Update app.py

app.py

@@ -19,73 +19,77 @@ def calculate_angle(a, b, c):
     return np.degrees(angle)
 
 def detect_pose_video(video_path, max_duration=20):
-    if not os.path.exists(video_path):
-        return None
-
-    cap = cv2.VideoCapture(video_path)
-    if not cap.isOpened():
-        raise ValueError("Cannot open video file")
-
-    # Video properties
-    fps = cap.get(cv2.CAP_PROP_FPS) or 20.0
-    width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH) or 640)
-    height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT) or 480)
-    max_frames = int(fps * max_duration)  # Limit to 20 seconds
-
-    out_path = "annotated_video.mp4"
-    fourcc = cv2.VideoWriter_fourcc(*'mp4v')
-    out = cv2.VideoWriter(out_path, fourcc, fps, (width, height))
-
-    frame_count = 0
-    while frame_count < max_frames:
-        ret, frame = cap.read()
-        if not ret:
-            break
-
-        # Resize if too big
-        max_dim = 640
-        h, w, _ = frame.shape
-        if max(h, w) > max_dim:
-            scale = max_dim / max(h, w)
-            frame = cv2.resize(frame, (int(w*scale), int(h*scale)))
-
-        frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
-        results = pose.process(frame_rgb)
-
-        if results.pose_landmarks:
-            mp_drawing.draw_landmarks(
-                frame,
-                results.pose_landmarks,
-                mp_pose.POSE_CONNECTIONS,
-                mp_drawing.DrawingSpec(color=(0,255,0), thickness=2, circle_radius=2),
-                mp_drawing.DrawingSpec(color=(0,0,255), thickness=2)
-            )
-
-            # Example: left elbow angle
-            landmarks = results.pose_landmarks.landmark
-            shoulder = [landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].x * frame.shape[1],
-                        landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].y * frame.shape[0]]
-            elbow = [landmarks[mp_pose.PoseLandmark.LEFT_ELBOW.value].x * frame.shape[1],
-                     landmarks[mp_pose.PoseLandmark.LEFT_ELBOW.value].y * frame.shape[0]]
-            wrist = [landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value].x * frame.shape[1],
-                     landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value].y * frame.shape[0]]
-
-            angle = calculate_angle(shoulder, elbow, wrist)
-            cv2.putText(frame, f"Left Elbow: {int(angle)} deg", (20,40),
-                        cv2.FONT_HERSHEY_SIMPLEX, 1, (255,255,0), 2)
-
-        out.write(frame)
-        frame_count += 1
-
-    cap.release()
-    out.release()
-    return out_path
+    try:
+        if not os.path.exists(video_path):
+            return None, "Error: Video file does not exist."
+
+        cap = cv2.VideoCapture(video_path)
+        if not cap.isOpened():
+            return None, "Error: Cannot open video file."
+
+        # Video properties
+        fps = cap.get(cv2.CAP_PROP_FPS) or 20.0
+        width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH) or 640)
+        height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT) or 480)
+        max_frames = int(fps * max_duration)
+
+        out_path = "annotated_video.mp4"
+        fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+        out = cv2.VideoWriter(out_path, fourcc, fps, (width, height))
+
+        frame_count = 0
+        while frame_count < max_frames:
+            ret, frame = cap.read()
+            if not ret:
+                break
+
+            # Resize frame if too big
+            max_dim = 640
+            h, w, _ = frame.shape
+            if max(h, w) > max_dim:
+                scale = max_dim / max(h, w)
+                frame = cv2.resize(frame, (int(w*scale), int(h*scale)))
+
+            frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+            results = pose.process(frame_rgb)
+
+            if results.pose_landmarks:
+                mp_drawing.draw_landmarks(
+                    frame,
+                    results.pose_landmarks,
+                    mp_pose.POSE_CONNECTIONS,
+                    mp_drawing.DrawingSpec(color=(0,255,0), thickness=2, circle_radius=2),
+                    mp_drawing.DrawingSpec(color=(0,0,255), thickness=2)
+                )
+
+                # Example: left elbow angle
+                landmarks = results.pose_landmarks.landmark
+                shoulder = [landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].x * frame.shape[1],
+                            landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].y * frame.shape[0]]
+                elbow = [landmarks[mp_pose.PoseLandmark.LEFT_ELBOW.value].x * frame.shape[1],
+                         landmarks[mp_pose.PoseLandmark.LEFT_ELBOW.value].y * frame.shape[0]]
+                wrist = [landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value].x * frame.shape[1],
+                         landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value].y * frame.shape[0]]
+
+                angle = calculate_angle(shoulder, elbow, wrist)
+                cv2.putText(frame, f"Left Elbow: {int(angle)} deg", (20,40),
+                            cv2.FONT_HERSHEY_SIMPLEX, 1, (255,255,0), 2)
+
+            out.write(frame)
+            frame_count += 1
+
+        cap.release()
+        out.release()
+        return out_path, "Video processed successfully."
+
+    except Exception as e:
+        return None, f"Error: {str(e)}"
 
 # Gradio interface
 demo = gr.Interface(
     fn=detect_pose_video,
     inputs=gr.Video(label="Upload Video"),
-    outputs=gr.Video(label="Annotated Video"),
+    outputs=[gr.Video(label="Annotated Video"), gr.Textbox(label="Status")],
     title="Human Pose Estimation on Video",
     description="Upload a video (max 20 seconds will be processed) and see pose landmarks & joint angles."
 )