Update app.py

app.py

@@ -75,23 +75,12 @@ interface_image = gr.Interface(
 
 ##################################################Video Inference################################################################
 def show_preds_video(
-    video_path: gr.components.Video = None,
-    model_path: gr.inputs.Dropdown = None,
-    image_size: gr.inputs.Slider = 640,
-    conf_threshold: gr.inputs.Slider = 0.25,
-    iou_threshold: gr.inputs.Slider = 0.45,
+    video_path: str = None,
+    model_path: str = None,
+    image_size: int = 640,
+    conf_threshold: float = 0.25,
+    iou_threshold: float = 0.45,
 ):
-    """
-    Video inference function
-    Args:
-        video_path: Input video
-        model_path: Path to the model
-        image_size: Image size
-        conf_threshold: Confidence threshold
-        iou_threshold: IOU threshold
-    Returns:
-        Rendered video
-    """
     cap = cv2.VideoCapture(video_path)
 
     while cap.isOpened():
@@ -106,8 +95,10 @@ def show_preds_video(
             results = model.predict(frame)
             annotated_frame = results[0].plot()
 
-            cv2.imshow("YOLOv8 Inference", annotated_frame)
+            # Do not display the frame using cv2.imshow
+            # cv2.imshow("YOLOv8 Inference", annotated_frame)
 
+            # Break the loop if 'q' is pressed
             if cv2.waitKey(1) & 0xFF == ord("q"):
                 break
         else:
@@ -115,7 +106,8 @@ def show_preds_video(
 
     cap.release()
     cv2.destroyAllWindows()
-    
+
+
 inputs_video = [
     gr.components.Video(type="filepath", label="Input Video"),
     gr.inputs.Dropdown(["foduucom/stockmarket-pattern-detection-yolov8"],