WebCourt

1. train a yolo model with dataset of about 120 images
2. convert the pytorch yolo model to tfjs
3. use the tfjs model in browser extension

Training

Labeling tool labelImg

Follow this Google Colab to train and convert to tfjs

After converted to tfjs, download and put the model in ./tf/yolo/tfjs-models/yolov8{model-size}, e.g ./tf/yolo/tfjs-models/yolov8m

Extension build and usage

Currently use yolov8m model for extension

build

1. yarn install
2. yarn build.chrome.dev
3. the extension will be built in ./tools/dist/chrome, load it in Chrome

usage

predict

1. Go to a website
2. Context menu -> WebCourt -> Predict

save and download tab screenshot

1. Go to a website
2. Context menu -> WebCourt -> Capture Tab Image
3. The Tab screenshot will be saved to extension's indexedDB, you can repeat 1 and 2 to save as many as screenshots
4. Click extension popup -> Options
5. Click Download Images
   • the images will be downloaded to Chrome <current download folder>/web-court-download
   • if no indexes specified, all screenshots will be downloaded and overwrite the existing
   • the indexes would be helpful if you have a lot of screenshots or you capture screenshots incrementally and only need to download the newly captured ones