Code for Text Prior Guided Scene Text Image Super-Resolution

Related tags

Text Data & NLPTPGSR
Overview

Text Prior Guided Scene Text Image Super-Resolution

https://arxiv.org/abs/2106.15368

Jianqi Ma, Shi Guo, Lei Zhang
Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China

Recovering TextZoom samples

TPGSR visualization

Environment:

python pytorch cuda numpy

Other possible python packages like pyyaml, cv2, Pillow and imgaug

Main idea

Single stage with loss

Multi-stage version

Configure your training

Download the pretrained recognizer from:

Aster: https://github.com/ayumiymk/aster.pytorch  
MORAN:  https://github.com/Canjie-Luo/MORAN_v2  
CRNN: https://github.com/meijieru/crnn.pytorch

Unzip the codes and walk into the '$TPGSR_ROOT$/', place the pretrained weights from recognizer in '$TPGSR_ROOT$/'.

Download the TextZoom dataset:

https://github.com/JasonBoy1/TextZoom

Train the corresponding model (e.g. TPGSR-TSRN):

chmod a+x train_TPGSR-TSRN.sh
./train_TPGSR-TSRN.sh
or
python3 main.py --arch="tsrn_tl_cascade" \       # The architecture
                --batch_size=48 \                # The batch size
                --STN \                          # Using STN net for alignment
		--mask \                         # Using the contour mask
		--use_distill \                  # Using the TP loss
		--gradient \                     # Using the Gradient Prior Loss
		--sr_share \                     # Sharing weights for SR Module
		--stu_iter=1 \                   # The number of interations in multi-stage version
		--vis_dir='vis_TPGSR-TSRN' \     # The checkpoint directory

Run the test-prefixed shell to test the corresponding model.

Adding '--go_test' in the shell file

Cite this paper:

@article{ma2021text,
title={Text Prior Guided Scene Text Image Super-resolution},
author={Ma, Jianqi and Guo, Shi and Zhang, Lei},
journal={arXiv preprint arXiv:2106.15368},
year={2021}
}
IMS-Toucan is a toolkit to train state-of-the-art Speech Synthesis models

IMS-Toucan is a toolkit to train state-of-the-art Speech Synthesis models. Everything is pure Python and PyTorch based to keep it as simple and beginner-friendly, yet powerful as possible.

Digital Phonetics at the University of Stuttgart 247 Jan 05, 2023
A machine learning model for analyzing text for user sentiment and determine whether its a positive, neutral, or negative review.

Sentiment Analysis on Yelp's Dataset Author: Roberto Sanchez, Talent Path: D1 Group Docker Deployment: Deployment of this application can be found her

Roberto Sanchez 0 Aug 04, 2021
Analyse japanese ebooks using MeCab to determine the difficulty level for japanese learners

japanese-ebook-analysis This aim of this project is to make analysing the contents of a japanese ebook easy and streamline the process for non-technic

Christoffer Aakre 14 Jul 23, 2022
Implementation of TF-IDF algorithm to find documents similarity with cosine similarity

NLP learning Trying to learn NLP to use in my projects! Table of Contents About The Project Built With Getting Started Requirements Run Usage License

Faraz Farangizadeh 3 Aug 25, 2022
Biterm Topic Model (BTM): modeling topics in short texts

Biterm Topic Model Bitermplus implements Biterm topic model for short texts introduced by Xiaohui Yan, Jiafeng Guo, Yanyan Lan, and Xueqi Cheng. Actua

Maksim Terpilowski 49 Dec 30, 2022
Textlesslib - Library for Textless Spoken Language Processing

textlesslib Textless NLP is an active area of research that aims to extend NLP t

Meta Research 379 Dec 27, 2022
Code for paper "Role-oriented Network Embedding Based on Adversarial Learning between Higher-order and Local Features"

Role-oriented Network Embedding Based on Adversarial Learning between Higher-order and Local Features Train python main.py --dataset brazil-flights C

wang zhang 0 Jun 28, 2022
Just Another Telegram Ai Chat Bot Written In Python With Pyrogram.

OkaeriChatBot Just another Telegram AI chat bot written in Python using Pyrogram. Requirements Python 3.7 or higher.

Wahyusaputra 2 Dec 23, 2021
Transformer related optimization, including BERT, GPT

This repository provides a script and recipe to run the highly optimized transformer-based encoder and decoder component, and it is tested and maintained by NVIDIA.

NVIDIA Corporation 1.7k Jan 04, 2023
An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

CRNN paper:An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition 1. create your ow

Tsukinousag1 3 Apr 02, 2022
This is my reading list for my PhD in AI, NLP, Deep Learning and more.

This is my reading list for my PhD in AI, NLP, Deep Learning and more.

Zhong Peixiang 156 Dec 21, 2022
A BERT-based reverse-dictionary of Korean proverbs

Wisdomify A BERT-based reverse-dictionary of Korean proverbs. 김유빈 : 모델링 / 데이터 수집 / 프로젝트 설계 / back-end 김종윤 : 데이터 수집 / 프로젝트 설계 / front-end Quick Start C

Eu-Bin KIM 94 Dec 08, 2022
An implementation of WaveNet with fast generation

pytorch-wavenet This is an implementation of the WaveNet architecture, as described in the original paper. Features Automatic creation of a dataset (t

Vincent Herrmann 858 Dec 27, 2022
Auto-researching tool generating word documents.

About ResearchTE automates researching by generating document with answers to given questions. Supports getting results from: Google DuckDuckGo (with

1 Feb 14, 2022
Russian GPT3 models.

Russian GPT-3 models (ruGPT3XL, ruGPT3Large, ruGPT3Medium, ruGPT3Small) trained with 2048 sequence length with sparse and dense attention blocks. We also provide Russian GPT-2 large model (ruGPT2Larg

Sberbank AI 1.6k Jan 05, 2023
This repository is home to the Optimus data transformation plugins for various data processing needs.

Transformers Optimus's transformation plugins are implementations of Task and Hook interfaces that allows execution of arbitrary jobs in optimus. To i

Open Data Platform 37 Dec 14, 2022
Quantifiers and Negations in RE Documents

Quantifiers-and-Negations-in-RE-Documents This project was part of my work for a

Nicolas Ruscher 1 Feb 01, 2022
Codes to pre-train Japanese T5 models

t5-japanese Codes to pre-train a T5 (Text-to-Text Transfer Transformer) model pre-trained on Japanese web texts. The model is available at https://hug

Megagon Labs 37 Dec 25, 2022
Pytorch implementation of winner from VQA Chllange Workshop in CVPR'17

2017 VQA Challenge Winner (CVPR'17 Workshop) pytorch implementation of Tips and Tricks for Visual Question Answering: Learnings from the 2017 Challeng

Mark Dong 166 Dec 11, 2022
Train and use generative text models in a few lines of code.

blather Train and use generative text models in a few lines of code. To see blather in action check out the colab notebook! Installation Use the packa

Dan Carroll 16 Nov 07, 2022