Update app.py

app.py

@@ -1,31 +1,32 @@
-import gradio as gr
+from fastapi import FastAPI, WebSocket
 import cv2
+from transformers import pipeline
 
-def video_feed():
-    cap = cv2.VideoCapture(0)  # Use 0 for the default camera
-    if not cap.isOpened():
-        raise RuntimeError("Could not start camera.")
+app = FastAPI()
+
+# Load the model from Hugging Face
+model = pipeline("object-detection", model="facebook/detr-resnet-50")
+
+@app.websocket("/ws")
+async def websocket_endpoint(websocket: WebSocket):
+    await websocket.accept()
+    cap = cv2.VideoCapture(0)  # Open the first webcam device
     
-    while True:
+    while cap.isOpened():
         ret, frame = cap.read()
         if not ret:
-            continue
-        # Convert the frame to RGB
-        frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
-        # Encode the frame as JPEG
-        _, buffer = cv2.imencode('.jpg', frame)
-        # Yield the frame as bytes
-        yield buffer.tobytes()
+            break
+        
+        # Convert the frame to a format suitable for the model
+        rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+        
+        # Use the model to make predictions
+        predictions = model(rgb_frame)
+        
+        # Send the predictions back to the client
+        await websocket.send_json(predictions)
 
     cap.release()
+    await websocket.close()
 
-iface = gr.Interface(
-    fn=video_feed,
-    inputs=[],
-    outputs=gr.Video(label="Live Webcam Feed"),
-    live=True,
-    description="A simple live webcam feed using Gradio."
-)
-
-if __name__ == "__main__":
-    iface.launch()
+# To run the app, use: uvicorn app:app --reload