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Removing 3D tutorial, this one still needs work
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Signed-off-by: Eric Kerfoot <[email protected]>
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ericspod committed Sep 5, 2024
1 parent 4f37e26 commit 9e994f4
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30 changes: 11 additions & 19 deletions generation/2d_ddpm/2d_ddpm_compare_schedulers.ipynb
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"cells": [
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"# Copyright (c) MONAI Consortium\n",
"# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
"# you may not use this file except in compliance with the License.\n",
"# You may obtain a copy of the License at\n",
"# http://www.apache.org/licenses/LICENSE-2.0\n",
"# Unless required by applicable law or agreed to in writing, software\n",
"# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
"# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
"# See the License for the specific language governing permissions and\n",
"# limitations under the License."
]
},
{
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"id": "d462dbf4",
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"source": [
"Copyright (c) MONAI Consortium \n",
"Licensed under the Apache License, Version 2.0 (the \"License\"); \n",
"you may not use this file except in compliance with the License. \n",
"You may obtain a copy of the License at \n",
"&nbsp;&nbsp;&nbsp;&nbsp;http://www.apache.org/licenses/LICENSE-2.0 \n",
"Unless required by applicable law or agreed to in writing, software \n",
"distributed under the License is distributed on an \"AS IS\" BASIS, \n",
"WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. \n",
"See the License for the specific language governing permissions and \n",
"limitations under the License.\n",
"\n",
"# Denoising Diffusion Probabilistic Models with MedNIST Dataset\n",
"\n",
"This tutorial compares the different schedulers available for sampling from a trained model with a reduced number of timesteps. The schedulers we will compare are:\n",
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30 changes: 11 additions & 19 deletions generation/2d_ddpm/2d_ddpm_inpainting.ipynb
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@@ -1,29 +1,21 @@
{
"cells": [
{
"cell_type": "code",
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"id": "4c8ec6e8",
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"outputs": [],
"source": [
"# Copyright (c) MONAI Consortium\n",
"# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
"# you may not use this file except in compliance with the License.\n",
"# You may obtain a copy of the License at\n",
"# http://www.apache.org/licenses/LICENSE-2.0\n",
"# Unless required by applicable law or agreed to in writing, software\n",
"# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
"# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
"# See the License for the specific language governing permissions and\n",
"# limitations under the License."
]
},
{
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"id": "9d71306f",
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"source": [
"Copyright (c) MONAI Consortium \n",
"Licensed under the Apache License, Version 2.0 (the \"License\"); \n",
"you may not use this file except in compliance with the License. \n",
"You may obtain a copy of the License at \n",
"&nbsp;&nbsp;&nbsp;&nbsp;http://www.apache.org/licenses/LICENSE-2.0 \n",
"Unless required by applicable law or agreed to in writing, software \n",
"distributed under the License is distributed on an \"AS IS\" BASIS, \n",
"WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. \n",
"See the License for the specific language governing permissions and \n",
"limitations under the License.\n",
"\n",
"# Inpainting with Denoising Diffusion Probabilistic Models\n",
"\n",
"This tutorial illustrates how to use MONAI for training a denoising diffusion probabilistic model (DDPM)[1] to inpaint 2D images.\n",
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30 changes: 11 additions & 19 deletions generation/2d_ddpm/2d_ddpm_tutorial.ipynb
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@@ -1,29 +1,21 @@
{
"cells": [
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"source": [
"# Copyright (c) MONAI Consortium\n",
"# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
"# you may not use this file except in compliance with the License.\n",
"# You may obtain a copy of the License at\n",
"# http://www.apache.org/licenses/LICENSE-2.0\n",
"# Unless required by applicable law or agreed to in writing, software\n",
"# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
"# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
"# See the License for the specific language governing permissions and\n",
"# limitations under the License."
]
},
{
"cell_type": "markdown",
"id": "9d71306f",
"metadata": {},
"source": [
"Copyright (c) MONAI Consortium \n",
"Licensed under the Apache License, Version 2.0 (the \"License\"); \n",
"you may not use this file except in compliance with the License. \n",
"You may obtain a copy of the License at \n",
"&nbsp;&nbsp;&nbsp;&nbsp;http://www.apache.org/licenses/LICENSE-2.0 \n",
"Unless required by applicable law or agreed to in writing, software \n",
"distributed under the License is distributed on an \"AS IS\" BASIS, \n",
"WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. \n",
"See the License for the specific language governing permissions and \n",
"limitations under the License.\n",
"\n",
"# Denoising Diffusion Probabilistic Models with MedNIST Dataset\n",
"\n",
"This tutorial illustrates how to use MONAI for training a denoising diffusion probabilistic model (DDPM)[1] to create\n",
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30 changes: 11 additions & 19 deletions generation/2d_ddpm/2d_ddpm_tutorial_ignite.ipynb
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@@ -1,29 +1,21 @@
{
"cells": [
{
"cell_type": "code",
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"id": "f5cbf8da",
"metadata": {},
"outputs": [],
"source": [
"# Copyright (c) MONAI Consortium\n",
"# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
"# you may not use this file except in compliance with the License.\n",
"# You may obtain a copy of the License at\n",
"# http://www.apache.org/licenses/LICENSE-2.0\n",
"# Unless required by applicable law or agreed to in writing, software\n",
"# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
"# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
"# See the License for the specific language governing permissions and\n",
"# limitations under the License."
]
},
{
"cell_type": "markdown",
"id": "53c8dfc0",
"metadata": {},
"source": [
"Copyright (c) MONAI Consortium \n",
"Licensed under the Apache License, Version 2.0 (the \"License\"); \n",
"you may not use this file except in compliance with the License. \n",
"You may obtain a copy of the License at \n",
"&nbsp;&nbsp;&nbsp;&nbsp;http://www.apache.org/licenses/LICENSE-2.0 \n",
"Unless required by applicable law or agreed to in writing, software \n",
"distributed under the License is distributed on an \"AS IS\" BASIS, \n",
"WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. \n",
"See the License for the specific language governing permissions and \n",
"limitations under the License.\n",
"\n",
"# Denoising Diffusion Probabilistic Models with MedNIST Dataset\n",
"\n",
"This tutorial illustrates how to use MONAI for training a denoising diffusion probabilistic model (DDPM)[1] to create\n",
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30 changes: 11 additions & 19 deletions generation/2d_ddpm/2d_ddpm_tutorial_v_prediction.ipynb
Original file line number Diff line number Diff line change
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "a33dc913",
"metadata": {},
"outputs": [],
"source": [
"# Copyright (c) MONAI Consortium\n",
"# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
"# you may not use this file except in compliance with the License.\n",
"# You may obtain a copy of the License at\n",
"# http://www.apache.org/licenses/LICENSE-2.0\n",
"# Unless required by applicable law or agreed to in writing, software\n",
"# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
"# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
"# See the License for the specific language governing permissions and\n",
"# limitations under the License."
]
},
{
"cell_type": "markdown",
"id": "a1851245",
"metadata": {},
"source": [
"Copyright (c) MONAI Consortium \n",
"Licensed under the Apache License, Version 2.0 (the \"License\"); \n",
"you may not use this file except in compliance with the License. \n",
"You may obtain a copy of the License at \n",
"&nbsp;&nbsp;&nbsp;&nbsp;http://www.apache.org/licenses/LICENSE-2.0 \n",
"Unless required by applicable law or agreed to in writing, software \n",
"distributed under the License is distributed on an \"AS IS\" BASIS, \n",
"WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. \n",
"See the License for the specific language governing permissions and \n",
"limitations under the License.\n",
"\n",
"# Denoising Diffusion Probabilistic Models using v-prediction parameterization\n",
"\n",
"This tutorial illustrates how to use MONAI for training a denoising diffusion probabilistic model (DDPM)[1] to create synthetic 2D images using v-prediction parameterization (Section 2.4 from [2]).\n",
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