Pytorch re-implementation of Paper: SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text Recognition (CVPR 2022)

Overview

SwinTextSpotter

This is the pytorch implementation of Paper: SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text Recognition (CVPR 2022). The paper is available at this link.

Models

SWINTS-swin-english-pretrain [config] | model_Google Drive | model_BaiduYun PW: 954t

SWINTS-swin-Total-Text [config] | model_Google Drive | model_BaiduYun PW: tf0i

SWINTS-swin-ctw [config] | model_Google Drive | model_BaiduYun PW: 4etq

SWINTS-swin-icdar2015 [config] | model_Google Drive | model_BaiduYun PW: 3n82

SWINTS-swin-ReCTS [config] | model_Google Drive | model_BaiduYun PW: a4be

SWINTS-swin-vintext [config] | model_Google Drive | model_BaiduYun PW: slmp

Installation

  • Python=3.8
  • PyTorch=1.8.0, torchvision=0.9.0, cudatoolkit=11.1
  • OpenCV for visualization

Steps

  1. Install the repository (we recommend to use Anaconda for installation.)
conda create -n SWINTS python=3.8 -y
conda activate SWINTS
conda install pytorch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0 cudatoolkit=11.1 -c pytorch -c conda-forge
pip install opencv-python
pip install scipy
pip install shapely
pip install rapidfuzz
pip install timm
pip install Polygon3
git clone https://github.com/mxin262/SwinTextSpotter.git
cd SwinTextSpotter
python setup.py build develop
  1. dataset path
datasets
|_ totaltext
|  |_ train_images
|  |_ test_images
|  |_ totaltext_train.json
|  |_ weak_voc_new.txt
|  |_ weak_voc_pair_list.txt
|_ mlt2017
|  |_ train_images
|  |_ annotations/icdar_2017_mlt.json
.......

Downloaded images

Downloaded label[Google Drive] [BaiduYun] PW: 46vd

Downloader lexicion[Google Drive] and place it to corresponding dataset.

You can also prepare your custom dataset following the example scripts. [example scripts]

Totaltext

To evaluate on Total Text, CTW1500, ICDAR2015, first download the zipped annotations with

cd datasets
mkdir evaluation
cd evaluation
wget -O gt_ctw1500.zip https://cloudstor.aarnet.edu.au/plus/s/xU3yeM3GnidiSTr/download
wget -O gt_totaltext.zip https://cloudstor.aarnet.edu.au/plus/s/SFHvin8BLUM4cNd/download
wget -O gt_icdar2015.zip https://drive.google.com/file/d/1wrq_-qIyb_8dhYVlDzLZTTajQzbic82Z/view?usp=sharing
wget -O gt_vintext.zip https://drive.google.com/file/d/11lNH0uKfWJ7Wc74PGshWCOgSxgEnUPEV/view?usp=sharing
  1. Pretrain SWINTS (e.g., with Swin-Transformer backbone)
python projects/SWINTS/train_net.py \
  --num-gpus 8 \
  --config-file projects/SWINTS/configs/SWINTS-swin-pretrain.yaml
  1. Fine-tune model on the mixed real dataset
python projects/SWINTS/train_net.py \
  --num-gpus 8 \
  --config-file projects/SWINTS/configs/SWINTS-swin-mixtrain.yaml
  1. Fine-tune model
python projects/SWINTS/train_net.py \
  --num-gpus 8 \
  --config-file projects/SWINTS/configs/SWINTS-swin-finetune-totaltext.yaml
  1. Evaluate SWINTS (e.g., with Swin-Transformer backbone)
python projects/SWINTS/train_net.py \
  --config-file projects/SWINTS/configs/SWINTS-swin-finetune-totaltext.yaml \
  --eval-only MODEL.WEIGHTS ./output/model_final.pth
  1. Visualize the detection and recognition results (e.g., with ResNet50 backbone)
python demo/demo.py \
  --config-file projects/SWINTS/configs/SWINTS-swin-finetune-totaltext.yaml \
  --input input1.jpg \
  --output ./output \
  --confidence-threshold 0.4 \
  --opts MODEL.WEIGHTS ./output/model_final.pth

Example results:

Acknowlegement

Adelaidet, Detectron2, ISTR, SwinT_detectron2, Focal-Transformer and MaskTextSpotterV3.

Citation

If our paper helps your research, please cite it in your publications:

@article{huang2022swints,
  title = {SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text Recognition},
  author = {Mingxin Huang and YuLiang liu and Zhenghao Peng and Chongyu Liu and Dahua Lin and Shenggao Zhu and Nicholas Yuan and Kai Ding and Lianwen Jin},
  journal={arXiv preprint arXiv:2203.10209},
  year = {2022}
}

Copyright

For commercial purpose usage, please contact Dr. Lianwen Jin: [email protected]

Copyright 2019, Deep Learning and Vision Computing Lab, South China China University of Technology. http://www.dlvc-lab.net

Owner
mxin262
mxin262
Code release for NeX: Real-time View Synthesis with Neural Basis Expansion

NeX: Real-time View Synthesis with Neural Basis Expansion Project Page | Video | Paper | COLAB | Shiny Dataset We present NeX, a new approach to novel

538 Jan 09, 2023
Created as part of CS50 AI's coursework. This AI makes use of knowledge entailment to calculate the best probabilities to win Minesweeper.

Minesweeper-AI Created as part of CS50 AI's coursework. This AI makes use of knowledge entailment to calculate the best probabilities to win Minesweep

Beckham 0 Jul 20, 2022
PyExplainer: A Local Rule-Based Model-Agnostic Technique (Explainable AI)

PyExplainer PyExplainer is a local rule-based model-agnostic technique for generating explanations (i.e., why a commit is predicted as defective) of J

AI Wizards for Software Management (AWSM) Research Group 14 Nov 13, 2022
(NeurIPS '21 Spotlight) IQ-Learn: Inverse Q-Learning for Imitation

Inverse Q-Learning (IQ-Learn) Official code base for IQ-Learn: Inverse soft-Q Learning for Imitation, NeurIPS '21 Spotlight IQ-Learn is an easy-to-use

Divyansh Garg 102 Dec 20, 2022
Official repository for "Action-Based Conversations Dataset: A Corpus for Building More In-Depth Task-Oriented Dialogue Systems"

Action-Based Conversations Dataset (ABCD) This respository contains the code and data for ABCD (Chen et al., 2021) Introduction Whereas existing goal-

ASAPP Research 49 Oct 09, 2022
This project aims to segment 4 common retinal lesions from Fundus Images.

This project aims to segment 4 common retinal lesions from Fundus Images.

Husam Nujaim 1 Oct 10, 2021
Estimation of human density in a closed space using deep learning.

Siemens HOLLZOF challenge - Human Density Estimation Add project description here. Installing Dependencies: Install Python3 either system-wide, user-w

3 Aug 08, 2021
DiffWave is a fast, high-quality neural vocoder and waveform synthesizer.

DiffWave DiffWave is a fast, high-quality neural vocoder and waveform synthesizer. It starts with Gaussian noise and converts it into speech via itera

LMNT 498 Jan 03, 2023
Image segmentation with private İstanbul Dataset

Image Segmentation This repo was created for academic research and test result. Repo will update after academic article online. This repo contains wei

İrem KÖMÜRCÜ 9 Dec 11, 2022
This program automatically runs Python code copied in clipboard

CopyRun This program runs Python code which is copied in clipboard WARNING!! USE AT YOUR OWN RISK! NO GUARANTIES IF ANYTHING GETS BROKEN. DO NOT COPY

vertinski 4 Sep 10, 2021
GT China coal model

GT China coal model The full version of a China coal transport model with a very high spatial reslution. What it does The code works in a few steps: T

0 Dec 13, 2021
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

Super Resolution Examples We run this script under TensorFlow 2.0 and the TensorLayer2.0+. For TensorLayer 1.4 version, please check release. 🚀 🚀 🚀

TensorLayer Community 2.9k Jan 08, 2023
A3C LSTM Atari with Pytorch plus A3G design

NEWLY ADDED A3G A NEW GPU/CPU ARCHITECTURE OF A3C FOR SUBSTANTIALLY ACCELERATED TRAINING!! RL A3C Pytorch NEWLY ADDED A3G!! New implementation of A3C

David Griffis 532 Jan 02, 2023
Official PyTorch Implementation of GAN-Supervised Dense Visual Alignment

GAN-Supervised Dense Visual Alignment — Official PyTorch Implementation Paper | Project Page | Video This repo contains training, evaluation and visua

944 Jan 07, 2023
Semantically Contrastive Learning for Low-light Image Enhancement

Semantically Contrastive Learning for Low-light Image Enhancement Here, we propose an effective semantically contrastive learning paradigm for Low-lig

48 Dec 16, 2022
Adversarial Adaptation with Distillation for BERT Unsupervised Domain Adaptation

Knowledge Distillation for BERT Unsupervised Domain Adaptation Official PyTorch implementation | Paper Abstract A pre-trained language model, BERT, ha

Minho Ryu 29 Nov 30, 2022
Lux AI environment interface for RLlib multi-agents

Lux AI interface to RLlib MultiAgentsEnv For Lux AI Season 1 Kaggle competition. LuxAI repo RLlib-multiagents docs Kaggle environments repo Please let

Jaime 12 Nov 07, 2022
Shared Attention for Multi-label Zero-shot Learning

Shared Attention for Multi-label Zero-shot Learning Overview This repository contains the implementation of Shared Attention for Multi-label Zero-shot

dathuynh 26 Dec 14, 2022
[WWW 2021] Source code for "Graph Contrastive Learning with Adaptive Augmentation"

GCA Source code for Graph Contrastive Learning with Adaptive Augmentation (WWW 2021) For example, to run GCA-Degree under WikiCS, execute: python trai

Big Data and Multi-modal Computing Group, CRIPAC 97 Jan 07, 2023
A PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing"

A PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf 2021). Abstract In this work we propose Pathfind

Benedek Rozemberczki 49 Dec 01, 2022