Is it possible to use Tensorflow.js for real-time OCR for language modeling ( to start with English) as I am willing to make client side native desktop application running in offline mode.? Motivation behind it is to avoid unnecessary network resource consumption and have higher level of security. I tried bundling Tesseract.js but its not real time and there is no much activity in respective forum for a longer.time. Any pointer in this regard would be a great help.

Is it possible to use Tensorflow.js for real-time OCR for language modeling ( to start with English) as I am willing to make client side native desktop application running in offline mode.? Motivation behind it is to avoid unnecessary network resource consumption and have higher level of security. I tried bundling Tesseract.js but its not real time and there is no much activity in respective forum for a longer.time. Any pointer in this regard would be a great help.

• javascript
• ocr
• tensorflow.js

• 1 Hey Jey Thanks for reply. I am tracking their site for last month ( since beginning of their js avatar) but couldn't get anything relevant. Can you share some link may be I missed ? It will be a great help. – Gaurav Srivastava Commented May 15, 2018 at 8:05

2 Answers 2

Define "real-time". If you mean every second on a webcam, then yes! If you want native performance, you should consider a mobile app instead, using TFLite. Most cases the running every second is acceptable.

I remend converting an existing TF model to TFJS for your research. Like this one: https://github./tensorflow/models/tree/master/research/attention_ocr

Or you could train your own, like the classic MNIST example in TFJS, seen here: https://storage.googleapis./tfjs-examples/mnist/dist/index.html

use tensorflow.js with electron.js. it have native performance. because instead of webgl it uses CUDA and native c libraries which gain super fast result