Official implementation for ICDAR 2021 paper "Handwritten Mathematical Expression Recognition with Bidirectionally Trained Transformer"

Overview

Handwritten Mathematical Expression Recognition with Bidirectionally Trained Transformer

arXiv

Description

Convert offline handwritten mathematical expression to LaTeX sequence using bidirectionally trained transformer.

How to run

First, install dependencies

# clone project   
git clone https://github.com/Green-Wood/BTTR

# install project   
cd BTTR
conda create -y -n bttr python=3.7
conda activate bttr
conda install --yes -c pytorch pytorch=1.7.0 torchvision cudatoolkit=<your-cuda-version>
pip install -e .   

Next, navigate to any file and run it. It may take 6~7 hours to coverage on 4 gpus using ddp.

# module folder
cd BTTR

# train bttr model using 4 gpus and ddp
python train.py --config config.yaml  

For single gpu user, you may change the config.yaml file to

gpus: 1
# gpus: 4
# accelerator: ddp

Imports

This project is setup as a package which means you can now easily import any file into any other file like so:

from bttr.datamodule import CROHMEDatamodule
from bttr import LitBTTR
from pytorch_lightning import Trainer

# model
model = LitBTTR()

# data
dm = CROHMEDatamodule(test_year=test_year)

# train
trainer = Trainer()
trainer.fit(model, datamodule=dm)

# test using the best model!
trainer.test(datamodule=dm)

Note

Metrics used in validation is not accurate.

For more accurate metrics:

  1. use test.py to generate result.zip
  2. download and install crohmelib, lgeval, and tex2symlg tool.
  3. convert tex file to symLg file using tex2symlg command
  4. evaluate two folder using evaluate command

Citation

@article{zhao2021handwritten,
  title={Handwritten Mathematical Expression Recognition with Bidirectionally Trained Transformer},
  author={Zhao, Wenqi and Gao, Liangcai and Yan, Zuoyu and Peng, Shuai and Du, Lin and Zhang, Ziyin},
  journal={arXiv preprint arXiv:2105.02412},
  year={2021}
}
Comments
  • can you provide predict.py code?

    can you provide predict.py code?

    Hi ~ @Green-Wood.

    I feel grateful mind for your help. I wanna get predict.py code that prints latex from an input image. If this code is provided, it will be very useful to others as well.

    Best regards.

    opened by ai-motive 17
  • val_exprate=0 and save checkpoint

    val_exprate=0 and save checkpoint

    hello!thanks for your time! When I transfer some code in decoder or use it directly,the val_exprate are always be 0.000,I don't know why. Another problem is,I noticed that this code don't have the function to save checkpoint or something.Can you give me some help?Thanks again!

    opened by Ashleyyyi 6
  • Val_exprate = 0

    Val_exprate = 0

    When I retrained the model according to the instruction, the val_exprate was always 0.00, did anyone encounter this problem, thank you! (I has not modified any codes) @Green-Wood

    opened by qingqianshuying 4
  • test.py error occurs

    test.py error occurs

    When I run test.py code, the following error occurs. Can i get some helps?

    in test.py code test_year = "2016" ckp_path = "pretrained model"

    GPU available: True, used: True
    TPU available: False, using: 0 TPU cores
    Load data from: /home/motive/PycharmProjects/BTTR/bttr/datamodule/../../data.zip
    Extract data from: 2016, with data size: 1147
    total  1147 batch data loaded
    LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
    Testing: 100%|██████████| 1147/1147 [07:34<00:00,  2.01s/it]ExpRate: 0.32258063554763794
    length of total file: 1147
    Testing: 100%|██████████| 1147/1147 [07:34<00:00,  2.52it/s]
    --------------------------------------------------------------------------------
    DATALOADER:0 TEST RESULTS
    {}
    --------------------------------------------------------------------------------
    Traceback (most recent call last):
      File "/home/motive/PycharmProjects/BTTR/test.py", line 17, in <module>
        trainer.test(model, datamodule=dm)
      File "/home/motive/anaconda3/envs/bttr/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 579, in test
        results = self._run(model)
      File "/home/motive/anaconda3/envs/bttr/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 759, in _run
        self.post_dispatch()
      File "/home/motive/anaconda3/envs/bttr/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 789, in post_dispatch
        self.accelerator.teardown()
      File "/home/motive/anaconda3/envs/bttr/lib/python3.7/site-packages/pytorch_lightning/accelerators/gpu.py", line 51, in teardown
        self.lightning_module.cpu()
      File "/home/motive/anaconda3/envs/bttr/lib/python3.7/site-packages/pytorch_lightning/utilities/device_dtype_mixin.py", line 141, in cpu
        return super().cpu()
      File "/home/motive/anaconda3/envs/bttr/lib/python3.7/site-packages/torch/nn/modules/module.py", line 471, in cpu
        return self._apply(lambda t: t.cpu())
      File "/home/motive/anaconda3/envs/bttr/lib/python3.7/site-packages/torch/nn/modules/module.py", line 359, in _apply
        module._apply(fn)
      File "/home/motive/anaconda3/envs/bttr/lib/python3.7/site-packages/torchmetrics/metric.py", line 317, in _apply
        setattr(this, key, [fn(cur_v) for cur_v in current_val])
      File "/home/motive/anaconda3/envs/bttr/lib/python3.7/site-packages/torchmetrics/metric.py", line 317, in <listcomp>
        setattr(this, key, [fn(cur_v) for cur_v in current_val])
      File "/home/motive/anaconda3/envs/bttr/lib/python3.7/site-packages/torch/nn/modules/module.py", line 471, in <lambda>
        return self._apply(lambda t: t.cpu())
    AttributeError: 'tuple' object has no attribute 'cpu'
    
    opened by ai-motive 3
  • How long does BTTR take to train?

    How long does BTTR take to train?

    Hi, thank you for great repository!

    How long does it take to train for your experiment in the paper? I mean training on CROHME 2014/2016/2019 on four NVIDIA 1080Ti GPUs.

    Thanks,

    opened by RyosukeFukatani 2
  • can you provide transfer learning code?

    can you provide transfer learning code?

    Hi~ @Green-Wood

    I wanna apply trasnfer learning using pretrained model.

    but, LightningCLI() is wrapped and difficult to customize.

    Thanks & best regards.

    opened by ai-motive 1
  • How can it get pretrained model ?

    How can it get pretrained model ?

    Hi, I wanna test your BTTR model but, it need to training process which will take a lot of time. So, can you give me a pretrained model link?

    Best regards.

    opened by ai-motive 1
  • After adding new token in dictionary getting error .

    After adding new token in dictionary getting error .

    Hi , getting error after adding new token in dictionary.txt

    Error(s) in loading state_dict for LitBTTR: size mismatch for bttr.decoder.word_embed.0.weight: copying a param with shape torch.Size([113, 256]) from checkpoint, the shape in current model is torch.Size([115, 256]). size mismatch for bttr.decoder.proj.weight: copying a param with shape torch.Size([113, 256]) from checkpoint, the shape in current model is torch.Size([115, 256]). size mismatch for bttr.decoder.proj.bias: copying a param with shape torch.Size([113]) from checkpoint, the shape in current model is torch.Size([115]).

    Kindly help me out how can i fix this error.

    opened by shivankaraditi 0
  • About dataset

    About dataset

    Could you tell me how to generate the offline math expression image from inkml file? My experiment show that a large scale image could improve the result obviously,so I'd like to know if there is unified offline data for academic research.

    opened by lightflash7 0
  • predicting on gpu is slower

    predicting on gpu is slower

    Hi ,

    As this model is a bit slower compared to the existing state-of-the-art model on CPU. So I tried to make predictions on GPU and surprisingly it slower on Gpu compare to CPU as well.

    I am attaching a code snapshot here

    device = torch.device('cuda')if torch.cuda.is_available() else torch.device('cpu')

    model = LitBTTR.load_from_checkpoint('pretrained-2014.ckpt',map_location=device)

    img = Image.open(img_path) img = ToTensor()(img) img.to(device)

    t1 = time.time() hyp = model.beam_search(img) t2 = time.time()

    Kindly help me out here how i can reduce prediction time

    FYI - using GPU on aws g4dn.xlarge configuration machine

    opened by Suma3 1
  • how to use TensorBoard?

    how to use TensorBoard?

    hello i don't know how to add scalar to TensorBoard? I want to do this kind of topic, hoping to improve some ExpRate, but I don’t know much about lightning TensorBoard.

    opened by win5923 9
Releases(v2.0)
Owner
Wenqi Zhao
Student in Nanjing University
Wenqi Zhao
U-Net: Convolutional Networks for Biomedical Image Segmentation

Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras This tutorial shows how to use Keras library to build deep ne

Yihui He 401 Nov 21, 2022
Planar Prior Assisted PatchMatch Multi-View Stereo

ACMP [News] The code for ACMH is released!!! [News] The code for ACMM is released!!! About This repository contains the code for the paper Planar Prio

Qingshan Xu 127 Dec 31, 2022
Pytorch implementation of PCT: Point Cloud Transformer

PCT: Point Cloud Transformer This is a Pytorch implementation of PCT: Point Cloud Transformer.

Yi_Zhang 265 Dec 22, 2022
Reproduced Code for Image Forgery Detection papers.

Image Forgery Detection With over 4.5 billion active internet users, the amount of multimedia content being shared every day has surpassed everyone’s

Umar Masud 15 Dec 06, 2022
Official codebase for "B-Pref: Benchmarking Preference-BasedReinforcement Learning" contains scripts to reproduce experiments.

B-Pref Official codebase for B-Pref: Benchmarking Preference-BasedReinforcement Learning contains scripts to reproduce experiments. Install conda env

48 Dec 20, 2022
Localized representation learning from Vision and Text (LoVT)

Localized Vision-Text Pre-Training Contrastive learning has proven effective for pre- training image models on unlabeled data and achieved great resul

Philip Müller 10 Dec 07, 2022
My usage of Real-ESRGAN to upscale anime, some test and results in the test_img folder

anime upscaler My usage of Real-ESRGAN to upscale anime, I hope to use this on a proper GPU cuz doing this on CPU is completely shit 😂 , I even tried

Shangar Muhunthan 29 Jan 07, 2023
Age Progression/Regression by Conditional Adversarial Autoencoder

Age Progression/Regression by Conditional Adversarial Autoencoder (CAAE) TensorFlow implementation of the algorithm in the paper Age Progression/Regre

Zhifei Zhang 603 Dec 22, 2022
Rainbow DQN implementation that outperforms the paper's results on 40% of games using 20x less data 🌈

Rainbow 🌈 An implementation of Rainbow DQN which reaches a median HNS of 205.7 after only 10M frames (the original Rainbow from Hessel et al. 2017 re

Dominik Schmidt 31 Dec 21, 2022
[ICCV'21] NEAT: Neural Attention Fields for End-to-End Autonomous Driving

NEAT: Neural Attention Fields for End-to-End Autonomous Driving Paper | Supplementary | Video | Poster | Blog This repository is for the ICCV 2021 pap

254 Jan 02, 2023
Node Editor Plug for Blender

NodeEditor Blender的程序化建模插件 Show Current 基本框架:自定义的tree-node-socket、tree中的node与socket采用字典查询、基于socket入度的拓扑排序 数据传递和处理依靠Tree中的字典,socket传递字典key TODO 增加更多的节点

Cuimi 11 Dec 03, 2022
Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 130+ Indicators

Pandas TA - A Technical Analysis Library in Python 3 Pandas Technical Analysis (Pandas TA) is an easy to use library that leverages the Pandas package

Kevin Johnson 3.2k Jan 09, 2023
Sequential Model-based Algorithm Configuration

SMAC v3 Project Copyright (C) 2016-2018 AutoML Group Attention: This package is a reimplementation of the original SMAC tool (see reference below). Ho

AutoML-Freiburg-Hannover 778 Jan 05, 2023
Official repository for the ISBI 2021 paper Transformer Assisted Convolutional Neural Network for Cell Instance Segmentation

SegPC-2021 This is the official repository for the ISBI 2021 paper Transformer Assisted Convolutional Neural Network for Cell Instance Segmentation by

Datascience IIT-ISM 13 Dec 14, 2022
Improving Generalization Bounds for VC Classes Using the Hypergeometric Tail Inversion

Improving Generalization Bounds for VC Classes Using the Hypergeometric Tail Inversion Preface This directory provides an implementation of the algori

Jean-Samuel Leboeuf 0 Nov 03, 2021
Code for "Adversarial attack by dropping information." (ICCV 2021)

AdvDrop Code for "AdvDrop: Adversarial Attack to DNNs by Dropping Information(ICCV 2021)." Human can easily recognize visual objects with lost informa

Ranjie Duan 52 Nov 10, 2022
Implementation of C-RNN-GAN.

Implementation of C-RNN-GAN. Publication: Title: C-RNN-GAN: Continuous recurrent neural networks with adversarial training Information: http://mogren.

Olof Mogren 427 Dec 25, 2022
CLIPImageClassifier wraps clip image model from transformers

CLIPImageClassifier CLIPImageClassifier wraps clip image model from transformers. CLIPImageClassifier is initialized with the argument classes, these

Jina AI 6 Sep 12, 2022
Generalized Data Weighting via Class-level Gradient Manipulation

Generalized Data Weighting via Class-level Gradient Manipulation This repository is the official implementation of Generalized Data Weighting via Clas

18 Nov 12, 2022
Artificial Intelligence playing minesweeper 🤖

AI playing Minesweeper ✨ Minesweeper is a single-player puzzle video game. The objective of the game is to clear a rectangular board containing hidden

Vaibhaw 8 Oct 17, 2022