exerciserepetitioncounter.py

import cv2
import mediapipe as mp
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) # First point
    b = np.array(b) # Mid point
    c = np.array(c) # End point
    
    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 - angle
        
    return angle 

# Curl counter variables
counter = 0 
stage = None

cap = cv2.VideoCapture(0)

# Setup Mediapipe instance
with mp_pose.Pose(min_detection_confidence=0.5, min_tracking_confidence=0.5) as pose:
    while cap.isOpened():
        ret, frame = cap.read()
        if not ret:
            break
        
        # Recolor image to RGB
        image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
        image.flags.writeable = False
      
        # Make detection
        results = pose.process(image)
    
        # Recolor back to BGR
        image.flags.writeable = True
        image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
        
        # Extract landmarks
        try:
            landmarks = results.pose_landmarks.landmark
            if not landmarks:
                print("No landmarks detected")
                continue
            
            # Get coordinates
            shoulder = [landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].x,
                        landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].y]
            elbow = [landmarks[mp_pose.PoseLandmark.LEFT_ELBOW.value].x,
                     landmarks[mp_pose.PoseLandmark.LEFT_ELBOW.value].y]
            wrist = [landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value].x,
                     landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value].y]
            
            # Calculate angle
            angle = calculate_angle(shoulder, elbow, wrist)
            print(f"Angle: {angle}")

            # Visualize angle
            cv2.putText(image, str(angle), 
                        tuple(np.multiply(elbow, [640, 480]).astype(int)), 
                        cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 2, cv2.LINE_AA)
            
            # Curl counter logic
            if angle > 160:
                stage = "down"
            if angle < 30 and stage == 'down':
                stage = "up"
                counter += 1
                print(f"Counter: {counter}")
                       
        except Exception as e:
            print(f"Error: {e}")
        
        # Render curl counter
        # Setup status box
        cv2.rectangle(image, (0, 0), (225, 73), (245, 117, 16), -1)
        
        # Rep data
        cv2.putText(image, 'REPS', (15, 12), 
                    cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0), 1, cv2.LINE_AA)
        cv2.putText(image, str(counter), 
                    (10, 60), 
                    cv2.FONT_HERSHEY_SIMPLEX, 2, (255, 255, 255), 2, cv2.LINE_AA)
        
        # Stage data
        cv2.putText(image, 'STAGE', (65, 12), 
                    cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0), 1, cv2.LINE_AA)
        cv2.putText(image, stage, 
                    (60, 60), 
                    cv2.FONT_HERSHEY_SIMPLEX, 2, (255, 255, 255), 2, cv2.LINE_AA)
        
        # Render detections
        mp_drawing.draw_landmarks(image, results.pose_landmarks, mp_pose.POSE_CONNECTIONS,
                                  mp_drawing.DrawingSpec(color=(245, 117, 66), thickness=2, circle_radius=2), 
                                  mp_drawing.DrawingSpec(color=(245, 66, 230), thickness=2, circle_radius=2))               
        
        cv2.imshow('Mediapipe Feed', image)

        if cv2.waitKey(10) & 0xFF == ord('q'):
            break

    cap.release()
    cv2.destroyAllWindows()