bugfixes, better test coverage (#28)

* add daily package testing workflow

* add ci tests for scripts

* fix cli argument

* fix function argument

* add export format selection

* update to v0.2.5

.github/workflows/ci.yml

@@ -73,4 +73,17 @@ jobs:
     - name: Test with unittest
       run: |
         pip install pytest
-        python -m unittest
+        python -m unittest
+    - name: Install SAHI package from local setup.py
+      run: >
+        pip install -e .
+    - name: Test SAHI scripts for mmdet < 2.9.0
+      if: matrix.mmdet-version == '2.8.0'
+      run: |
+        # predict_folder
+        python scripts/predict_folder.py --image_dir tests/data/coco_utils/ --visual_output_dir outputs/ --model_path tests/data/models/mmdet_retinanet/retinanet_r50_fpn_2x_coco_20200131-fdb43119.pth --config_path tests/data/models/mmdet_retinanet/retinanet_r50_fpn_1x_coco.py
+    - name: Test SAHI scripts for mmdet == 2.9.0
+      if: matrix.mmdet-version == '2.9.0'
+      run: |
+        # predict_folder
+        python scripts/predict_folder.py --image_dir tests/data/coco_utils/ --visual_output_dir outputs/ --model_path tests/data/models/mmdet_retinanet/retinanet_r50_fpn_2x_coco_20200131-fdb43119.pth --config_path tests/data/models/mmdet_retinanet/retinanet_r50_fpn_1x_coco_v290.py

.github/workflows/package_testing.yml

@@ -0,0 +1,66 @@
+name: Package Testing
+
+on:
+  schedule:
+    - cron: '0 0 * * *'  # Runs at 00:00 UTC every day
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    strategy:
+      matrix:
+        operating-system: [ubuntu-latest, windows-latest, macos-latest]
+        python-version: [3.6, 3.7, 3.8]
+        mmdet-version : [2.8.0, 2.9.0]
+      fail-fast: false
+
+    steps:
+    - name: Checkout
+      uses: actions/checkout@v2
+    - name: Set up Python
+      uses: actions/setup-python@v2
+      with:
+        python-version: ${{ matrix.python-version }}
+    - name: Restore Ubuntu cache
+      uses: actions/cache@v1
+      if: matrix.operating-system == 'ubuntu-latest'
+      with:
+        path: ~/.cache/pip
+        key: ${{ matrix.os }}-${{ matrix.python-version }}-${{ hashFiles('**/setup.py')}}
+        restore-keys: ${{ matrix.os }}-${{ matrix.python-version }}-
+    - name: Restore MacOS cache
+      uses: actions/cache@v1
+      if:  matrix.operating-system == 'macos-latest'
+      with:
+        path: ~/Library/Caches/pip
+        key: ${{ matrix.os }}-${{ matrix.python-version }}-${{ hashFiles('**/setup.py')}}
+        restore-keys: ${{ matrix.os }}-${{ matrix.python-version }}-
+    - name: Restore Windows cache
+      uses: actions/cache@v1
+      if: matrix.operating-system == 'windows-latest'
+      with:
+        path: ~\AppData\Local\pip\Cache
+        key: ${{ matrix.os }}-${{ matrix.python-version }}-${{ hashFiles('**/setup.py')}}
+        restore-keys: ${{ matrix.os }}-${{ matrix.python-version }}-
+    - name: Update pip
+      run: python -m pip install --upgrade pip
+    - name: Install latest SAHI package
+      run: >
+        pip install --upgrade --force-reinstall sahi
+    - name: Install MMDetection
+      run: >
+        pip install mmcv-full==1.2.5 mmdet==${{ matrix.mmdet-version }}
+    - name: Test with unittest
+      run: |
+        python -m unittest
+    - name: Test SAHI scripts for mmdet < 2.9.0
+      if: matrix.mmdet-version == '2.8.0'
+      run: |
+        # predict_folder
+        python scripts/predict_folder.py --image_dir tests/data/coco_utils/ --visual_output_dir outputs/ --model_path tests/data/models/mmdet_retinanet/retinanet_r50_fpn_2x_coco_20200131-fdb43119.pth --config_path tests/data/models/mmdet_retinanet/retinanet_r50_fpn_1x_coco.py
+    - name: Test SAHI scripts for mmdet == 2.9.0
+      if: matrix.mmdet-version == '2.9.0'
+      run: |
+        # predict_folder
+        python scripts/predict_folder.py --image_dir tests/data/coco_utils/ --visual_output_dir outputs/ --model_path tests/data/models/mmdet_retinanet/retinanet_r50_fpn_2x_coco_20200131-fdb43119.pth --config_path tests/data/models/mmdet_retinanet/retinanet_r50_fpn_1x_coco_v290.py

sahi/__init__.py

@@ -1 +1 @@
-__version__ = "0.2.4"
+__version__ = "0.2.5"

sahi/predict.py

@@ -265,6 +265,7 @@ def predict_folder(
     visual_bbox_thickness: int = 1,
     visual_text_size: float = 1,
     visual_text_thickness: int = 1,
+    visual_export_format: str = "png",
     verbose: int = 1,
 ):
     """
@@ -311,6 +312,8 @@ def predict_folder(
         visual_bbox_thickness: int
         visual_text_size: float
         visual_text_thickness: int
+        visual_export_format: str
+            Can be specified as 'jpg' or 'png'
         verbose: int
             0: no print
             1: print slice/prediction durations, number of slices, model loading/file exporting durations
@@ -377,7 +380,7 @@ def predict_folder(
                 image=image,
                 detection_model=detection_model,
                 shift_amount=[0, 0],
-                full_image_size=None,
+                full_shape=None,
                 merger=None,
                 matcher=None,
                 verbose=0,
@@ -414,6 +417,7 @@ def predict_folder(
                 text_th=visual_text_thickness,
                 output_dir=visual_output_dir,
                 file_name=filename_without_extension,
+                export_format=visual_export_format,
             )
         time_end = time.time() - time_start
         durations_in_seconds["export_files"] = time_end

sahi/utils/cv.py

@@ -195,6 +195,7 @@ def visualize_object_predictions(
     color: tuple = (0, 0, 0),
     output_dir: str = "",
     file_name: str = "prediction_visual",
+    export_format: str = "png",
 ):
     """
     Visualizes prediction category names, bounding boxes over the source image
@@ -207,6 +208,7 @@ def visualize_object_predictions(
         color: annotation color in the form: (0, 255, 0)
         output_dir: directory for resulting visualization to be exported
         file_name: exported file will be saved as: output_dir+file_name+".png"
+        export_format: can be specified as 'jpg' or 'png'
     """
     elapsed_time = time.time()
     # deepcopy image so that original is not altered
@@ -258,7 +260,7 @@ def visualize_object_predictions(
         # create output folder if not present
         create_dir(output_dir)
         # save inference result
-        save_path = os.path.join(output_dir, file_name + ".png")
+        save_path = os.path.join(output_dir, file_name + "." + export_format)
         cv2.imwrite(save_path, cv2.cvtColor(image, cv2.COLOR_RGB2BGR))
     elapsed_time = time.time() - elapsed_time
     return {"image": image, "elapsed_time": elapsed_time}

scripts/predict_folder.py

@@ -4,6 +4,7 @@
 
 if __name__ == "__main__":
     parser = argparse.ArgumentParser()
+    parser.add_argument("--image_dir", type=str, default="", help="image directory")
     parser.add_argument(
         "--model_name",
         type=str,
@@ -25,7 +26,7 @@
     parser.add_argument(
         "--prediction_score_threshold",
         type=float,
-        default="",
+        default=0.25,
         help="all predictions with score < prediction_score_threshold will be discarded",
     )
     parser.add_argument(
@@ -46,7 +47,6 @@
         default=None,
         help='remap category ids based on category names, after performing inference e.g. {"car": 3}',
     )
-    parser.add_argument("--image_dir", type=str, default="", help="image directory")
     parser.add_argument(
         "--visual_output_dir", type=str, default="", help="output visual directory"
     )
@@ -62,6 +62,7 @@
     parser.add_argument("--overlap_height_ratio", type=float, default=0.2)
     parser.add_argument("--overlap_width_ratio", type=float, default=0.2)
     parser.add_argument("--match_iou_threshold", type=float, default=0.5)
+    parser.add_argument("--visual_export_format", type=str, default="png")
 
     opt = parser.parse_args()
 
@@ -86,4 +87,5 @@
         overlap_height_ratio=opt.overlap_height_ratio,
         overlap_width_ratio=opt.overlap_width_ratio,
         match_iou_threshold=opt.match_iou_threshold,
+        visual_export_format=opt.visual_export_format,
     )