Update app.py

extract and store frames

app.py

@@ -506,6 +506,59 @@ async def list_videos():
     except Exception as e:
         raise HTTPException(status_code=500, detail=f"Failed to fetch videos: {str(e)}")
 
+@app.post("/extract-and-store-frames/")
+async def extract_and_store_frames(file_name: str):
+    try:
+        # URL du fichier vidéo dans le dataset
+        video_url = f"https://huggingface.co/datasets/{DATASET_REPO}/resolve/main/{file_name}"
+        headers = {"Authorization": f"Bearer {HF_TOKEN}"}
+        response = requests.get(video_url, headers=headers)
+
+        if response.status_code != 200:
+            raise HTTPException(status_code=404, detail="Vidéo introuvable dans le dataset")
+
+        # Charger la vidéo en mémoire
+        video_bytes = io.BytesIO(response.content)
+        temp_video_path = "/tmp/temp_video.mp4"
+        with open(temp_video_path, "wb") as f:
+            f.write(video_bytes.getvalue())
+
+        cap = cv2.VideoCapture(temp_video_path)
+        if not cap.isOpened():
+            raise HTTPException(status_code=500, detail="Impossible de charger la vidéo")
+
+        frame_size = (128, 128)
+        video_stem = Path(file_name).stem
+        frames_dir = f"frames/{video_stem}/"
+        os.makedirs(frames_dir, exist_ok=True)
+
+        frame_id = 0
+        while True:
+            ret, frame = cap.read()
+            if not ret:
+                break
+
+            frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+            img = Image.fromarray(frame_rgb).resize(frame_size)
+            frame_filename = f"{frames_dir}{video_stem}_{frame_id}.png"
+            img.save(frame_filename)
+            frame_id += 1
+
+        cap.release()
+
+        # Upload frames to Hugging Face dataset
+        for frame_file in os.listdir(frames_dir):
+            frame_path = os.path.join(frames_dir, frame_file)
+            hf_api.upload_file(path_or_fileobj=frame_path,
+                               path_in_repo=f"frames/{video_stem}/{frame_file}",
+                               repo_id=DATASET_REPO,
+                               repo_type="dataset",
+                               token=HF_TOKEN)
+
+        return {"status": "success", "message": f"{frame_id} frames extraites et stockées."}
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Erreur lors de l'extraction des frames : {str(e)}")
+
 
 @app.get("/get-video-frames/")
 async def get_video_frames(file_name: str, frame_id: int) -> dict: