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https://github.com/handtracking-io/yoha
A practical hand tracking engine.
https://github.com/handtracking-io/yoha
ai hand-recognition hand-tracking javascript typescript web
Last synced: 1 day ago
JSON representation
A practical hand tracking engine.
- Host: GitHub
- URL: https://github.com/handtracking-io/yoha
- Owner: handtracking-io
- License: mit
- Created: 2021-07-27T14:06:48.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2024-03-30T22:11:01.000Z (9 months ago)
- Last Synced: 2024-12-06T03:01:53.559Z (8 days ago)
- Topics: ai, hand-recognition, hand-tracking, javascript, typescript, web
- Language: TypeScript
- Homepage:
- Size: 31.4 MB
- Stars: 2,072
- Watchers: 28
- Forks: 149
- Open Issues: 16
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome - handtracking-io/yoha - A practical hand tracking engine. (TypeScript)
- awesome - handtracking-io/yoha - A practical hand tracking engine. (TypeScript)
README
Yoha
A practical hand tracking engine.
Note: Yoha is currently unmaintained.
Quick Links:
Installation
`npm install @handtracking.io/yoha`
Please note:
- You need to serve the files from `node_modules/@handtracking.io/yoha` since the library needs to download the model files from here. (Webpack Example)
- You need to serve your page with https for webcam access. (Webpack Example)
- You should use cross-origin isolation as it improves the engine's performance in certain scenarios. (Webpack Example)
Description
Yoha is a hand tracking engine that is built with the goal of being a versatile solution
in practical scenarios where hand tracking is employed to add value to
an application. While ultimately the goal is to be a general purpose hand
tracking engine supporting any hand pose, the engine evolves
around specific hand poses that users/developers find useful. These poses
are detected by the engine which allows to build applications with meaningful interactions.
See the demo for an example.
Yoha is currently in beta.
About the name: Yoha is short for ("Your Hand Tracking").
## Language Support
Yoha is currently available for the web via JavaScript. More languages will be added
in the future. If you want to port Yoha to another language and need help feel free reach out.
## Technical Details
Yoha was built from scratch. It uses a custom neural
network trained using a custom dataset. The backbone for the
inference in the browser is currently TensorFlow.js
### Features:
- Detection of 21 2D-landmark coordinates (single hand).
- Hand presence detection.
- Hand orientation (left/right hand) detection.
- Inbuilt pose detection.
#### Supported Hand Poses:
- Pinch (index finger and thumb touch)
- Fist
Your desired pose is not on this list? Feel free to create an issue for it.
### Performance
Yoha was built with performance in mind. It is able to provide realtime user
experience on a broad range of laptops and desktop devices. The performance
on mobile devices is not great which hopefuly will change with the further
development of inference frameworks like
TensorFlow.js
Please note that native inference speed can not be compared
with the web inference speed. Differently put, if you were to
run Yoha natively it would be much faster than via the web
browser.
## Minimal Example
- [Source](https://github.com/handtracking-io/yoha/tree/main/example/)
- Running locally:
```
git clone https://github.com/handtracking-io/yoha && \
cd yoha/example && \
yarn && \
yarn start
```
## Drawing Demo
- [Live Version](https://handtracking-io.github.io/yoha/draw_demo)
- [Source](https://github.com/handtracking-io/yoha/tree/main/src/demos/draw)
- Running locally:
```
git clone https://github.com/handtracking-io/yoha && \
cd yoha && \
./download_models.sh && \
yarn && \
yarn start
```