add rknn conversion - install and use scripts, auto convert to rknn after AI training is done and put pt and rknn models to /azaion/models directory

preprocessing.py

@@ -116,30 +116,35 @@ def process_image(img_ann):
     ))
 
 
-def main():
+def preprocess_annotations():
     os.makedirs(processed_images_dir, exist_ok=True)
     os.makedirs(processed_labels_dir, exist_ok=True)
-    while True:
-        processed_images = set(f.name for f in os.scandir(processed_images_dir))
-        images = []
-        with os.scandir(data_images_dir) as imd:
-            for image_file in imd:
-                if image_file.is_file() and image_file.name not in processed_images:
-                    images.append(image_file)
 
-        for image_file in images:
-            try:
-                image_path = os.path.join(data_images_dir, image_file.name)
-                labels_path = os.path.join(data_labels_dir, f'{Path(image_path).stem}.txt')
-                image = cv2.imdecode(np.fromfile(image_path, dtype=np.uint8), cv2.IMREAD_UNCHANGED)
-                process_image(ImageLabel(
-                    image_path=image_path,
-                    image=image,
-                    labels_path=labels_path,
-                    labels=read_labels(labels_path)
-                ))
-            except Exception as e:
-                print(f'Error appeared {e}')
+    processed_images = set(f.name for f in os.scandir(processed_images_dir))
+    images = []
+    with os.scandir(data_images_dir) as imd:
+        for image_file in imd:
+            if image_file.is_file() and image_file.name not in processed_images:
+                images.append(image_file)
+
+    for image_file in images:
+        try:
+            image_path = os.path.join(data_images_dir, image_file.name)
+            labels_path = os.path.join(data_labels_dir, f'{Path(image_path).stem}.txt')
+            image = cv2.imdecode(np.fromfile(image_path, dtype=np.uint8), cv2.IMREAD_UNCHANGED)
+            process_image(ImageLabel(
+                image_path=image_path,
+                image=image,
+                labels_path=labels_path,
+                labels=read_labels(labels_path)
+            ))
+        except Exception as e:
+            print(f'Error appeared {e}')
+
+
+def main():
+    while True:
+        preprocess_annotations()
         print('All processed, waiting for 2 minutes...')
         time.sleep(120)