Samleo8 / FOTS

An Implementation of the FOTS: Fast Oriented Text Spotting with a Unified Network

FOTS: Fast Oriented Text Spotting with a Unified Network

Introduction

This is a pytorch re-implementation of FOTS: Fast Oriented Text Spotting with a Unified Network. The features are summarized blow:

• Only detection part is implemented.

Contents

1. Installation
2. Download
3. Train
4. Test

Installation

1. Any version of torch version >= 0.3.1 should be ok.

Download

1. Models trained on ICDAR 2015 (training set) + ICDAR 2017 (training set)

Train

If you want to train the model, you should provide the dataset path, in the dataset path, a separate gt text file should be provided for each image and run

python main_train.py

Pre-trained model

Download from here: https://drive.google.com/uc?export=download&confirm=qiR5&id=1oYfxKUA7YKZCnSgTN3Gk-u0N7uBPbJbT Disclaimer: This is not my model.

Test

run

python eval.py
	[-m|--model <path_to_model (default: models/retrained_model.pth.tar)>]
	[-i|--input_dir <input_directory (default: testdata)>] [-o|--output_dir <output_directory (default: testdata/results)>]

a text file will be then written to the output path.