use multiple devices

main_test.py

@@ -4,10 +4,11 @@ import traceback
 import cv2
 import numpy as np
 import logging
-from fastapi import FastAPI, WebSocket
+from fastapi import FastAPI, WebSocket, WebSocketDisconnect
 from keras.models import load_model
 from keras.utils import img_to_array
 import urllib.request
+from urllib.error import URLError
 
 # Configure logging
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
@@ -31,12 +32,13 @@ for class_name, index in class_indices.items():
 face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
 
 # Replace with your IP camera stream URL
-url = 'http://192.168.1.7/cam-hi.jpg'
+base_dev_url = 'http://192.168.1.7/'
+img_endpoint = '/cam-hi.jpg'
 
-
-@app.websocket("/ws/emotion")
-async def websocket_endpoint(websocket: WebSocket):
+@app.websocket("/ws/emotion/{device_uid}")
+async def websocket_endpoint(websocket: WebSocket, device_uid: str):
     await websocket.accept()
+    url = base_dev_url+device_uid+img_endpoint
     try:
         while True:
             try:
@@ -87,7 +89,8 @@ async def websocket_endpoint(websocket: WebSocket):
                             "y": int(y),
                             "width": int(w),
                             "height": int(h)
-                        }
+                        },
+                        "error": False
                     })
 
                 logging.info(f"Detected emotions: {emotions}")