test.py

# import cv2
# import streamlit as st
# import numpy as np
# import tempfile

# # Use this line to capture video from the webcam
# cap = cv2.VideoCapture(0)


# # Set the title for the Streamlit app
# st.title("Video Capture with OpenCV")

# frame_placeholder = st.empty()

# # Add a "Stop" button and store its state in a variable
# stop_button_pressed = st.button("Stop")

# while cap.isOpened() and not stop_button_pressed:
#     ret, frame = cap.read()

#     if not ret:
#         st.write("The video capture has ended.")
#         break

#     # You can process the frame here if needed
#     # e.g., apply filters, transformations, or object detection

#     # Convert the frame from BGR to RGB format
#     frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)

#     # Display the frame using Streamlit's st.image
#     frame_placeholder.image(frame, channels="RGB")

#     # Break the loop if the 'q' key is pressed or the user clicks the "Stop" button
#     if cv2.waitKey(1) & 0xFF == ord("q") or stop_button_pressed: 
#         break

# cap.release()
# cv2.destroyAllWindows()   


import cv2
import streamlit as st

# Set the title of the Streamlit app
st.title("Webcam Feed")

# Create a checkbox to start/stop the webcam
run = st.checkbox("Run")

# Create an empty placeholder to display the webcam feed
FRAME_WINDOW = st.image([])

# Initialize the webcam
camera = cv2.VideoCapture(0)

while run:
    # Read a frame from the webcam
    _, frame = camera.read()

    # Convert the frame from BGR to RGB color format
    frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)

    # Resize the frame to 100px x 100px
    frame = cv2.resize(frame, (100, 100))

    # Display the resized frame in the placeholder
    FRAME_WINDOW.image(frame)

# Release the webcam when the loop ends
camera.release()