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import cv2
import mediapipe as mp
import numpy as np
import gradio as gr
mp_pose = mp.solutions.pose
pose = mp_pose.Pose(min_detection_confidence=0.5, min_tracking_confidence=0.5)
mp_drawing = mp.solutions.drawing_utils
def calculate_angle(a, b, c):
a, b, c = np.array(a), np.array(b), np.array(c)
radians = np.arctan2(c[1]-b[1], c[0]-b[0]) - np.arctan2(a[1]-b[1], a[0]-b[0])
return np.abs(radians * 180.0 / np.pi)
def check_pullup_feedback(landmarks):
shoulder = [landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value].x,
landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value].y]
elbow = [landmarks[mp_pose.PoseLandmark.RIGHT_ELBOW.value].x,
landmarks[mp_pose.PoseLandmark.RIGHT_ELBOW.value].y]
wrist = [landmarks[mp_pose.PoseLandmark.RIGHT_WRIST.value].x,
landmarks[mp_pose.PoseLandmark.RIGHT_WRIST.value].y]
angle = calculate_angle(shoulder, elbow, wrist)
target_angle = 70
tolerance = 20
accuracy = max(0, min(100, (1 - abs(angle - target_angle) / tolerance) * 100))
if angle > (target_angle + tolerance / 2):
feedback = ("Incomplete Pull-up - Your elbows remain too extended. Engage your back muscles to pull higher.")
elif angle < (target_angle - tolerance / 2):
feedback = ("Over-bending - Your elbows are too flexed. Try to control your descent.")
else:
feedback = "Correct Pull-up - Great form!"
return feedback, int(accuracy)
def draw_accuracy_bar(image, accuracy):
bar_x, bar_y = 50, image.shape[0] - 50
bar_width, bar_height = 200, 20
fill_width = int((accuracy / 100) * bar_width)
color = (0, 255, 0) if accuracy >= 80 else (0, 0, 255) if accuracy < 50 else (0, 255, 255)
cv2.rectangle(image, (bar_x, bar_y), (bar_x + bar_width, bar_y + bar_height), (200,200,200), 2)
cv2.rectangle(image, (bar_x, bar_y), (bar_x + fill_width, bar_y + bar_height), color, -1)
cv2.putText(image, f"Accuracy: {accuracy}%", (bar_x, bar_y-10),
cv2.FONT_HERSHEY_DUPLEX, 0.6, (255,255,255), 2)
def analyze_pullups(video_path):
cap = cv2.VideoCapture(video_path)
frame_width, frame_height = int(cap.get(3)), int(cap.get(4))
fps = cap.get(cv2.CAP_PROP_FPS) if cap.get(cv2.CAP_PROP_FPS) > 0 else 30
output_video = "output_pullups.mp4"
fourcc = cv2.VideoWriter_fourcc(*'mp4v')
out = cv2.VideoWriter(output_video, fourcc, fps, (frame_width, frame_height))
while cap.isOpened():
ret, frame = cap.read()
if not ret:
break
image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
results = pose.process(image)
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
if results.pose_landmarks:
mp_drawing.draw_landmarks(image, results.pose_landmarks, mp_pose.POSE_CONNECTIONS)
landmarks = results.pose_landmarks.landmark
feedback, accuracy = check_pullup_feedback(landmarks)
draw_accuracy_bar(image, accuracy)
text_color = (0, 255, 0) if "Correct" in feedback else (0, 0, 255)
cv2.putText(image, feedback, (50, 50),
cv2.FONT_HERSHEY_COMPLEX, 1, text_color, 3)
out.write(image)
cap.release()
out.release()
return output_video
gr.Interface(
fn=analyze_pullups,
inputs=gr.Video(),
outputs=gr.Video(),
title="Pull-ups Form Analyzer",
description="Upload a video of your pull-ups and receive form feedback!"
).launch()
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