import cv2
import mediapipe as mp
import gradio as gr

mp_drawing = mp.solutions.drawing_utils
mp_pose = mp.solutions.pose

def detect_pose(frame):
    with mp_pose.Pose(min_detection_confidence=0.5, min_tracking_confidence=0.5) as pose:
        results = pose.process(frame)
        if results.pose_landmarks:
            mp_drawing.draw_landmarks(frame, results.pose_landmarks, mp_pose.POSE_CONNECTIONS,
                                      landmark_drawing_spec=mp_drawing.DrawingSpec(color=(0, 0, 255), thickness=2, circle_radius=4),
                                      connection_drawing_spec=mp_drawing.DrawingSpec(color=(0, 255, 0), thickness=2))
    return frame

def process_video(frame):
    frame = detect_pose(frame)
    return frame

def video_stream():
    cap = cv2.VideoCapture(0)
    while True:
        ret, frame = cap.read()
        if not ret:
            break
        frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
        frame = process_video(frame)
        frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
        yield frame

iface = gr.Interface(
    fn=lambda x: x,
    inputs=gr.Video(source="webcam", type="numpy"),
    outputs="video",
    live=True,
    title="Live Pose Detection"
)

iface.launch()