app_realtime_visuali.py

import streamlit as st
import cv2
import mediapipe as mp
import numpy as np
import tempfile
import numpy as np



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


def calculate_angle(a, b, c):
    a = np.array(a)
    b = np.array(b)  
    c = np.array(c)  
    
    radians = np.arctan2(c[1] - b[1], c[0] - b[0]) - np.arctan2(a[1] - b[1], a[0] - b[0])
    angle = np.abs(radians * 180.0 / np.pi)
    
    if angle > 180.0:
        angle = 360.0 - angle
        
    return angle

st.title("런닝 바른 자세")
st.write("본인 영상 올리세용~")
uploaded_file = st.file_uploader("Choose your video", type=["mp4", "mov", "avi"])

if uploaded_file is not None:
    tfile = tempfile.NamedTemporaryFile(delete=False)
    tfile.write(uploaded_file.read())
    
    cap = cv2.VideoCapture(tfile.name)
    
    stframe = st.empty()
    
    with mp_pose.Pose(static_image_mode=False, min_detection_confidence=0.5, min_tracking_confidence=0.5) as pose:
        while cap.isOpened():
            ret, frame = cap.read()
            if not ret:
                break
            
           
            image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
            image.flags.writeable = False
            results = pose.process(image)
            
            image.flags.writeable = True
            image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
            
         
            if results.pose_landmarks:
                landmarks = results.pose_landmarks.landmark
               
                left_shoulder = [landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].x, landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].y]
                left_elbow = [landmarks[mp_pose.PoseLandmark.LEFT_ELBOW.value].x, landmarks[mp_pose.PoseLandmark.LEFT_ELBOW.value].y]
                left_wrist = [landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value].x, landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value].y]
                left_hip = [landmarks[mp_pose.PoseLandmark.LEFT_HIP.value].x, landmarks[mp_pose.PoseLandmark.LEFT_HIP.value].y]
                left_knee = [landmarks[mp_pose.PoseLandmark.LEFT_KNEE.value].x, landmarks[mp_pose.PoseLandmark.LEFT_KNEE.value].y]
                left_ankle = [landmarks[mp_pose.PoseLandmark.LEFT_ANKLE.value].x, landmarks[mp_pose.PoseLandmark.LEFT_ANKLE.value].y]
                
               
                left_elbow_angle = calculate_angle(left_shoulder, left_elbow, left_wrist)
                left_knee_angle = calculate_angle(left_hip, left_knee, left_ankle)
                neck_angle = calculate_angle([landmarks[mp_pose.PoseLandmark.NOSE.value].x, landmarks[mp_pose.PoseLandmark.NOSE.value].y],
                                             [landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].x, landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].y],
                                             [landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value].x, landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value].y])
                
    
                mp_drawing.draw_landmarks(image, results.pose_landmarks, mp_pose.POSE_CONNECTIONS)
                cv2.putText(image, f'Elbow Angle: {int(left_elbow_angle)}', 
                            tuple(np.multiply(left_elbow, [image.shape[1], image.shape[0]]).astype(int)), 
                            cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 2, cv2.LINE_AA
                                    )
                cv2.putText(image, f'Knee Angle: {int(left_knee_angle)}', 
                            tuple(np.multiply(left_knee, [image.shape[1], image.shape[0]]).astype(int)), 
                            cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 2, cv2.LINE_AA
                                    )
                cv2.putText(image, f'Neck Angle: {int(neck_angle)}', 
                            (50, 50), 
                            cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 2, cv2.LINE_AA
                                    )
            
            stframe.image(image, channels="BGR")
            
    cap.release()
    tfile.close()