Yolo Pose Estimation and Skeleton

From wikiluntti
Revision as of 20:51, 5 October 2025 by Mol (talk | contribs) (→‎References)

Introduction

Make a pose estimator and use it to make a moving skeleton.

Use Yolo from Ultralytics.

  • Python 3.7+
  • Yolo v11
  • A CUDA-enabled GPU (optional but recommended for faster inference).

pip install ultralytics opencv-python numpy

Yolo

There are 17 keypoints. YOLOv11’s pose model outputs:

  • (x, y) coordinates for each keypoint and
  • confidence scores indicating the model’s certainty in each keypoint’s position.

Image detection

from ultralytics import YOLO
import matplotlib.pyplot as plt
import cv2
from PIL import Image

model = YOLO("yolo11n-pose.pt")  # n, s, m, l, x versions available

results = model.predict(source="sample_image.jpg")  

plt.figure(figsize=(10, 10))
plt.title('YOLOv11 Pose Results')
plt.axis('off')
plt.imshow(cv2.cvtColor(results[0].plot(), cv2.COLOR_BGR2RGB))

Pose to skeleton

Images

Video

References