Update utils.py

utils.py

@@ -66,7 +66,7 @@ def process_video(video_path, pose_detector, skeleton_generator):
         if not cap.isOpened():
             return None, None
 
-        # Get video properties
+        # Get video properties again
         frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
         frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
         fps = int(cap.get(cv2.CAP_PROP_FPS))
@@ -148,7 +148,6 @@ def process_video(video_path, pose_detector, skeleton_generator):
             if frame_count > 1000:  # Safety limit for very long videos
                 break
 
-
         # Release resources
         if cap is not None:
             cap.release()
@@ -177,43 +176,43 @@ def process_gif(gif_path, pose_detector, skeleton_generator):
     This implementation uses Pillow to extract frames from the GIF, processes each frame,
     and creates a temporary MP4 video with the processed frames.
     """
-    from PIL import Image, ImageSequence
-    import cv2
-    import numpy as np
-    import tempfile
-
-    # Открываем GIF с помощью Pillow
-    gif = Image.open(gif_path)
-    frames = []
-    for frame in ImageSequence.Iterator(gif):
-        frame = frame.convert("RGB")
-        frame_np = np.array(frame)
-        # Переводим RGB в BGR (OpenCV использует BGR)
-        frame_cv = cv2.cvtColor(frame_np, cv2.COLOR_RGB2BGR)
-        frames.append(frame_cv)
-    
-    processed_frames = []
-    animation_frames = []
-    # Обрабатываем каждый кадр
-    for frame in frames:
-        landmarks, annotated_frame = pose_detector.detect_video_frame(frame)
-        if annotated_frame is None:
-            annotated_frame = frame
-        processed_frames.append(annotated_frame)
-        if landmarks is not None:
-            skeleton_data = skeleton_generator.generate_skeleton(landmarks)
-        else:
-            skeleton_data = None
-        animation_frames.append(skeleton_data)
-    
-    # Сохраняем обработанные кадры в временное видео (MP4)
-    height, width = processed_frames[0].shape[:2]
-    fps = 10  # Можно подобрать подходящее значение для GIF
-    fourcc = cv2.VideoWriter_fourcc(*'mp4v')
-    temp_video = tempfile.NamedTemporaryFile(suffix='.mp4', delete=False)
-    out = cv2.VideoWriter(temp_video.name, fourcc, fps, (width, height))
-    for frame in processed_frames:
-        out.write(frame)
-    out.release()
-    
-    return temp_video.name, animation_frames
+    try:
+        from PIL import Image, ImageSequence
+        # Открываем GIF с помощью Pillow
+        gif = Image.open(gif_path)
+        frames = []
+        for frame in ImageSequence.Iterator(gif):
+            frame = frame.convert("RGB")
+            frame_np = np.array(frame)
+            # Переводим RGB в BGR (OpenCV использует BGR)
+            frame_cv = cv2.cvtColor(frame_np, cv2.COLOR_RGB2BGR)
+            frames.append(frame_cv)
+        
+        processed_frames = []
+        animation_frames = []
+        # Обрабатываем каждый кадр
+        for frame in frames:
+            landmarks, annotated_frame = pose_detector.detect_video_frame(frame)
+            if annotated_frame is None:
+                annotated_frame = frame
+            processed_frames.append(annotated_frame)
+            if landmarks is not None:
+                skeleton_data = skeleton_generator.generate_skeleton(landmarks)
+            else:
+                skeleton_data = None
+            animation_frames.append(skeleton_data)
+        
+        # Сохраняем обработанные кадры в временное видео (MP4)
+        height, width = processed_frames[0].shape[:2]
+        fps = 10  # Можно подобрать подходящее значение для GIF
+        fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+        temp_video = tempfile.NamedTemporaryFile(suffix='.mp4', delete=False)
+        out = cv2.VideoWriter(temp_video.name, fourcc, fps, (width, height))
+        for frame in processed_frames:
+            out.write(frame)
+        out.release()
+        
+        return temp_video.name, animation_frames
+    except Exception as e:
+        print(f"Error processing GIF: {str(e)}")
+        return None, None