DeepDocClassifier

Abstract

This is a reimplementation of the ICDAR-2015 paper deepdocclassifier. The model demonstrated here is AlexNet (pretrained on imagenet) and finetuned for document classification on the Tobacoo-3428 dataset available here. A sample of the training set is as following.

Dependencies

• PyTorch
• TorchSummary
• Flask
• werkzeug
• seaborn
• TensorboardX
• imgaug

Model Summary

Web Interface

Run the web interface on a server by calling the web.py script from src/web/. It will open an interface on the server's ip and it can be accessed from anywhere by searching

server_ip:8008/interface/

in your server. This will present an interface as following.

You can upload your image and it will passed through the network loaded in web.py

Results

We get an evaluation accuracy of ~69% and test accuracy of 62% as opposed to +77% accuracy reported by the authors. The original network from the paper gives the result on the left, we get the one on the right