSxYsUoV64cL7744jVnrH766ScaNmyIt7c3VapUYc6cOfk6FhGRK/Xs2RO4/ANodq9y5cpp5XgRkZvQmXYREaB///48//zzfPbZZ5hMJk6ePElsbCzDhw9n9OjR+XbczZs389FHH1GvXj2H9qFDh/L999/z1VdfYTabGThwIF27duWXX34BLl9y2qlTJwIDA9mwYQOnTp2id+/eeHp62u/BP3LkCJ06deKZZ55h3rx5rFq1iqeeeory5csTERGRb2MSEckyY8YM5s2bx4wZM7TCuojILVLRLiICvPTSS1itVtq2bcv58+dp3bo13t7eDB8+nEGDBuXLMVNSUoiMjGTWrFmMGzfO3p6cnMynn37K/Pnzuf/++wGYPXs2NWvWZOPGjTRv3pyVK1eyd+9efvzxRwICArj77rsZO3YsI0eO5PXXX8fLy4vo6GhCQ0OZNGkSADVr1mT9+vVMnjxZRbuIiIiIi9Dl8SIigMlk4pVXXiExMZHdu3ezceNGzpw5w9ixY/PtmFFRUXTq1Inw8HCH9q1bt5KRkeHQXqNGDUJCQoiNjQUgNjaWunXrOjxqMyIiAovFYn/EUmxs7DX7joiIsO8jO+np6VgsFoeXiIiIiBhHZ9pFRK7g5eVFrVq18v04CxYsYNu2bWzevPmabfHx8Xh5eeHv7+/QHhAQQHx8vL3PlQV71vasbTfqY7FYuHDhAr6+vtcce8KECbzxxhu3PC4RERERyVsq2kWkSHvyySdz1O+zzz7Ls2MeP36c559/npiYGHx8fPJsv3lh1KhRDBs2zP7eYrEQHBxsYCIRERGRok1Fu4gUaXPmzKFixYo0aNDA/mii/LZ161ZOnz5Nw4YN7W2ZmZmsW7eOadOmsWLFCi5evEhSUpLD2faEhAQCAwOBy6vd//rrrw77zVpd/so+V684n5CQgJ+fX7Zn2QG8vb3x9va+7TGKiIiISN5Q0S4iRdqzzz7LF198wZEjR+jbty9PPPEEpUuXztdjtm3bll27djm09e3blxo1ajBy5EiCg4Px9PRk1apVdOvWDbj8HPm4uDjCwsIACAsLY/z48Zw+fZpy5coBEBMTg5+fn/3y/rCwMJYtW+ZwnJiYGPs+RERERMT5aSE6ESnSpk+fzqlTpxgxYgTfffcdwcHBdO/enRUrVuTbmfeSJUtSp04dh1fx4sUpU6YMderUwWw2069fP4YNG8aaNWvYunUrffv2JSwsjObNmwPQrl07atWqRa9evdixYwcrVqzg1VdfJSoqyn6m/JlnnuHw4cOMGDGCffv2MWPGDL788kuGDh2aL+MSERERkbynol1Eijxvb28ef/xxYmJi2Lt3L7Vr1+a5556jUqVKpKSkGJJp8uTJPPjgg3Tr1o3WrVsTGBjIokWL7Nvd3d1ZunQp7u7uhIWF8cQTT9C7d2/efPNNe5/Q0FC+//57YmJiqF+/PpMmTeKTTz7R495EREREXIgujxcRuYKbmxsmkwmbzUZmZmaBHfenn35yeO/j48P06dOZPn36dT9TsWLFay5/v1qbNm347bff8iKiiIiIiBhAZ9pFpMhLT0/niy++4IEHHqBatWrs2rWLadOmERcXR4kSJYyOJyIiIiJFmM60i0iR9txzz7FgwQKCg4N58skn+eKLLyhbtqzRsUREREREABXtIlLERUdHExISQuXKlVm7di1r167Ntt+V95OLiIiIiBQUFe0iUqT17t0bk8lkdAwRERERkWypaBeRIm3OnDlGRxARERERuS4tRCciIiIiIiLipFS0i4iIiIiIiDgpFe0iIiIiIiIiTkpFu4iIiIiIiIiTUtEuIiIiIiIi4qRUtIuIiIiIiIg4KRXtIiIiIiIiIk5KRbuIiIiIiIiIk1LRLiIiIiIiIuKkVLSLiIiIiIiIOCkV7SIiIiIiIiJOSkW7iIiIiIiIiJNS0S4iIiIiIiLipDyMDiAiIiIiIq7JZrP975//e39lm70P2HDsxw22XW8fWQ256W+7/IHr5rn+uG6w7Yafu/7WG+3z1rPc+jj+2cfNjn+TY9z8EDnKYTKBCTCZTP/7J7iZTP9sM5lwM4EJk2PfK/6ctR3TP5832ff9v75X7cMtax//O5YzUtEuIiIiIpLPvttxkv9uP4HVdrkIstr+KTZtNrDabFj/9+esovJGfa/855V9bf/re00fm+2q9uzaLn/YelX7lcfIahMprNxMjj8cmK4q/K/cTlbh72ay/3AwM7IhzSqXydNMKtpFRERERPLZkb9S+fH300bHKFKyTpxmFVNZf87aZiIHZ1Zv0uVme8jJydub5bjZPm60+UZnj2+42/w65g0+eOUPR/YfqbjyxykcflSy2f9546y5Zb1mp7k7wCVr3v+qpaJdRERERCSf3V+jHAF+3ldcopt1xi7r8lyTw6W6bv87jed2Vd8r+/1zWa/jGcDs+l55qbGbyYSb25WfuUFftyuPx//OLJpyXhCbrmzL+vP1+19Z1P1zDNNV76+zDye+vFnyV3ZXmdhwvFLEdsWPAZcL83/arVf8AJDd5668wsR2nR8Osv58p79vno/PqYv2CRMmsGjRIvbt24evry8tWrTgnXfeoXr16vY+aWlpvPDCCyxYsID09HQiIiKYMWMGAQEBBiYXEREREflHnTvN1LnTbHQMkUIp6952APecXEHhYpx69fi1a9cSFRXFxo0biYmJISMjg3bt2pGammrvM3ToUL777ju++uor1q5dy8mTJ+natauBqUVERERERETyhlOfaV++fLnD+zlz5lCuXDm2bt1K69atSU5O5tNPP2X+/Pncf//9AMyePZuaNWuyceNGmjdvbkRsERERERERkTzh1Gfar5acnAxA6dKlAdi6dSsZGRmEh4fb+9SoUYOQkBBiY2Ovu5/09HQsFovDS0RERERERMTZuEzRbrVaGTJkCC1btqROnToAxMfH4+Xlhb+/v0PfgIAA4uPjr7uvCRMmYDab7a/g4OD8jC4iIiIiIiJyS1ymaI+KimL37t0sWLDgtvc1atQokpOT7a/jx4/nQUIRERERcQYTJkygSZMmlCxZknLlytGlSxf279/v0CctLY2oqCjKlClDiRIl6NatGwkJCQYlFhG5Ppco2gcOHMjSpUtZs2YNFSpUsLcHBgZy8eJFkpKSHPonJCQQGBh43f15e3vj5+fn8BIRERGRwkGLGYtIYeLUC9HZbDYGDRrE4sWL+emnnwgNDXXY3qhRIzw9PVm1ahXdunUDYP/+/cTFxREWFmZEZBERERExmBYzFpHCxKmL9qioKObPn89///tfSpYsab9P3Ww24+vri9lspl+/fgwbNozSpUvj5+fHoEGDCAsL02QrIiIiIkDuFzPO7ntkeno66enp9vdayFhECopTXx4/c+ZMkpOTadOmDeXLl7e/Fi5caO8zefJkHnzwQbp160br1q0JDAxk0aJFBqYWEREREWeRV4sZayFjETGKU59pt9lsN+3j4+PD9OnTmT59egEkEhERERFXkrWY8fr1629rP6NGjWLYsGH29xaLRYW7iBQIpy7aRURERERuVdZixuvWrbvuYsZXnm2/0WLG3t7eeHt753dkEZFrOPXl8SIiIiIiuWWz2Rg4cCCLFy9m9erVN1zMOIsWMxYRZ6Uz7SIiIiJSqGgxYxEpTFS0i4iIiEihMnPmTADatGnj0D579mz+/e9/A5cXM3Zzc6Nbt26kp6cTERHBjBkzCjipiMjN6fJ4EZECNmHCBJo0aULJkiUpV64cXbp0Yf/+/Q590tLSiIqKokyZMpQoUYJu3bqRkJDg0CcuLo5OnTpRrFgxypUrx4svvsilS5cc+vz00080bNgQb29vqlSpwpw5c/J7eCIihrPZbNm+sgp2+Gcx48TERFJTU1m0aNF172cXETGSinYRkQK2du1aoqKi2LhxIzExMWRkZNCuXTtSU1PtfYYOHcp3333HV199xdq1azl58iRdu3a1b8/MzKRTp05cvHiRDRs28PnnnzNnzhzGjBlj73PkyBE6derEfffdx/bt2xkyZAhPPfUUK1asKNDxioiIiMitM9ly8ly1Qs5isWA2m0lOTsbPz8/oOCLiYm53Djlz5gzlypVj7dq1tG7dmuTkZO644w7mz5/Pv/71LwD27dtHzZo1iY2NpXnz5vzwww88+OCDnDx5koCAAACio6MZOXIkZ86cwcvLi5EjR/L999+ze/du+7F69OhBUlISy5cvzzZLeno66enpDmMLDg7W/Cgit6Qwf8cqzGMTkYKR03lEZ9pFRAyWnJwMQOnSpQHYunUrGRkZhIeH2/vUqFGDkJAQYmNjAYiNjaVu3br2gh0gIiICi8XCnj177H2u3EdWn6x9ZGfChAmYzWb7S88gFhERETGWinYREQNZrVaGDBlCy5YtqVOnDgDx8fF4eXk5PDsYICAgwL4Ccnx8vEPBnrU9a9uN+lgsFi5cuJBtnlGjRpGcnGx/HT9+/LbHKCIiIiK3TqvHi4gYKCoqit27d7N+/XqjowDg7e2Nt7e30TFERERE5H90pl1ExCADBw5k6dKlrFmzhgoVKtjbAwMDuXjxIklJSQ79ExIS7CsbBwYGXrOafNb7m/Xx8/PD19c3r4cjIiIiIvlARbuISAGz2WwMHDiQxYsXs3r1akJDQx22N2rUCE9PT1atWmVv279/P3FxcYSFhQEQFhbGrl27OH36tL1PTEwMfn5+1KpVy97nyn1k9cnah4iIiIg4P10eLyJSwKKiopg/fz7//e9/KVmypP0edLPZjK+vL2azmX79+jFs2DBKly6Nn58fgwYNIiwsjObNmwPQrl07atWqRa9evZg4cSLx8fG8+uqrREVF2S9vf+aZZ5g2bRojRozgySefZPXq1Xz55Zd8//33ho1dRERERHJHZ9pFRArYzJkzSU5Opk2bNpQvX97+Wrhwob3P5MmTefDBB+nWrRutW7cmMDCQRYsW2be7u7uzdOlS3N3dCQsL44knnqB37968+eab9j6hoaF8//33xMTEUL9+fSZNmsQnn3xCREREgY5XRERERG6dntOOnrMpIrenMM8hhXlsIpL/CvMcUpjHJiIFQ89pFxEREREREXFxKtpFREREREREnJSKdhEREREREREnpaJdRERERERExEmpaBcRERERERFxUiraRURERERERJyUinYRERERERERJ6WiXURERERERMRJqWgXERERERERcVIeRgcQERHJL1arjfRLVtIyMrnwv1ea/WXlwsVs2v7X71Km1b4fm81xv1e9zWa77YbbHbdd1fc29n2zz7qu3A3kVsad289c/b9DTri7mfD2cMfXyx0fD3d8vdzw9XTH29Md3/+9fDwvt2f1s7d5uuPt4YabmynXxxUREdemol1ERAqUzWYjI9PmUCxfuKKIvqbtyn4XM0m7lMmFi9ar+mVyIePatrQM680DibgQbw+3K4r+ywW9j6ebQ9GfVfg79snafrmvj8M+/vl81g8Inu4mTCb9QCAi4gxUtIuISJ6Zuuogu04kZ1uMp1/KtJ/ZthpwBtjL3Q0fT7f/FTRXFihu9oLm6qKFK2oWE44FzNX1zNXlzbXbTTfYduMP386+C4vcDutW/h7yu0jNtNoc/ru48r+Tyz9IWUmz/zB1uT09w8rFK676SL9kJf2SFcjI16zubiZ8/vcDgeNZ/8v/vczq3RgfT/d8zSAiIpepaBcRkTyz5dhZ1h04k+P+biYuF8vXKQyuLKZ9PN0czg5e2e+fy4r/uezY8eyiO+66rFhc1KVM6+WC/n/Fffr/rja5cM2VJf8U/ze9auU6V7dk/aCWabWRejGT1IuZ2WbSf08iIgVHRbuIiOSZ3s0r0r524D+X4F5ZTOsSXJFb4uHuRgl3N0p45+/XNpvNxsVMa/ZXAVzV5umutYxFRAqKinYREckz4bUCjI4gIrfIZLq8UJ63hztmX0+j44iIyP/oZ1IRERERERERJ6WiXURERERERMRJqWgXERERERERcVIq2kVERERERESclIp2ERERERERESelol1ERERERETESaloFxEREREREXFSKtpFREREREREnJSKdhEREREREREnpaJdRERERERExEmpaBcRERERERFxUiraRURERERERJyUinYRERERERERJ6WiXURERERERMRJqWgXERERERERcVIq2kVERERERESclIp2ERERERERESelol1ERERERETESaloFxEREREREXFSKtpFREREREREnJSKdhEREREREREnVWiK9unTp1OpUiV8fHxo1qwZv/76q9GRREScguZHEZHr0xwpIs6uUBTtCxcuZNiwYbz22mts27aN+vXrExERwenTp42OJiJiKM2PIiLXpzlSRFxBoSja33//ffr370/fvn2pVasW0dHRFCtWjM8++8zoaCIihtL8KCJyfZojRcQVeBgd4HZdvHiRrVu3MmrUKHubm5sb4eHhxMbGZvuZ9PR00tPT7e+Tk5MBsFgs+RtWRAqlrLnDZrMZnMSR5kcRMZqzzo+Q+zlS86OI5LWczpEuX7T/9ddfZGZmEhAQ4NAeEBDAvn37sv3MhAkTeOONN65pDw4OzpeMIlI0nDt3DrPZbHQMO82PIuIsnG1+hNzPkZofRSS/3GyOdPmi/VaMGjWKYcOG2d9brVYSExMpU6YMJpPppp+3WCwEBwdz/Phx/Pz88jNqvioM4ygMYwCNw5ncyhhsNhvnzp0jKCgon9PlP82Pl2kczqMwjAGK7jg0PzoqDP8eFIYxQOEYR2EYAxTtceR0jnT5or1s2bK4u7uTkJDg0J6QkEBgYGC2n/H29sbb29uhzd/fP9fH9vPzc+l/sbIUhnEUhjGAxuFMcjsGZzuDBJof84LG4TwKwxigaI7DGedHyP0cmVfzIxSOfw8KwxigcIyjMIwBiu44cjJHuvxCdF5eXjRq1IhVq1bZ26xWK6tWrSIsLMzAZCIixtL8KCJyfZojRcRVuPyZdoBhw4bRp08fGjduTNOmTZkyZQqpqan07dvX6GgiIobS/Cgicn2aI0XEFRSKov2xxx7jzJkzjBkzhvj4eO6++26WL19+zcIiecXb25vXXnvtmkukXE1hGEdhGANoHM6kMIzhSpofb43G4TwKwxhA43BWmiNzrzCMAQrHOArDGEDjyAmTzRmfwSEiIiIiIiIirn9Pu4iIiIiIiEhhpaJdRERERERExEmpaBcRERERERFxUiraRURERERERJyUivZbMH36dCpVqoSPjw/NmjXj119/NTpSrqxbt47OnTsTFBSEyWRiyZIlRkfKtQkTJtCkSRNKlixJuXLl6NKlC/v37zc6Vq7NnDmTevXq4efnh5+fH2FhYfzwww9Gx7otb7/9NiaTiSFDhhgdJVdef/11TCaTw6tGjRpGx3I5mh+Np/nReWl+LNo0PxpP86Pz0vx4Yyrac2nhwoUMGzaM1157jW3btlG/fn0iIiI4ffq00dFyLDU1lfr16zN9+nSjo9yytWvXEhUVxcaNG4mJiSEjI4N27dqRmppqdLRcqVChAm+//TZbt25ly5Yt3H///Tz88MPs2bPH6Gi3ZPPmzXz00UfUq1fP6Ci3pHbt2pw6dcr+Wr9+vdGRXIrmR+eg+dE5aX4s2jQ/OgfNj85J82MO2CRXmjZtaouKirK/z8zMtAUFBdkmTJhgYKpbB9gWL15sdIzbdvr0aRtgW7t2rdFRblupUqVsn3zyidExcu3cuXO2qlWr2mJiYmz33nuv7fnnnzc6Uq689tprtvr16xsdw6VpfnROmh+Np/lRND86J82PxtP8mDM6054LFy9eZOvWrYSHh9vb3NzcCA8PJzY21sBkkpycDEDp0qUNTnLrMjMzWbBgAampqYSFhRkdJ9eioqLo1KmTw38frubgwYMEBQVRuXJlIiMjiYuLMzqSy9D86Lw0PxpP82PRpvnReWl+NJ7mx5zxyPM9FmJ//fUXmZmZBAQEOLQHBASwb98+g1KJ1WplyJAhtGzZkjp16hgdJ9d27dpFWFgYaWlplChRgsWLF1OrVi2jY+XKggUL2LZtG5s3bzY6yi1r1qwZc+bMoXr16pw6dYo33niDVq1asXv3bkqWLGl0PKen+dE5aX40nuZH0fzonDQ/Gk/zY86paBeXFxUVxe7du132/rrq1auzfft2kpOT+frrr+nTpw9r1651mYn3+PHjPP/888TExODj42N0nFvWoUMH+5/r1atHs2bNqFixIl9++SX9+vUzMJnIrdP8aCzNjyLOS/OjsTQ/5o6K9lwoW7Ys7u7uJCQkOLQnJCQQGBhoUKqibeDAgSxdupR169ZRoUIFo+PcEi8vL6pUqQJAo0aN2Lx5Mx988AEfffSRwclyZuvWrZw+fZqGDRva2zIzM1m3bh3Tpk0jPT0dd3d3AxPeGn9/f6pVq8ahQ4eMjuISND86H82PxtP8KKD50RlpfjSe5sfc0T3tueDl5UWjRo1YtWqVvc1qtbJq1SqXvIfEldlsNgYOHMjixYtZvXo1oaGhRkfKM1arlfT0dKNj5Fjbtm3ZtWsX27dvt78aN25MZGQk27dvd8kJFyAlJYU//viD8uXLGx3FJWh+dB6aH52H5kcBzY/ORPOj89D8mDs6055Lw4YNo0+fPjRu3JimTZsyZcoUUlNT6du3r9HRciwlJcXh158jR46wfft2SpcuTUhIiIHJci4qKor58+fz3//+l5IlSxIfHw+A2WzG19fX4HQ5N2rUKDp06EBISAjnzp1j/vz5/PTTT6xYscLoaDlWsmTJa+4FK168OGXKlHGpe8SGDx9O586dqVixIidPnuS1117D3d2dxx9/3OhoLkPzo3PQ/Og8ND9KFs2PzkHzo/PQ/JhL+b4+fSH04Ycf2kJCQmxeXl62pk2b2jZu3Gh0pFxZs2aNDbjm1adPH6Oj5Vh2+QHb7NmzjY6WK08++aStYsWKNi8vL9sdd9xha9u2rW3lypVGx7ptrvjIjscee8xWvnx5m5eXl+3OO++0PfbYY7ZDhw4ZHcvlaH40nuZH56b5sejS/Gg8zY/OTfPj9ZlsNpstb38GEBEREREREZG8oHvaRURERERERJyUinYRERERERERJ6WiXURERERERMRJqWgXERERERERcVIq2kVERERERESclIp2ERERERERESelol1ERERERETESaloFxEREREREXFSKtql0Pr3v/9Nly5dDDt+r169eOutt3LUt0ePHkyaNCmfE4mIXKb5UUTk+jRHirMx2Ww2m9EhRHLLZDLdcPtrr73G0KFDsdls+Pv7F0yoK+zYsYP777+fY8eOUaJEiZv23717N61bt+bIkSOYzeYCSCgihZXmRxGR69McKa5IRbu4pPj4ePufFy5cyJgxY9i/f7+9rUSJEjma6PLLU089hYeHB9HR0Tn+TJMmTfj3v/9NVFRUPiYTkcJO86OIyPVpjhRXpMvjxSUFBgbaX2azGZPJ5NBWokSJay5tatOmDYMGDWLIkCGUKlWKgIAAZs2aRWpqKn379qVkyZJUqVKFH374weFYu3fvpkOHDpQoUYKAgAB69erFX3/9dd1smZmZfP3113Tu3NmhfcaMGVStWhUfHx8CAgL417/+5bC9c+fOLFiw4Pb/ckSkSNP8KCJyfZojxRWpaJci5fPPP6ds2bL8+uuvDBo0iGeffZZHH32UFi1asG3bNtq1a0evXr04f/48AElJSdx///00aNCALVu2sHz5chISEujevft1j7Fz506Sk5Np3LixvW3Lli0MHjyYN998k/3797N8+XJat27t8LmmTZvy66+/kp6enj+DFxG5Ac2PIiLXpzlSDGUTcXGzZ8+2mc3ma9r79Olje/jhh+3v7733Xts999xjf3/p0iVb8eLFbb169bK3nTp1ygbYYmNjbTabzTZ27Fhbu3btHPZ7/PhxG2Dbv39/tnkWL15sc3d3t1mtVnvbN998Y/Pz87NZLJbrjmPHjh02wHb06NEbjldEJKc0P4qIXJ/mSHEVOtMuRUq9evXsf3Z3d6dMmTLUrVvX3hYQEADA6dOngcuLgaxZs8Z+f1OJEiWoUaMGAH/88Ue2x7hw4QLe3t4OC5088MADVKxYkcqVK9OrVy/mzZtn/yU2i6+vL8A17SIiBUHzo4jI9WmOFCOpaJcixdPT0+G9yWRyaMuaJK1WKwApKSl07tyZ7du3O7wOHjx4zaVJWcqWLcv58+e5ePGiva1kyZJs27aNL774gvLlyzNmzBjq169PUlKSvU9iYiIAd9xxR56MVUQkNzQ/iohcn+ZIMZKKdpEbaNiwIXv27KFSpUpUqVLF4VW8ePFsP3P33XcDsHfvXod2Dw8PwsPDmThxIjt37uTo0aOsXr3avn337t1UqFCBsmXL5tt4RETyiuZHEZHr0xwpeUlFu8gNREVFkZiYyOOPP87mzZv5448/WLFiBX379iUzMzPbz9xxxx00bNiQ9evX29uWLl3K1KlT2b59O8eOHWPu3LlYrVaqV69u7/Pzzz/Trl27fB+TiEhe0PwoInJ9miMlL6loF7mBoKAgfvnlFzIzM2nXrh1169ZlyJAh+Pv74+Z2/f98nnrqKebNm2d/7+/vz6JFi7j//vupWbMm0dHRfPHFF9SuXRuAtLQ0lixZQv/+/fN9TCIieUHzo4jI9WmOlLxkstlsNqNDiBQ2Fy5coHr16ixcuJCwsLCb9p85cyaLFy9m5cqVBZBORMQ4mh9FRK5Pc6RkR2faRfKBr68vc+fO5a+//spRf09PTz788MN8TiUiYjzNjyIi16c5UrKjM+0iIiIiIiIiTkpn2kVERERERESclIp2ERERERERESelol1ERERERETESaloFxEREREREXFSKtpFREREREREnJSKdhEREREREREnpaJdRERERERExEmpaBcRERERERFxUiraRURERERERJzU/wMbAuNE7MSKTAAAAABJRU5ErkJggg==\n" + "image/png": 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\n" }, "metadata": {} }, @@ -641,12 +743,13 @@ "name": "stdout", "text": [ "Copying files from IDC buckets..\n", - "Done in 0.622454 seconds.\n", - "Chris Rorden's dcm2niiX version v1.0.20181125 (JP2:OpenJPEG) GCC9.3.0 (64-bit Linux)\n", + "Done in 1.81282 seconds.\n", + "Chris Rorden's dcm2niiX version v1.0.20211006 (JP2:OpenJPEG) GCC11.2.0 x86-64 (64-bit Linux)\n", "Found 112 DICOM file(s)\n", - "Convert 112 DICOM as //content/dcm2niix/1.2.840.113654.2.55.154809705591242159075253605419469935510/1.2.840.113654.2.55.154809705591242159075253605419469935510_0_OPA_GE_LSQX_STANDARD_310_2.5_120_64_0.1_1.5_19990102000000_2 (512x512x112x1)\n", - "compress: \"/usr/bin/pigz\" -n -f -6 \"//content/dcm2niix/1.2.840.113654.2.55.154809705591242159075253605419469935510/1.2.840.113654.2.55.154809705591242159075253605419469935510_0_OPA_GE_LSQX_STANDARD_310_2.5_120_64_0.1_1.5_19990102000000_2.nii\"\n", - "Conversion required 5.111221 seconds (0.253575 for core code).\n" + "Convert 112 DICOM as /content/dcm2niix/1.2.840.113654.2.55.154809705591242159075253605419469935510/1.2.840.113654.2.55.154809705591242159075253605419469935510_0,OPA,GE,LSQX,STANDARD,310,2.5,120,64,0.1,1.5_19990102000000_2 (512x512x112x1)\n", + "Compress: \"/usr/bin/pigz\" -b 960 -n -f -6 \"/content/dcm2niix/1.2.840.113654.2.55.154809705591242159075253605419469935510/1.2.840.113654.2.55.154809705591242159075253605419469935510_0,OPA,GE,LSQX,STANDARD,310,2.5,120,64,0.1,1.5_19990102000000_2.nii\"\n", + "Conversion required 3.148048 seconds (0.215932 for core code).\n", + "\n" ] }, { @@ -655,7 +758,7 @@ "text/plain": [ "
" ], - "image/png": 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\n" + "image/png": 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\n" }, "metadata": {} }, @@ -664,12 +767,13 @@ "name": "stdout", "text": [ "Copying files from IDC buckets..\n", - "Done in 0.523157 seconds.\n", - "Chris Rorden's dcm2niiX version v1.0.20181125 (JP2:OpenJPEG) GCC9.3.0 (64-bit Linux)\n", + "Done in 1.62311 seconds.\n", + "Chris Rorden's dcm2niiX version v1.0.20211006 (JP2:OpenJPEG) GCC11.2.0 x86-64 (64-bit Linux)\n", "Found 158 DICOM file(s)\n", - "Convert 158 DICOM as //content/dcm2niix/1.2.840.113654.2.55.185309182591805634517860395342326800332/1.2.840.113654.2.55.185309182591805634517860395342326800332_1_OPA_GE_LSQX_STANDARD_360_2.5_120_48_0_1.5_20000102000000_2 (512x512x158x1)\n", - "compress: \"/usr/bin/pigz\" -n -f -6 \"//content/dcm2niix/1.2.840.113654.2.55.185309182591805634517860395342326800332/1.2.840.113654.2.55.185309182591805634517860395342326800332_1_OPA_GE_LSQX_STANDARD_360_2.5_120_48_0_1.5_20000102000000_2.nii\"\n", - "Conversion required 4.528913 seconds (0.330428 for core code).\n" + "Convert 158 DICOM as /content/dcm2niix/1.2.840.113654.2.55.185309182591805634517860395342326800332/1.2.840.113654.2.55.185309182591805634517860395342326800332_1,OPA,GE,LSQX,STANDARD,360,2.5,120,48,0,1.5_20000102000000_2 (512x512x158x1)\n", + "Compress: \"/usr/bin/pigz\" -b 960 -n -f -6 \"/content/dcm2niix/1.2.840.113654.2.55.185309182591805634517860395342326800332/1.2.840.113654.2.55.185309182591805634517860395342326800332_1,OPA,GE,LSQX,STANDARD,360,2.5,120,48,0,1.5_20000102000000_2.nii\"\n", + "Conversion required 4.381163 seconds (0.334753 for core code).\n", + "\n" ] }, { @@ -678,7 +782,7 @@ "text/plain": [ "
" ], - "image/png": 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\n" 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\n" }, "metadata": {} }, @@ -687,12 +791,13 @@ "name": "stdout", "text": [ "Copying files from IDC buckets..\n", - "Done in 0.627716 seconds.\n", - "Chris Rorden's dcm2niiX version v1.0.20181125 (JP2:OpenJPEG) GCC9.3.0 (64-bit Linux)\n", + "Done in 1.51796 seconds.\n", + "Chris Rorden's dcm2niiX version v1.0.20211006 (JP2:OpenJPEG) GCC11.2.0 x86-64 (64-bit Linux)\n", "Found 130 DICOM file(s)\n", - "Convert 130 DICOM as //content/dcm2niix/1.2.840.113654.2.55.216614002338888733987350522981366678482/1.2.840.113654.2.55.216614002338888733987350522981366678482_0_OPA_GE_HSQX_BONE_340_2.5_120_56_0.1_1.5_19990102000000_3 (512x512x130x1)\n", - "compress: \"/usr/bin/pigz\" -n -f -6 \"//content/dcm2niix/1.2.840.113654.2.55.216614002338888733987350522981366678482/1.2.840.113654.2.55.216614002338888733987350522981366678482_0_OPA_GE_HSQX_BONE_340_2.5_120_56_0.1_1.5_19990102000000_3.nii\"\n", - "Conversion required 5.185668 seconds (0.251798 for core code).\n" + "Convert 130 DICOM as /content/dcm2niix/1.2.840.113654.2.55.216614002338888733987350522981366678482/1.2.840.113654.2.55.216614002338888733987350522981366678482_0,OPA,GE,HSQX,BONE,340,2.5,120,56,0.1,1.5_19990102000000_3 (512x512x130x1)\n", + "Compress: \"/usr/bin/pigz\" -b 960 -n -f -6 \"/content/dcm2niix/1.2.840.113654.2.55.216614002338888733987350522981366678482/1.2.840.113654.2.55.216614002338888733987350522981366678482_0,OPA,GE,HSQX,BONE,340,2.5,120,56,0.1,1.5_19990102000000_3.nii\"\n", + "Conversion required 4.998344 seconds (0.265265 for core code).\n", + "\n" ] }, { @@ -701,7 +806,7 @@ "text/plain": [ "
" ], - "image/png": 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\n" + "image/png": 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\n" }, "metadata": {} }, @@ -710,12 +815,13 @@ "name": "stdout", "text": [ "Copying files from IDC buckets..\n", - "Done in 0.628309 seconds.\n", - "Chris Rorden's dcm2niiX version v1.0.20181125 (JP2:OpenJPEG) GCC9.3.0 (64-bit Linux)\n", + "Done in 1.61235 seconds.\n", + "Chris Rorden's dcm2niiX version v1.0.20211006 (JP2:OpenJPEG) GCC11.2.0 x86-64 (64-bit Linux)\n", "Found 128 DICOM file(s)\n", - "Convert 128 DICOM as //content/dcm2niix/1.2.840.113654.2.55.22770087029972268579113866309746562015/1.2.840.113654.2.55.22770087029972268579113866309746562015_1_OPA_GE_HSQX_STANDARD_380_2.5_120_56_0.1_1.5_20000102000000_2 (512x512x128x1)\n", - "compress: \"/usr/bin/pigz\" -n -f -6 \"//content/dcm2niix/1.2.840.113654.2.55.22770087029972268579113866309746562015/1.2.840.113654.2.55.22770087029972268579113866309746562015_1_OPA_GE_HSQX_STANDARD_380_2.5_120_56_0.1_1.5_20000102000000_2.nii\"\n", - "Conversion required 3.568104 seconds (0.243330 for core code).\n" + "Convert 128 DICOM as /content/dcm2niix/1.2.840.113654.2.55.22770087029972268579113866309746562015/1.2.840.113654.2.55.22770087029972268579113866309746562015_1,OPA,GE,HSQX,STANDARD,380,2.5,120,56,0.1,1.5_20000102000000_2 (512x512x128x1)\n", + "Compress: \"/usr/bin/pigz\" -b 960 -n -f -6 \"/content/dcm2niix/1.2.840.113654.2.55.22770087029972268579113866309746562015/1.2.840.113654.2.55.22770087029972268579113866309746562015_1,OPA,GE,HSQX,STANDARD,380,2.5,120,56,0.1,1.5_20000102000000_2.nii\"\n", + "Conversion required 3.456564 seconds (0.219700 for core code).\n", + "\n" ] }, { @@ -724,7 +830,7 @@ "text/plain": [ "
" ], - "image/png": 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\n" + "image/png": 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OQ0RERERERoRFO9EbKnif3c+Td9mJiIiIiEi7WLQTvYHs3DwcuXofAB+NJyIiIiIi7WPRTvQGTtxMQ0Z2LhysLdCouq3YcYiIiIiIyMiwaCd6AxGXkgEAXTzlkEolIqchIiIiIiJjo9dFe15eHmbOnAl3d3dYWVmhVq1amDNnDgRBULcRBAGzZs2Ck5MTrKys4Ofnh2vXromYmsoLQRCw/1IqAOAtLweR0xARERERkTHS66L9m2++wYoVK7B06VJcvnwZ33zzDebPn48lS5ao28yfPx+LFy9GeHg4oqOjUbFiRQQEBCArK0vE5FQeXLijRLIyCxXMTdC6VhWx4xARERERkREyFTvAqxw/fhzvvPMOevToAQCoUaMGfv31V5w8eRJA/p3ORYsWYcaMGXjnnXcAAOvXr4dcLsf27dsxcODAQo+bnZ2N7Oxs9bJSqdTxlZAxKng0vn2dqrA0MxE5DRERERERGSO9vtPeunVrHDhwAFevXgUAnD17FkePHkW3bt0AAAkJCUhOToafn596H5lMhpYtWyIqKqrI44aFhUEmk6k/Li4uur0QMkr7nk31xlHjiYiIiIhIV/T6Tvv06dOhVCrh4eEBExMT5OXl4auvvkJgYCAAIDk5/06nXK5ZNMnlcvW2woSGhiIkJES9rFQqWbhTiSSlPcaV5EeQSoBOHnyfnYiIiIiIdEOvi/bffvsNGzZswMaNG1G/fn2cOXMGEydOhLOzM4YOHVrq41pYWMDCwkKLSam82X85/y67Tw072FU0FzkNEREREREZK70u2qdMmYLp06er30339vbG7du3ERYWhqFDh8LR0REAkJKSAicnJ/V+KSkpaNy4sRiRqZyIePZovD8fjSciIiIiIh3S63faHz9+DKlUM6KJiQlUKhUAwN3dHY6Ojjhw4IB6u1KpRHR0NHx9fcs0K5Ufisc5iE5IA8D32YmIiIiISLf0+k57r1698NVXX8HV1RX169fH6dOn8f333+Ojjz4CAEgkEkycOBFz585FnTp14O7ujpkzZ8LZ2Rm9e/cWNzwZrUPxqchTCajjUAlu9hXFjkNEREREREZMr++0L1myBO+++y7GjBkDT09PTJ48GSNHjsScOXPUbaZOnYpx48ZhxIgRaN68OTIyMrBnzx5YWlqKmJyMWcRljhpPrxYZGYlevXrB2dkZEokE27dv19guCAJmzZoFJycnWFlZwc/PD9euXdNok5aWhsDAQNjY2MDW1hZBQUHIyMjQaHPu3Dm0a9cOlpaWcHFxwfz581/K8vvvv8PDwwOWlpbw9vbGX3/9pfXrJSIiIiLd0eui3draGosWLcLt27fx5MkT3LhxA3PnzoW5+X8Df0kkEsyePRvJycnIysrC/v37UbduXRFTkzHLzs3Dkfj7AFi0U9EyMzPRqFEjLFu2rNDt8+fPx+LFixEeHo7o6GhUrFgRAQEByMrKUrcJDAzExYsXERERgV27diEyMhIjRoxQb1cqlfD394ebmxtiY2Px7bff4osvvsDKlSvVbY4fP45BgwYhKCgIp0+fRu/evdG7d29cuHBBdxdPRERERFolEQRBEDuE2JRKJWQyGRQKBWxsbMSOQ3rsyNX7GLr6JKpaWyA6tAukUonYkUgPvKoPkUgk2LZtm/qVHUEQ4OzsjE8++QSTJ08GACgUCsjlcqxduxYDBw7E5cuX4eXlhZiYGPj4+AAA9uzZg+7du+Off/6Bs7MzVqxYgc8++wzJycnqX2ROnz4d27dvx5UrVwAA7733HjIzM7Fr1y51nlatWqFx48YIDw8v9Fqys7ORnZ2tcW0uLi7sH4moVIz5O5YxXxsRlY3i9iN6faedSN9EXEoGAPh5OrBgp1JJSEhAcnIy/Pz81OtkMhlatmyJqKgoAEBUVBRsbW3VBTsA+Pn5QSqVIjo6Wt2mffv2Gk8eBQQEID4+Hg8fPlS3ef48BW0KzlOYsLAwyGQy9cfFxeXNL5qIiIiISo1FO1ExCYKA/ZdSAfDReCq95OT8X/zI5Zr/huRyuXpbcnIyHBwcNLabmprCzs5Oo01hx3j+HEW1KdhemNDQUCgUCvUnKSmppJdIRERERFqk16PHE+mTC3eUSFZmoYK5CVrXqiJ2HCKdsLCwgIWFhdgxiIiIiOgZ3mknKqaCR+Pb16kKSzMTkdOQoXJ0dAQApKSkaKxPSUlRb3N0dERqaqrG9tzcXKSlpWm0KewYz5+jqDYF24mIiIhI/7FoJyqmfZfyix8/PhpPb8Dd3R2Ojo44cOCAep1SqUR0dDR8fX0BAL6+vkhPT0dsbKy6zcGDB6FSqdCyZUt1m8jISOTk5KjbREREoF69eqhcubK6zfPnKWhTcB4iIiIi0n8s2omKISntMa4kP4JUAnT2cHj9DlSuZWRk4MyZMzhz5gyA/MHnzpw5g8TEREgkEkycOBFz587Fjh07cP78eQwZMgTOzs7qEeY9PT3RtWtXDB8+HCdPnsSxY8cwduxYDBw4EM7OzgCAwYMHw9zcHEFBQbh48SI2b96MH374ASEhIeocEyZMwJ49e7BgwQJcuXIFX3zxBU6dOoWxY8eW9Y+EiKhM5eXlYebMmXB3d4eVlRVq1aqFOXPm4PlJkwRBwKxZs+Dk5AQrKyv4+fnh2rVrIqYmIioc32knKob9l/PvsvvUsINdRfPXtKby7tSpU+jUqZN6uaCQHjp0KNauXYupU6ciMzMTI0aMQHp6Otq2bYs9e/bA0tJSvc+GDRswduxYdOnSBVKpFP369cPixYvV22UyGfbt24fg4GA0a9YMVapUwaxZszTmcm/dujU2btyIGTNm4NNPP0WdOnWwfft2NGjQoAx+CkRE4vnmm2+wYsUKrFu3DvXr18epU6cwbNgwyGQyjB8/HgAwf/58LF68GOvWrYO7uztmzpyJgIAAXLp0SaM/JiISG+dpB+fZpNcbvOoEjt/4FzN6eOLjdjXFjkN6xpj7EGO+NiLSPbH6kJ49e0Iul+Pnn39Wr+vXrx+srKzwf//3fxAEAc7Ozvjkk08wefJkAIBCoYBcLsfatWsxcODA156D/SMRvSnO006kJYrHOYhOSAMA+HnyfXYiIiJ917p1axw4cABXr14FAJw9exZHjx5Ft27dAOS/tpScnAw/Pz/1PjKZDC1btkRUVFShx8zOzoZSqdT4EBGVBT4eT/Qah6+mIk8loI5DJdSoUlHsOERERPQa06dPh1KphIeHB0xMTJCXl4evvvoKgYGBAIDk5PwZYeRyzV/Gy+Vy9bYXhYWF4csvv9RtcCKiQvBOO9FrFIwa/xZHjSciIjIIv/32GzZs2ICNGzciLi4O69atw3fffYd169aV+pihoaFQKBTqT1JSkhYTExEVjXfaiV4hOzcPR+LvA2DRTkREZCimTJmC6dOnq99N9/b2xu3btxEWFoahQ4fC0dERAJCSkgInJyf1fikpKWjcuHGhx7SwsICFhYXOsxMRvYh32ole4cTNNGRk56KqtQUaVbcVOw4REREVw+PHjyGVan7NNTExgUqlAgC4u7vD0dERBw4cUG9XKpWIjo6Gr69vmWYlInod3mkneoX9zx6N9/N0gFQqETkNERERFUevXr3w1VdfwdXVFfXr18fp06fx/fff46OPPgIASCQSTJw4EXPnzkWdOnXUU745Ozujd+/e4oYnInoBi3aiIgiCoJ6fnY/GExERGY4lS5Zg5syZGDNmDFJTU+Hs7IyRI0di1qxZ6jZTp05FZmYmRowYgfT0dLRt2xZ79uzhHO1EpHc4Tzs4zyYV7vw/CvRaehRWZiY4PestWJqZiB2J9JQx9yHGfG1EpHvG3IcY87URUdkobj/CO+1ERYi4lD/lS/u6VViwlwPZ2dmIjo7G7du38fjxY1StWhVNmjSBu7u72NGIiIiIqBxj0U5UhIjLqQCAt7wcRU5CunTs2DH88MMP2LlzJ3JyciCTyWBlZYW0tDRkZ2ejZs2aGDFiBEaNGgVra2ux4xIRERFROcPR44kKkZT2GJfvKSGVAJ09HMSOQzry9ttv47333kONGjWwb98+PHr0CP/++y/++ecfPH78GNeuXcOMGTNw4MAB1K1bFxEREWJHJiIiIqJyhnfaiQpRMACdTw072FU0FzkN6UqPHj2wZcsWmJmZFbq9Zs2aqFmzJoYOHYpLly7h3r17ZZyQiIiIiMo7Fu1EhVCPGu/JUeON2ciRI4vd1svLC15eXjpMQ0RERET0Mj4eT/QCxZMcRN9MA8Cp3sqzmzdv4uLFi1CpVGJHISIiIqJyjEU70QsOx6ciVyWgjkMl1KhSUew4pGM5OTn4/PPP0atXL3z11VfIy8vDoEGDUKdOHTRs2BANGjTArVu3xI5JREREROUUi3aiF+y79OzReN5lLxemT5+OFStWwNHREatXr0bfvn1x+vRpbNy4EZs2bYKpqSk+++wzsWMSERERUTnFd9qJnvM0V4Uj8fcBAH4s2suFP/74A2vXrkX37t1x9epVeHh44M8//0S3bt0AAA4ODggMDBQ5JRERERGVV7zTTvScEzf/RUZ2LqpaW6BxdVux41AZuHv3Lho1agQAqFu3LiwsLFC7dm319rp16yI5OVmseERERERUzrFoJ3pOxLNH4/08HSCVSkROQ2UhLy9PY8o3U1NTmJiYqJelUikEQRAjGhERERERH48nKiAIwn9TvfHR+HJl7969kMlkAACVSoUDBw7gwoULAID09HQRkxERERFReceineiZi3eVuKfIgpWZCVrXqiJ2HCpDQ4cO1Vh+cf52iYRPXRARERGROFi0Ez1TMGp8+7pVYGlm8prWZCw4DzsRERER6TMW7UTPRKinenMUOQkREZFxuXXrFs6cOYPbt2/j8ePHqFq1Kpo0aQJfX19YWlqKHY+ISK+xaC8hQRBw5Op9nLiZhundPMSOQ1qSlPYYl+8pIZUAnT0cxI5DZSgyMrJY7dq3b6/jJERExue3334DADRu3BhyuRzOzs6wsrJCWloabty4AUtLSwQGBmLatGlwc3MTOS0RkX5i0V5CdxVZCFp3CnkqAT0bOqFBNZnYkUgLDjwbgM7HzQ52Fc1FTkNlqWPHjup31osaJV4ikSAvL68sYxERGbwmTZqoZ+O4cOECvLy8NLZnZ2cjKioKmzZtgo+PD5YvX47+/fuLEZWISK9xyrcSqmZrhbcbOQMAlh++LnIa0pYIjhpfblWuXBkuLi6YOXMmrl27hocPH770SUtLEzsmEZHB+frrr3Hw4EEAQPXq1V/abmFhgY4dOyI8PBxXrlxBzZo1yzoiEZFBYNFeCqM71gIA7L6QjOupGSKnoTeleJKD6Jv5RRmL9vLn3r17+OabbxAVFQVvb28EBQXh+PHjsLGxgUwmU3+IiKhkAgICit3W3t4ezZo102EaIiLDVaLH41UqFY4cOYK///77pYFE/Pz84OLioquceqWu3Br+XnLsu5SC8CM38F3/RmJHojdwOD4VuSoBdRwqoUaVimLHoTJmbm6O9957D++99x4SExOxdu1ajB07FtnZ2Rg6dCi+/PJLmJryTSIiIm0RBAGHDh3CkydP0Lp1a1SuXFnsSEREeq1Yd9qfPHmCuXPnwsXFBd27d8fu3buRnp4OExMTXL9+HZ9//jnc3d3RvXt3nDhxQteZ9cKYTrUBANtP38E/Dx+LnIbeRMGo8X68y17uubq6YtasWdi/fz/q1q2Lr7/+GkqlUuxYREQGKz09HQDg6+uL4cOHQ6lUol27dvDz80OvXr3g6emJc+fOiRuSiEjPFator1u3Ls6dO4dVq1ZBqVQiKioKW7Zswf/93//hr7/+QmJiIm7cuIF27dph4MCBWLVqla5zi66xiy3a1q6CXJWAVZE3xY5DpfQ0V4Uj8fcB8NH48i47OxsbN26En58fGjRogCpVquDPP/+EnZ2d2NGIiAzWjBkzAAB9+/bF+fPn0bVrV+Tl5SEqKgrR0dHw9PTEZ599JnJKIiL9JhGKGi75OZcvX4anp2exDpiTk4PExETUqlXrjcOVFaVSCZlMBoVCARsbm2Lvd/z6Awz+KRoWplIcndYZVa0tdJiSdCHy6n0MWX0SVa0tEB3aBVKpROxIVMZOnjyJNWvWYNOmTahRowaGDRuG999/v0TFemn7EENgzNdGRLrn7OyMe/fuQaFQ4NGjR3BxccHBgwfRsWNHAPl98Ntvv43k5GRxg5YC+0cielPF7UeK9aJmcQt2ADAzMzOogv1N+NayR2MXW5xJSsfqYwmY1pXzthsa9aPxng4s2MupVq1awdXVFePHj1cPgnT06NGX2r399ttlHY2IyOClpqaq/16tWjVYWlpqjIHk6uqK+/fvixGNiMhglHp0pdzcXPz44484fPgw8vLy0KZNGwQHB8PS0lKb+fSaRCJBcKfaGL7+FP4v6jZGdagFmZWZ2LGomARBwP7LBUU7H40vzxITEzFnzpwit3OediKi0lGpVBrLJiYmkEj++yX5838nIqLClbpoHz9+PK5evYq+ffsiJycH69evx6lTp/Drr79qM5/e6+LhgHpya8SnPML/nbiN4GcD1JH+u3hXiXuKLFiZmaBN7SpixyGRvPiFkoiItC88PByWlpbIzc3F2rVrUaVK/n93Hz16JHIyIiL9V+yifdu2bejTp496ed++fYiPj4eJiQmA/Lk4W7Vqpf2Eek4qlWBMp1qYsOkMfj6agI/auMPK3ETsWFQM+549Gt++bhVYmvF/MyIiIm1zcXFBYmIili1bBqlUCkdHR/zyyy8abVxdXUVKR0RkGIo1ejwArF69Gr1798bdu3cBAE2bNsWoUaOwZ88e7Ny5E1OnTkXz5s11FlSf9fB2gqtdBaRlPsWmmESx41Ax/fc+Ox+NL69KMkXl48ePcfHiRR2mISIyPufPn1f/mZCQUOSHiIiKVuyifefOnRg0aBA6duyIJUuWYOXKlbCxscFnn32GmTNnwsXFBRs3btRlVr1laiLFqA75g++tjLyJp7l83Fbf/fPwMS7fU0IqAbqwaC+3PvjgAwQEBOD3339HZmZmoW0uXbqETz/9FLVq1UJsbKxWzpuXl4eZM2fC3d0dVlZWqFWrFubMmYPnJ/MQBAGzZs2Ck5MTrKys4Ofnh2vXrmkcJy0tDYGBgbCxsYGtrS2CgoKQkZGh0ebcuXNo166devCn+fPna+UaiIiIiKhslOid9vfeew8BAQGYOnUqAgICEB4ejgULFugqm0Hp16waFu2/inuKLGw/fQcDmru8ficSzf5nd9l93OxgV9Fc5DQklkuXLmHFihWYMWMGBg8ejLp168LZ2RmWlpZ4+PAhrly5goyMDPTp0wf79u2Dt7e3Vs77zTffYMWKFVi3bh3q16+PU6dOYdiwYZDJZBg/fjwAYP78+Vi8eDHWrVsHd3d3zJw5EwEBAbh06ZJ6wM/AwEDcu3cPERERyMnJwbBhwzBixAj1L1CVSiX8/f3h5+eH8PBwnD9/Hh999BFsbW0xYsQIrVwLEdGrPHnyRGM5NDQU2dnZ6mUTExPMmTOnXA1kTERUUsWap70wkZGRCA4ORteuXQ2+s9XWPJs//X0Tc/+8DPcqFbE/pANMOIWY3gr86QSOXf8Xn3X3xPD2NcWOQ3rg1KlTOHr0KG7fvo0nT56gSpUqaNKkCTp16vTaOdtL2of07NkTcrkcP//8s3pdv379YGVlhf/7v/+DIAhwdnbGJ598gsmTJwMAFAoF5HI51q5di4EDB+Ly5cvw8vJCTEwMfHx8AAB79uxB9+7d8c8//8DZ2RkrVqzAZ599huTkZJib5/9yavr06di+fTuuXLlSrJ8L5yEmojexcOFChISEqPsQa2tr1K9fH1ZWVgCAK1euYOrUqZg0aZLISUuO/SMRvani9iPFfjw+MTERAwYMgLe3NwIDA1GnTh3ExsaiQoUKaNSoEXbv3q2V4IZsUAtX2FYwQ8KDTOy+cE/sOFQExZMcRN9MAwD4efHReMrn4+ODiRMnYuHChQgPD8fcuXPRr1+/1xbspdG6dWscOHAAV69eBQCcPXsWR48eRbdu3QAACQkJSE5Ohp+fn3ofmUyGli1bIioqCgAQFRUFW1tbdcEOAH5+fpBKpYiOjla3ad++vbpgB/IHDY2Pj8fDhw8LzZadnQ2lUqnxISIqrd9///2ldRs3bsShQ4dw6NAhfPvtt/jtt99ESEZEZDiKXbQPGTIEUqkU3377LRwcHDBy5EiYm5vjyy+/xPbt2xEWFoYBAwboMqveq2hhimGt3QEAyw7dQCkfYiAdOxyfilyVgNoOleBepaLYcagcmj59OgYOHAgPDw+YmZmhSZMmmDhxIgIDAwEAycnJAAC5XPOXSnK5XL0tOTkZDg4OGttNTU1hZ2en0aawYzx/jheFhYVBJpOpPy4ufNWHiErv5s2bGsuWlpaQSv/7+tmiRQtcunSprGMRERmUYhftp06dwldffYWuXbvi+++/x7lz59TbPD09ERkZqXFXSFvu3LmD999/H/b29rCysoK3tzdOnTql3l6cwZrK0tDWbqhoboLL95Q4HH9ftBxUtIJR49/iXXYSyW+//YYNGzZg48aNiIuLw7p16/Ddd99h3bp1YkdDaGgoFAqF+pOUlCR2JCIyYAqFQmP5/v37qFGjhnpZpVJpvONOREQvK3bR3qxZM8yaNQv79u3DtGnTCh2QSdsDGz18+BBt2rSBmZkZdu/ejUuXLmHBggWoXLmyuk3BYE3h4eGIjo5GxYoVERAQgKysLK1mKS7bCuYIbOUGAFh26LooGahoT3NVOPLslyks2kksU6ZMUd9t9/b2xgcffIBJkyYhLCwMAODo6AgASElJ0dgvJSVFvc3R0RGpqaka23Nzc5GWlqbRprBjPH+OF1lYWMDGxkbjQ0RUWs7Ozq/cfu7cOVSvXr2M0hARGaZiF+3r169HdnY2Jk2ahDt37uDHH3/UZS4A+SMsu7i4YM2aNWjRogXc3d3h7++PWrXyp1cTBAGLFi3CjBkz8M4776Bhw4ZYv3497t69i+3bt+s8X1E+busOcxMpTt1+iJMJaaLloJeduPkvHmXnokolCzSubit2HCqnHj9+rPF4KJA/grJKlT9dpLu7OxwdHXHgwAH1dqVSiejoaPj6+gIAfH19kZ6erjEN3cGDB6FSqdCyZUt1m8jISOTk5KjbREREoF69ehq//CQi0hV/f38AKPRmypMnT/Dll1+iR48eZR2LiMigFLtod3Nzwx9//IGLFy9iw4YNr/3NqTbs2LEDPj4+6N+/PxwcHNCkSROsWrVKvb04gzUVRtcDLTnYWKK/T/5vjXm3Xb/sv5x/l9HP0wFSju5PRdD1kzq9evXCV199hT///BO3bt3Ctm3b8P3336NPnz4AAIlEgokTJ2Lu3LnYsWMHzp8/jyFDhsDZ2Rm9e/cGkP9aUteuXTF8+HCcPHkSx44dw9ixYzFw4EB1/zx48GCYm5sjKCgIFy9exObNm/HDDz8gJCREp9dHRFTgk08+AZA/2Oe3336L//3vf/jf//6H+fPno169enj48CE+/fRTkVMSEem3YhXtmZmZJTpoSdsX5ebNm1ixYgXq1KmDvXv3YvTo0Rg/frz6vc/iDNZUmLIYaGlk+1owkUpw5Op9XLijeP0OpHOCIKjnZ+ej8fQilUqFOXPmoFq1aqhUqZJ68KSZM2dqTM2mDUuWLMG7776LMWPGwNPTE5MnT8bIkSMxZ84cdZupU6di3LhxGDFiBJo3b46MjAzs2bNHY3rNDRs2wMPDA126dEH37t3Rtm1brFy5Ur1dJpNh3759SEhIQLNmzfDJJ59g1qxZnKOdiMpMwYCZdevWxfTp09GnTx/06dMHoaGh8PLywtGjR1/6HkdERJqKNU+7k5MTJkyYgKFDh8LJyanQNoIgYP/+/fj+++/Rvn17hIaGvnE4c3Nz+Pj44Pjx4+p148ePR0xMDKKionD8+HG0adMGd+/e1cg1YMAASCQSbN68udDjZmdnawx6olQq4eLiovV5NidtPoNtp++gu7cjlgc209pxqXQu3FGg55KjsDIzwelZb8HSzETsSKRHZs+ejXXr1mH27NkYPnw4Lly4gJo1a2Lz5s1YtGjRK5/eMea5eo352ohI957vQ3Jzc3H9ev4TiLVr19bJlJplif0jEb2p4vYjpsU52OHDh/Hpp5/iiy++QKNGjeDj4wNnZ2dYWlri4cOHuHTpEqKiomBqaorQ0FCMHDlSKxfh5OQELy8vjXWenp7YsmULAM3Bmp4v2lNSUtC4ceMij2thYQELCwutZHyV0R1rYdvpO9h9IRnXUzNQ26GSzs9JRdv37C57uzpVWLDTS9avX4+VK1eiS5cuGDVqlHp9o0aNcOXKFRGTEREZBzs7O7Ro0ULsGEREBqdYj8fXq1cPW7ZswdWrVzFgwADcuXMHf/zxB1atWoXDhw+jWrVqWLVqFW7duoUxY8bAxEQ7BVGbNm0QHx+vse7q1atwc8sfnb04gzWJqa7cGv5ecggCEH7khthxyj0+Gk+vcufOHdSuXful9SqVSmMgNyIiKp5Ro0bhzp07xWq7efNmbNiwQceJiIgMU7HutBdwdXXFJ598oh5URNcmTZqE1q1bY968eRgwYABOnjyJlStXqt/ZfH6wpjp16sDd3R0zZ87UGKxJbGM61ca+SynYfvoOJvrVQfXKFcSOVC798/AxLt1TQioBuniyaKeXeXl54e+//1b/UrDAH3/8gSZNmoiUiojIcFWtWhWtWrUCAPz0009o167dS09qHj16FJs2bYKzs7PGmBxERPSfEhXtZa158+bYtm0bQkNDMXv2bLi7u2PRokUIDAxUt5k6dSoyMzMxYsQIpKeno23bti8N1iSmxi62aFu7Co5ef4BVkTfx5TsNxI5ULhXcZfdxs4NdRXOR05A+mjVrFoYOHYo7d+5ApVJh69atiI+Px/r167Fr1y6x4xERGZw5c+Zg6NChqFOnDn7++WdMmTJFY7u1tTX8/PywcuVKdO3aVaSURET6r1gD0Rk7XQ8kcvz6Awz+KRoWplIcndYZVa11/z49aQr86QSOXf8Xn3b3wIj2tcSOQ3rq77//xuzZs3H27FlkZGSgadOmmDVrlnqe4aIY82BExnxtRKR7z/cheXl5SExMxJMnT1ClShXUqlULEonhTr/K/pGI3pRWB6KjN+Nbyx6NXWxxJikdq48lYFpXD7EjlSuKJzmIvpkGAHjLy1HkNKTP2rVrh4iICLFjEBEZpcqVK6Ny5cpixyAiMjjFGoiO3oxEIkFwp/wBrn6Jug3FEw5qVZYOx6ciVyWgtkMluFepKHYcIiIiIiKiYmPRXka6eDigntwaGdm5+L8Tt8WOU65EcNR4KobKlSvDzs7upY+9vT2qVauGDh06YM2aNWLHJCKiYrpz5w7ef/992Nvbw8rKCt7e3jh16pR6uyAImDVrFpycnGBlZQU/Pz9cu3ZNxMRERIUrVdH+999/4/3334evr696Ko9ffvkFR48e1Wo4YyKVSjCmU/671D8fTcCTp3kiJyofnuaqcCT+PgDAj6PG0yvMmjULUqkUPXr0wJdffokvv/wSPXr0gFQqRXBwMOrWrYvRo0dj1apVYkclIqLXePjwIdq0aQMzMzPs3r0bly5dwoIFCzQez58/fz4WL16M8PBwREdHo2LFiggICEBWVpaIyYmIXlbid9q3bNmCDz74AIGBgTh9+jSys7MBAAqFAvPmzcNff/2l9ZDGooe3Exbsu4rEtMfYFJOIYW3cxY5k9KIT/sWj7FxUqWSBJi62YschPXb06FHMnTsXo0aN0lj/448/Yt++fdiyZQsaNmyIxYsXY/jw4SKlJCKi4vjmm2/g4uKi8YSUu/t/37sEQcCiRYswY8YMvPPOOwCA9evXQy6XY/v27Rg4cGCZZyYiKkqJ77TPnTsX4eHhWLVqFczMzNTr27Rpg7i4OK2GMzamJlKM6pB/t31l5E08zVWJnMj4FTwa7+fpAKnUcEeoJd3bu3cv/Pz8XlrfpUsX7N27FwDQvXt33Lx5s6yjEREZhdzcXOzfvx8//vgjHj16BAC4e/cuMjIytH6uHTt2wMfHB/3794eDgwOaNGmi8aRUQkICkpOTNfp9mUyGli1bIioqqtBjZmdnQ6lUanyIiMpCiYv2+Ph4tG/f/qX1MpkM6enp2shk1Po1qwYHawvcU2Rh++k7YscxaoIgqOdn5/vs9Dp2dnbYuXPnS+t37twJOzs7AEBmZiasra3LOhoRkcFLTEyEt7c33nnnHQQHB+P+/fxX17755htMnjxZ6+e7efMmVqxYgTp16mDv3r0YPXo0xo8fj3Xr1gEAkpOTAQByueb3A7lcrt72orCwMMhkMvXHxcVF67mJiApT4sfjHR0dcf36ddSoUUNj/dGjR1GzZk1t5TJaFqYmGNG+Jub+eRkrjtxAv2bVYcI7wDpx8a4SdxVZsDIzQZvaVcSOQ3pu5syZGD16NA4dOoQWLVoAAGJiYvDXX38hPDwcABAREYEOHTqIGZOIyCBNnz4dPj4+OHv2LOzt7dXr+/Tpo5NXjlQqFXx8fDBv3jwAQJMmTXDhwgWEh4dj6NChpTpmaGgoQkJC1MtKpZKFOxGViRLfaR8+fDgmTJiA6OhoSCQS3L17Fxs2bMDkyZMxevRoXWQ0OoNauMK2ghkSHmRi94V7YscxWgWPxrerUwWWZiYipyF9N3z4cBw5cgQVK1bE1q1bsXXrVlSoUAFHjhxBUFAQAOCTTz7B5s2bRU5KRGR4jh8/jhkzZsDc3FxjfY0aNdSDGmuTk5MTvLy8NNZ5enoiMTERQP5NKABISUnRaJOSkqLe9iILCwvY2NhofIiIykKJ77RPnz4dKpUKXbp0wePHj9G+fXtYWFhg8uTJGDdunC4yGp2KFqYY1todC/dfxbJDN9DD2wkSCe+2axuneqOSatOmDdq0aSN2DCIio6NSqZCX9/LMOf/8849OXjtq06YN4uPjNdZdvXoVbm5uAPIHpXN0dMSBAwfQuHFjAPl3zqOjo3kTioj0TonvtEskEnz22WdIS0vDhQsXcOLECdy/fx9z5szRRT6jNbS1Gyqam+DyPSUOP5uSjLTnn4ePcemeElIJ0NnDQew4ZGCysrI42BARkRZ17twZixYtUi9LJBJkZGTg888/R/fu3bV+vkmTJuHEiROYN28erl+/jo0bN2LlypUIDg5Wn3/ixImYO3cuduzYgfPnz2PIkCFwdnZG7969tZ6HiOhNlPhOewFzc/OXHjui4rOtYI7AVm5YGXkTSw9dR8d6VXm3XYsKBqBr5lYZ9pUsRE5DhuDx48eYOnUqfvvtN/z7778vbS/sDhERERXPV199hXfffRdeXl7IysrC4MGDce3aNVSpUgW//vqr1s/XvHlzbNu2DaGhoZg9ezbc3d2xaNEiBAYGqttMnToVmZmZGDFiBNLT09G2bVvs2bMHlpaWWs9DRPQmSly09+nTp9DiUiKRwNLSErVr18bgwYNRr149rQQ0Zh+3dcfaY7cQe/shTiakoWVN+9fvRMWy/3IqAD4aT8U3ZcoUHDp0CCtWrMAHH3yAZcuW4c6dO/jxxx/x9ddfix2PiMigVatWDWfPnsWmTZtw7tw5ZGRkICgoCIGBgbCystLJOXv27ImePXsWuV0ikWD27NmYPXu2Ts5PRKQtJS7aZTIZtm/fDltbWzRr1gwAEBcXh/T0dPj7+2Pz5s345ptvcODAAb4b+hoONpbo71MdG6ITsfzwDRbtWqJ4koMTN/PvlL7lVfhgMkQv2rlzJ9avX4+OHTti2LBhaNeuHWrXrg03Nzds2LBB4+4MERGVnKmpKd5//32xYxARGZxSTfk2ePBgLF26FFJp/ivxKpUKEyZMgLW1NTZt2oRRo0Zh2rRpOHr0qNYDG5uR7WthU0wSjly9jwt3FGhQTSZ2JIN3OD4VuSoBtR0qwb1KRbHjkIFIS0tTT1tpY2ODtLQ0AEDbtm05KBER0Rv666+/UKFChZfWP/+kpru7uwjJiIj0X4mL9p9//hnHjh1TF+wAIJVKMW7cOLRu3Rrz5s3D2LFj0a5dO60GNVau9hXwdiNnbDt9B8sPX8fywGZiRzJ4BaPG+3ny0Xgqvpo1ayIhIQGurq7w8PDAb7/9hhYtWmDnzp2wtbUVOx4RkUEbPHgwJBIJBEHQWF+wTiKRoG3btti+fTsqV64sUkoiIv1U4tHjc3NzceXKlZfWX7lyRT1Qk6WlJQdVK4HRHWsBAHZfSMb11AyR0xi2p7kqHHk2Gj/fZ6eSGDZsGM6ePQsgf2rLZcuWwdLSEpMmTcKUKVNETkdEZNi2b9+O5s2bIyIiAgqFAgqFAhEREWjZsiV27dqFyMhI/Pvvv5g8ebLYUYmI9E6J77R/8MEHCAoKwqefformzZsDAGJiYjBv3jwMGTIEAHDkyBHUr19fu0mNWF25Nfy95Nh3KQXhR27gu/6NxI5ksKIT/sWj7FxUqWSBJi62YschAzJp0iT13/38/HDlyhXExsaidu3aaNiwoYjJiIgM3/Tp0/HTTz+hdevW6nVdunSBpaUlRowYgYsXL2LRokX46KOPRExJRKSfSly0L1y4EHK5HPPnz0dKSv5jyHK5HJMmTcK0adMAAP7+/ujatat2kxq5MZ1qY9+lFGw/fQcT/eqgeuWX3/ui1/vv0XgHSKV82oNKz83NDTKZjI/GExFpQUJCAmxsbF5ab2Njg5s3bwIA6tSpgwcPHpR1NCIivVfix+NNTEzw2Wef4d69e0hPT0d6ejru3buHTz/9FCYmJgAAV1dXVK9eXethjVljF1u0rV0FuSoBqyJvih3HIAmCoJ6fne+zU0l988032Lx5s3p5wIABsLe3V09TREREpde4cWNMmTIF9+/fV6+7f/8+pk6dqn5y89q1a3BxcRErIhGR3ipx0f48GxubQn9rSqUzplP+u+2bYpJw/1G2yGkMz8W7StxVZMHKzARt61QROw4ZmPDwcPWXxYiICERERGD37t3o1q0b32knInpDS5cuRUJCAqpXr47atWujdu3aqF69Om7duoWffvoJAJCRkYEZM2aInJSISP+U+PF4APjjjz/w22+/ITExEU+fPtXYFhcXp5Vg5ZFvTXs0drHFmaR0rD6WgGldPcSOZFAKHo1vV6cKLM1MRE5DhiY5OVldtO/atQsDBgyAv78/atSogZYtW4qcjojIsNWpUweXLl3Cvn37cPXqVQBAvXr18NZbb6lnJOrdu7eICYmI9FeJ77QvXrwYw4YNg1wux+nTp9GiRQvY29vj5s2b6Natmy4ylhsSiQTBnWoDAH6Jug3FkxyRExmWgqKdo8ZTaVSuXBlJSUkAgD179sDPzw9A/msXBTNjEBFR6UmlUnTt2hXjx4/H+PHjERAQoDGFMBERFa7Ed9qXL1+OlStXYtCgQVi7di2mTp2KmjVrYtasWUhLS9NFxnKli4cD6smtEZ/yCP934ra6iKdX++fhY1y6p4RUAnT2cBA7Dhmgvn37YvDgwahTpw7+/fdf9S8hT58+jdq1+f9DIqI3lZmZiSNHjhT6pOb48eNFSkVEpP9KXLQnJiaqp+uwsrLCo0ePAORPBdeqVSssXbpUuwnLGalUgjGdamHCpjP4+WgCPmrjDitzPur9OgcupwIAmrlVhn0lC5HTkCFauHAhatSogaSkJMyfPx+VKlUCANy7dw9jxowROR0RkWE7e/YsBgwYgMePHyMzMxN2dnZ48OABKlSoAAcHBxbtRESvUOJnkhwdHdV31F1dXXHixAkA+VN5CIKg3XTlVA9vJ7jaVUBa5lNsikkUO45B4KPx9KbMzMwwefJk/PDDD2jSpIl6/aRJk/Dxxx+LmIyIyPB9+umn6NWrFx4+fAgrKyucOHECt2/fRrNmzfDdd9+JHY+ISK+V+E57586dsWPHDjRp0gTDhg3DpEmT8Mcff+DUqVPo27evLjKWO6YmUozqUAufbjuPlZE3EdjSDeamfOerKIonOThx818AwFtejiKnIUO1fv36V24fMmRIGSUhIjI+58+fx08//QSpVAoTExNkZ2ejZs2amD9/PoYOHcrvkEREr1Dion3lypVQqVQAgODgYNjb2+P48eN4++23MXLkSK0HLK/6NauGRfuv4p4iC9tP38GA5py3tCiH41ORqxJQq2pFuFepKHYcMlATJkzQWM7JycHjx49hbm6OChUqsGgnInoDpqam6kHnHBwckJiYCE9PT8hkMvUgoEREVLgSF+1SqVRjpM+BAwdi4MCBWg1FgIWpCUa0r4m5f17GiiM30K9ZdZhIJWLH0kv7n73Pzrvs9CYePnz40rpr165h9OjRnKediOgNNWzYEDExMahTpw46dOiAWbNm4cGDB/jll1/QoEEDseMREem1Ej9zvWfPHhw9elS9vGzZMjRu3BiDBw8u9Esvld6gFq6wrWCGhAeZ2H3hnthx9NLTXBUOXyko2vk+O2lXnTp18PXXX790F56IiEpm1qxZcHJyAgB89dVXqFy5MkaPHo379+9j5cqVIqcjItJvJS7ap0yZAqVSCSD//aSQkBB0794dCQkJCAkJ0XrA8qyihSmGtXYHACw7dIMD/RUi6ua/eJSdiyqVzNHExVbsOGSETE1NcffuXbFjEBEZtKZNm6JTp04A8h+P37NnD5RKJWJjY9GoUSOR0xER6bcSPx6fkJAALy8vAMCWLVvQq1cvzJs3D3FxcejevbvWA5Z3Q1u7YWXkDVy+p8Th+PvoxDnI1S7eVeCT384CyH80XsrXB+gN7NixQ2NZEATcu3cPS5cuRZs2bURKRURkHJ48eQJTU1NUqFABAHD79m1s27YNXl5e8Pf3FzkdEZF+K/GddnNzczx+/BgAsH//fnVHa2dnp74DT9pjW8Ecga3cAABLD13n3fZnTtz8FwN/PIEHGdnwcLTGJ/51xY5EBq53794an759++KLL75Aw4YNsXr1aq2f786dO3j//fdhb28PKysreHt749SpU+rtgiCoHye1srKCn58frl27pnGMtLQ0BAYGwsbGBra2tggKCkJGRoZGm3PnzqFdu3awtLSEi4sL5s+fr/VrISJ6nUGDBqln6UhPT0eLFi2wYMECvPPOO1ixYoXI6YiI9FuJi/a2bdsiJCQEc+bMwcmTJ9GjRw8AwNWrV1G9enWtByTg47buMDeRIvb2Q5xMSBM7juj2XUzGkNUn8Sg7Fy1q2GHzSF9UqWQhdiwycCqVSuOTl5eH5ORkbNy4Uf0eprY8fPgQbdq0gZmZGXbv3o1Lly5hwYIFqFy5srrN/PnzsXjxYoSHhyM6OhoVK1ZEQEAAsrKy1G0CAwNx8eJFREREYNeuXYiMjMSIESPU25VKJfz9/eHm5obY2Fh8++23+OKLL/j+KBGVubNnz6Jdu3YAgD/++AOOjo64ffs21q9fj8WLF4ucjohIv5X48filS5dizJgx+OOPP7BixQpUq1YNALB792507dpV6wEJcLCxRH+f6tgQnYjlh2+gZU17sSOJ5rdTSZi+5RxUAuDnKcfSwU1gaWYidiyiEvnmm2/g4uKCNWvWqNe5u7ur/y4IAhYtWoQZM2bgnXfeAZA/j7xcLsf27dsxcOBAXL58GXv27EFMTAx8fHwAAEuWLEH37t3x3XffwdnZGRs2bMDTp0+xevVqmJubo379+jhz5gy+//57jeL+ednZ2cjOzlYv8wkqItKGJ0+ewNraGgCwb98+9O3bF1KpFK1atcLt27dFTkdEpN9KfKfd1dUVu3btwtmzZxEUFKRev3DhQv6mVIdGtq8FE6kER67ex4U7CrHjiCL8yA1M/SO/YH+3WXWEv9+UBTsZpB07dsDHxwf9+/eHg4MDmjRpglWrVqm3JyQkIDk5GX5+fup1MpkMLVu2RFRUFAAgKioKtra26oIdAPz8/CCVShEdHa1u0759e5ibm6vbBAQEID4+vsjZPsLCwiCTydQfFxcXrV47EZVPNWvWxPbt25GUlIS9e/eqX69MTU2FjY2NyOmIiPRbiYv2xMTEV35IN1ztK+DtRs4AgOWHr4ucpmwJgoB5f13G17uvAABGtq+Jb99tCFOTEv/zJdILN2/exIoVK1CnTh3s3bsXo0ePxvjx47Fu3ToAQHJyMgBALtecxlAul6u3JScnw8FBc2BKU1NT2NnZabQp7BjPn+NFoaGhUCgU6k9SUtIbXi0RETB16lRMnjwZNWrUQMuWLeHr6wsg/657kyZNRE5HRKTfSvx4fI0aNSCRFD1Kd15e3hsFoqKN7lgL207fwe4LybiemoHaDpXEjqRzuXkqTNtyHlvi/gEAhHbzwMgOtURORfRmVCoVfHx8MG/ePABAkyZNcOHCBYSHh2Po0KGiZrOwsICFBceIICLt6t27N/z9/XHv3j2NKd66dOmCPn36iJiMiEj/lfhW5enTpxEXF6f+REdHIzw8HHXr1sXvv/+ui4z0TF25Nfy95BCE/EfFjV1WTh5G/V8stsT9AxOpBPPfbciCnYyCk5OTeurMAp6enuqnlRwdHQEAKSkpGm1SUlLU2xwdHZGamqqxPTc3F2lpaRptCjvG8+cgIiorjo6OaNKkCaTS/75+tmjRAh4eHiKmIiLSfyW+0/78b0cL+Pj4wNnZGd9++y369u2rlWBUuDGdamPfpRRsP30HE/3qoHrlCmJH0gnFkxx8vC4GMbcewsJUiqWDm+ItL/nrdyQqpRo1auCjjz7Chx9+CFdXV52eq02bNoiPj9dYd/XqVbi55U/v6O7uDkdHRxw4cACNGzcGkD8gXHR0NEaPHg0A8PX1RXp6OmJjY9GsWTMAwMGDB6FSqdCyZUt1m88++ww5OTkwMzMDAERERKBevXoaI9UTEelaz549YWpa9NfOgwcPlmEaIiLDorWXguvVq4eYmBhtHY6K0NjFFm1rV0GuSsCqyJtix9GJVGUW3vsxCjG3HsLawhTrP2rBgp10buLEidi6dStq1qyJt956C5s2bdIYRV2bJk2ahBMnTmDevHm4fv06Nm7ciJUrVyI4OBgAIJFIMHHiRMydOxc7duzA+fPnMWTIEDg7O6N3794A8u/Md+3aFcOHD8fJkydx7NgxjB07FgMHDoSzc/74F4MHD4a5uTmCgoJw8eJFbN68GT/88ANCQkJ0cl1EREXx9vZGo0aN1B8vLy88ffoUcXFx8Pb2FjseEZFekwiCIJRkhxen/xEEAffu3cMXX3yBK1eu4MyZM9rMVyaUSiVkMhkUCoVBjGB6/MYDDF4VDQtTKY5O64yq1sbz/untfzPxwc8nkZj2GFUqWWD9Ry3g5az//5uQ8YiLi8PatWvx66+/Ii8vD4MHD8ZHH32Epk2bFrlPafqQXbt2ITQ0FNeuXYO7uztCQkIwfPhw9XZBEPD5559j5cqVSE9PR9u2bbF8+XLUrVtX3SYtLQ1jx47Fzp07IZVK0a9fPyxevBiVKv033sW5c+cQHByMmJgYVKlSBePGjcO0adOK/fMwtP6RiPTL6/qQL774AhkZGfjuu+9ESPdm2D8S0Zsqbj9S4qJdKpW+NBCdIAhwcXHBpk2b1KOBGhJD63QFQUCf5cdxJikdozvWwrSuxvEu2MW7CgxdHYMHGdlwtauAX4JawM2+otixqJzKycnB8uXLMW3aNOTk5MDb2xvjx4/HsGHDXuoDDa0PKQljvjYi0r3X9SHXr19HixYtkJaWJkK6N8P+kYjeVHH7kRK/037o0CGNZalUiqpVq6J27dqvfFeJtEcikSC4U20MX38Kv0TdxqgOtSCzMhM71hs5cfNfDF93Co+yc+HpZIN1HzWHg7Wl2LGoHMrJycG2bduwZs0aREREoFWrVggKCsI///yDTz/9FPv378fGjRvFjklEZBSioqJgacn/3hMRvUqJq+wOHTroIgeVUBcPB9STWyM+5RF+ibqFsZ3riB2p1PZdTMbYX0/jaa4KLWrYYdVQH4P/JQQZnri4OKxZswa//vorpFIphgwZgoULF2qMatynTx80b95cxJRERIYpMDBQPSAm8N/rladOncLMmTNFTEZEpP94a9xASaUSjOlUCxM2ncHqY7cQ1LYmrMxNxI5VYr/FJGH61nNQCYCfpxxLBzeBpZnhXQcZvubNm+Ott97CihUr0Lt3b40vlwXc3d0xcOBAEdIRERk2mUym0a9KpVLUq1cPs2fPhr+/v4jJiIj0H4t2A9bD2wkL9l1FYtpjbIpJxLA27mJHKpHwIzfw9e4rAID+zaojrK83TE20NqEBUbHl5eVh9erVePvtt185FVrFihWxZs2aMkxGRGQcli9fzve+iYhKiRWSATM1kWJUh1oAgJWRN/E0VyVyouIRBAHz/rqsLthHtq+J+e82ZMFOojExMcHIkSORnp4udhQiIiIiIg2skgxcv2bV4GBtgXuKLGw/fUfsOK+Vm6fC5N/PYeWzOeZDu3kgtLvnS6NxE5W1Bg0a4ObNm2LHICIiIiLSUOyiXalUFvrJy8vTZT56DQtTE4xoXxMAsOLIDeSpSjSDX5nKysnDyF9isSXuH5hIJZj/bkOMfPakAJHY5s6di8mTJ2PXrl24d+/eS30dEREREZEYiv1Ou62tbaF3Q01MTODu7o7Jkydj+PDhWg1HxTOohSuWHrqOhAeZ2H3hHno2dBY70ksUT3Lw8boYxNx6CAtTKZYOboq3vORixyJS6969OwDg7bff1ujrBEGARCLhLyiJiIiISBTFLtpfnJ+9QHp6OmJjYzFlyhSYmppi2LBhWgv3oq+//hqhoaGYMGECFi1aBADIysrCJ598gk2bNiE7OxsBAQFYvnw55PLyUxBWtDDFsNbuWLj/KpYduoEe3k569bh5qjILQ1afxJXkR7C2MMVPQ33Qsqa92LGINBTVxxER0Zu7dOkSWrVqVei27du3o3fv3mUbiIjIgBS7aH/V/OzvvPMOatSogSVLluisaI+JicGPP/6Ihg0baqyfNGkS/vzzT/z++++QyWQYO3Ys+vbti2PHjukkh74a2toNKyNv4PI9JQ7H30cnDwexIwEAbj3IxAero5GU9gRVKllg/Uct4OXM0WNJ/7yqjyMiojdT8N3M3V1zppstW7ZgyJAhyMzMFCkZEZH+09pAdB06dMD169e1dTgNGRkZCAwMxKpVqzSmY1IoFPj555/x/fffo3PnzmjWrBnWrFmD48eP48SJEzrJoq9sK5gjsJUbAGDpoesQBPHfbb94V4F3w6OQlPYErnYVsHV0axbspNfS09OxYMECfPzxx/j444+xcOFCKBQKsWMRERm8IUOGwM/PD8nJyep1mzdvxpAhQ7B27VrxghERGQCtFe0KhQIymUxbh9MQHByMHj16wM/PT2N9bGwscnJyNNZ7eHjA1dUVUVFRRR4vOzvbKAeZ+ritO8xNpIi9/RAnE9JEzXLi5r8Y+OMJPMjIhqeTDf4Y7QtX+wqiZiJ6lVOnTqFWrVpYuHAh0tLSkJaWhu+//x61atVCXFyc2PGIiAzap59+iu7du8PPzw9paWnYuHEjhg0bhvXr16N///5ixyMi0mtaKdpzcnLw7bffomXLlto4nIZNmzYhLi4OYWFhL21LTk6Gubk5bG1tNdbL5XKN3+S+KCwsDDKZTP1xcXHRdmxRONhYor9PdQDAssM3RMux92Iyhqw+iUfZuWjhbodNI1rBwdpStDxExTFp0iS8/fbbuHXrFrZu3YqtW7ciISEBPXv2xMSJE8WOR0Rk8JYsWYJGjRqhVatWGD58OH799Vf069dP7FhERHqv2O+09+3bt9D1CoUCFy9ehEQiwd9//621YACQlJSECRMmICIiApaW2iv6QkNDERISol5WKpVGU7iPbF8Lm2KSEHn1Pi7cUaBBNd08/VCU32KSMH3rOagEwM9TjqWDm8DSzKRMMxCVxqlTp7Bq1SqYmv7XLZqammLq1Knw8fERMRkRkWHasWMHHj9+DAD466+/UKFCBfTt2xd///03Bg0aBIlEgh07dgDIn7mDiIgKV+yivahH311cXNCvXz8EBgZq/fH42NhYpKamomnTpup1eXl5iIyMxNKlS7F37148ffoU6enpGnfbU1JS4OjoWORxLSwsYGFhodWs+sLVvgLebuSMbafvYPnh61ge2KxMzisIAn6MvImvd18BAPRvVh1hfb1haqK1NzCIdMrGxgaJiYnw8PDQWJ+UlARra2uRUhERGa7nR4QfPHiwxrbVq1dj9erVAMBpNYmIXqPYRfuaNWt0maNQXbp0wfnz5zXWDRs2DB4eHpg2bRpcXFxgZmaGAwcOqB+vio+PR2JiInx9fcs8r74Y3bEWtp2+g90XknE9NQO1HSrp9HwqlYCw3Zex6u8EAMDIDjUxvauHXk07R/Q67733HoKCgvDdd9+hdevWAIBjx45hypQpGDRokMjpiIgMj0qlglKphEwmQ3p6OmxsOBgtEVFpFLtoB4ATJ05g586dePr0Kbp06YKuXbvqKhcAwNraGg0aNNBYV7FiRdjb26vXBwUFISQkBHZ2drCxscG4cePg6+tb5Fyg5UFduTX8veTYdykF4Udu4Lv+jXR2rpw8FaZvOY8tcf8AAD7t7oER7Wvp7HxEuvLdd99BIpFgyJAhyM3NBQCYmZlh9OjR+Prrr0VOR0RkfF58UpKIiApX7GeX//jjD7Rp0wY//PADfvrpJ/To0QPfffedLrMVy8KFC9GzZ0/069cP7du3h6OjI7Zu3Sp2LNGN6VQbALD99B388/CxTs6RlZOHUb/EYkvcPzCRSvDtuw1ZsJPBMjc3xw8//ICHDx/izJkzOHPmDNLS0rBw4UKjfZ2GiKisLFy4EJs3b1Yv9+/fH3Z2dqhWrRrOnj2r8/N//fXXkEgkGgOLZmVlITg4GPb29qhUqRL69euHlJQUnWchIiqpYhftYWFhGD58OBQKBR4+fIi5c+di3rx5usxWqMOHD2PRokXqZUtLSyxbtgxpaWnIzMzE1q1bX/k+e3nR2MUWbWtXQa5KwKrIm1o/vuJJDj74ORoHrqTCwlSK8Pebob+PcQzmR+VbhQoV4O3tDW9vb1SowGkKiYi0YfXq1epBfyMiIrB//37s2bMH3bp1w5QpU3R67piYGPz4449o2LChxvpJkyZh586d+P3333HkyBHcvXu3yIGXiYjEVOzH4+Pj47F582aYmOSPBP7JJ59g1qxZSE1NhYODg84CUumN6VQLR68/wKaYJIztXAdVrbVztzBVmYUhq0/iSvIjWFua4uehzdHC3U4rxyYSS1ZWFpYsWYJDhw4hNTUVKpVKYzvnaiciKr3U1FR10b5r1y4MGDAA/v7+qFGjhk6mDC6QkZGBwMBArFq1CnPnzlWvVygU+Pnnn7Fx40Z07twZQP74TZ6enjhx4kShr1lmZ2cjOztbvaxUKnWWm4joecW+0/748WONAUTMzc1haWmJjIwMnQSjN+db0x6NXWyRnavC6mMJWjnmrQeZ6Bd+HFeSH6GqtQU2j/BlwU5GISgoCPPnz4ebmxt69uyJd955R+NDRESlZ2tri6SkJADAnj174OfnByB/9hldjhwfHByMHj16qM9XIDY2Fjk5ORrrPTw84OrqiqioqEKPFRYWBplMpv4Yy3TBRKT/SjQQ3U8//YRKlf4biTw3Nxdr165FlSpV1OvGjx+vvXT0RiQSCYI71cbw9afwS9RtjOpQCzIrs1If78IdBT5cE4MHGdlws6+AXz5qCVd7Pj5MxmHXrl3466+/0KZNG7GjEBEZnV69emHw4MGoU6cO/v33X3Tr1g0AcPr0adSuXVsn59y0aRPi4uIQExPz0rbk5GSYm5u/NBCeXC5HcnJyoccLDQ1FSEiIelmpVLJwJ6IyUeyi3dXVFatWrdJY5+joiF9++UW9LJFIWLTrmS4eDqgnt0Z8yiP8EnULYzvXKdVxTtz8F8PXncKj7Fx4Otlg3UfN4WBtqeW0ROKpVq0a52MnItKRsLAw1K1bF0lJSZg/f776JtC9e/cwZswYrZ8vKSkJEyZMQEREBCwttfN9xcLCggOTEpEoil2037p1S4cxSFekUgnGdKqFCZvOYPWxWwhqWxNW5iYlOsbei8kY9+tpPM1VoYW7HX4a6gMby9LfsSfSRwsWLMC0adMQHh4ONzc3seMQERkVMzMzTJ48+aX1kyZN0sn5YmNjkZqaiqZNm6rX5eXlITIyEkuXLsXevXvx9OnTl6adS0lJ4YDGRKR3SvR4PBmmHt5OWLDvKhLTHmNTTCKGtXEv9r6/xSRh+tZzUAnAW15yLBnUBJZmJSv6iQyBj48PsrKyULNmTVSoUAFmZpq/mEpLSxMpGRGRYdqxY4f6laO//vrrlTNyvP3221o9d5cuXXD+/HmNdcOGDYOHhwemTZsGFxcXmJmZ4cCBA+jXrx+A/EGXExMT4evrq9UsRERvqthF+8GDBzF27FicOHFCY0A6IH8EztatW2PFihVo37691kPSmzE1kWJUh1r4dNt5rIy8icCWbjA3ffUYhIIgIPzITXyz5woAYIBPdczr4w1Tk2KPXUhkUAYNGoQ7d+5g3rx5kMvlkEgkYkciIjJovXv3xrVr1wAAgwcPLrKdRCLR+mB01tbWaNCggca6ihUrwt7eXr0+KCgIISEhsLOzg42NDcaNGwdfX99CR44nIhJTsYv2RYsWYfjw4S8V7AAgk8kwcuRILFy4kEW7nurXrBoW7b+Ke4osbD99BwOaFz1wikolIGz3Zaz6O3/E+ZEdamJ6Vw8WMWTUjh8/jqioKDRq1EjsKERERkGlUqmnRUtPTy/0O6SYFi5cCKlUin79+iE7OxsBAQFYvny52LGIiF5S7NumZ8+eRdeuXYvc7u/vj9jYWK2EIu2zMDXBiPY1AQArjtxAnkootF1OngpT/jinLtg/7e6B0G6eLNjJ6Hl4eODJkydixyAiIh05fPgwFi1apF62tLTEsmXLkJaWhszMTGzdupXvsxORXip20Z6SkvLSO57PMzU1xf3797USinRjUAtX2FYwQ8KDTOy+cO+l7U+e5mHUL7HYEvcPTKQSfNe/EUa0ryVCUqKy9/XXX+OTTz7B4cOH8e+//0KpVGp8iIio9H755Rf07NkTDRo0gLe3N95++22sX78eglD4TQQiIvpPsYv2atWq4cKFC0VuP3fuHJycnLQSinSjooUphrXOH4Ru2aEbGv+hVDzJwZDV0ThwJRUWplL8+H4zvNusulhRicpc165dERUVhS5dusDBwQGVK1dG5cqVYWtri8qVK4sdj4jIIBV81xg3bhzu3LkDb29v1K9fH7dv38aHH36IPn36iJyQiEj/Ffud9u7du2PmzJno2rXrS/NdPnnyBJ9//jl69uyp9YCkXUNbu2Fl5A1cvqfE4fj76OThgFRlFoasPokryY9gbWmKn4c2Rwt3O7GjEpWpQ4cOiR2BiMjobNiwAUD+SPIvfk88ePAgevfujfXr12PIkCFixCMiMggSoZjPJaWkpKBp06YwMTHB2LFjUa9ePQDAlStXsGzZMuTl5SEuLg5yuVyngXVBqVRCJpNBoVDo3SApujDvr8tYGXkTzdwqY0H/Rnj/52j88/AJqlpbYP1HLeDpZPw/AyJtMuY+xJivjYh0r3Pnzjh06FCRfci8efNw5MgR7N27V4R0b4b9IxG9qeL2I8V+PF4ul+P48eNo0KABQkND0adPH/Tp0weffvopGjRogKNHjxpkwV4efdzWHeYmUsTefoheS4/in4dP4GZfAVtGtWbBTuXa33//jffffx+tW7fGnTt3AOS/h3n06FGRkxERGaaLFy++cnu3bt1w9uzZMkpDRGSYSjTptpubG/766y88ePAA0dHROHHiBB48eIC//voL7u7uuspIWuZgY4n+Pvnvqz/KyoWnkw1+H+ULV/sKIicjEs+WLVsQEBAAKysrxMXFITs7GwCgUCgwb948kdMRERmmhw8fvnK7XC5/bRsiovKuREV7gcqVK6N58+Zo0aIFB2gyUGM61YarXQV09nDA5pGt4GBt+fqdiIzY3LlzER4ejlWrVmnMlNGmTRvExcWJmIyIyHDl5eW9cruJiQlyc3PLKA0RkWEq9kB0ZFyq2VrhyJSOnH+d6Jn4+Hi0b9/+pfUymQzp6ellH4iIyAgUDJ0UGBhY6NTBBU81ERFR0Up1p52MAwt2ov84Ojri+vXrL60/evQoatasqdNzf/3115BIJJg4caJ6XVZWFoKDg2Fvb49KlSqhX79+SElJ0dgvMTERPXr0QIUKFeDg4IApU6a8dMfq8OHDaNq0KSwsLFC7dm2sXbtWp9dCRPS8wYMHA8j/BWhhHwcHB44cT0T0GrzTTkQEYPjw4ZgwYQJWr14NiUSCu3fvIioqCpMnT8bMmTN1dt6YmBj8+OOPaNiwocb6SZMm4c8//8Tvv/8OmUyGsWPHom/fvjh27BiA/EdOe/ToAUdHRxw/fhz37t3DkCFDYGZmpn4HPyEhAT169MCoUaOwYcMGHDhwAB9//DGcnJwQEBCgs2siIiqwfPlybNiwAcuXL+cI60REpcSinYgIwPTp06FSqdClSxc8fvwY7du3h4WFBSZPnoxx48bp5JwZGRkIDAzEqlWrMHfuXPV6hUKBn3/+GRs3bkTnzp0BAGvWrIGnpydOnDiBVq1aYd++fbh06RL2798PuVyOxo0bY86cOZg2bRq++OILmJubIzw8HO7u7liwYAEAwNPTE0ePHsXChQtZtBMREREZCD4eT0SE/NdFPvvsM6SlpeHChQs4ceIE7t+/jzlz5ujsnMHBwejRowf8/Pw01sfGxiInJ0djvYeHB1xdXREVFQUAiIqKgre3t8ZUmwEBAVAqleoplqKiol46dkBAgPoYhcnOzoZSqdT4EBEREZF4eKediOg55ubm8PLy0vl5Nm3ahLi4OMTExLy0LTk5Gebm5rC1tdVYL5fLkZycrG7zfMFesL1g26vaKJVKPHnyBFZWVi+dOywsDF9++WWpr4uIiIiItItFOxGVax999FGx2q1evVpr50xKSsKECRMQEREBS0v9mm4xNDQUISEh6mWlUgkXFxcRExERERGVbyzaiahcW7t2Ldzc3NCkSRP11ES6Fhsbi9TUVDRt2lS9Li8vD5GRkVi6dCn27t2Lp0+fIj09XeNue0pKChwdHQHkj3Z/8uRJjeMWjC7/fJsXR5xPSUmBjY1NoXfZAcDCwgIWFhZvfI1EREREpB0s2omoXBs9ejR+/fVXJCQkYNiwYXj//fdhZ2en03N26dIF58+f11g3bNgweHh4YNq0aXBxcYGZmRkOHDiAfv36AcifRz4xMRG+vr4AAF9fX3z11VdITU2Fg4MDACAiIgI2Njbqx/t9fX3x119/aZwnIiJCfQwiIiIi0n8ciI6IyrVly5bh3r17mDp1Knbu3AkXFxcMGDAAe/fu1dmdd2trazRo0EDjU7FiRdjb26NBgwaQyWQICgpCSEgIDh06hNjYWAwbNgy+vr5o1aoVAMDf3x9eXl744IMPcPbsWezduxczZsxAcHCw+k75qFGjcPPmTUydOhVXrlzB8uXL8dtvv2HSpEk6uS4iIiIi0j4W7URU7llYWGDQoEGIiIjApUuXUL9+fYwZMwY1atRARkaGKJkWLlyInj17ol+/fmjfvj0cHR2xdetW9XYTExPs2rULJiYm8PX1xfvvv48hQ4Zg9uzZ6jbu7u74888/ERERgUaNGmHBggX46aefON0bERERkQHh4/FERM+RSqWQSCQQBAF5eXlldt7Dhw9rLFtaWmLZsmVYtmxZkfu4ubm99Pj7izp27IjTp09rIyIRERERiYB32omo3MvOzsavv/6Kt956C3Xr1sX58+exdOlSJCYmolKlSmLHIyIiIqJyjHfaiahcGzNmDDZt2gQXFxd89NFH+PXXX1GlShWxYxERERERAWDRTkTlXHh4OFxdXVGzZk0cOXIER44cKbTd8++TExERERGVFRbtRFSuDRkyBBKJROwYRERERESFYtFOROXa2rVrxY5ARERERFQkDkRHREREREREpKdYtBMRERERERHpKRbtRERERERERHqKRTsRERERERGRnmLRTkRERERERKSnOHo8EREREZGOnUxIQ9SNf4vcLkB47TGE1zR5/RFef5DiHEMQAJWQn1glCPnLqheWn/tTJQDCi8t41faCvz9bj6LbqYT80Or98N9+Lx7nxWyvulbhFT+nV+/3im2v2POV+xXrf9gX9yl5/qJ2KSr3q6+1ZOcoao/SnaOIYxV9qKKvvRTHWjXEB61q2r+iRcmxaCciIiIi0rHom/9i4f6rYscgIh3LU5XityyvwaKdiIiIiEjHGlSTYXBL1yK3S16zv+QVDSSv2PvV+73unK8+rlQigfTZn3huWYJnf0okkEokz9rmL0teaKex/NyfL66X4Nmy9MX9Xjj+8+2eX37WrmA/Cf47T0l+NkX/SArfUJqff1E/95JmKu2/C12fo6THKt3PsKR7vCpXUe0L3+JoY1nkOUqLRTsRERERkY518nBAJw8HsWMQkQHiQHREREREREREeopFOxEREREREZGeYtFOREREREREpKdYtBMRERERERHpKRbtRERERERERHqKRTsRERERERGRnmLRTkRERERERKSnWLQTERERERER6Sm9LtrDwsLQvHlzWFtbw8HBAb1790Z8fLxGm6ysLAQHB8Pe3h6VKlVCv379kJKSIlJiIiIiIiIiIu3R66L9yJEjCA4OxokTJxAREYGcnBz4+/sjMzNT3WbSpEnYuXMnfv/9dxw5cgR3795F3759RUxNREREREREpB2mYgd4lT179mgsr127Fg4ODoiNjUX79u2hUCjw888/Y+PGjejcuTMAYM2aNfD09MSJEyfQqlUrMWITERERERERaYVe32l/kUKhAADY2dkBAGJjY5GTkwM/Pz91Gw8PD7i6uiIqKqrI42RnZ0OpVGp8iIiIiIiIiPSNwRTtKpUKEydORJs2bdCgQQMAQHJyMszNzWFra6vRVi6XIzk5uchjhYWFQSaTqT8uLi66jE5ERERERERUKgZTtAcHB+PChQvYtGnTGx8rNDQUCoVC/UlKStJCQiIiIiLSBxzMmIiMiUEU7WPHjsWuXbtw6NAhVK9eXb3e0dERT58+RXp6ukb7lJQUODo6Fnk8CwsL2NjYaHyIiIiIyDhwMGMiMiZ6PRCdIAgYN24ctm3bhsOHD8Pd3V1je7NmzWBmZoYDBw6gX79+AID4+HgkJibC19dXjMhEREREJDIOZkxExkSvi/bg4GBs3LgR//vf/2Btba1+T10mk8HKygoymQxBQUEICQmBnZ0dbGxsMG7cOPj6+rKzJSIiIiIAJR/MuLDvkdnZ2cjOzlYvcyBjIiorev14/IoVK6BQKNCxY0c4OTmpP5s3b1a3WbhwIXr27Il+/fqhffv2cHR0xNatW0VMTURERET6QluDGXMgYyISi17faRcE4bVtLC0tsWzZMixbtqwMEhERERGRISkYzPjo0aNvdJzQ0FCEhISol5VKJQt3IioTel20ExERERGVVsFgxpGRkUUOZvz83fZXDWZsYWEBCwsLXUcmInqJXj8eT0RERERUUoIgYOzYsdi2bRsOHjz4ysGMC3AwYyLSV7zTTkRERERGhYMZE5ExYdFOREREREZlxYoVAICOHTtqrF+zZg0+/PBDAPmDGUulUvTr1w/Z2dkICAjA8uXLyzgpEdHr8fF4IqIyFhYWhubNm8Pa2hoODg7o3bs34uPjNdpkZWUhODgY9vb2qFSpEvr164eUlBSNNomJiejRowcqVKgABwcHTJkyBbm5uRptDh8+jKZNm8LCwgK1a9fG2rVrdX15RESiEwSh0E9BwQ78N5hxWloaMjMzsXXr1iLfZyciEhOLdiKiMnbkyBEEBwfjxIkTiIiIQE5ODvz9/ZGZmaluM2nSJOzcuRO///47jhw5grt376Jv377q7Xl5eejRoweePn2K48ePY926dVi7di1mzZqlbpOQkIAePXqgU6dOOHPmDCZOnIiPP/4Ye/fuLdPrJSIiIqLSkwjFmVfNyCmVSshkMigUCtjY2Igdh4gMzJv2Iffv34eDgwOOHDmC9u3bQ6FQoGrVqti4cSPeffddAMCVK1fg6emJqKgotGrVCrt370bPnj1x9+5dyOVyAEB4eDimTZuG+/fvw9zcHNOmTcOff/6JCxcuqM81cOBApKenY8+ePYVmyc7ORnZ2tsa1ubi4sH8kolIx5u9YxnxtRFQ2ituP8E47EZHIFAoFAMDOzg4AEBsbi5ycHPj5+anbeHh4wNXVFVFRUQCAqKgoeHt7qwt2AAgICIBSqcTFixfVbZ4/RkGbgmMUJiwsDDKZTP3hHMRERERE4mLRTkQkIpVKhYkTJ6JNmzZo0KABACA5ORnm5uYacwcDgFwuV4+AnJycrFGwF2wv2PaqNkqlEk+ePCk0T2hoKBQKhfqTlJT0xtdIRERERKXH0eOJiEQUHByMCxcu4OjRo2JHAQBYWFjAwsJC7BhERERE9AzvtBMRiWTs2LHYtWsXDh06hOrVq6vXOzo64unTp0hPT9don5KSoh7Z2NHR8aXR5AuWX9fGxsYGVlZW2r4cIiIiItIBFu1ERGVMEASMHTsW27Ztw8GDB+Hu7q6xvVmzZjAzM8OBAwfU6+Lj45GYmAhfX18AgK+vL86fP4/U1FR1m4iICNjY2MDLy0vd5vljFLQpOAYRERER6T8+Hk9EVMaCg4OxceNG/O9//4O1tbX6HXSZTAYrKyvIZDIEBQUhJCQEdnZ2sLGxwbhx4+Dr64tWrVoBAPz9/eHl5YUPPvgA8+fPR3JyMmbMmIHg4GD14+2jRo3C0qVLMXXqVHz00Uc4ePAgfvvtN/z555+iXTsRERERlQzvtBMRlbEVK1ZAoVCgY8eOcHJyUn82b96sbrNw4UL07NkT/fr1Q/v27eHo6IitW7eqt5uYmGDXrl0wMTGBr68v3n//fQwZMgSzZ89Wt3F3d8eff/6JiIgINGrUCAsWLMBPP/2EgICAMr1eIiIiIio9ztMOzrNJRG/GmPsQY742ItI9Y+5DjPnaiKhscJ52IiIiIiIiIgPHop2IiIiIiIhIT7FoJyIiIiIiItJTLNqJiIiIiIiI9BSLdiIiIiIiIiI9xaKdiIiIiIiISE+xaCciIiIiIiLSUyzaiYiIiIiIiPQUi3YiIiIiIiIiPcWinYiIiIiIiEhPsWgnIiIiIiIi0lOmYgcgIiIyZoIgIFclICdPhZy8gj9VyM0T8PTZnwXrcvIE5OapNNerBOTkqpCrUuHps+2vP1b+n7kqFVSqZzkgPJfpuXwaWTWSF6O9UMT6V7dFIW1fmbHwXTXaF3XMl/cp2QZtnqOon0Fx9y9JhtIcr9gHBPD7qNYwN+W9HyKissCinYiItGbH2btI/DcTgGbh9t/fBc2C7tlCQakgCP8VSfl/xwvH+m9l/nFf3Vaz8CvZuVSqwovmwgroIgtwVf6fRMamqF9mEBGR9rFoJyIirfn9VBL+vvZA7Bh6z1QqgZmJFKYmEpg/+9PMRPrsU7BNCnMTCUylUpiZSmH2mn1MC/4ulcDMVKo+h1QqUZ9X8lwGyXMLkmdbNNe9ui2KbPvy+TT2L+xYL6x/1bFeblPE+iL3eNU+JWtf9B4lP0fRxynpHiU/R/55StbeVMq77EREZYVFOxERaU2HulXhLLNSFwD5f/5XEL5YxEkgee7vLxRpRbYp2P5cWfa6ti+sL1h4VRupVFKCAvq/YrvQwloqhZnps/1NJKUqxIiIiKh8YtFORERa83G7mmJHICIiIjIqfLaJiIiIiIiISE+xaCciIiIiIiLSUyzaiYiIiIiIiPQUi3YiIiIiIiIiPcWinYiIiIiIiEhPsWgnIiIiIiIi0lMs2omIiIiIiIj0FIt2IiIiIiIiIj3Fop2IiIiIiIhIT7FoJyIiIiIiItJTLNqJiIiIiIiI9BSLdiIiIiIiIiI9xaKdiIiIiIiISE+xaCciIiIiIiLSUyzaiYiIiIiIiPQUi3YiIiIiIiIiPcWinYiIiIiIiEhPsWgnIiIiIiIi0lMs2omIiIiIiIj0FIt2IiIiIiIiIj1lNEX7smXLUKNGDVhaWqJly5Y4efKk2JGIiPQC+0cioqKxjyQifWcURfvmzZsREhKCzz//HHFxcWjUqBECAgKQmpoqdjQiIlGxfyQiKhr7SCIyBEZRtH///fcYPnw4hg0bBi8vL4SHh6NChQpYvXq12NGIiETF/pGIqGjsI4nIEJiKHeBNPX36FLGxsQgNDVWvk0ql8PPzQ1RUVKH7ZGdnIzs7W72sUCgAAEqlUrdhicgoFfQdgiCInEQT+0ciEpu+9o9AyftI9o9EpG3F7SMNvmh/8OAB8vLyIJfLNdbL5XJcuXKl0H3CwsLw5ZdfvrTexcVFJxmJqHx49OgRZDKZ2DHU2D8Skb7Qt/4RKHkfyf6RiHTldX2kwRftpREaGoqQkBD1skqlQlpaGuzt7SGRSF67v1KphIuLC5KSkmBjY6PLqDplDNdhDNcA8Dr0SWmuQRAEPHr0CM7OzjpOp3vsH/PxOvSHMVwDUH6vg/2jJmP4d2AM1wDwOvSJMVwDoNvvkAZftFepUgUmJiZISUnRWJ+SkgJHR8dC97GwsICFhYXGOltb2xKf28bGxqD/YRUwhuswhmsAeB36pKTXoG93kAD2j9rA69AfxnANQPm8Dn3sH4GS95Ha6h8B4/h3YAzXAPA69IkxXAOgm++QBj8Qnbm5OZo1a4YDBw6o16lUKhw4cAC+vr4iJiMiEhf7RyKiorGPJCJDYfB32gEgJCQEQ4cOhY+PD1q0aIFFixYhMzMTw4YNEzsaEZGo2D8SERWNfSQRGQKjKNrfe+893L9/H7NmzUJycjIaN26MPXv2vDSwiLZYWFjg888/f+kRKUNjDNdhDNcA8Dr0iTFcw/PYP5YOr0N/GMM1ALwOfcU+suSM4RoAXoc+MYZrAHR7HRJBH+fgICIiIiIiIiLDf6ediIiIiIiIyFixaCciIiIiIiLSUyzaiYiIiIiIiPQUi3YiIiIiIiIiPcWivRSWLVuGGjVqwNLSEi1btsTJkyfFjlQikZGR6NWrF5ydnSGRSLB9+3axI5VYWFgYmjdvDmtrazg4OKB3796Ij48XO1aJrVixAg0bNoSNjQ1sbGzg6+uL3bt3ix3rjXz99deQSCSYOHGi2FFK5IsvvoBEItH4eHh4iB3L4LB/FB/7R/3F/rF8Y/+oH4yhjzTG/hFgH/kqLNpLaPPmzQgJCcHnn3+OuLg4NGrUCAEBAUhNTRU7WrFlZmaiUaNGWLZsmdhRSu3IkSMIDg7GiRMnEBERgZycHPj7+yMzM1PsaCVSvXp1fP3114iNjcWpU6fQuXNnvPPOO7h48aLY0UolJiYGP/74Ixo2bCh2lFKpX78+7t27p/4cPXpU7EgGhf2jfmD/qJ/YP5Zv7B/1hzH0kcbWPwLsI19LoBJp0aKFEBwcrF7Oy8sTnJ2dhbCwMBFTlR4AYdu2bWLHeGOpqakCAOHIkSNiR3ljlStXFn766SexY5TYo0ePhDp16ggRERFChw4dhAkTJogdqUQ+//xzoVGjRmLHMGjsH/UT+0fxsX8k9o/6y1j6SEPtHwWBfWRx8E57CTx9+hSxsbHw8/NTr5NKpfDz80NUVJSIyUihUAAA7OzsRE5Senl5edi0aRMyMzPh6+srdpwSCw4ORo8ePTT+/2Forl27BmdnZ9SsWROBgYFITEwUO5LBYP+ov9g/io/9Y/nG/lG/GXofaej9I8A+sjhMtXo0I/fgwQPk5eVBLpdrrJfL5bhy5YpIqUilUmHixIlo06YNGjRoIHacEjt//jx8fX2RlZWFSpUqYdu2bfDy8hI7Vols2rQJcXFxiImJETtKqbVs2RJr165FvXr1cO/ePXz55Zdo164dLly4AGtra7Hj6T32j/qJ/aP42D8S+0f9Zch9pDH0jwD7yOJi0U4GLzg4GBcuXDDY9+vq1auHM2fOQKFQ4I8//sDQoUNx5MgRg+l4k5KSMGHCBERERMDS0lLsOKXWrVs39d8bNmyIli1bws3NDb/99huCgoJETEZUeuwfxcX+kUi/GXIfaej9I8A+siRYtJdAlSpVYGJigpSUFI31KSkpcHR0FClV+TZ27Fjs2rULkZGRqF69uthxSsXc3By1a9cGADRr1gwxMTH44Ycf8OOPP4qcrHhiY2ORmpqKpk2bqtfl5eUhMjISS5cuRXZ2NkxMTERMWDq2traoW7curl+/LnYUg8D+Uf+wfxQf+0cC2D/qK0PvIw29fwTYR5YE32kvAXNzczRr1gwHDhxQr1OpVDhw4IDBvkNiqARBwNixY7Ft2zYcPHgQ7u7uYkfSGpVKhezsbLFjFFuXLl1w/vx5nDlzRv3x8fFBYGAgzpw5Y5CdLQBkZGTgxo0bcHJyEjuKQWD/qD/YP+oP9o8EsH/UN8baRxpa/wiwjywJ3mkvoZCQEAwdOhQ+Pj5o0aIFFi1ahMzMTAwbNkzsaMWWkZGh8ZufhIQEnDlzBnZ2dnB1dRUxWfEFBwdj48aN+N///gdra2skJycDAGQyGaysrEROV3yhoaHo1q0bXF1d8ejRI2zcuBGHDx/G3r17xY5WbNbW1i+9B1axYkXY29sb1PthkydPRq9eveDm5oa7d+/i888/h4mJCQYNGiR2NIPB/lE/sH/UH+wfqQD7R/1hDH2kMfSPAPvIEtHp2PRGasmSJYKrq6tgbm4utGjRQjhx4oTYkUrk0KFDAoCXPkOHDhU7WrEVlh+AsGbNGrGjlchHH30kuLm5Cebm5kLVqlWFLl26CPv27RM71hszxOk63nvvPcHJyUkwNzcXqlWrJrz33nvC9evXxY5lcNg/io/9o35j/1h+sX/UD8bQRxpr/ygI7COLIhEEQdDerwCIiIiIiIiISFv4TjsRERERERGRnmLRTkRERERERKSnWLQTERERERER6SkW7URERERERER6ikU7ERERERERkZ5i0U5ERERERESkp1i0ExEREREREekpFu1EREREREREeopFOxmtDz/8EL179xbt/B988AHmzZtXrLYDBw7EggULdJyIiCgf+0cioqKxjyR9IxEEQRA7BFFJSSSSV27//PPPMWnSJAiCAFtb27IJ9ZyzZ8+ic+fOuH37NipVqvTa9hcuXED79u2RkJAAmUxWBgmJyFixfyQiKhr7SDJELNrJICUnJ6v/vnnzZsyaNQvx8fHqdZUqVSpWR6crH3/8MUxNTREeHl7sfZo3b44PP/wQwcHBOkxGRMaO/SMRUdHYR5Ih4uPxZJAcHR3VH5lMBolEorGuUqVKLz3a1LFjR4wbNw4TJ05E5cqVIZfLsWrVKmRmZmLYsGGwtrZG7dq1sXv3bo1zXbhwAd26dUOlSpUgl8vxwQcf4MGDB0Vmy8vLwx9//IFevXpprF++fDnq1KkDS0tLyOVyvPvuuxrbe/XqhU2bNr35D4eIyjX2j0RERWMfSYaIRTuVK+vWrUOVKlVw8uRJjBs3DqNHj0b//v3RunVrxMXFwd/fHx988AEeP34MAEhPT0fnzp3RpEkTnDp1Cnv27EFKSgoGDBhQ5DnOnTsHhUIBHx8f9bpTp05h/PjxmD17NuLj47Fnzx60b99eY78WLVrg5MmTyM7O1s3FExG9AvtHIqKisY8kUQlEBm7NmjWCTCZ7af3QoUOFd955R73coUMHoW3bturl3NxcoWLFisIHH3ygXnfv3j0BgBAVFSUIgiDMmTNH8Pf31zhuUlKSAECIj48vNM+2bdsEExMTQaVSqddt2bJFsLGxEZRKZZHXcfbsWQGAcOvWrVdeLxFRcbF/JCIqGvtIMhS8007lSsOGDdV/NzExgb29Pby9vdXr5HI5ACA1NRVA/mAghw4dUr/fVKlSJXh4eAAAbty4Ueg5njx5AgsLC42BTt566y24ubmhZs2a+OCDD7Bhwwb1b2ILWFlZAcBL64mIygL7RyKiorGPJDGxaKdyxczMTGNZIpForCvoJFUqFQAgIyMDvXr1wpkzZzQ+165de+nRpAJVqlTB48eP8fTpU/U6a2trxMXF4ddff4WTkxNmzZqFRo0aIT09Xd0mLS0NAFC1alWtXCsRUUmwfyQiKhr7SBITi3aiV2jatCkuXryIGjVqoHbt2hqfihUrFrpP48aNAQCXLl3SWG9qago/Pz/Mnz8f586dw61bt3Dw4EH19gsXLqB69eqoUqWKzq6HiEhb2D8SERWNfSRpE4t2olcIDg5GWloaBg0ahJiYGNy4cQN79+7FsGHDkJeXV+g+VatWRdOmTXH06FH1ul27dmHx4sU4c+YMbt++jfXr10OlUqFevXrqNn///Tf8/f11fk1ERNrA/pGIqGjsI0mbWLQTvYKzszOOHTuGvLw8+Pv7w9vbGxMnToStrS2k0qL/7/Pxxx9jw4YN6mVbW1ts3boVnTt3hqenJ8LDw/Hrr7+ifv36AICsrCxs374dw4cP1/k1ERFpA/tHIqKisY8kbZIIgiCIHYLI2Dx58gT16tXD5s2b4evr+9r2K1aswLZt27Bv374ySEdEJB72j0RERWMfSYXhnXYiHbCyssL69evx4MGDYrU3MzPDkiVLdJyKiEh87B+JiIrGPpIKwzvtRERERERERHqKd9qJiIiIiIiI9BSLdiIiIiIiIiI9xaKdiIiIiIiISE+xaCciIiIiIiLSUyzaiYiIiIiIiPQUi3YiIiIiIiIiPcWinYiIiIiIiEhPsWgnIiIiIiIi0lMs2omIiIiIiIj01P8DurT0OUFF4wsAAAAASUVORK5CYII=\n" }, "metadata": {} }, @@ -733,12 +839,13 @@ "name": "stdout", "text": [ "Copying files from IDC buckets..\n", - "Done in 0.930332 seconds.\n", - "Chris Rorden's dcm2niiX version v1.0.20181125 (JP2:OpenJPEG) GCC9.3.0 (64-bit Linux)\n", + "Done in 1.61463 seconds.\n", + "Chris Rorden's dcm2niiX version v1.0.20211006 (JP2:OpenJPEG) GCC11.2.0 x86-64 (64-bit Linux)\n", "Found 180 DICOM file(s)\n", - "Convert 180 DICOM as //content/dcm2niix/1.2.840.113654.2.55.243990451406006403331425809632881193215/1.2.840.113654.2.55.243990451406006403331425809632881193215_1_OPA_GE_LSQX_STANDARD_360_2.5_120_64_0.1_1.5_20000102000000_2 (512x512x180x1)\n", - "compress: \"/usr/bin/pigz\" -n -f -6 \"//content/dcm2niix/1.2.840.113654.2.55.243990451406006403331425809632881193215/1.2.840.113654.2.55.243990451406006403331425809632881193215_1_OPA_GE_LSQX_STANDARD_360_2.5_120_64_0.1_1.5_20000102000000_2.nii\"\n", - "Conversion required 6.475957 seconds (0.332813 for core code).\n" + "Convert 180 DICOM as /content/dcm2niix/1.2.840.113654.2.55.243990451406006403331425809632881193215/1.2.840.113654.2.55.243990451406006403331425809632881193215_1,OPA,GE,LSQX,STANDARD,360,2.5,120,64,0.1,1.5_20000102000000_2 (512x512x180x1)\n", + "Compress: \"/usr/bin/pigz\" -b 960 -n -f -6 \"/content/dcm2niix/1.2.840.113654.2.55.243990451406006403331425809632881193215/1.2.840.113654.2.55.243990451406006403331425809632881193215_1,OPA,GE,LSQX,STANDARD,360,2.5,120,64,0.1,1.5_20000102000000_2.nii\"\n", + "Conversion required 6.356902 seconds (0.419911 for core code).\n", + "\n" ] }, { @@ -747,43 +854,56 @@ "text/plain": [ "
" ], - "image/png": 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\n" + "image/png": 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\n" }, "metadata": {} } ], "source": [ + "# Initialize a DataFrame to store runtime statistics\n", "runtime_stats = pd.DataFrame(columns=['SeriesInstanceUID','download_time',\n", " 'NiftiConverter_time', 'cpu_usage','ram_usage_mb', 'ram_total_mb', 'disk_usage_all', 'disk_total'\n", " ])\n", "\n", + "# Main execution\n", "if __name__ == \"__main__\":\n", + " # Loop over all series IDs\n", " for series_id in SeriesInstanceUIDs:\n", + " # Create a ThreadPoolExecutor\n", " with ThreadPoolExecutor() as executor:\n", + " # Initialize a MemoryMonitor instance\n", " monitor = MemoryMonitor()\n", + " # Start a new thread to measure memory usage\n", " mem_thread = executor.submit(monitor.measure_usage)\n", " try:\n", + " # Start a new thread to download and process the series\n", " proc_thread = executor.submit(download_and_process_series, series_id)\n", + " # Wait for the processing thread to finish\n", " proc_thread.result()\n", " finally:\n", + " # Stop the memory monitor thread\n", " monitor.keep_measuring = False\n", + " # Get the results from the memory monitor thread\n", " cpu_usage, ram_usage_mb, time_stamps, ram_total_mb, disk_usage_all, disk_total= mem_thread.result()\n", - " \n", + "\n", + " # Update the runtime statistics DataFrame with the results\n", " cpu_idx = runtime_stats.index[runtime_stats['SeriesInstanceUID'] == series_id][0]\n", " runtime_stats.iloc[cpu_idx, runtime_stats.columns.get_loc('cpu_usage')] = [[cpu_usage]]\n", "\n", " ram_usage_mb_idx = runtime_stats.index[runtime_stats['SeriesInstanceUID'] == series_id][0]\n", " runtime_stats.iloc[ram_usage_mb_idx, runtime_stats.columns.get_loc('ram_usage_mb')] = [[ram_usage_mb]]\n", - " \n", + "\n", " ram_total_mb_idx = runtime_stats.index[runtime_stats['SeriesInstanceUID'] == series_id][0]\n", " runtime_stats.iloc[ram_total_mb_idx, runtime_stats.columns.get_loc('ram_total_mb')] = [[ram_total_mb]]\n", "\n", " disk_usage_gb_idx = runtime_stats.index[runtime_stats['SeriesInstanceUID'] == series_id][0]\n", " runtime_stats.iloc[disk_usage_gb_idx, runtime_stats.columns.get_loc('disk_usage_all')] = [[disk_usage_all]]\n", "\n", - " runtime_stats['disk_total']=disk_total \n", + " # Update total disk space for all rows (assuming it's the same for all series)\n", + " runtime_stats['disk_total']=disk_total\n", "\n", - " fig, ((ax1,ax2, ax3)) = plt.subplots(1,3, figsize=(12, 4)) \n", + " # Plot CPU usage, memory usage and disk usage over time\n", + " fig, ((ax1,ax2, ax3)) = plt.subplots(1,3, figsize=(12, 4))\n", "\n", " ax1.plot(time_stamps, cpu_usage)\n", " ax1.set_ylim(0, 100)\n", @@ -799,7 +919,8 @@ " ax3.set_ylim(0, disk_total)\n", " ax3.set_xlabel('Time (s)')\n", " ax3.set_ylabel('Disk usage (GB)')\n", - " plt.show()" + "\n", + " plt.show()\n" ] }, { @@ -813,53 +934,51 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": { "id": "tba4tK6pvja9" }, "outputs": [], "source": [ + "def check_dcm2niix_errors(path: str) -> None:\n", + " \"\"\"\n", + " Check for errors in the conversion of DICOM to NIfTI files.\n", "\n", - "# def check_dcm2niix_errors(path):\n", - "# for series_id in os.listdir(path):\n", - "# series_id_path = os.path.join(path, series_id)\n", - "# if os.path.isdir(series_id_path):\n", - "# num_files = len([f for f in os.listdir(series_id_path) if os.path.isfile(os.path.join(series_id_path, f))])\n", - "# if num_files > 1:\n", - "# print(f'Found one more than one nifti for the {series_id}')\n", - "# with open('dcm2niix_errors.csv', 'a') as csvfile:\n", - "# writer = csv.writer(csvfile)\n", - "# writer.writerow([series_id])\n", - "# shutil.rmtree(f'dcm2niix/{series_id}')\n", - "def check_dcm2niix_errors(path):\n", + " Args:\n", + " path: The path to the directory containing the series directories.\n", + " \"\"\"\n", + " # Loop over all series directories in the path\n", " for series_id in os.listdir(path):\n", " series_id_path = os.path.join(path, series_id)\n", + "\n", + " # Check if the path is a directory\n", " if os.path.isdir(series_id_path):\n", + " # Count the number of files in the directory\n", " num_files = len([f for f in os.listdir(series_id_path) if os.path.isfile(os.path.join(series_id_path, f))])\n", - " if num_files == 0:\n", - " print(f'No NIfTI files found for {series_id}')\n", - " with open('dcm2niix_errors.csv', 'a') as csvfile:\n", - " writer = csv.writer(csvfile)\n", - " writer.writerow([series_id])\n", - " shutil.rmtree(f'dcm2niix/{series_id}')\n", - " elif num_files > 1:\n", - " print(f'Found more than one NIfTI file for {series_id}')\n", + "\n", + " # If no files or more than one file found, log an error and remove the directory\n", + " if num_files == 0 or num_files > 1:\n", + " print(f'{\"No\" if num_files == 0 else \"More than one\"} NIfTI file{\"s\" if num_files > 1 else \"\"} found for {series_id}')\n", + "\n", " with open('dcm2niix_errors.csv', 'a') as csvfile:\n", " writer = csv.writer(csvfile)\n", " writer.writerow([series_id])\n", - " shutil.rmtree(f'dcm2niix/{series_id}')" + "\n", + " shutil.rmtree(os.path.join('dcm2niix', series_id))\n" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": { "id": "wP7_k4msvl2E" }, "outputs": [], "source": [ + "# Check if the converter type is 'dcm2niix'\n", "if converterType.lower()=='dcm2niix':\n", - " check_dcm2niix_errors(f'/{curr_dir}/dcm2niix')" + " # If it is, call the function to check for errors in the 'dcm2niix' directory\n", + " check_dcm2niix_errors(f'/{curr_dir}/dcm2niix')\n" ] }, { @@ -873,13 +992,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "-q3J_d00v0gz", - "outputId": "c543c58e-92ae-409a-a7fe-f619e6f8e636" + "outputId": "3b14bfe4-5b05-42ca-8963-a3c332a657a7" }, "outputs": [ { @@ -887,40 +1006,47 @@ "name": "stdout", "text": [ "dcm2niix/\n", - "dcm2niix/1.2.840.113654.2.55.243990451406006403331425809632881193215/\n", - "dcm2niix/1.2.840.113654.2.55.243990451406006403331425809632881193215/1.2.840.113654.2.55.243990451406006403331425809632881193215_1_OPA_GE_LSQX_STANDARD_360_2.5_120_64_0.1_1.5_20000102000000_2.nii.gz\n", - "dcm2niix/1.2.840.113654.2.55.146601594654322994982630019583270053397/\n", - "dcm2niix/1.2.840.113654.2.55.146601594654322994982630019583270053397/1.2.840.113654.2.55.146601594654322994982630019583270053397_1_OPA_GE_LSQX_STANDARD_360_2.5_140_40_0_1.5_20000102000000_2.nii.gz\n", - "dcm2niix/1.3.6.1.4.1.14519.5.2.1.7009.9004.118722452529394350711166589345/\n", - "dcm2niix/1.3.6.1.4.1.14519.5.2.1.7009.9004.118722452529394350711166589345/1.3.6.1.4.1.14519.5.2.1.7009.9004.11872245252939435071116658934_1_OPA_GE_LSPR16_STANDARD_330_2.5_120_80_58.2_1.4_20000102000000_2.nii.gz\n", "dcm2niix/1.3.6.1.4.1.14519.5.2.1.7009.9004.431377773401197924485551006033/\n", - "dcm2niix/1.3.6.1.4.1.14519.5.2.1.7009.9004.431377773401197924485551006033/1.3.6.1.4.1.14519.5.2.1.7009.9004.43137777340119792448555100603_1_OPA_GE_LS16_STANDARD_339_2.5_120_40_29.1_1.4_20000102000000_2.nii.gz\n", - "dcm2niix/1.2.840.113654.2.55.113040386178547843571271236478024341696/\n", - "dcm2niix/1.2.840.113654.2.55.113040386178547843571271236478024341696/1.2.840.113654.2.55.113040386178547843571271236478024341696_0_OPA_GE_LSQX_STANDARD_352_2.5_120_64_0.1_1.5_19990102000000_2.nii.gz\n", + "dcm2niix/1.3.6.1.4.1.14519.5.2.1.7009.9004.431377773401197924485551006033/1.3.6.1.4.1.14519.5.2.1.7009.9004.431377773401197924485551006033_1,OPA,GE,LS16,STANDARD,339,2.5,120,40,29.1,1.4_20000102000000_2.nii.gz\n", "dcm2niix/1.2.840.113654.2.55.216614002338888733987350522981366678482/\n", - "dcm2niix/1.2.840.113654.2.55.216614002338888733987350522981366678482/1.2.840.113654.2.55.216614002338888733987350522981366678482_0_OPA_GE_HSQX_BONE_340_2.5_120_56_0.1_1.5_19990102000000_3.nii.gz\n", - "dcm2niix/1.2.840.113654.2.55.22770087029972268579113866309746562015/\n", - "dcm2niix/1.2.840.113654.2.55.22770087029972268579113866309746562015/1.2.840.113654.2.55.22770087029972268579113866309746562015_1_OPA_GE_HSQX_STANDARD_380_2.5_120_56_0.1_1.5_20000102000000_2.nii.gz\n", + "dcm2niix/1.2.840.113654.2.55.216614002338888733987350522981366678482/1.2.840.113654.2.55.216614002338888733987350522981366678482_0,OPA,GE,HSQX,BONE,340,2.5,120,56,0.1,1.5_19990102000000_3.nii.gz\n", + "dcm2niix/1.2.840.113654.2.55.146601594654322994982630019583270053397/\n", + "dcm2niix/1.2.840.113654.2.55.146601594654322994982630019583270053397/1.2.840.113654.2.55.146601594654322994982630019583270053397_1,OPA,GE,LSQX,STANDARD,360,2.5,140,40,0,1.5_20000102000000_2.nii.gz\n", + "dcm2niix/1.2.840.113654.2.55.243990451406006403331425809632881193215/\n", + "dcm2niix/1.2.840.113654.2.55.243990451406006403331425809632881193215/1.2.840.113654.2.55.243990451406006403331425809632881193215_1,OPA,GE,LSQX,STANDARD,360,2.5,120,64,0.1,1.5_20000102000000_2.nii.gz\n", + "dcm2niix/1.2.840.113654.2.55.142419057730651121165090739113900499978/\n", + "dcm2niix/1.2.840.113654.2.55.142419057730651121165090739113900499978/1.2.840.113654.2.55.142419057730651121165090739113900499978_2,OPA,GE,LSQX,BONE,360,2.5,120,72,0.1,1.5_20010102000000_3.nii.gz\n", + "dcm2niix/1.2.840.113654.2.55.113040386178547843571271236478024341696/\n", + "dcm2niix/1.2.840.113654.2.55.113040386178547843571271236478024341696/1.2.840.113654.2.55.113040386178547843571271236478024341696_0,OPA,GE,LSQX,STANDARD,352,2.5,120,64,0.1,1.5_19990102000000_2.nii.gz\n", "dcm2niix/1.2.840.113654.2.55.100875189782210690344207306235124901243/\n", - "dcm2niix/1.2.840.113654.2.55.100875189782210690344207306235124901243/1.2.840.113654.2.55.100875189782210690344207306235124901243_0_OPA_GE_LSQX_STANDARD_360_2.5_120_na_na_na_19990102000000_2.nii.gz\n", - "dcm2niix/1.2.840.113654.2.55.14382674871619950799472325766084940706/\n", - "dcm2niix/1.2.840.113654.2.55.14382674871619950799472325766084940706/1.2.840.113654.2.55.14382674871619950799472325766084940706_0_OPA_GE_LSQX_STANDARD_350_2.5_120_na_na_na_19990102000000_2.nii.gz\n", + "dcm2niix/1.2.840.113654.2.55.100875189782210690344207306235124901243/1.2.840.113654.2.55.100875189782210690344207306235124901243_0,OPA,GE,LSQX,STANDARD,360,2.5,120,na,na,na_19990102000000_2.nii.gz\n", "dcm2niix/1.2.840.113654.2.55.185309182591805634517860395342326800332/\n", - "dcm2niix/1.2.840.113654.2.55.185309182591805634517860395342326800332/1.2.840.113654.2.55.185309182591805634517860395342326800332_1_OPA_GE_LSQX_STANDARD_360_2.5_120_48_0_1.5_20000102000000_2.nii.gz\n", - "dcm2niix/1.2.840.113654.2.55.142419057730651121165090739113900499978/\n", - "dcm2niix/1.2.840.113654.2.55.142419057730651121165090739113900499978/1.2.840.113654.2.55.142419057730651121165090739113900499978_2_OPA_GE_LSQX_BONE_360_2.5_120_72_0.1_1.5_20010102000000_3.nii.gz\n", + "dcm2niix/1.2.840.113654.2.55.185309182591805634517860395342326800332/1.2.840.113654.2.55.185309182591805634517860395342326800332_1,OPA,GE,LSQX,STANDARD,360,2.5,120,48,0,1.5_20000102000000_2.nii.gz\n", "dcm2niix/1.2.840.113654.2.55.154809705591242159075253605419469935510/\n", - "dcm2niix/1.2.840.113654.2.55.154809705591242159075253605419469935510/1.2.840.113654.2.55.154809705591242159075253605419469935510_0_OPA_GE_LSQX_STANDARD_310_2.5_120_64_0.1_1.5_19990102000000_2.nii.gz\n" + "dcm2niix/1.2.840.113654.2.55.154809705591242159075253605419469935510/1.2.840.113654.2.55.154809705591242159075253605419469935510_0,OPA,GE,LSQX,STANDARD,310,2.5,120,64,0.1,1.5_19990102000000_2.nii.gz\n", + "dcm2niix/1.2.840.113654.2.55.14382674871619950799472325766084940706/\n", + "dcm2niix/1.2.840.113654.2.55.14382674871619950799472325766084940706/1.2.840.113654.2.55.14382674871619950799472325766084940706_0,OPA,GE,LSQX,STANDARD,350,2.5,120,na,na,na_19990102000000_2.nii.gz\n", + "dcm2niix/1.3.6.1.4.1.14519.5.2.1.7009.9004.118722452529394350711166589345/\n", + "dcm2niix/1.3.6.1.4.1.14519.5.2.1.7009.9004.118722452529394350711166589345/1.3.6.1.4.1.14519.5.2.1.7009.9004.118722452529394350711166589345_1,OPA,GE,LSPR16,STANDARD,330,2.5,120,80,58.2,1.4_20000102000000_2.nii.gz\n", + "dcm2niix/1.2.840.113654.2.55.22770087029972268579113866309746562015/\n", + "dcm2niix/1.2.840.113654.2.55.22770087029972268579113866309746562015/1.2.840.113654.2.55.22770087029972268579113866309746562015_1,OPA,GE,HSQX,STANDARD,380,2.5,120,56,0.1,1.5_20000102000000_2.nii.gz\n" ] } ], "source": [ + "# Attempt to remove the archive file if it exists\n", "try:\n", " os.remove('downloadDicomAndConvertNiftiFiles.tar.lz4')\n", "except OSError:\n", " pass\n", + "\n", + "# Record the start time of the archiving process\n", "start_time = time.time()\n", + "\n", + "# Create a tar archive of the converterType directory, compress it with lz4, and save it as downloadDicomAndConvertNiftiFiles.tar.lz4\n", "!tar cvf - -C {curr_dir} {converterType} | lz4 > downloadDicomAndConvertNiftiFiles.tar.lz4\n", + "\n", + "# Calculate and record the time taken for the archiving process\n", "archiving_time = time.time() - start_time\n" ] }, @@ -935,21 +1061,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": { "colab": { "base_uri": "https://localhost:8080/", - "height": 869 + "height": 1000 }, "id": "z9n17x4vhDQp", - "outputId": "81426151-207c-46bd-b339-10ae382e04aa" + "outputId": "962d3fe4-3d41-48d5-ab0f-da089b637911" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ - "\r \rCompressed 5085 bytes into 3220 bytes ==> 63.32%\n" + "\r \rCompressed 5374 bytes into 3466 bytes ==> 64.50%\n" ] }, { @@ -957,80 +1083,79 @@ "data": { "text/plain": [ " SeriesInstanceUID download_time \\\n", - "0 1.3.6.1.4.1.14519.5.2.1.7009.9004.118722452529... 0.753602 \n", - "1 1.3.6.1.4.1.14519.5.2.1.7009.9004.431377773401... 0.549510 \n", - "2 1.2.840.113654.2.55.10087518978221069034420730... 0.647338 \n", - "3 1.2.840.113654.2.55.11304038617854784357127123... 0.940775 \n", - "4 1.2.840.113654.2.55.14241905773065112116509073... 0.744970 \n", - "5 1.2.840.113654.2.55.14382674871619950799472325... 0.745200 \n", - "6 1.2.840.113654.2.55.14660159465432299498263001... 0.751185 \n", - "7 1.2.840.113654.2.55.15480970559124215907525360... 0.748934 \n", - "8 1.2.840.113654.2.55.18530918259180563451786039... 0.650335 \n", - "9 1.2.840.113654.2.55.21661400233888873398735052... 0.755432 \n", - "10 1.2.840.113654.2.55.22770087029972268579113866... 0.759236 \n", - "11 1.2.840.113654.2.55.24399045140600640333142580... 1.050337 \n", + "0 1.3.6.1.4.1.14519.5.2.1.7009.9004.118722452529... 1.723828 \n", + "1 1.3.6.1.4.1.14519.5.2.1.7009.9004.431377773401... 1.736683 \n", + "2 1.2.840.113654.2.55.10087518978221069034420730... 1.619671 \n", + "3 1.2.840.113654.2.55.11304038617854784357127123... 2.128867 \n", + "4 1.2.840.113654.2.55.14241905773065112116509073... 1.829752 \n", + "5 1.2.840.113654.2.55.14382674871619950799472325... 1.624063 \n", + "6 1.2.840.113654.2.55.14660159465432299498263001... 1.729227 \n", + "7 1.2.840.113654.2.55.15480970559124215907525360... 1.921425 \n", + "8 1.2.840.113654.2.55.18530918259180563451786039... 1.739839 \n", + "9 1.2.840.113654.2.55.21661400233888873398735052... 1.627476 \n", + "10 1.2.840.113654.2.55.22770087029972268579113866... 1.721012 \n", + "11 1.2.840.113654.2.55.24399045140600640333142580... 1.723548 \n", "\n", " NiftiConverter_time cpu_usage \\\n", - "0 6.378470 [[[66.0, 75.9, 99.5, 100.0, 100.0, 100.0, 100.... \n", - "1 5.276177 [[[27.6, 85.9, 100.0, 100.0, 100.0, 100.0]]] \n", - "2 3.958123 [[[77.7, 74.9, 100.0, 100.0, 100.0]]] \n", - "3 7.098707 [[[59.7, 79.3, 88.0, 100.0, 100.0, 100.0, 100.... \n", - "4 3.617335 [[[22.6, 69.0, 99.5, 100.0, 100.0]]] \n", - "5 4.601916 [[[45.5, 86.4, 100.0, 100.0, 100.0, 100.0]]] \n", - "6 4.265746 [[[44.2, 69.8, 100.0, 100.0, 100.0, 97.5]]] \n", - "7 5.242166 [[[22.0, 79.8, 99.5, 100.0, 100.0, 100.0]]] \n", - "8 4.665271 [[[84.0, 81.0, 99.5, 100.0, 100.0, 100.0]]] \n", - "9 5.286575 [[[36.5, 73.2, 100.0, 100.0, 100.0, 100.0, 94.... \n", - "10 3.668736 [[[24.1, 72.3, 100.0, 100.0, 100.0]]] \n", - "11 6.631536 [[[46.2, 76.8, 83.1, 100.0, 100.0, 100.0, 100.... \n", + "0 6.428793 [[[71.0, 43.1, 59.9, 100.0, 100.0, 100.0, 100.... \n", + "1 3.833364 [[[71.9, 57.6, 45.7, 100.0, 100.0, 100.0]]] \n", + "2 4.912183 [[[58.6, 31.5, 59.6, 100.0, 100.0, 100.0, 100.... \n", + "3 5.493229 [[[73.6, 30.5, 41.6, 82.4, 100.0, 100.0, 100.0... \n", + "4 4.331430 [[[68.0, 92.9, 93.5, 100.0, 100.0, 100.0, 100.... \n", + "5 3.451945 [[[32.2, 30.1, 57.1, 100.0, 100.0, 98.5]]] \n", + "6 4.721215 [[[25.4, 73.4, 90.5, 100.0, 100.0, 100.0, 100.... \n", + "7 3.185453 [[[66.5, 51.0, 33.7, 94.5, 100.0, 100.0]]] \n", + "8 4.412652 [[[75.5, 64.1, 52.5, 100.0, 100.0, 100.0, 100.... \n", + "9 5.026524 [[[30.6, 31.6, 58.8, 100.0, 100.0, 100.0, 100.... \n", + "10 3.483806 [[[66.6, 32.7, 47.5, 100.0, 100.0, 100.0]]] \n", + "11 6.394813 [[[35.5, 38.3, 53.3, 99.5, 100.0, 100.0, 100.0... \n", "\n", " ram_usage_mb ram_total_mb \\\n", - "0 [[[1117.19140625, 1227.59765625, 1235.2421875,... [12985.5390625] \n", - "1 [[[1121.84765625, 1213.125, 1196.703125, 1196.... [12985.5390625] \n", - "2 [[[1133.328125, 1212.9609375, 1213.0, 1213.144... [12985.5390625] \n", - "3 [[[1139.1953125, 1149.19921875, 1261.37109375,... [12985.5390625] \n", - "4 [[[1145.1640625, 1217.36328125, 1219.96875, 12... [12985.5390625] \n", - "5 [[[1150.484375, 1220.41015625, 1223.1015625, 1... [12985.5390625] \n", - "6 [[[1153.33203125, 1232.08203125, 1234.27734375... [12985.5390625] \n", - "7 [[[1158.3828125, 1160.84765625, 1195.16796875,... [12985.5390625] \n", - "8 [[[1117.2265625, 1203.69921875, 1205.9140625, ... [12985.5390625] \n", - "9 [[[1115.6875, 1188.91015625, 1192.25390625, 11... [12985.5390625] \n", - "10 [[[1116.0703125, 1190.3203125, 1191.88671875, ... [12985.5390625] \n", - "11 [[[1119.47265625, 1118.42578125, 1222.68359375... [12985.5390625] \n", + "0 [[[1066.140625, 1093.390625, 1187.18359375, 11... [12982.6171875] \n", + "1 [[[1113.1953125, 1109.00390625, 1182.625, 1175... [12982.6171875] \n", + "2 [[[1105.35546875, 1114.90234375, 1189.17578125... [12982.6171875] \n", + "3 [[[1121.5859375, 1127.84375, 1163.1171875, 123... [12982.6171875] \n", + "4 [[[1117.69140625, 1156.44140625, 1264.5390625,... [12982.6171875] \n", + "5 [[[1149.23828125, 1160.30859375, 1217.2265625,... [12982.6171875] \n", + "6 [[[1183.44140625, 1178.22265625, 1255.6796875,... [12982.6171875] \n", + "7 [[[1141.72265625, 1141.03515625, 1116.05078125... [12982.6171875] \n", + "8 [[[1117.546875, 1125.08984375, 1188.86328125, ... [12982.6171875] \n", + "9 [[[1108.95703125, 1117.12109375, 1174.66796875... [12982.6171875] \n", + "10 [[[1102.47265625, 1107.71875, 1152.8984375, 11... [12982.6171875] \n", + "11 [[[1129.3828125, 1119.234375, 1176.6875, 1192.... [12982.6171875] \n", "\n", " disk_usage_all disk_total \\\n", - "0 [[[23.34793472290039, 23.437042236328125, 23.5... 107.715084 \n", - "1 [[[23.388256072998047, 23.501541137695312, 23.... 107.715084 \n", - "2 [[[23.41504669189453, 23.547466278076172, 23.5... 107.715084 \n", - "3 [[[23.449085235595703, 23.543102264404297, 23.... 107.715084 \n", - "4 [[[23.495494842529297, 23.604618072509766, 23.... 107.715084 \n", - "5 [[[23.530906677246094, 23.621097564697266, 23.... 107.715084 \n", - "6 [[[23.562366485595703, 23.667278289794922, 23.... 107.715084 \n", - "7 [[[23.596027374267578, 23.651153564453125, 23.... 107.715084 \n", - "8 [[[23.624435424804688, 23.744911193847656, 23.... 107.715084 \n", - "9 [[[23.66510772705078, 23.757343292236328, 23.7... 107.715084 \n", - "10 [[[23.700927734375, 23.81143569946289, 23.8361... 107.715084 \n", - "11 [[[23.73427963256836, 23.822872161865234, 23.9... 107.715084 \n", + "0 [[[26.284500122070312, 26.302242279052734, 26.... 107.715084 \n", + "1 [[[26.324874877929688, 26.330169677734375, 26.... 107.715084 \n", + "2 [[[26.35169219970703, 26.36469268798828, 26.48... 107.715084 \n", + "3 [[[26.385753631591797, 26.385818481445312, 26.... 107.715084 \n", + "4 [[[26.432231903076172, 26.434978485107422, 26.... 107.715084 \n", + "5 [[[26.467655181884766, 26.475418090820312, 26.... 107.715084 \n", + "6 [[[26.499176025390625, 26.508411407470703, 26.... 107.715084 \n", + "7 [[[26.532894134521484, 26.53396987915039, 26.5... 107.715084 \n", + "8 [[[26.56130599975586, 26.570758819580078, 26.6... 107.715084 \n", + "9 [[[26.602039337158203, 26.61188507080078, 26.7... 107.715084 \n", + "10 [[[26.63787078857422, 26.64669418334961, 26.76... 107.715084 \n", + "11 [[[26.671253204345703, 26.68230438232422, 26.7... 107.715084 \n", "\n", " csv_read_time archiving_time \n", - "0 0.016416 1.554871 \n", - "1 0.016416 1.554871 \n", - "2 0.016416 1.554871 \n", - "3 0.016416 1.554871 \n", - "4 0.016416 1.554871 \n", - "5 0.016416 1.554871 \n", - "6 0.016416 1.554871 \n", - "7 0.016416 1.554871 \n", - "8 0.016416 1.554871 \n", - "9 0.016416 1.554871 \n", - "10 0.016416 1.554871 \n", - "11 0.016416 1.554871 " + "0 0.016354 1.819073 \n", + "1 0.016354 1.819073 \n", + "2 0.016354 1.819073 \n", + "3 0.016354 1.819073 \n", + "4 0.016354 1.819073 \n", + "5 0.016354 1.819073 \n", + "6 0.016354 1.819073 \n", + "7 0.016354 1.819073 \n", + "8 0.016354 1.819073 \n", + "9 0.016354 1.819073 \n", + "10 0.016354 1.819073 \n", + "11 0.016354 1.819073 " ], "text/html": [ "\n", - "
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\n", + " const docLinkHtml = 'Like what you see? Visit the ' +\n", + " 'data table notebook'\n", + " + ' to learn more about interactive tables.';\n", + " element.innerHTML = '';\n", + " dataTable['output_type'] = 'display_data';\n", + " await google.colab.output.renderOutput(dataTable, element);\n", + " const docLink = document.createElement('div');\n", + " docLink.innerHTML = docLinkHtml;\n", + " element.appendChild(docLink);\n", + " }\n", + " \n", "
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\n" ] }, "metadata": {}, - "execution_count": 20 + "execution_count": 17 } ], "source": [ + "# Save the runtime statistics DataFrame to a CSV file\n", "runtime_stats.to_csv('runtime.csv')\n", - "runtime_stats['csv_read_time']=read_time\n", - "runtime_stats['archiving_time']=archiving_time\n", "\n", + "# Add the csv_read_time and archiving_time to the DataFrame as new columns\n", + "runtime_stats['csv_read_time'] = read_time\n", + "runtime_stats['archiving_time'] = archiving_time\n", + "\n", + "# Attempt to remove the lz4 file if it exists\n", "try:\n", " os.remove('downloadDicomAndConvertUsageMetrics.lz4')\n", "except OSError:\n", " pass\n", + "\n", + "# Compress the runtime.csv file using lz4 and save it as downloadDicomAndConvertUsageMetrics.lz4\n", "!lz4 {curr_dir}/runtime.csv downloadDicomAndConvertUsageMetrics.lz4\n", - "runtime_stats" + "\n", + "# Print the runtime statistics DataFrame\n", + "runtime_stats\n" ] } ], From 002d8c36c2fbd9048be55802c4074ef4080b22e4 Mon Sep 17 00:00:00 2001 From: Vamsi Thiriveedhi <115020590+vkt1414@users.noreply.github.com> Date: Sun, 24 Sep 2023 18:52:43 -0400 Subject: [PATCH 27/40] test ghcr.io container registry --- .github/workflows/download_convert.yml | 42 ++++++++++++++++++++++++-- 1 file changed, 40 insertions(+), 2 deletions(-) diff --git a/.github/workflows/download_convert.yml b/.github/workflows/download_convert.yml index 89c8262..1e08d76 100644 --- a/.github/workflows/download_convert.yml +++ b/.github/workflows/download_convert.yml @@ -34,7 +34,7 @@ jobs: username: ${{ secrets.DOCKER_USERNAME }} password: ${{ secrets.DOCKER_PASSWORD }} - - name: Build and push Docker image + - name: Build and push Docker image to Docker Hub uses: docker/build-push-action@v5 with: context: . @@ -46,6 +46,25 @@ jobs: env: COMMIT_HASH: ${{ env.COMMIT_HASH }} + - name: Login to GitHub Container Registry (ghcr.io) + uses: docker/login-action@v1 + with: + registry: ghcr.io + username: ${{ github.actor }} + password: ${{ secrets.GITHUB_TOKEN }} + + - name: Build and push Docker image to GitHub Container Registry + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/download_convert/Dockerfile + push: true + tags: ghcr.io/imagingdatacommons/download_convert:dev + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} + build-and-push-prod: if: github.ref == 'refs/heads/main' runs-on: ubuntu-latest @@ -70,7 +89,7 @@ jobs: username: ${{ secrets.DOCKER_USERNAME }} password: ${{ secrets.DOCKER_PASSWORD }} - - name: Build and push Docker image + - name: Build and push Docker image to Docker Hub uses: docker/build-push-action@v5 with: context: . @@ -81,3 +100,22 @@ jobs: GIT_HASH=${{ env.COMMIT_HASH }} env: COMMIT_HASH: ${{ env.COMMIT_HASH }} + + - name: Login to GitHub Container Registry (ghcr.io) + uses: docker/login-action@v1 + with: + registry: ghcr.io + username: ${{ github.actor }} + password: ${{ secrets.GITHUB_TOKEN }} + + - name: Build and push Docker image to GitHub Container Registry + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/download_convert/Dockerfile + push: true + tags: ghcr.io/imagingdatacommons/download_convert + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} From 6e8eb14d001dcab41d824dd6a4f077491f0bf592 Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Mon, 25 Sep 2023 11:01:31 -0400 Subject: [PATCH 28/40] add ghcr.io build and push steps to all --- .../download_convert_inference_totalseg.yml | 40 ++++++++++++++++++ ...d_convert_inference_totalseg_radiomics.yml | 41 +++++++++++++++++++ .github/workflows/inference_totalseg.yml | 39 ++++++++++++++++++ .../per_frame_functional_group_sequence.yml | 40 ++++++++++++++++++ .github/workflows/radiomics.yml | 41 +++++++++++++++++++ 5 files changed, 201 insertions(+) diff --git a/.github/workflows/download_convert_inference_totalseg.yml b/.github/workflows/download_convert_inference_totalseg.yml index 662ad60..29b5f97 100644 --- a/.github/workflows/download_convert_inference_totalseg.yml +++ b/.github/workflows/download_convert_inference_totalseg.yml @@ -50,6 +50,27 @@ jobs: env: COMMIT_HASH: ${{ env.COMMIT_HASH }} + - name: Login to GitHub Container Registry (ghcr.io) + uses: docker/login-action@v1 + with: + registry: ghcr.io + username: ${{ github.actor }} + password: ${{ secrets.GITHUB_TOKEN }} + + - name: Build and push Docker image to GitHub Container Registry + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/download_convert_inference_totalseg/Dockerfile + push: true + tags: ghcr.io/imagingdatacommons/download_convert_inference_totalseg:dev + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} + + + build-and-push-prod: if: github.ref == 'refs/heads/main' runs-on: ubuntu-latest @@ -89,3 +110,22 @@ jobs: GIT_HASH=${{ env.COMMIT_HASH }} env: COMMIT_HASH: ${{ env.COMMIT_HASH }} + + - name: Login to GitHub Container Registry (ghcr.io) + uses: docker/login-action@v1 + with: + registry: ghcr.io + username: ${{ github.actor }} + password: ${{ secrets.GITHUB_TOKEN }} + + - name: Build and push Docker image to GitHub Container Registry + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/download_convert_inference_totalseg/Dockerfile + push: true + tags: ghcr.io/imagingdatacommons/download_convert_inference_totalseg + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file diff --git a/.github/workflows/download_convert_inference_totalseg_radiomics.yml b/.github/workflows/download_convert_inference_totalseg_radiomics.yml index c456f89..57b156a 100644 --- a/.github/workflows/download_convert_inference_totalseg_radiomics.yml +++ b/.github/workflows/download_convert_inference_totalseg_radiomics.yml @@ -50,6 +50,28 @@ jobs: env: COMMIT_HASH: ${{ env.COMMIT_HASH }} + - name: Login to GitHub Container Registry (ghcr.io) + uses: docker/login-action@v1 + with: + registry: ghcr.io + username: ${{ github.actor }} + password: ${{ secrets.GITHUB_TOKEN }} + + - name: Build and push Docker image to GitHub Container Registry + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile + push: true + tags: ghcr.io/imagingdatacommons/download_convert_inference_totalseg_radiomics:dev + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} + + + + build-and-push-prod: if: github.ref == 'refs/heads/main' runs-on: ubuntu-latest @@ -89,3 +111,22 @@ jobs: GIT_HASH=${{ env.COMMIT_HASH }} env: COMMIT_HASH: ${{ env.COMMIT_HASH }} + + - name: Login to GitHub Container Registry (ghcr.io) + uses: docker/login-action@v1 + with: + registry: ghcr.io + username: ${{ github.actor }} + password: ${{ secrets.GITHUB_TOKEN }} + + - name: Build and push Docker image to GitHub Container Registry + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile + push: true + tags: ghcr.io/imagingdatacommons/download_convert_inference_totalseg_radiomics + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file diff --git a/.github/workflows/inference_totalseg.yml b/.github/workflows/inference_totalseg.yml index d61b7f1..53de809 100644 --- a/.github/workflows/inference_totalseg.yml +++ b/.github/workflows/inference_totalseg.yml @@ -50,6 +50,26 @@ jobs: env: COMMIT_HASH: ${{ env.COMMIT_HASH }} + - name: Login to GitHub Container Registry (ghcr.io) + uses: docker/login-action@v1 + with: + registry: ghcr.io + username: ${{ github.actor }} + password: ${{ secrets.GITHUB_TOKEN }} + + - name: Build and push Docker image to GitHub Container Registry + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/inference_totalseg/Dockerfile + push: true + tags: ghcr.io/imagingdatacommons/inference_totalseg:dev + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} + + build-and-push-prod: if: github.ref == 'refs/heads/main' runs-on: ubuntu-latest @@ -89,3 +109,22 @@ jobs: GIT_HASH=${{ env.COMMIT_HASH }} env: COMMIT_HASH: ${{ env.COMMIT_HASH }} + + - name: Login to GitHub Container Registry (ghcr.io) + uses: docker/login-action@v1 + with: + registry: ghcr.io + username: ${{ github.actor }} + password: ${{ secrets.GITHUB_TOKEN }} + + - name: Build and push Docker image to GitHub Container Registry + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/inference_totalseg/Dockerfile + push: true + tags: ghcr.io/imagingdatacommons/inference_totalseg + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file diff --git a/.github/workflows/per_frame_functional_group_sequence.yml b/.github/workflows/per_frame_functional_group_sequence.yml index 4806a60..53e70c3 100644 --- a/.github/workflows/per_frame_functional_group_sequence.yml +++ b/.github/workflows/per_frame_functional_group_sequence.yml @@ -46,6 +46,27 @@ jobs: env: COMMIT_HASH: ${{ env.COMMIT_HASH }} + - name: Login to GitHub Container Registry (ghcr.io) + uses: docker/login-action@v1 + with: + registry: ghcr.io + username: ${{ github.actor }} + password: ${{ secrets.GITHUB_TOKEN }} + + - name: Build and push Docker image to GitHub Container Registry + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/per_frame_functional_group_sequence/Dockerfile + push: true + tags: ghcr.io/imagingdatacommons/per_frame_functional_group_sequence:dev + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} + + + build-and-push-prod: if: github.ref == 'refs/heads/main' runs-on: ubuntu-latest @@ -81,3 +102,22 @@ jobs: GIT_HASH=${{ env.COMMIT_HASH }} env: COMMIT_HASH: ${{ env.COMMIT_HASH }} + + - name: Login to GitHub Container Registry (ghcr.io) + uses: docker/login-action@v1 + with: + registry: ghcr.io + username: ${{ github.actor }} + password: ${{ secrets.GITHUB_TOKEN }} + + - name: Build and push Docker image to GitHub Container Registry + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/per_frame_functional_group_sequence/Dockerfile + push: true + tags: ghcr.io/imagingdatacommons/per_frame_functional_group_sequence + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file diff --git a/.github/workflows/radiomics.yml b/.github/workflows/radiomics.yml index 6624120..e28f2df 100644 --- a/.github/workflows/radiomics.yml +++ b/.github/workflows/radiomics.yml @@ -46,6 +46,28 @@ jobs: env: COMMIT_HASH: ${{ env.COMMIT_HASH }} + - name: Login to GitHub Container Registry (ghcr.io) + uses: docker/login-action@v1 + with: + registry: ghcr.io + username: ${{ github.actor }} + password: ${{ secrets.GITHUB_TOKEN }} + + - name: Build and push Docker image to GitHub Container Registry + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/radiomics/Dockerfile + push: true + tags: ghcr.io/imagingdatacommons/radiomics:dev + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} + + + + build-and-push-prod: if: github.ref == 'refs/heads/main' runs-on: ubuntu-latest @@ -81,3 +103,22 @@ jobs: GIT_HASH=${{ env.COMMIT_HASH }} env: COMMIT_HASH: ${{ env.COMMIT_HASH }} + + - name: Login to GitHub Container Registry (ghcr.io) + uses: docker/login-action@v1 + with: + registry: ghcr.io + username: ${{ github.actor }} + password: ${{ secrets.GITHUB_TOKEN }} + + - name: Build and push Docker image to GitHub Container Registry + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/radiomics/Dockerfile + push: true + tags: ghcr.io/imagingdatacommons/radiomics + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file From 13dac0d0331d9a9ffa150d27801e0fa483715edc Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Tue, 26 Sep 2023 15:51:52 -0400 Subject: [PATCH 29/40] remove plastimatch from apt-package installation --- Dockerfiles/download_convert/Dockerfile | 6 +++--- Dockerfiles/download_convert_inference_totalseg/Dockerfile | 6 +++--- .../Dockerfile | 6 +++--- 3 files changed, 9 insertions(+), 9 deletions(-) diff --git a/Dockerfiles/download_convert/Dockerfile b/Dockerfiles/download_convert/Dockerfile index c4c3094..bf73301 100644 --- a/Dockerfiles/download_convert/Dockerfile +++ b/Dockerfiles/download_convert/Dockerfile @@ -14,7 +14,7 @@ RUN apt-get update \ dcm2niix=1.0.20181125-1\ lz4=1.8.3-1+deb10u1\ pigz=2.4-1\ - plastimatch=1.7.4+dfsg.1-2\ + #plastimatch=1.7.4+dfsg.1-2\ wget=1.20.1-1.1\ zip=3.0-11+b1\ && rm -rf /var/lib/apt/lists/* @@ -31,8 +31,8 @@ RUN pip3 install --no-cache-dir \ papermill==2.4.0 # Download and install s5cmd for interacting with cloud storage -ENV S5CMD_URL="https://github.com/peak/s5cmd/releases/download/v2.0.0/s5cmd_2.0.0_Linux-64bit.tar.gz" -ENV S5CMD_FN="s5cmd_2.0.0_Linux-64bit.tar.gz" +ENV S5CMD_URL="https://github.com/peak/s5cmd/releases/download/v2.2.2/s5cmd_2.2.2_Linux-64bit.tar.gz" +ENV S5CMD_FN="s5cmd_2.2.2_Linux-64bit.tar.gz" RUN wget ${S5CMD_URL} \ && tar -xvzf ${S5CMD_FN} \ && rm ${S5CMD_FN} \ diff --git a/Dockerfiles/download_convert_inference_totalseg/Dockerfile b/Dockerfiles/download_convert_inference_totalseg/Dockerfile index 284fb05..fe2ee43 100644 --- a/Dockerfiles/download_convert_inference_totalseg/Dockerfile +++ b/Dockerfiles/download_convert_inference_totalseg/Dockerfile @@ -20,7 +20,7 @@ RUN apt-get update && apt-get install -y --no-install-recommends\ ffmpeg=7:4.2.7-0ubuntu0.1\ lz4=1.9.2-2ubuntu0.20.04.1\ pigz=2.4-1\ - plastimatch=1.8.0+dfsg.1-2build1\ + #plastimatch=1.8.0+dfsg.1-2build1\ python3-dev=3.8.2-0ubuntu2\ python3-pip=20.0.2-5ubuntu1.9\ unzip=6.0-25ubuntu1.1\ @@ -53,8 +53,8 @@ RUN chmod +x /root/weights_download.sh RUN /root/weights_download.sh # Download and install s5cmd for interacting with cloud storage -ENV S5CMD_URL="https://github.com/peak/s5cmd/releases/download/v2.0.0/s5cmd_2.0.0_Linux-64bit.tar.gz" -ENV S5CMD_FN="s5cmd_2.0.0_Linux-64bit.tar.gz" +ENV S5CMD_URL="https://github.com/peak/s5cmd/releases/download/v2.2.2/s5cmd_2.2.2_Linux-64bit.tar.gz" +ENV S5CMD_FN="s5cmd_2.2.2_Linux-64bit.tar.gz" RUN wget ${S5CMD_URL} \ && tar -xvzf ${S5CMD_FN} \ && rm ${S5CMD_FN} \ diff --git a/Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile b/Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile index 862160c..080e391 100644 --- a/Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile +++ b/Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile @@ -21,7 +21,7 @@ RUN apt-get update && apt-get install -y --no-install-recommends \ ffmpeg=7:4.2.7-0ubuntu0.1\ lz4=1.9.2-2ubuntu0.20.04.1\ pigz=2.4-1\ - plastimatch=1.8.0+dfsg.1-2build1\ + #plastimatch=1.8.0+dfsg.1-2build1\ python3-dev=3.8.2-0ubuntu2\ python3-pip=20.0.2-5ubuntu1.9\ unzip=6.0-25ubuntu1.1\ @@ -57,8 +57,8 @@ RUN chmod +x /root/weights_download.sh RUN /root/weights_download.sh # Download and install s5cmd for interacting with cloud storage -ENV S5CMD_URL="https://github.com/peak/s5cmd/releases/download/v2.0.0/s5cmd_2.0.0_Linux-64bit.tar.gz" -ENV S5CMD_FN="s5cmd_2.0.0_Linux-64bit.tar.gz" +ENV S5CMD_URL="https://github.com/peak/s5cmd/releases/download/v2.2.2/s5cmd_2.2.2_Linux-64bit.tar.gz" +ENV S5CMD_FN="s5cmd_2.2.2_Linux-64bit.tar.gz" RUN wget ${S5CMD_URL} \ && tar -xvzf ${S5CMD_FN} \ && rm ${S5CMD_FN} \ From c89ceb3b97029d0299ac6821f581aafebaed0963 Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Tue, 26 Sep 2023 16:35:49 -0400 Subject: [PATCH 30/40] remove plastimatch from apt-get, use dcm2niix by default, upgrade s5cmd --- Dockerfiles/radiomics/Dockerfile | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/Dockerfiles/radiomics/Dockerfile b/Dockerfiles/radiomics/Dockerfile index 1d20b63..1b67d21 100644 --- a/Dockerfiles/radiomics/Dockerfile +++ b/Dockerfiles/radiomics/Dockerfile @@ -15,7 +15,7 @@ RUN apt-get update \ #dcm2niix\ lz4=1.8.3-1+deb10u1\ pigz=2.4-1\ - plastimatch=1.7.4+dfsg.1-2\ + #plastimatch=1.7.4+dfsg.1-2\ python3-dev=3.7.3-1\ unzip=6.0-23+deb10u3\ wget=1.20.1-1.1\ @@ -39,8 +39,8 @@ RUN pip3 install --no-cache-dir \ pyradiomics==3.0.1 # Download and install s5cmd for interacting with cloud storage -ENV S5CMD_URL="https://github.com/peak/s5cmd/releases/download/v2.0.0/s5cmd_2.0.0_Linux-64bit.tar.gz" -ENV S5CMD_FN="s5cmd_2.0.0_Linux-64bit.tar.gz" +ENV S5CMD_URL="https://github.com/peak/s5cmd/releases/download/v2.2.2/s5cmd_2.2.2_Linux-64bit.tar.gz" +ENV S5CMD_FN="s5cmd_2.2.2_Linux-64bit.tar.gz" RUN wget ${S5CMD_URL} \ && tar -xvzf ${S5CMD_FN} \ && rm ${S5CMD_FN} \ From b8f5468dba471d5463b01466f3dc08bbbd4a0f4c Mon Sep 17 00:00:00 2001 From: Andrey Fedorov Date: Wed, 27 Sep 2023 11:28:04 -0400 Subject: [PATCH 31/40] add PR trigger to the workflow --- .github/workflows/download_convert.yml | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/.github/workflows/download_convert.yml b/.github/workflows/download_convert.yml index 1e08d76..7a7a763 100644 --- a/.github/workflows/download_convert.yml +++ b/.github/workflows/download_convert.yml @@ -3,12 +3,13 @@ name: download_convert on: push: branches: - - dev - main paths: - 'Dockerfiles/download_convert/**' - '.github/workflows/download_convert.yml' - + pull_request: + branches: [ "main" ] + jobs: build-and-push-dev: if: github.ref == 'refs/heads/dev' From a541cc54266dddfeec6092ef43ba7034c2d71dff Mon Sep 17 00:00:00 2001 From: Andrey Fedorov Date: Wed, 27 Sep 2023 11:39:56 -0400 Subject: [PATCH 32/40] simplify GA workflow --- .github/workflows/download_convert.yml | 64 +------------------------- 1 file changed, 1 insertion(+), 63 deletions(-) diff --git a/.github/workflows/download_convert.yml b/.github/workflows/download_convert.yml index 7a7a763..bc2b074 100644 --- a/.github/workflows/download_convert.yml +++ b/.github/workflows/download_convert.yml @@ -1,73 +1,11 @@ name: download_convert on: - push: - branches: - - main - paths: - - 'Dockerfiles/download_convert/**' - - '.github/workflows/download_convert.yml' pull_request: branches: [ "main" ] jobs: - build-and-push-dev: - if: github.ref == 'refs/heads/dev' - runs-on: ubuntu-latest - steps: - - name: Checkout code - uses: actions/checkout@v4 - - - name: Set up Git - run: | - git config --global user.email "actions@github.com" - git config --global user.name "GitHub Actions" - - - name: Get Git Commit Hash - id: git-commit-hash - run: | - COMMIT_HASH=$(git rev-parse HEAD) - echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - - - name: Login to Docker Hub - uses: docker/login-action@v3 - with: - username: ${{ secrets.DOCKER_USERNAME }} - password: ${{ secrets.DOCKER_PASSWORD }} - - - name: Build and push Docker image to Docker Hub - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/download_convert/Dockerfile - push: true - tags: imagingdatacommons/download_convert:dev - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} - - - name: Login to GitHub Container Registry (ghcr.io) - uses: docker/login-action@v1 - with: - registry: ghcr.io - username: ${{ github.actor }} - password: ${{ secrets.GITHUB_TOKEN }} - - - name: Build and push Docker image to GitHub Container Registry - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/download_convert/Dockerfile - push: true - tags: ghcr.io/imagingdatacommons/download_convert:dev - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} - - build-and-push-prod: - if: github.ref == 'refs/heads/main' + build-and-push: runs-on: ubuntu-latest steps: - name: Checkout code From 3a64510e663b02514e47dc7988742859781523e5 Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Thu, 28 Sep 2023 13:54:01 -0400 Subject: [PATCH 33/40] simplify gihub actions workflow to main branch only --- .../download_convert_inference_totalseg.yml | 75 +----------------- ...d_convert_inference_totalseg_radiomics.yml | 76 +------------------ .github/workflows/inference_totalseg.yml | 71 +---------------- .../per_frame_functional_group_sequence.yml | 70 +---------------- .github/workflows/radiomics.yml | 69 +---------------- 5 files changed, 17 insertions(+), 344 deletions(-) diff --git a/.github/workflows/download_convert_inference_totalseg.yml b/.github/workflows/download_convert_inference_totalseg.yml index 29b5f97..7f2c357 100644 --- a/.github/workflows/download_convert_inference_totalseg.yml +++ b/.github/workflows/download_convert_inference_totalseg.yml @@ -1,17 +1,11 @@ name: download_convert_inference_totalseg on: - push: - branches: - - dev - - main - paths: - - 'Dockerfiles/download_convert_inference_totalseg/**' - - .github/workflows/download_convert_inference_totalseg.yml + pull_request: + branches: [ "main" ] jobs: - build-and-push-dev: - if: github.ref == 'refs/heads/dev' + build-and-push: runs-on: ubuntu-latest steps: - name: Checkout code @@ -38,68 +32,7 @@ jobs: username: ${{ secrets.DOCKER_USERNAME }} password: ${{ secrets.DOCKER_PASSWORD }} - - name: Build and push Docker image (dev) - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/download_convert_inference_totalseg/Dockerfile - push: true - tags: imagingdatacommons/download_convert_inference_totalseg:dev - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} - - - name: Login to GitHub Container Registry (ghcr.io) - uses: docker/login-action@v1 - with: - registry: ghcr.io - username: ${{ github.actor }} - password: ${{ secrets.GITHUB_TOKEN }} - - - name: Build and push Docker image to GitHub Container Registry - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/download_convert_inference_totalseg/Dockerfile - push: true - tags: ghcr.io/imagingdatacommons/download_convert_inference_totalseg:dev - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} - - - - build-and-push-prod: - if: github.ref == 'refs/heads/main' - runs-on: ubuntu-latest - steps: - - name: Checkout code - uses: actions/checkout@v4 - - - name: Set up Git - run: | - git config --global user.email "actions@github.com" - git config --global user.name "GitHub Actions" - - - name: Get Git Commit Hash - id: git-commit-hash - run: | - COMMIT_HASH=$(git rev-parse HEAD) - echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - - - name: Copy additional files to build context - run: | - cp Dockerfiles/download_convert_inference_totalseg/weights_download.sh . - - - name: Login to Docker Hub - uses: docker/login-action@v3 - with: - username: ${{ secrets.DOCKER_USERNAME }} - password: ${{ secrets.DOCKER_PASSWORD }} - - - name: Build and push Docker image (main) + - name: Build and push Docker image uses: docker/build-push-action@v5 with: context: . diff --git a/.github/workflows/download_convert_inference_totalseg_radiomics.yml b/.github/workflows/download_convert_inference_totalseg_radiomics.yml index 57b156a..0eb0e44 100644 --- a/.github/workflows/download_convert_inference_totalseg_radiomics.yml +++ b/.github/workflows/download_convert_inference_totalseg_radiomics.yml @@ -1,79 +1,11 @@ name: download_convert_inference_totalseg_radiomics on: - push: - branches: - - dev - - main - paths: - - 'Dockerfiles/download_convert_inference_totalseg_radiomics/**' - - .github/workflows/download_convert_inference_totalseg_radiomics.yml + pull_request: + branches: [ "main" ] + -jobs: - build-and-push-dev: - if: github.ref == 'refs/heads/dev' - runs-on: ubuntu-latest - steps: - - name: Checkout code - uses: actions/checkout@v4 - - - name: Set up Git - run: | - git config --global user.email "actions@github.com" - git config --global user.name "GitHub Actions" - - - name: Get Git Commit Hash - id: git-commit-hash - run: | - COMMIT_HASH=$(git rev-parse HEAD) - echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - - - name: Copy additional files to build context - run: | - cp Dockerfiles/download_convert_inference_totalseg_radiomics/weights_download.sh . - - - name: Login to Docker Hub - uses: docker/login-action@v3 - with: - username: ${{ secrets.DOCKER_USERNAME }} - password: ${{ secrets.DOCKER_PASSWORD }} - - - name: Build and push Docker image (dev) - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile - push: true - tags: imagingdatacommons/download_convert_inference_totalseg_radiomics:dev - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} - - - name: Login to GitHub Container Registry (ghcr.io) - uses: docker/login-action@v1 - with: - registry: ghcr.io - username: ${{ github.actor }} - password: ${{ secrets.GITHUB_TOKEN }} - - - name: Build and push Docker image to GitHub Container Registry - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile - push: true - tags: ghcr.io/imagingdatacommons/download_convert_inference_totalseg_radiomics:dev - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} - - - - - build-and-push-prod: - if: github.ref == 'refs/heads/main' + build-and-push: runs-on: ubuntu-latest steps: - name: Checkout code diff --git a/.github/workflows/inference_totalseg.yml b/.github/workflows/inference_totalseg.yml index 53de809..e55c456 100644 --- a/.github/workflows/inference_totalseg.yml +++ b/.github/workflows/inference_totalseg.yml @@ -1,77 +1,12 @@ name: inference_totalseg on: - push: - branches: - - dev - - main - paths: - - 'Dockerfiles/inference_totalseg/**' - - .github/workflows/inference_totalseg.yml + pull_request: + branches: [ "main" ] jobs: - build-and-push-dev: - if: github.ref == 'refs/heads/dev' - runs-on: ubuntu-latest - steps: - - name: Checkout code - uses: actions/checkout@v4 - - - name: Set up Git - run: | - git config --global user.email "actions@github.com" - git config --global user.name "GitHub Actions" - - - name: Get Git Commit Hash - id: git-commit-hash - run: | - COMMIT_HASH=$(git rev-parse HEAD) - echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - - - name: Copy additional files to build context - run: | - cp Dockerfiles/inference_totalseg/weights_download.sh . - - - name: Login to Docker Hub - uses: docker/login-action@v3 - with: - username: ${{ secrets.DOCKER_USERNAME }} - password: ${{ secrets.DOCKER_PASSWORD }} - - - name: Build and push Docker image - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/inference_totalseg/Dockerfile - push: true - tags: imagingdatacommons/inference_totalseg:dev - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} - - - name: Login to GitHub Container Registry (ghcr.io) - uses: docker/login-action@v1 - with: - registry: ghcr.io - username: ${{ github.actor }} - password: ${{ secrets.GITHUB_TOKEN }} - - - name: Build and push Docker image to GitHub Container Registry - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/inference_totalseg/Dockerfile - push: true - tags: ghcr.io/imagingdatacommons/inference_totalseg:dev - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} - - build-and-push-prod: - if: github.ref == 'refs/heads/main' + build-and-push: runs-on: ubuntu-latest steps: - name: Checkout code diff --git a/.github/workflows/per_frame_functional_group_sequence.yml b/.github/workflows/per_frame_functional_group_sequence.yml index 53e70c3..5f5df16 100644 --- a/.github/workflows/per_frame_functional_group_sequence.yml +++ b/.github/workflows/per_frame_functional_group_sequence.yml @@ -1,74 +1,10 @@ name: per_frame_functional_group_sequence on: - push: - branches: - - dev - - main - paths: - - 'Dockerfiles/per_frame_functional_group_sequence/**' - - .github/workflows/per_frame_functional_group_sequence.yml + pull_request: + branches: [ "main" ] -jobs: - build-and-push-dev: - if: github.ref == 'refs/heads/dev' - runs-on: ubuntu-latest - steps: - - name: Checkout code - uses: actions/checkout@v4 - - - name: Set up Git - run: | - git config --global user.email "actions@github.com" - git config --global user.name "GitHub Actions" - - - name: Get Git Commit Hash - id: git-commit-hash - run: | - COMMIT_HASH=$(git rev-parse HEAD) - echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - - - name: Login to Docker Hub - uses: docker/login-action@v3 - with: - username: ${{ secrets.DOCKER_USERNAME }} - password: ${{ secrets.DOCKER_PASSWORD }} - - - name: Build and push Docker image - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/per_frame_functional_group_sequence/Dockerfile - push: true - tags: imagingdatacommons/per_frame_functional_group_sequence:dev - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} - - - name: Login to GitHub Container Registry (ghcr.io) - uses: docker/login-action@v1 - with: - registry: ghcr.io - username: ${{ github.actor }} - password: ${{ secrets.GITHUB_TOKEN }} - - - name: Build and push Docker image to GitHub Container Registry - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/per_frame_functional_group_sequence/Dockerfile - push: true - tags: ghcr.io/imagingdatacommons/per_frame_functional_group_sequence:dev - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} - - - - build-and-push-prod: - if: github.ref == 'refs/heads/main' + build-and-push: runs-on: ubuntu-latest steps: - name: Checkout code diff --git a/.github/workflows/radiomics.yml b/.github/workflows/radiomics.yml index e28f2df..378cfd0 100644 --- a/.github/workflows/radiomics.yml +++ b/.github/workflows/radiomics.yml @@ -1,75 +1,12 @@ name: radiomics on: - push: - branches: - - dev - - main - paths: - - 'Dockerfiles/radiomics/**' - - .github/workflows/radiomics.yml + pull_request: + branches: [ "main" ] jobs: - build-and-push-dev: - if: github.ref == 'refs/heads/dev' - runs-on: ubuntu-latest - steps: - - name: Checkout code - uses: actions/checkout@v4 - - - name: Set up Git - run: | - git config --global user.email "actions@github.com" - git config --global user.name "GitHub Actions" - - - name: Get Git Commit Hash - id: git-commit-hash - run: | - COMMIT_HASH=$(git rev-parse HEAD) - echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - - - name: Login to Docker Hub - uses: docker/login-action@v3 - with: - username: ${{ secrets.DOCKER_USERNAME }} - password: ${{ secrets.DOCKER_PASSWORD }} - - - name: Build and push Docker image - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/radiomics/Dockerfile - push: true - tags: imagingdatacommons/radiomics:dev - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} - - - name: Login to GitHub Container Registry (ghcr.io) - uses: docker/login-action@v1 - with: - registry: ghcr.io - username: ${{ github.actor }} - password: ${{ secrets.GITHUB_TOKEN }} - - - name: Build and push Docker image to GitHub Container Registry - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/radiomics/Dockerfile - push: true - tags: ghcr.io/imagingdatacommons/radiomics:dev - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} - - - - build-and-push-prod: - if: github.ref == 'refs/heads/main' + build-and-push: runs-on: ubuntu-latest steps: - name: Checkout code From b2359867c1c233169684945d6c38978fcb49e194 Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Thu, 28 Sep 2023 13:59:09 -0400 Subject: [PATCH 34/40] fix ga script--jobs --- .../download_convert_inference_totalseg_radiomics.yml | 2 +- .github/workflows/per_frame_functional_group_sequence.yml | 3 ++- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/.github/workflows/download_convert_inference_totalseg_radiomics.yml b/.github/workflows/download_convert_inference_totalseg_radiomics.yml index 0eb0e44..dc3a791 100644 --- a/.github/workflows/download_convert_inference_totalseg_radiomics.yml +++ b/.github/workflows/download_convert_inference_totalseg_radiomics.yml @@ -4,7 +4,7 @@ on: pull_request: branches: [ "main" ] - +jobs: build-and-push: runs-on: ubuntu-latest steps: diff --git a/.github/workflows/per_frame_functional_group_sequence.yml b/.github/workflows/per_frame_functional_group_sequence.yml index 5f5df16..be0d633 100644 --- a/.github/workflows/per_frame_functional_group_sequence.yml +++ b/.github/workflows/per_frame_functional_group_sequence.yml @@ -3,7 +3,8 @@ name: per_frame_functional_group_sequence on: pull_request: branches: [ "main" ] - + +jobs: build-and-push: runs-on: ubuntu-latest steps: From 1cc82ead57b0763d70499ab094c7b5486e30c462 Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Thu, 28 Sep 2023 14:38:14 -0400 Subject: [PATCH 35/40] rename radiomics to dicom_seg_pyradiomics_sr --- .../{radiomics => dicom_seg_pyradiomics_sr}/Dockerfile | 4 ++-- .../Dockerfile | 6 +++--- .../weights_download.sh | 0 3 files changed, 5 insertions(+), 5 deletions(-) rename Dockerfiles/{radiomics => dicom_seg_pyradiomics_sr}/Dockerfile (91%) rename Dockerfiles/{download_convert_inference_totalseg_radiomics => download_convert_inference_totalseg_dicom_seg_pyradiomics_sr}/Dockerfile (94%) rename Dockerfiles/{download_convert_inference_totalseg_radiomics => download_convert_inference_totalseg_dicom_seg_pyradiomics_sr}/weights_download.sh (100%) diff --git a/Dockerfiles/radiomics/Dockerfile b/Dockerfiles/dicom_seg_pyradiomics_sr/Dockerfile similarity index 91% rename from Dockerfiles/radiomics/Dockerfile rename to Dockerfiles/dicom_seg_pyradiomics_sr/Dockerfile index 1b67d21..8308740 100644 --- a/Dockerfiles/radiomics/Dockerfile +++ b/Dockerfiles/dicom_seg_pyradiomics_sr/Dockerfile @@ -5,8 +5,8 @@ ARG GIT_HASH LABEL PYTHON_BASE_DOCKER_IMAGE="python:3.11.2-slim-buster"\ MAINTAINER="IDC " \ GIT_HASH=${GIT_HASH}\ - PATH_TO_DOCKER_FILE="https://github.com/imagingdatacommons/Cloud-Resources-Workflows/blob/${GIT_HASH}/Dockerfiles/radiomics/Dockerfile"\ - IMAGE_NAME_ON_DOCKERHUB="imagingdatacommons/radiomics" + PATH_TO_DOCKER_FILE="https://github.com/imagingdatacommons/Cloud-Resources-Workflows/blob/${GIT_HASH}/Dockerfiles/dicom_seg_pyradiomics_sr/Dockerfile"\ + IMAGE_NAME_ON_DOCKERHUB="imagingdatacommons/dicom_seg_pyradiomics_sr" # Install some basic system utilities RUN apt-get update \ diff --git a/Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile b/Dockerfiles/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr/Dockerfile similarity index 94% rename from Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile rename to Dockerfiles/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr/Dockerfile index 080e391..4e0e274 100644 --- a/Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile +++ b/Dockerfiles/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr/Dockerfile @@ -5,8 +5,8 @@ ARG GIT_HASH LABEL BASE_DOCKER_IMAGE="nvidia/cuda:12.1.0-base-ubuntu20.04"\ MAINTAINER="IDC " \ GIT_HASH=${GIT_HASH}\ - PATH_TO_DOCKER_FILE="https://github.com/imagingdatacommons/Cloud-Resources-Workflows/blob/${GIT_HASH}/Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile"\ - IMAGE_NAME_ON_DOCKERHUB="imagingdatacommons/download_convert_inference_totalseg_radiomics" + PATH_TO_DOCKER_FILE="https://github.com/imagingdatacommons/Cloud-Resources-Workflows/blob/${GIT_HASH}/Dockerfiles/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr/Dockerfile"\ + IMAGE_NAME_ON_DOCKERHUB="imagingdatacommons/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr" # Set noninteractive mode to avoid geographic area prompt during package installation @@ -70,4 +70,4 @@ ENV DCMQI_FN="dcmqi-1.2.5-linux.tar.gz" RUN wget ${DCMQI_URL} \ && tar -xvzf ${DCMQI_FN} \ && rm ${DCMQI_FN} \ - && mv dcmqi-1.2.5-linux/bin/* /bin \ No newline at end of file + && mv dcmqi-1.2.5-linux/bin/* /bin diff --git a/Dockerfiles/download_convert_inference_totalseg_radiomics/weights_download.sh b/Dockerfiles/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr/weights_download.sh similarity index 100% rename from Dockerfiles/download_convert_inference_totalseg_radiomics/weights_download.sh rename to Dockerfiles/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr/weights_download.sh From 91a1b47a25df386255f76f191ec66a15ab66ad5c Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Thu, 28 Sep 2023 14:42:52 -0400 Subject: [PATCH 36/40] rename radiomics to dicom_seg_pyradiomics_sr --- ...d_convert_inference_totalseg_radiomics.yml | 64 ------------------- .github/workflows/radiomics.yml | 61 ------------------ 2 files changed, 125 deletions(-) delete mode 100644 .github/workflows/download_convert_inference_totalseg_radiomics.yml delete mode 100644 .github/workflows/radiomics.yml diff --git a/.github/workflows/download_convert_inference_totalseg_radiomics.yml b/.github/workflows/download_convert_inference_totalseg_radiomics.yml deleted file mode 100644 index dc3a791..0000000 --- a/.github/workflows/download_convert_inference_totalseg_radiomics.yml +++ /dev/null @@ -1,64 +0,0 @@ -name: download_convert_inference_totalseg_radiomics - -on: - pull_request: - branches: [ "main" ] - -jobs: - build-and-push: - runs-on: ubuntu-latest - steps: - - name: Checkout code - uses: actions/checkout@v4 - - - name: Set up Git - run: | - git config --global user.email "actions@github.com" - git config --global user.name "GitHub Actions" - - - name: Get Git Commit Hash - id: git-commit-hash - run: | - COMMIT_HASH=$(git rev-parse HEAD) - echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - - - name: Copy additional files to build context - run: | - cp Dockerfiles/download_convert_inference_totalseg_radiomics/weights_download.sh . - - - name: Login to Docker Hub - uses: docker/login-action@v3 - with: - username: ${{ secrets.DOCKER_USERNAME }} - password: ${{ secrets.DOCKER_PASSWORD }} - - - name: Build and push Docker image (main) - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile - push: true - tags: imagingdatacommons/download_convert_inference_totalseg_radiomics - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} - - - name: Login to GitHub Container Registry (ghcr.io) - uses: docker/login-action@v1 - with: - registry: ghcr.io - username: ${{ github.actor }} - password: ${{ secrets.GITHUB_TOKEN }} - - - name: Build and push Docker image to GitHub Container Registry - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/download_convert_inference_totalseg_radiomics/Dockerfile - push: true - tags: ghcr.io/imagingdatacommons/download_convert_inference_totalseg_radiomics - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file diff --git a/.github/workflows/radiomics.yml b/.github/workflows/radiomics.yml deleted file mode 100644 index 378cfd0..0000000 --- a/.github/workflows/radiomics.yml +++ /dev/null @@ -1,61 +0,0 @@ -name: radiomics - -on: - pull_request: - branches: [ "main" ] - -jobs: - - build-and-push: - runs-on: ubuntu-latest - steps: - - name: Checkout code - uses: actions/checkout@v4 - - - name: Set up Git - run: | - git config --global user.email "actions@github.com" - git config --global user.name "GitHub Actions" - - - name: Get Git Commit Hash - id: git-commit-hash - run: | - COMMIT_HASH=$(git rev-parse HEAD) - echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV - - - name: Login to Docker Hub - uses: docker/login-action@v3 - with: - username: ${{ secrets.DOCKER_USERNAME }} - password: ${{ secrets.DOCKER_PASSWORD }} - - - name: Build and push Docker image - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/radiomics/Dockerfile - push: true - tags: imagingdatacommons/radiomics - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} - - - name: Login to GitHub Container Registry (ghcr.io) - uses: docker/login-action@v1 - with: - registry: ghcr.io - username: ${{ github.actor }} - password: ${{ secrets.GITHUB_TOKEN }} - - - name: Build and push Docker image to GitHub Container Registry - uses: docker/build-push-action@v5 - with: - context: . - file: ./Dockerfiles/radiomics/Dockerfile - push: true - tags: ghcr.io/imagingdatacommons/radiomics - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file From a4446ae33f1cf82c70ced92251648b7aca7a8192 Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Thu, 28 Sep 2023 14:45:00 -0400 Subject: [PATCH 37/40] rename radiomics to dicom_seg_pyradiomics_sr --- .../workflows/dicom_seg_pyradiomics_sr.yml | 61 ++++++++++++++++++ ...ence_totalseg_dicom_seg_pyradiomics_sr.yml | 64 +++++++++++++++++++ 2 files changed, 125 insertions(+) create mode 100644 .github/workflows/dicom_seg_pyradiomics_sr.yml create mode 100644 .github/workflows/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr.yml diff --git a/.github/workflows/dicom_seg_pyradiomics_sr.yml b/.github/workflows/dicom_seg_pyradiomics_sr.yml new file mode 100644 index 0000000..1229831 --- /dev/null +++ b/.github/workflows/dicom_seg_pyradiomics_sr.yml @@ -0,0 +1,61 @@ +name: dicom_seg_pyradiomics_sr + +on: + pull_request: + branches: [ "main" ] + +jobs: + + build-and-push: + runs-on: ubuntu-latest + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Git + run: | + git config --global user.email "actions@github.com" + git config --global user.name "GitHub Actions" + + - name: Get Git Commit Hash + id: git-commit-hash + run: | + COMMIT_HASH=$(git rev-parse HEAD) + echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV + + - name: Login to Docker Hub + uses: docker/login-action@v3 + with: + username: ${{ secrets.DOCKER_USERNAME }} + password: ${{ secrets.DOCKER_PASSWORD }} + + - name: Build and push Docker image + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/dicom_seg_pyradiomics_sr/Dockerfile + push: true + tags: imagingdatacommons/dicom_seg_pyradiomics_sr + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} + + - name: Login to GitHub Container Registry (ghcr.io) + uses: docker/login-action@v1 + with: + registry: ghcr.io + username: ${{ github.actor }} + password: ${{ secrets.GITHUB_TOKEN }} + + - name: Build and push Docker image to GitHub Container Registry + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/dicom_seg_pyradiomics_sr/Dockerfile + push: true + tags: ghcr.io/imagingdatacommons/dicom_seg_pyradiomics_sr + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file diff --git a/.github/workflows/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr.yml b/.github/workflows/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr.yml new file mode 100644 index 0000000..4b7f24a --- /dev/null +++ b/.github/workflows/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr.yml @@ -0,0 +1,64 @@ +name: download_convert_inference_totalseg_dicom_seg_pyradiomics_sr + +on: + pull_request: + branches: [ "main" ] + +jobs: + build-and-push: + runs-on: ubuntu-latest + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Set up Git + run: | + git config --global user.email "actions@github.com" + git config --global user.name "GitHub Actions" + + - name: Get Git Commit Hash + id: git-commit-hash + run: | + COMMIT_HASH=$(git rev-parse HEAD) + echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV + + - name: Copy additional files to build context + run: | + cp Dockerfiles/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr/weights_download.sh . + + - name: Login to Docker Hub + uses: docker/login-action@v3 + with: + username: ${{ secrets.DOCKER_USERNAME }} + password: ${{ secrets.DOCKER_PASSWORD }} + + - name: Build and push Docker image (main) + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr/Dockerfile + push: true + tags: imagingdatacommons/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} + + - name: Login to GitHub Container Registry (ghcr.io) + uses: docker/login-action@v1 + with: + registry: ghcr.io + username: ${{ github.actor }} + password: ${{ secrets.GITHUB_TOKEN }} + + - name: Build and push Docker image to GitHub Container Registry + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr/Dockerfile + push: true + tags: ghcr.io/imagingdatacommons/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file From 71aea6d0ed3128c44d4e3669f2d6a5a631437e83 Mon Sep 17 00:00:00 2001 From: Vamsi Thiriveedhi <115020590+vkt1414@users.noreply.github.com> Date: Thu, 28 Sep 2023 15:25:58 -0400 Subject: [PATCH 38/40] Add docker builds status from github actions --- README.md | 14 ++++++++++++++ 1 file changed, 14 insertions(+) diff --git a/README.md b/README.md index aff344b..6394aa1 100644 --- a/README.md +++ b/README.md @@ -1 +1,15 @@ This repo will contain the source code used to develop workflows for analysis on Terra or Seven Bridges Genomics + +Docker Images Build Status + +[![download_convert](https://github.com/ImagingDataCommons/Cloud-Resources-Workflows/actions/workflows/download_convert.yml/badge.svg)](https://github.com/ImagingDataCommons/Cloud-Resources-Workflows/actions/workflows/download_convert.yml) + +[![inference_totalseg](https://github.com/ImagingDataCommons/Cloud-Resources-Workflows/actions/workflows/inference_totalseg.yml/badge.svg)](https://github.com/ImagingDataCommons/Cloud-Resources-Workflows/actions/workflows/inference_totalseg.yml) + +[![dicom_seg_pyradiomics_sr](https://github.com/ImagingDataCommons/Cloud-Resources-Workflows/actions/workflows/dicom_seg_pyradiomics_sr.yml/badge.svg)](https://github.com/ImagingDataCommons/Cloud-Resources-Workflows/actions/workflows/dicom_seg_pyradiomics_sr.yml) + +[![per_frame_functional_group_sequence](https://github.com/ImagingDataCommons/Cloud-Resources-Workflows/actions/workflows/per_frame_functional_group_sequence.yml/badge.svg)](https://github.com/ImagingDataCommons/Cloud-Resources-Workflows/actions/workflows/per_frame_functional_group_sequence.yml) + +[![download_convert_inference_totalseg](https://github.com/ImagingDataCommons/Cloud-Resources-Workflows/actions/workflows/download_convert_inference_totalseg.yml/badge.svg)](https://github.com/ImagingDataCommons/Cloud-Resources-Workflows/actions/workflows/download_convert_inference_totalseg.yml) + +[![download_convert_inference_totalseg_dicom_seg_pyradiomics_sr](https://github.com/ImagingDataCommons/Cloud-Resources-Workflows/actions/workflows/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr.yml/badge.svg)](https://github.com/ImagingDataCommons/Cloud-Resources-Workflows/actions/workflows/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr.yml) From d298e03a3727a13bfcc3f8fc641bf7cb14305ca7 Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Mon, 2 Oct 2023 15:24:52 -0400 Subject: [PATCH 39/40] push docker images only on push events --- .github/workflows/download_convert.yml | 38 ++++++++++++++++++-------- 1 file changed, 27 insertions(+), 11 deletions(-) diff --git a/.github/workflows/download_convert.yml b/.github/workflows/download_convert.yml index bc2b074..760c58d 100644 --- a/.github/workflows/download_convert.yml +++ b/.github/workflows/download_convert.yml @@ -1,11 +1,14 @@ name: download_convert on: + push: + branches: [ "main" ] pull_request: branches: [ "main" ] + jobs: - build-and-push: + build: runs-on: ubuntu-latest steps: - name: Checkout code @@ -22,24 +25,41 @@ jobs: COMMIT_HASH=$(git rev-parse HEAD) echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV + - name: Build Docker image + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/download_convert/Dockerfile + tags: imagingdatacommons/download_convert + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} + + push-dockerhub: + needs: build + if: github.event_name == 'push' && github.ref == 'refs/heads/main' + runs-on: ubuntu-latest + steps: - name: Login to Docker Hub uses: docker/login-action@v3 with: username: ${{ secrets.DOCKER_USERNAME }} password: ${{ secrets.DOCKER_PASSWORD }} - - name: Build and push Docker image to Docker Hub + - name: Push Docker image to Docker Hub uses: docker/build-push-action@v5 with: context: . file: ./Dockerfiles/download_convert/Dockerfile push: true tags: imagingdatacommons/download_convert - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} + push-ghcr: + needs: build + if: github.event_name == 'push' && github.ref == 'refs/heads/main' + runs-on: ubuntu-latest + steps: - name: Login to GitHub Container Registry (ghcr.io) uses: docker/login-action@v1 with: @@ -47,14 +67,10 @@ jobs: username: ${{ github.actor }} password: ${{ secrets.GITHUB_TOKEN }} - - name: Build and push Docker image to GitHub Container Registry + - name: Push Docker image to GitHub Container Registry uses: docker/build-push-action@v5 with: context: . file: ./Dockerfiles/download_convert/Dockerfile push: true tags: ghcr.io/imagingdatacommons/download_convert - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} From 434d7e5ab5b0964117596096dc73db298d4868ce Mon Sep 17 00:00:00 2001 From: vkt1414 Date: Mon, 2 Oct 2023 15:46:49 -0400 Subject: [PATCH 40/40] push docker images only on push events --- .../workflows/dicom_seg_pyradiomics_sr.yml | 38 +++++++++++++------ .../download_convert_inference_totalseg.yml | 37 ++++++++++++------ ...ence_totalseg_dicom_seg_pyradiomics_sr.yml | 38 +++++++++++++------ .github/workflows/inference_totalseg.yml | 37 ++++++++++++------ .../per_frame_functional_group_sequence.yml | 37 ++++++++++++------ 5 files changed, 132 insertions(+), 55 deletions(-) diff --git a/.github/workflows/dicom_seg_pyradiomics_sr.yml b/.github/workflows/dicom_seg_pyradiomics_sr.yml index 1229831..3a5ee52 100644 --- a/.github/workflows/dicom_seg_pyradiomics_sr.yml +++ b/.github/workflows/dicom_seg_pyradiomics_sr.yml @@ -1,12 +1,15 @@ name: dicom_seg_pyradiomics_sr on: + push: + branches: [ "main" ] pull_request: branches: [ "main" ] + jobs: - build-and-push: + build: runs-on: ubuntu-latest steps: - name: Checkout code @@ -23,24 +26,41 @@ jobs: COMMIT_HASH=$(git rev-parse HEAD) echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV + - name: Build Docker image + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/dicom_seg_pyradiomics_sr/Dockerfile + tags: imagingdatacommons/dicom_seg_pyradiomics_sr + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} + + push-dockerhub: + needs: build + if: github.event_name == 'push' && github.ref == 'refs/heads/main' + runs-on: ubuntu-latest + steps: - name: Login to Docker Hub uses: docker/login-action@v3 with: username: ${{ secrets.DOCKER_USERNAME }} password: ${{ secrets.DOCKER_PASSWORD }} - - name: Build and push Docker image + - name: Push Docker image to Docker Hub uses: docker/build-push-action@v5 with: context: . file: ./Dockerfiles/dicom_seg_pyradiomics_sr/Dockerfile push: true tags: imagingdatacommons/dicom_seg_pyradiomics_sr - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} + push-ghcr: + needs: build + if: github.event_name == 'push' && github.ref == 'refs/heads/main' + runs-on: ubuntu-latest + steps: - name: Login to GitHub Container Registry (ghcr.io) uses: docker/login-action@v1 with: @@ -48,14 +68,10 @@ jobs: username: ${{ github.actor }} password: ${{ secrets.GITHUB_TOKEN }} - - name: Build and push Docker image to GitHub Container Registry + - name: Push Docker image to GitHub Container Registry uses: docker/build-push-action@v5 with: context: . file: ./Dockerfiles/dicom_seg_pyradiomics_sr/Dockerfile push: true tags: ghcr.io/imagingdatacommons/dicom_seg_pyradiomics_sr - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file diff --git a/.github/workflows/download_convert_inference_totalseg.yml b/.github/workflows/download_convert_inference_totalseg.yml index 7f2c357..c3eddbb 100644 --- a/.github/workflows/download_convert_inference_totalseg.yml +++ b/.github/workflows/download_convert_inference_totalseg.yml @@ -1,11 +1,13 @@ name: download_convert_inference_totalseg on: + push: + branches: [ "main" ] pull_request: branches: [ "main" ] jobs: - build-and-push: + build: runs-on: ubuntu-latest steps: - name: Checkout code @@ -26,24 +28,41 @@ jobs: run: | cp Dockerfiles/download_convert_inference_totalseg/weights_download.sh . + - name: Build Docker image + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/download_convert_inference_totalseg/Dockerfile + tags: imagingdatacommons/download_convert_inference_totalseg + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} + + push-dockerhub: + needs: build + if: github.event_name == 'push' && github.ref == 'refs/heads/main' + runs-on: ubuntu-latest + steps: - name: Login to Docker Hub uses: docker/login-action@v3 with: username: ${{ secrets.DOCKER_USERNAME }} password: ${{ secrets.DOCKER_PASSWORD }} - - name: Build and push Docker image + - name: Push Docker image to Docker Hub uses: docker/build-push-action@v5 with: context: . file: ./Dockerfiles/download_convert_inference_totalseg/Dockerfile push: true tags: imagingdatacommons/download_convert_inference_totalseg - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} + push-ghcr: + needs: build + if: github.event_name == 'push' && github.ref == 'refs/heads/main' + runs-on: ubuntu-latest + steps: - name: Login to GitHub Container Registry (ghcr.io) uses: docker/login-action@v1 with: @@ -51,14 +70,10 @@ jobs: username: ${{ github.actor }} password: ${{ secrets.GITHUB_TOKEN }} - - name: Build and push Docker image to GitHub Container Registry + - name: Push Docker image to GitHub Container Registry uses: docker/build-push-action@v5 with: context: . file: ./Dockerfiles/download_convert_inference_totalseg/Dockerfile push: true tags: ghcr.io/imagingdatacommons/download_convert_inference_totalseg - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file diff --git a/.github/workflows/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr.yml b/.github/workflows/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr.yml index 4b7f24a..dbdf69d 100644 --- a/.github/workflows/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr.yml +++ b/.github/workflows/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr.yml @@ -1,11 +1,14 @@ name: download_convert_inference_totalseg_dicom_seg_pyradiomics_sr on: + push: + branches: [ "main" ] pull_request: branches: [ "main" ] + jobs: - build-and-push: + build: runs-on: ubuntu-latest steps: - name: Checkout code @@ -26,24 +29,41 @@ jobs: run: | cp Dockerfiles/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr/weights_download.sh . + - name: Build Docker image + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr/Dockerfile + tags: imagingdatacommons/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} + + push-dockerhub: + needs: build + if: github.event_name == 'push' && github.ref == 'refs/heads/main' + runs-on: ubuntu-latest + steps: - name: Login to Docker Hub uses: docker/login-action@v3 with: username: ${{ secrets.DOCKER_USERNAME }} password: ${{ secrets.DOCKER_PASSWORD }} - - name: Build and push Docker image (main) + - name: Push Docker image to Docker Hub uses: docker/build-push-action@v5 with: context: . file: ./Dockerfiles/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr/Dockerfile push: true tags: imagingdatacommons/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} + push-ghcr: + needs: build + if: github.event_name == 'push' && github.ref == 'refs/heads/main' + runs-on: ubuntu-latest + steps: - name: Login to GitHub Container Registry (ghcr.io) uses: docker/login-action@v1 with: @@ -51,14 +71,10 @@ jobs: username: ${{ github.actor }} password: ${{ secrets.GITHUB_TOKEN }} - - name: Build and push Docker image to GitHub Container Registry + - name: Push Docker image to GitHub Container Registry uses: docker/build-push-action@v5 with: context: . file: ./Dockerfiles/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr/Dockerfile push: true tags: ghcr.io/imagingdatacommons/download_convert_inference_totalseg_dicom_seg_pyradiomics_sr - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file diff --git a/.github/workflows/inference_totalseg.yml b/.github/workflows/inference_totalseg.yml index e55c456..dcdf4db 100644 --- a/.github/workflows/inference_totalseg.yml +++ b/.github/workflows/inference_totalseg.yml @@ -1,12 +1,14 @@ name: inference_totalseg on: + push: + branches: [ "main" ] pull_request: branches: [ "main" ] jobs: - build-and-push: + build: runs-on: ubuntu-latest steps: - name: Checkout code @@ -27,24 +29,41 @@ jobs: run: | cp Dockerfiles/inference_totalseg/weights_download.sh . + - name: Build Docker image + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/inference_totalseg/Dockerfile + tags: imagingdatacommons/inference_totalseg + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} + + push-dockerhub: + needs: build + if: github.event_name == 'push' && github.ref == 'refs/heads/main' + runs-on: ubuntu-latest + steps: - name: Login to Docker Hub uses: docker/login-action@v3 with: username: ${{ secrets.DOCKER_USERNAME }} password: ${{ secrets.DOCKER_PASSWORD }} - - name: Build and push Docker image + - name: Push Docker image to Docker Hub uses: docker/build-push-action@v5 with: context: . file: ./Dockerfiles/inference_totalseg/Dockerfile push: true tags: imagingdatacommons/inference_totalseg - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} + push-ghcr: + needs: build + if: github.event_name == 'push' && github.ref == 'refs/heads/main' + runs-on: ubuntu-latest + steps: - name: Login to GitHub Container Registry (ghcr.io) uses: docker/login-action@v1 with: @@ -52,14 +71,10 @@ jobs: username: ${{ github.actor }} password: ${{ secrets.GITHUB_TOKEN }} - - name: Build and push Docker image to GitHub Container Registry + - name: Push Docker image to GitHub Container Registry uses: docker/build-push-action@v5 with: context: . file: ./Dockerfiles/inference_totalseg/Dockerfile push: true tags: ghcr.io/imagingdatacommons/inference_totalseg - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file diff --git a/.github/workflows/per_frame_functional_group_sequence.yml b/.github/workflows/per_frame_functional_group_sequence.yml index be0d633..7c34bae 100644 --- a/.github/workflows/per_frame_functional_group_sequence.yml +++ b/.github/workflows/per_frame_functional_group_sequence.yml @@ -1,11 +1,13 @@ name: per_frame_functional_group_sequence on: + push: + branches: [ "main" ] pull_request: branches: [ "main" ] jobs: - build-and-push: + build: runs-on: ubuntu-latest steps: - name: Checkout code @@ -22,24 +24,41 @@ jobs: COMMIT_HASH=$(git rev-parse HEAD) echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV + - name: Build Docker image + uses: docker/build-push-action@v5 + with: + context: . + file: ./Dockerfiles/per_frame_functional_group_sequence/Dockerfile + tags: imagingdatacommons/per_frame_functional_group_sequence + build-args: | + GIT_HASH=${{ env.COMMIT_HASH }} + env: + COMMIT_HASH: ${{ env.COMMIT_HASH }} + + push-dockerhub: + needs: build + if: github.event_name == 'push' && github.ref == 'refs/heads/main' + runs-on: ubuntu-latest + steps: - name: Login to Docker Hub uses: docker/login-action@v3 with: username: ${{ secrets.DOCKER_USERNAME }} password: ${{ secrets.DOCKER_PASSWORD }} - - name: Build and push Docker image + - name: Push Docker image to Docker Hub uses: docker/build-push-action@v5 with: context: . file: ./Dockerfiles/per_frame_functional_group_sequence/Dockerfile push: true tags: imagingdatacommons/per_frame_functional_group_sequence - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} + push-ghcr: + needs: build + if: github.event_name == 'push' && github.ref == 'refs/heads/main' + runs-on: ubuntu-latest + steps: - name: Login to GitHub Container Registry (ghcr.io) uses: docker/login-action@v1 with: @@ -47,14 +66,10 @@ jobs: username: ${{ github.actor }} password: ${{ secrets.GITHUB_TOKEN }} - - name: Build and push Docker image to GitHub Container Registry + - name: Push Docker image to GitHub Container Registry uses: docker/build-push-action@v5 with: context: . file: ./Dockerfiles/per_frame_functional_group_sequence/Dockerfile push: true tags: ghcr.io/imagingdatacommons/per_frame_functional_group_sequence - build-args: | - GIT_HASH=${{ env.COMMIT_HASH }} - env: - COMMIT_HASH: ${{ env.COMMIT_HASH }} \ No newline at end of file