Fix: AttributeError: 'Video' object has no attribute 'stream'

app.py

@@ -6,8 +6,9 @@ mp_drawing = mp.solutions.drawing_utils
 mp_drawing_styles = mp.solutions.drawing_styles
 mp_hands = mp.solutions.hands
 
-def fun(img):
-    print(type(img))
+def process_frame(img):
+    if img is None:
+        return None
     with mp_hands.Hands(
         model_complexity=0,
         min_detection_confidence=0.5,
@@ -17,7 +18,7 @@ def fun(img):
         image = cv2.flip(img[:, :, ::-1], 1)
         # Convert the BGR image to RGB before processing.
         results = hands.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
-        image.flags.writeable = True
+        img.flags.writeable = True
         if results.multi_hand_landmarks:
             for hand_landmarks in results.multi_hand_landmarks:
                 mp_drawing.draw_landmarks(
@@ -27,21 +28,27 @@ def fun(img):
                     mp_drawing_styles.get_default_hand_landmarks_style(),
                     mp_drawing_styles.get_default_hand_connections_style()
                 )
-
         return cv2.flip(image[:, :, ::-1], 1)
 
 with gr.Blocks(title="Realtime Keypoint Detection | Data Science Dojo", css="footer {display:none !important} .output-markdown{display:none !important}") as demo:
     with gr.Row():
         with gr.Column():
-            webcam_input = gr.Video(label="Webcam Input", format="mp4")  # Webcam input
+            video_input = gr.Video(label="Webcam Input", format="mp4")  # Video input for real-time processing
 
         with gr.Column():
-            output = gr.Image(label="Output Image")
+            output_image = gr.Image(label="Output Image")  # Processed image output
+
+    def update_frame(video):
+        frame = cv2.VideoCapture(video).read()[1]  # Read the current frame
+        if frame is not None:
+            processed_frame = process_frame(frame)
+            return processed_frame
+        return None
 
-    webcam_input.stream(
-        fn=fun,
-        inputs=webcam_input,
-        outputs=output
+    video_input.change(
+        update_frame, 
+        inputs=[video_input], 
+        outputs=[output_image]
     )
 
 demo.launch(debug=True)