SkalskiP / yolov5js

Effortless YOLOv5 javascript deployment
https://skalskip.github.io/yolov5js
MIT License
51 stars 8 forks source link
ai deep-learning deep-neural-networks javascript machine-learning tensorflowjs typescript yolo yolov5

npm NPM npm

CodeSandbox

yolov5.js

Logo

Install

npm install --save yolov5js

Example

Want to use yolov5js in your project but don't know how? Take a peek at our sample React app or run it in codesandbox.

Convert

# clone YOLOv5 repository
git clone https://github.com/ultralytics/yolov5.git
cd yolov5

# create python virtual environment [recommended]
virtualenv venv
source venv/bin/activate

# install dependencies
pip install -r requirements.txt
pip install tensorflowjs

# convert model to tensorflow.js format
python export.py --weights yolov5s.pt --include tfjs

Zoo

Use and share pretrained YOLOv5 tensorflow.js models with yolov5.js-zoo.

Documentation

Our proper documentation are still under construction 🚧. We are working on it really hard.

Load pre-trained model from zoo ```javascript import {load, YOLO_V5_N_COCO_MODEL_CONFIG} from 'yolov5js' const model = await load(YOLO_V5_N_COCO_MODEL_CONFIG) ```
Load custom model from file ```javascript import {load, ModelConfig} from 'yolov5js' const uploadJSONInput = document.getElementById('upload-json'); const uploadWeightsInput = document.getElementById('upload-weights'); const config = { source: [uploadJSONInput.files[0], uploadWeightsInput.files[0]] } const model = await load(config) ```

Kudos

Kudos to ultralytics team as well as all other open-source contributors for building YOLOv5 project, and making it all possible.

License

Project is freely distributable under the terms of the MIT license.