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https://github.com/wonder-tree/posecamera
PoseCamera: Realtime Human Pose Estimation Python SDK
https://github.com/wonder-tree/posecamera
computer-vision mobilenet opencv openpose pose-estimation python pytorch
Last synced: about 1 month ago
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PoseCamera: Realtime Human Pose Estimation Python SDK
- Host: GitHub
- URL: https://github.com/wonder-tree/posecamera
- Owner: Wonder-Tree
- License: apache-2.0
- Created: 2020-07-16T05:10:27.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2021-07-20T13:40:39.000Z (over 3 years ago)
- Last Synced: 2024-03-23T17:48:17.377Z (8 months ago)
- Topics: computer-vision, mobilenet, opencv, openpose, pose-estimation, python, pytorch
- Language: Python
- Homepage: https://wonder-tree.github.io
- Size: 4.94 MB
- Stars: 7
- Watchers: 4
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Contributing: contributing/README.md
- License: LICENSE
Awesome Lists containing this project
README
## PoseCamera
[](https://badge.fury.io/py/posecamera) [](https://github.com/Wonder-Tree/PoseCamera/actions) [](https://www.codefactor.io/repository/github/wonder-tree/posecamera) [](https://github.com/Wonder-Tree/PoseCamera/discussions)
PoseCamera is python based SDK for human pose estimation through RGB webcam.
### Install
install posecamera package through pip
```python
pip install posecamera
```
If you are having issues with the installation on Windows OS then check this [page](https://wonder-tree.github.io/PoseCamera-Docs/#/pages/troubleshooting)
### Usage
> See Google colab notebook https://colab.research.google.com/drive/1pzsgxaz1ZVesh_j-96PBak_OQKP19HHA?usp=sharing
draw pose keypoints on image
```python
import posecamera
import cv2
det = posecamera.pose_tracker.PoseTracker()
image = cv2.imread("example.jpg")
pose = det(image)
for name, (y, x, score) in pose.keypoints.items():
cv2.circle(image, (int(x), int(y)), 4, (255, 0, 0), -1)
cv2.imshow("PoseCamera", image)
cv2.waitKey(0)
```
output of the above example
or get keypoints array
```text
for pose in poses:
keypoints = pose.keypoints
```
Handtracker
```
import posecamera
import cv2
det = posecamera.hand_tracker.HandTracker()
image = cv2.imread("tmp/hands.jpg")
keypoints, bbox = det(image)
for hand_keypoints in keypoints:
for (x, y) in hand_keypoints:
cv2.circle(image, (int(x), int(y)), 3, (255, 0, 0), -1)
cv2.imshow("PoseCamera - Hand Tracking", image)
cv2.waitKey(0)
```
#### Using Docker
The official docker image is hosted on [Docker Hub](https://hub.docker.com/r/wondertree/posecamera). The very first step is to install the docker [docker](https://docs.docker.com/get-docker/) on your system.
> Also note that your Nvidia driver Needs to be compatible with CUDA10.2.
Doing inference on live webcam feed.
```bash
xhost +; docker run --name posecamera --rm --net=host --gpus all -e DISPLAY=$DISPLAY --device=/dev/video0:/dev/video0 wondertree/posecamera --video=0
```
> GPU & Webcam support \(if running docker\) is not available on Windows Operating System.
To run inference on images use the following command.
```bash
docker run --name posecamera --rm --net=host -e DISPLAY=$DISPLAY wondertree/posecamera --images ./tmp/female_pose.jpg --cpu
```
For more details read our [Docs](https://wonder-tree.github.io/PoseCamera-Docs/)
The base of this repository is based on the following research paper.
```text
@inproceedings{osokin2018lightweight_openpose,
author={Osokin, Daniil},
title={Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose},
booktitle = {arXiv preprint arXiv:1811.12004},
year = {2018}
}
```
The base of hand tracking is based on the following repository : https://google.github.io/mediapipe/solutions/hands
#### Share your thoughts
Join our [Discussion Channel](https://github.com/Wonder-Tree/PoseCamera/discussions)! We love to hear your ideas, suggestions or pull request