This is yolo model object detect web app, powered by ONNXRUNTIME-WEB.
Support Webgpu and wasm(cpu).
Model | Input Size | Param. |
---|---|---|
YOLOv10-N | 640 | 2.3M |
YOLOv10-S | 640 | 7.2M |
YOLOv9-T | 640 | 2.0M |
YOLOv9-S | 640 | 7.1M |
GELAN-S2 | 640 | |
YOLOv8-N | 640 | 3.2M |
YOLOv8-S | 640 | 11.2M |
Build decoder model from onnx-modifier by myself.
View model graph detail in netron.app
git clone https://github.com/nomi30701/yolo-object-detection-onnxruntime-web.git
cd yolo-object-detection-onnxruntime-web
yarn install # install dependencies
yarn dev # start dev server
- Conver YOLO model to onnx format. Read more on Ultralytics or yolov9_2_onnx.ipynb example.
- Copy your yolo model to
./public/models
folder. - Add
<option>
HTML element inApp.jsx
,value="YOUR_FILE_NAME"
. (Also can click "Add model" button)... <option value="YOUR_FILE_NAME">CUSTOM-MODEL</option> <option value="yolov10n-simplify">yolov10n-2.3M</option> <option value="yolov10s-simplify">yolov10s-7.2M</option> ...
- select your model on page.
- DONE!👍
✨ Support Webgpu
For Yolov10 and v8 onnx format support Webgpu, export model set
opset=12
.
✨ NMS setting
Yolov10 does not need nms.
If custom model are yolov10, add
"yolov10"
in file name.