This example creates a Chrome extension, enabling users to right-click on images within a web page, and perform multi-class object detection on them. The extension will apply a MobileNetV2 classifier to the image, and then print the predicted class on top of the image.
To build the extension, use the command:
yarn
yarn build
To install the unpacked extension in chrome, follow the instructions here. Briefly, navigate to chrome://extensions
, make sure that the Developer mode
switch is turned on in the upper right, and click Load Unpacked
. Then select the appropriate directory (the dist
directory containing manifest.json
);
If it worked you should see an icon for the TF.js mobilenet
Chrome extension.
Once the extension is installed, you should be able to classify images in the browser. To do so, navigate to a site with images on it, such as the Google image search page for the term "tiger" used here. Then right click on the image you wish to classify. You should see a menu option for Classify image with TensorFlow.js
. Clicking that image should cause the extension to execute the model on the image, and then add some text over the image indicating the prediction.
To remove the extension, click Remove
on the extension page, or use the Remove from Chrome...
menu option when right clicking the icon.