yolozone 0.0.2

No project description provided

YoloZone

YoloZone is a helper library for detecting and analyzing human poses in images and videos using the YOLO models. It provides simple functions for finding keypoints, angles, and distances between points in a pose.

Installation

pip install yolozone

Keypoints / Landmarks

We use the YOLO model for pose landmarks without any changes. The model returns 17 keypoints / landmarks.

Keypoint	Description
0	Nose
1	Left Eye
2	Right Eye
3	Left Ear
4	Right Ear
5	Left Shoulder
6	Right Shoulder
7	Left Elbow
8	Right Elbow
9	Left Wrist
10	Right Wrist
11	Left Hip
12	Right Hip
13	Left Knee
14	Right Knee
15	Left Ankle
16	Right Ankle

Usage

from yolozone import PoseDetector
import cv2

model = PoseDetector(model="yolov8n-pose.pt") # Initialize model
cap = cv2.VideoCapture(0) # Initialize video capture for webcam / cameras
# cap = cv2.VideoCapture("test/video.mp4") # Initialize video capture for video

while True:
    try:
        ret, frame = cap.read() # Read frame
        
        # Find keypoints
        keypoints = model.find_keypoints(frame, device="mps")

        # Get Points and Lines to Draw pose
        points, lines = model.draw_pose(keypoints)

        # Draw points
        for point in points:
            cv2.circle(frame, point, 5, (255, 255, 255), 2)
        
        # Draw lines
        for line in lines:
            cv2.line(frame, line[0], line[1], (255, 255, 255), 2) # line[0] and line[1] are starting and ending points of the line
        
        # Find angle between Left Shoulder (5) , Left Elbow (7) and Left Wrist (9)
        angle, text, text_position = model.angle_between_3_points(keypoints, 5, 7, 9)
        cv2.putText(frame, text, text_position, cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 2)
        cv2.circle(frame, text_position, 5, (255, 0, 0), -1)

        # Find distance between Left Shoulder (5) and Left Wrist (9)
        distance, text, text_position, pointOutA, pointOutB = model.distance_between_2_points(keypoints, 5, 9)
        cv2.putText(frame, text, text_position, cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
        cv2.line(frame, pointOutA, pointOutB, (0, 255, 0), 2)

        # Find distance between Right Shoulder (6) and Right Wrist (10)
        distance, text, text_position, pointOutC, pointOutD = model.distance_between_2_points(keypoints, 6, 10)
        cv2.putText(frame, text, text_position, cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
        cv2.line(frame, pointOutC, pointOutD, (0, 255, 0), 2)

        # Find the angle between Left Shoulder (5), Left Wrist (9) and Right Shoulder (6), Right Wrist (10)
        angle, text, text_position = model.angle_between_2_lines(keypoints, 5, 9, 6, 10)
        cv2.putText(frame, text, text_position, cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
    
    except Exception as e:
        print(e)
        pass

    cv2.imshow("frame", frame)
    cv2.waitKey(1)

Features

Pose Detection (WIP)

• Keypoints / Landmarks
• Angles between 3 points
• Distance between 2 points
• Angle between 2 lines

Object Detection (WIP)

Face Detection (WIP)

References

• Ultralytics YOLOv8