import cv2
import mediapipe as mp
import streamlit as st
from PIL import Image
import numpy as np

# Initialize MediaPipe Pose
mp_pose = mp.solutions.pose
pose = mp_pose.Pose()
mp_drawing = mp.solutions.drawing_utils

def process_frame(frame):
    # Convert the frame to RGB
    image_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
    results = pose.process(image_rgb)
    if results.pose_landmarks:
        # Draw the pose annotations on the image
        mp_drawing.draw_landmarks(frame, results.pose_landmarks, mp_pose.POSE_CONNECTIONS)
    return frame

def main():
    st.title("Live Pose Detection")
    st.write("This app uses MediaPipe for real-time pose detection.")

    # Create a placeholder for the video stream
    stframe = st.empty()

    # Open the webcam
    cap = cv2.VideoCapture(0)

    while cap.isOpened():
        ret, frame = cap.read()
        if not ret:
            st.write("Error: Could not read frame.")
            break

        # Process the frame
        frame = process_frame(frame)

        # Convert the frame to RGB format
        frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
        # Convert to PIL Image and display
        stframe.image(Image.fromarray(frame_rgb), channels='RGB', use_column_width=True)

    cap.release()
    cv2.destroyAllWindows()

if __name__ == "__main__":
    main()