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YOLOv7 Node.js

love onnxruntime-node opencv.js-4.5.5


YOLOv7 Live Detection Application on Node.js. Serving YOLOv7 in Node.js using onnxruntime-node.

Setup

git clone https://github.com/Hyuto/yolov7-node.git
cd yolov7-node
yarn install # Install dependencies

Run ~~

yarn start

Model

YOLOv7 model converted to onnx model.

used model : yolov7-tiny
size       : 24 MB

Use Another Model

⚠️ Expensive Computation : YOLOv7 model used in this repo is the smallest with size of 24 MB, so other models is definitely bigger than this which can exhausting computation.

Use another YOLOv7 model.

  1. Clone yolov7 repository

    git clone https://github.com/WongKinYiu/yolov7.git && cd yolov7

    Install requirements.txt first

    pip install -r requirements.txt

    Then export desired YOLOv7 model and configurations to onnx

    python export.py --weights <YOLOv7-MODEL>.pt --grid --end2end --simplify \
         --topk-all 100 --iou-thres 0.65 --conf-thres 0.35 --img-size 640 640 --max-wh 640

    Note : You can run it on colab too

    colab-badge

  2. Copy yolov7*.onnx to ./src

  3. Update modelInfo in index.js to new model name

    ...
    // model configs
    const modelInfo = {
       name: "yolov7-tiny.onnx", // change this to new model filename
       inputShape: [1, 3, 640, 640], // change this if model input shape isn't 640 x 640
    };
    ...
  4. Done! 😊

Reference

https://github.com/WongKinYiu/yolov7