Update utils.py

utils.py

@@ -173,6 +173,47 @@ def process_video(video_path, pose_detector, skeleton_generator):
 
 def process_gif(gif_path, pose_detector, skeleton_generator):
     """
-    Process GIF for pose detection and skeleton generation
+    Process GIF for pose detection and skeleton generation.
+    This implementation uses Pillow to extract frames from the GIF, processes each frame,
+    and creates a temporary MP4 video with the processed frames.
     """
-    return process_video(gif_path, pose_detector, skeleton_generator)
+    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