Update app.py

app.py

@@ -9,7 +9,7 @@ max_len = 10
 def ocr(plate_image, ocr_model):
   try:
     if 'yolo' in ocr_model:
-      model = YOLO(f'/content/drive/MyDrive/{ocr_model}.pt', task='detect')
+      model = YOLO(f'./weights/{ocr_model}.pt', task='detect')
       preds = model.predict(plate_image)
       return ''.join([model.names[int(pred.boxes.cls.cpu().numpy()[0])] for pred in preds[0]])
     else:
@@ -20,7 +20,7 @@ def ocr(plate_image, ocr_model):
 
 def process_image(image, detection_model, ocr_model, yolo_thresh, perpective_width, perpective_height):
     task = 'obb' if 'obb' in detection_model else 'detect'
-    model = YOLO(f'/content/drive/MyDrive/{detection_model}.pt', task=task)
+    model = YOLO(f'./weights/{detection_model}.pt', task=task)
 
     predict  = model(image, conf=yolo_thresh)
     
@@ -44,7 +44,7 @@ def create_interface():
         with gr.Row():
             with gr.Column(scale=1):
               detection_model = gr.Dropdown(label="Detection Model", choices=["yolov8-m", "yolov8-obb-m","yolov8-s", "yolov8-obb-s"], value="yolov8-m")
-              ocr_model = gr.Dropdown(label="OCR Model", choices=["trocr-v1", "trocr-v2"], value="trocr-v1")
+              ocr_model = gr.Dropdown(label="OCR Model", choices=["yolov32c", "trocr"], value="yolov32c")
               yolo_thresh = gr.Slider(minimum=0.0, maximum=1.0, label='yolo_threshold')
               with gr.Row():
                 perpective_width = gr.Slider(minimum=100, maximum=500, label='perpective_width')