app.py

import gradio as gr

import math
import time
import mediapipe as mp

import cv2
from PIL import Image
import numpy as np
import datetime
import copy
from openpose import util
from openpose.body import Body
import matplotlib.pyplot as plt

    
mp_pose = mp.solutions.pose

pose = mp_pose.Pose(static_image_mode=True, min_detection_confidence=0.3, model_complexity=2)

mp_drawing = mp.solutions.drawing_utils 

def change_example(choice):
    if choice == "plank":
        return gr.Image.update(value="examples/plank.jpg")
    elif choice == "downdog":
        return gr.update(value="examples/downdog.jpg")
    elif choice == "tree":
        return gr.update(value="examples/tree.jpg")
    else:
        return gr.update(visible=False)

def points(image):
    results = pose.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
    image_height, image_width, _ = image.shape

    img_copy = image.copy()

    if results.pose_landmarks:
        mp_drawing.draw_landmarks(image=img_copy, landmark_list=results.pose_landmarks, connections=mp_pose.POSE_CONNECTIONS)
       
        img = plt.figure(figsize = [10, 10])

        plt.axis('off')
        plt.imshow(img_copy[:,:,::-1])
        return img

    else:
        return gr.Image("examples/Error.png")

def landmarks(image):
    results = pose.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
    height, width, _ = image.shape

    landmarks = []

    if results.pose_landmarks:          
        for landmark in results.pose_landmarks.landmark:            
            landmarks.append((int(landmark.x * width), int(landmark.y * height),
                                  (landmark.z * width)))
    return landmarks 

def calculateAngle(landmark1, landmark2, landmark3):

    x1, y1, _ = landmark1
    x2, y2, _ = landmark2
    x3, y3, _ = landmark3

    angle = math.degrees(math.atan2(y3 - y2, x3 - x2) - math.atan2(y1 - y2, x1 - x2))
    
    if angle < 0:
        angle += 360
    if angle > 180:
        angle = 360 - angle
    
    return angle

def correct_plank(landmarks):
    recommendation = ""
    result = ""
    left_knee_angle = calculateAngle(landmarks[mp_pose.PoseLandmark.LEFT_HIP.value],
                                     landmarks[mp_pose.PoseLandmark.LEFT_KNEE.value],
                                     landmarks[mp_pose.PoseLandmark.LEFT_ANKLE.value])

    right_knee_angle = calculateAngle(landmarks[mp_pose.PoseLandmark.RIGHT_HIP.value],
                                      landmarks[mp_pose.PoseLandmark.RIGHT_KNEE.value],
                                      landmarks[mp_pose.PoseLandmark.RIGHT_ANKLE.value])
    
    left_hip_angle = calculateAngle(landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value],
                                     landmarks[mp_pose.PoseLandmark.LEFT_HIP.value],
                                     landmarks[mp_pose.PoseLandmark.LEFT_KNEE.value])

    right_hip_angle = calculateAngle(landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value],
                                      landmarks[mp_pose.PoseLandmark.RIGHT_HIP.value],
                                      landmarks[mp_pose.PoseLandmark.RIGHT_KNEE.value])
    
    if (left_knee_angle>180 or left_knee_angle<170):
        recommendation = recommendation + "The left knee should be straight. "
    if (right_knee_angle>180 or right_knee_angle<170):
        recommendation = recommendation + "The right knee should be straight. "
    if ((left_hip_angle>180 or left_hip_angle<170) or (right_hip_angle>180 or right_hip_angle<170)):
        recommendation = recommendation + "The spine should be straight. "
    if recommendation == "":
        result = "Great! You are doing the exercise correctly"
    else:
        result = "Almost perfect, but \n"
    return result + recommendation    

def correct_dog(landmarks):
    recommendation = ""
    result = ""
    left_hip_angle = calculateAngle(landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value],
                                     landmarks[mp_pose.PoseLandmark.LEFT_HIP.value],
                                     landmarks[mp_pose.PoseLandmark.LEFT_KNEE.value])

    right_hip_angle = calculateAngle(landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value],
                                      landmarks[mp_pose.PoseLandmark.RIGHT_HIP.value],
                                      landmarks[mp_pose.PoseLandmark.RIGHT_KNEE.value])
    
    left_leg = calculateAngle(landmarks[mp_pose.PoseLandmark.LEFT_HIP.value],
                              landmarks[mp_pose.PoseLandmark.LEFT_KNEE.value],
                              landmarks[mp_pose.PoseLandmark.LEFT_ANKLE.value])
    right_leg = calculateAngle(landmarks[mp_pose.PoseLandmark.RIGHT_HIP.value],
                               landmarks[mp_pose.PoseLandmark.RIGHT_KNEE.value],
                               landmarks[mp_pose.PoseLandmark.RIGHT_ANKLE.value])
    
    right_hand = calculateAngle(landmarks[mp_pose.PoseLandmark.RIGHT_HIP.value],
                                landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value],
                                landmarks[mp_pose.PoseLandmark.RIGHT_ELBOW.value])

    left_hand = calculateAngle(landmarks[mp_pose.PoseLandmark.LEFT_HIP.value],
                               landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value],
                               landmarks[mp_pose.PoseLandmark.LEFT_ELBOW.value])
    
    if (left_hip_angle>90 or right_hip_angle>90):
        recommendation += "The spine should be bent. "
    if not (170 < left_leg < 181 or 170 < right_leg < 181):
        recommendation = "Legs should be straight. "
    if not (170 < left_hand < 181 or 181 > right_hand > 170):
        recommendation = "Hands should be straight. "
    if recommendation == "":
        result = "Great! You are doing the exercise correctly"
    else:
        result = "Almost perfect, but \n"

    return result + recommendation

def correct_tree(landmarks):
    recommendation = ""
    result = ""
    left_hip_angle = calculateAngle(landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value],
                                     landmarks[mp_pose.PoseLandmark.LEFT_HIP.value],
                                     landmarks[mp_pose.PoseLandmark.LEFT_KNEE.value])

    right_hip_angle = calculateAngle(landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value],
                                      landmarks[mp_pose.PoseLandmark.RIGHT_HIP.value],
                                      landmarks[mp_pose.PoseLandmark.RIGHT_KNEE.value])
    
    left_leg = calculateAngle(
                                     landmarks[mp_pose.PoseLandmark.LEFT_HIP.value],
                                     landmarks[mp_pose.PoseLandmark.LEFT_KNEE.value],
                                     landmarks[mp_pose.PoseLandmark.LEFT_ANKLE.value])
    right_leg = calculateAngle(
                                      landmarks[mp_pose.PoseLandmark.RIGHT_HIP.value],
                                      landmarks[mp_pose.PoseLandmark.RIGHT_KNEE.value],
                                      landmarks[mp_pose.PoseLandmark.RIGHT_ANKLE.value])
    
    right_hand = calculateAngle(
                                      landmarks[mp_pose.PoseLandmark.RIGHT_HIP.value],
                                      landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value],
                                     landmarks[mp_pose.PoseLandmark.RIGHT_ELBOW.value])

    left_hand = calculateAngle(
                                      landmarks[mp_pose.PoseLandmark.LEFT_HIP.value],
                                      landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value],
                                      landmarks[mp_pose.PoseLandmark.LEFT_ELBOW.value])
    
    
    #if (left_hand>90 or right_hand>90):
    #    recommendation += "Hands should be bent. "
    if not (((175 < right_leg < 181) and (left_leg < 100)) or ((175 < left_leg < 181) and (right_leg < 100))):
        recommendation = "One leg should be straight and another should be bent. "
    if recommendation == "":
        result = "Great! You are doing the exercise correctly"
    else:
        result = "Almost perfect, but \n"

    return result + recommendation

def detect(video, radio):
    video_clip = cv2.VideoCapture(video)
    frames = video_clip.get(cv2.CAP_PROP_FRAME_COUNT)
    
    i=0
    while(video_clip.isOpened()):
        is_read, frame = video_clip.read()
        image = frame
        if i == round(frames/2):
            image = frame
            break
        i+=1
    new_image = points(image)

    result = ""
    if radio == "plank":
        result = correct_plank(landmarks(image))
        
    if radio == "downdog":
        result = correct_dog(landmarks(image))

    if radio == "tree":
        result = correct_tree(landmarks(image))
        
    return new_image, result

with gr.Blocks() as demo:
    with gr.Row():
        with gr.Column():
            radio = gr.Radio(["plank", "downdog", "tree"], label="Choose the exercise")
            image1 = gr.Image("examples/Example.png")
            video = gr.Video(label="Upload video with exercise")
            check_btn = gr.Button(value="Let's go")
        with gr.Column():
            image = gr.Plot() 
            result = gr.Textbox()
    radio.change(fn=change_example, inputs=radio, outputs=image1)
    check_btn.click(detect, inputs=[video, radio], outputs=[image, result])
    
demo.launch()
    
            
#gr.Interface(
#    fn=detect,
#    inputs=gr.Video(label="Upload video with exercise"), 
#    outputs="image", 
#    title="Are you doing the exercise correct?"
#).launch()