Coder Social home page Coder Social logo

cnn-lstm-ctc-amharic-ocr-'s Introduction

CNN-LSTM-CTC Amharic OCR

End-to-End learning

  • This method uses CNN-LSTM-CTC networks.
  • To train and test this model, please use the ADOCR dataset from http://www.dfki.uni-kl.de/~belay/. (new link) https://bdu-birhanu.github.io/amharic.html However, to play with the code you may also use the sample database given, together with the source code, in this directory.
  • Both the text-line images and corresponding ground truth are given in numpy format.

To run the code with Terminal use the following info:

# Load and Pre-process data
python data_loader.py

# Train
python train_model.py

# Test and results
python test_model.py

Some issues to know

  1. The test environment is
    • Python 2.7
    • Keras 2.2.4
    • tensorflow 1.14

cnn-lstm-ctc-amharic-ocr-'s People

Contributors

bdu-birhanu avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.