Create app.py

app.py

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+import cv2
+import numpy as np
+import requests
+
+# Start the webcam feed
+cap = cv2.VideoCapture(0)
+
+while True:
+    ret, frame = cap.read()
+    if not ret:
+        print("Failed to grab frame.")
+        break
+
+    # Process the frame if needed
+    # For example, convert to grayscale:
+    gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+
+    # Send the frame to Hugging Face API for inference
+    # Convert the frame to a format suitable for the API (e.g., a base64-encoded image)
+    _, buffer = cv2.imencode('.jpg', frame)
+    frame_bytes = buffer.tobytes()
+
+    # Define your Hugging Face API endpoint and model
+    model_endpoint = "https://api-inference.huggingface.co/models/your-model"
+    
+    headers = {
+        "Authorization": "Bearer your-huggingface-api-token"
+    }
+
+    # Send frame as a POST request to Hugging Face
+    response = requests.post(model_endpoint, headers=headers, files={"file": ("frame.jpg", frame_bytes, "image/jpeg")})
+
+    if response.status_code == 200:
+        result = response.json()  # Process the result
+        print(result)  # Do something with the result, like display it
+    else:
+        print("Error:", response.status_code, response.text)
+
+    # Show the webcam feed (with potential processed data)
+    cv2.imshow("Webcam Feed", gray_frame)
+
+    # Exit if 'q' is pressed
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+# Release the webcam and close any OpenCV windows
+cap.release()
+cv2.destroyAllWindows()