Update app.py

app.py

@@ -235,7 +235,6 @@
 # # http://localhost:8000/docs#/
 # # (.venv) PS C:\Users\antoi\Documents\Work_Learn\Labeling-Deploy\FastAPI> uvicorn main:app --host 0.0.0.0 --port 8000 --workers 1
 
-
 from fastapi import FastAPI, UploadFile, File, HTTPException
 import cv2
 import torch
@@ -452,6 +451,40 @@ def convertir_sequences_en_json(dataframe):
 
 
 
+# Endpoint pour analyser la vidéo à partir d'une URL
+@app.post("/analyze_video/")
+async def analyze_video(user_name: str, video_url: Optional[str] = None):
+    try:
+        # Log for debugging purposes
+        print(f"Received user_name: {user_name}")
+        print(f"Received video_url: {video_url}")
+
+        # Assurez-vous d'avoir une URL valide à ce stade
+        if not video_url:
+            raise HTTPException(status_code=400, detail="No valid video URL provided.")
+
+        # Télécharge la vidéo temporairement pour l'analyser
+        temp_file_path = "/tmp/video_to_analyze.mp4"
+        os.system(f"wget -O {temp_file_path} {video_url}")
+
+        # Analyser la vidéo via l'URL
+        dataframe_sequences = identifier_sequences_surfing(temp_file_path, intervalle=1)
+        json_result = convertir_sequences_en_json(dataframe_sequences)
+
+        # Supprimer la vidéo temporaire après l'analyse
+        os.remove(temp_file_path)
+
+        return {
+            "message": "Video analyzed successfully!",
+            "file_url": video_url,
+            "analysis": json_result
+        }
+
+    except Exception as e:
+        print(f"Error during video analysis: {str(e)}")  # Log the error
+        raise HTTPException(status_code=500, detail=f"Failed to analyze video: {str(e)}")
+
+
 
 @app.post("/upload_video/")
 async def upload_video(user_name: str, file: UploadFile = File(...)):