APP 03 : REAL-TIME IN-BROWSER INFERENCE
The article explaining how to use a customized Tensorflow Lite model for in-browser inference is here.
IN-BROWSER ML INFERENCE
I developed this app for image classification using tflite and Javascript. Instead of the default and supported model EfficientNet, I used a PyTorch model. The JS code loads the quantized .tflite model in the browser from a remote repo.
This solution allows anyone to train any customized model in Tensorflow/PyTorch, convert to .tflite and deploy in the web browser.
