update app.py url linked to frontend for analyze_video

app.py

@@ -11,6 +11,7 @@ from fastapi.responses import HTMLResponse
 from huggingface_hub import HfApi
 import os
 from dotenv import load_dotenv
+from typing import Optional
 
 # Charger les variables d'environnement, y compris la clé API Hugging Face
 load_dotenv()
@@ -109,41 +110,87 @@ def convertir_sequences_en_json(dataframe):
     events.append(event)
     return events
 
-# Endpoint pour analyser la vidéo et uploader sur Hugging Face
-@app.post("/analyze_video/")
-async def analyze_video(user_name: str, file: UploadFile = File(...)):
-    try:
-        # Sauvegarder la vidéo temporairement
-        temp_file_path = f"/tmp/{file.filename}"
-        with open(temp_file_path, "wb") as buffer:
-            shutil.copyfileobj(file.file, buffer)
+# # Endpoint pour analyser la vidéo et uploader sur Hugging Face
+# @app.post("/analyze_video/")
+# async def analyze_video(user_name: str, file: UploadFile = File(...)):
+#     try:
+#         # Sauvegarder la vidéo temporairement
+#         temp_file_path = f"/tmp/{file.filename}"
+#         with open(temp_file_path, "wb") as buffer:
+#             shutil.copyfileobj(file.file, buffer)
 
-        # Uploader la vidéo sur Hugging Face Hub
-        dataset_name = "2nzi/Video-Sequence-Labeling"
-        target_path_in_repo = f"{user_name}/raw/{file.filename}"
+#         # Uploader la vidéo sur Hugging Face Hub
+#         dataset_name = "2nzi/Video-Sequence-Labeling"
+#         target_path_in_repo = f"{user_name}/raw/{file.filename}"
 
-        hf_api.upload_file(
-            path_or_fileobj=temp_file_path,
-            path_in_repo=target_path_in_repo,
-            repo_id=dataset_name,
-            repo_type="dataset",
-            token=api_key
-        )
+#         hf_api.upload_file(
+#             path_or_fileobj=temp_file_path,
+#             path_in_repo=target_path_in_repo,
+#             repo_id=dataset_name,
+#             repo_type="dataset",
+#             token=api_key
+#         )
 
-        # Analyser la vidéo pour trouver des séquences "Surfing"
-        dataframe_sequences = identifier_sequences_surfing(temp_file_path, intervalle=1)
-        json_result = convertir_sequences_en_json(dataframe_sequences)
+#         # Analyser la vidéo pour trouver des séquences "Surfing"
+#         dataframe_sequences = identifier_sequences_surfing(temp_file_path, intervalle=1)
+#         json_result = convertir_sequences_en_json(dataframe_sequences)
+
+#         # Supprimer le fichier temporaire après l'upload
+#         os.remove(temp_file_path)
 
-        # Supprimer le fichier temporaire après l'upload
-        os.remove(temp_file_path)
+#         return {"message": "Video uploaded and analyzed successfully!", 
+#                 "file_url": f"https://huggingface.co/datasets/{dataset_name}/resolve/main/{target_path_in_repo}", 
+#                 "analysis": json_result}
 
-        return {"message": "Video uploaded and analyzed successfully!", 
-                "file_url": f"https://huggingface.co/datasets/{dataset_name}/resolve/main/{target_path_in_repo}", 
-                "analysis": json_result}
+#     except Exception as e:
+#         raise HTTPException(status_code=500, detail=f"Failed to upload or analyze video: {str(e)}")
+
+
+@app.post("/analyze_video/")
+async def analyze_video(user_name: str, file: Optional[UploadFile] = File(None), video_url: Optional[str] = None):
+    try:
+        # Vérifier si la vidéo est fournie sous forme de fichier ou d'URL
+        if file:
+            # Sauvegarder la vidéo temporairement
+            temp_file_path = f"/tmp/{file.filename}"
+            with open(temp_file_path, "wb") as buffer:
+                shutil.copyfileobj(file.file, buffer)
+
+            # Uploader la vidéo sur Hugging Face Hub
+            dataset_name = "2nzi/Video-Sequence-Labeling"
+            target_path_in_repo = f"{user_name}/raw/{file.filename}"
+
+            hf_api.upload_file(
+                path_or_fileobj=temp_file_path,
+                path_in_repo=target_path_in_repo,
+                repo_id=dataset_name,
+                repo_type="dataset",
+                token=os.getenv("HUGGINGFACE_WRITE_API_KEY")
+            )
+
+            # URL de la vidéo sur Hugging Face
+            video_url = f"https://huggingface.co/datasets/{dataset_name}/resolve/main/{target_path_in_repo}"
+            # Supprimer le fichier temporaire après l'upload
+            os.remove(temp_file_path)
+
+        # Assurez-vous d'avoir une URL valide à ce stade
+        if not video_url:
+            raise HTTPException(status_code=400, detail="No valid video URL or file provided.")
+
+        # Analyser la vidéo via l'URL
+        dataframe_sequences = identifier_sequences_surfing(video_url, intervalle=1)
+        json_result = convertir_sequences_en_json(dataframe_sequences)
+
+        return {
+            "message": "Video uploaded and analyzed successfully!",
+            "file_url": video_url,
+            "analysis": json_result
+        }
 
     except Exception as e:
         raise HTTPException(status_code=500, detail=f"Failed to upload or analyze video: {str(e)}")
 
+
 # Fonction pour uploader une vidéo vers un dataset Hugging Face
 def upload_to_hf_dataset(user_name: str, video_path: str):
     dataset_name = "2nzi/Video-Sequence-Labeling"