Easily access your device's camera using a WebSocket client API to perform real-time AI and computer vision tasks on a live video stream. The app broadcasts live camera frames as JPEG images over WebSocket connections, allowing multiple clients to connect concurrently and perform AI or computer vision processing in parallel. Displaying the live camera stream using Python A simple Python example using OpenCV and WebSocket libraries to connect to the WebSocket CAM app and display the live camera stream. pip install opencv-python numpy websocket-client import cv2 import numpy as np import websocket SERVER_URL = "ws://192.168.18.50:8080" def on_message(ws, message): # Convert received bytes into a numpy array np_arr = np.frombuffer(message, np.uint8) frame = cv2.imdecode(np_arr, cv2.IMREAD_COLOR) if frame is not None: cv2.imshow("Camera Stream", frame) if cv2.waitKey(1) & 0xFF == 27: # ESC key to exit ws.close() cv2.destroyAllWindows() else: print("Failed to decode frame") def on_error(ws, error): print("WebSocket error:", error) def on_close(ws, close_status_code, close_msg): print("Connection closed:", close_status_code, close_msg) cv2.destroyAllWindows() def on_open(ws): print("Connected to WebSocket CAM. Open the camera to see the live stream.") if __name__ == "__main__": websocket.enableTrace(False) ws = websocket.WebSocketApp( SERVER_URL, on_open=on_open, on_message=on_message, on_error=on_error, on_close=on_close, ) try: ws.run_forever() except KeyboardInterrupt: print("\nStopped by user") ws.close() cv2.destroyAllWindows() Start the WebSocket server in the app, then run this Python script in multiple terminals to view several live streams simultaneously. Examples Working examples of this app are available here: https://github.com/UmerCodez/WebsocketCAM-examples License GNU General Public License v3.0