ok

scripts/up_serving.sh

@@ -4,5 +4,6 @@ RATIO_GPU=${RATIO_GPU:-0.45}
 echo "Using GPU: $NVIDIA_VISIBLE_DEVICES"
 echo "Limiting GPU to ratio: $RATIO_GPU"
 
+cd /src/mot/serving
 python3 -m mot.serving.app &
 /usr/bin/tf_serving_entrypoint.sh --per_process_gpu_memory_fraction=$RATIO_GPU

src/mot/object_detection/query_server.py

@@ -86,7 +86,7 @@ def localizer_tensorflow_serving_inference(
                 [0.1, 0.1, 0.9, 0.9],
                 [0.0, 0.2, 0.1, 0.4],
                 [0.2, 0.4, 0.5, 0.7],
-                ], (y1, x1, y2, x2) scaled between 0 and 1
+                ], # (y1, x1, y2, x2) scaled between 0 and 1
             'output/labels:0': [3, 1, 2], # the labels start at 1 since 0 is for background
             'output/scores:0': [0.98, 0.87, 0.76] # sorted in descending order
         }

src/mot/serving/inference.py

@@ -80,14 +80,26 @@ def process_video():
     def process_zip():
         images_folder = os.path.join(upload_folder, "{}_split".format(filename))
         with zipfile.ZipFile(full_filepath, 'r') as zip_obj:
-            file_names = zip_obj.namelist()
-            for file_name in file_names:
-                zip_obj.extract(file_name, images_folder)
-                if os.path.basename(file_name):
-                    shutil.move(
-                        os.path.join(images_folder, file_name),
-                        os.path.join(images_folder, os.path.basename(file_name))
-                    )
+            zip_obj.extractall(images_folder)
+
+        def move_files_to_root(directory, root_directory):
+            for x in os.listdir(directory):
+                path = os.path.join(directory, x)
+                if x.startswith("._") or x.startswith("__"):
+                    # unwanted files such as __MACOSX
+                    shutil.rmtree(path)
+                else:
+                    if os.path.isfile(path):
+                        # we want to move this file to the root of the zip directory
+                        if not os.path.isfile(os.path.join(root_directory, x)):
+                            # unless it is aleady present at root
+                            shutil.move(path, root_directory)
+                    else:
+                        # if there is a folder, we want to move back the files to root
+                        move_files_to_root(path, root_directory)
+
+        move_files_to_root(images_folder, images_folder)
+
         return images_folder
 
     if file.mimetype == "":
@@ -154,8 +166,6 @@ def _process_image(image_path: str) -> Dict:
     ```
     """
     image = cv2.imread(image_path)  # cv2 opens in BGR
-    if image is None:
-        return None
     predictions = localizer_tensorflow_serving_inference(image, SERVING_URL, return_all_scores=True)
     return predictions
 

src/mot/serving/viz.py

@@ -25,8 +25,8 @@ def draw_boxes(image_path: str, trashes: List[Dict]):
             img,
             trash["label"] + " " + str(round(trash["score"], 2)),
             (box[0], box[1] - 10),
-            cv2.FONT_HERSHEY_COMPLEX,
-            2,
+            cv2.FONT_HERSHEY_SIMPLEX,
+            1,
             CLASS_NAME_TO_COLOR[trash["label"]],
             cv2.LINE_4,
         )