update package versions in workflows (#592)

.github/workflows/ci.yml

@@ -80,13 +80,13 @@ jobs:
           pip install mmcv-full==1.6.1 -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.11.0/index.html
           pip install mmdet==2.25.1
 
-      - name: Install YOLOv5(6.1.8) and Norfair(1.0.0)
+      - name: Install YOLOv5(6.2.1) and Norfair(1.0.0)
         run: >
-          pip install yolov5==6.1.8 norfair==1.0.0
+          pip install yolov5==6.2.1 norfair==1.0.0
 
-      - name: Install Transformers(4.21.2)
+      - name: Install Transformers(4.22.1)
         run: >
-          pip install transformers==4.21.2
+          pip install transformers==4.22.1
 
       - name: Install Layer (0.10.*)
         run: >
@@ -96,9 +96,9 @@ jobs:
         run: |
           python -m unittest
 
-      - name: Install pycocotools(2.0.4)
+      - name: Install pycocotools(2.0.5)
         run: >
-          pip install pycocotools==2.0.4
+          pip install pycocotools==2.0.5
 
       - name: Install SAHI package from local setup.py
         run: >

.github/workflows/ci_torch1.10.yml

@@ -81,15 +81,15 @@ jobs:
           pip install mmcv-full==1.6.1 -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.10.0/index.html
           pip install mmdet==2.25.1
 
-      - name: Install YOLOv5(6.1.8) and Norfair(1.0.0)
+      - name: Install YOLOv5(6.2.1) and Norfair(1.0.0)
         run: >
-          pip install yolov5==6.1.8 norfair==1.0.0
+          pip install yolov5==6.2.1 norfair==1.0.0
 
       - name: Install Detectron2(0.6)
         run: >
           python -m pip install detectron2 -f https://dl.fbaipublicfiles.com/detectron2/wheels/cpu/torch1.10/index.html
 
-      - name: Install Transformers(4.21.2)
+      - name: Install Transformers(4.22.1)
         if: >
           matrix.python-version != '3.6'
         run: >
@@ -105,9 +105,9 @@ jobs:
         run: |
           python -m unittest
 
-      - name: Install pycocotools(2.0.4)
+      - name: Install pycocotools(2.0.5)
         run: >
-          pip install pycocotools==2.0.4
+          pip install pycocotools==2.0.5
 
       - name: Install SAHI package from local setup.py
         run: >

.github/workflows/package_testing.yml

@@ -67,9 +67,9 @@ jobs:
           pip install mmcv-full==1.6.1 -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.10.0/index.html
           pip install mmdet==2.25.1
 
-      - name: Install YOLOv5(6.1.8) and Norfair(1.0.0)
+      - name: Install YOLOv5(6.2.1) and Norfair(1.0.0)
         run: >
-          pip install yolov5==6.1.8 norfair==1.0.0
+          pip install yolov5==6.2.1 norfair==1.0.0
           
       - name: Install Detectron2(0.6)
         run: >
@@ -87,9 +87,9 @@ jobs:
         run: >
           pip install -U "layer>=0.10.0,<0.11.0"
 
-      - name: Install pycocotools(2.0.4)
+      - name: Install pycocotools(2.0.5)
         run: >
-          pip install pycocotools==2.0.4
+          pip install pycocotools==2.0.5
 
       - name: Install latest SAHI package
         run: >

README.md

@@ -49,7 +49,7 @@ Object detection and instance segmentation are by far the most important fields
 
 - [Introduction to SAHI](https://medium.com/codable/sahi-a-vision-library-for-performing-sliced-inference-on-large-images-small-objects-c8b086af3b80)
 
-- [Official paper](https://arxiv.org/abs/2202.06934) (ICIP 2022 oral, 9+ citations)
+- [Official paper](https://arxiv.org/abs/2202.06934) (ICIP 2022 oral, 11+ citations)
 
 - [Pretrained weights and ICIP 2022 paper files](https://github.com/fcakyon/small-object-detection-benchmark)
 
@@ -115,7 +115,7 @@ conda install pytorch=1.11.0 torchvision=0.12.0 cudatoolkit=11.3 -c pytorch
 - Install your desired detection framework (yolov5):
 
 ```console
-pip install yolov5==6.1.8
+pip install yolov5==6.2.1
 ```
 
 - Install your desired detection framework (mmdet):

sahi/model.py

@@ -421,12 +421,23 @@ def has_mask(self):
         """
         Returns if model output contains segmentation mask
         """
-        has_mask = self.model.with_mask
-        return has_mask
+        import yolov5
+        from packaging import version
+
+        if version.parse(yolov5.__version__) < version.parse("6.2.0"):
+            return False
+        else:
+            return False  # fix when yolov5 supports segmentation models
 
     @property
     def category_names(self):
-        return self.model.names
+        import yolov5
+        from packaging import version
+
+        if version.parse(yolov5.__version__) >= version.parse("6.1.9"):
+            return list(self.model.names.values())
+        else:
+            return self.model.names
 
     def _create_object_prediction_list_from_original_predictions(
         self,