import streamlit as st
import cv2
import numpy as np

def main():
    st.set_page_config(page_title="Streamlit Webcam Canny Edge App")
    st.title("Webcam Canny Edge Detection App")
    st.caption("Powered by OpenCV, Streamlit")

    # Capture video from the webcam
    cap = cv2.VideoCapture(0)
    frame_placeholder = st.empty()
    stop_button_pressed = st.button("Stop")

    while cap.isOpened() and not stop_button_pressed:
        ret, frame = cap.read()
        if not ret:
            st.write("Video Capture Ended")
            break
        
        # Convert the frame to grayscale
        gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        
        # Apply Canny edge detection
        edges = cv2.Canny(gray_frame, 100, 200)
        
        # Create an overlay of edges on the original frame
        edges_colored = cv2.cvtColor(edges, cv2.COLOR_GRAY2BGR)
        overlay = cv2.addWeighted(frame, 0.7, edges_colored, 0.3, 0)

        # Resize the frame for better display (smaller size)
        overlay_resized = cv2.resize(overlay, (320, 240))  # Change size here

        # Display the overlay
        frame_placeholder.image(overlay_resized, channels="BGR", caption="Webcam Feed with Canny Edges", use_column_width=True)

        # Break loop on 'q' key or stop button press
        if cv2.waitKey(1) & 0xFF == ord("q") or stop_button_pressed:
            break

    cap.release()
    cv2.destroyAllWindows()

if __name__ == "__main__":
    main()