app.py

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()