TextBPN Adaptive Boundary Proposal Network for Arbitrary Shape Text Detection

S.X.Zhang

Last update: Dec 13, 2022

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Overview

TextBPN

Adaptive Boundary Proposal Network for Arbitrary Shape Text Detection； Accepted by ICCV2021.

Note: The complete code (including training and testing) will be released in TextBPN V2. Relevant work is advancing, and those who are interested in our work can pay more attention to the updates here.

1.Prerequisites t

python 3.9;
PyTorch 1.7.0;
Numpy >=1.2.0
CUDA 11.1;
GCC >=10.0;
NVIDIA GPU(with 11G or larger GPU memory for inference);

2.Dataset Links

3.Models

Total-Text model (pretrained on ICDAR2017-MLT)
CTW-1500 model (pretrained on ICDAR2017-MLT)
MSRA-TD500 model (pretrained on ICDAR2017-MLT)

4.Running Evaluation

run:

sh eval.sh

The details are as follows:

#!/bin/bash
##################### Total-Text ###################################
# test_size=[640,1024]--cfglib/option
CUDA_LAUNCH_BLOCKING=1 python eval_textBPN.py --exp_name Totaltext --checkepoch 390 --dis_threshold 0.3 --cls_threshold 0.825 --test_size 640 1024 --gpu 1

###################### CTW-1500 ####################################
# test_size=[640,1024]--cfglib/option
# CUDA_LAUNCH_BLOCKING=1 python eval_textBPN.py --exp_name Ctw1500 --checkepoch 560 --dis_threshold 0.3 --cls_threshold 0.8 --test_size 640 1024 --gpu 1

#################### MSRA-TD500 ######################################
# test_size=[640,1024]--cfglib/option
#CUDA_LAUNCH_BLOCKING=1 python eval_textBPN.py --exp_name TD500 --checkepoch 680 --dis_threshold 0.3 --cls_threshold 0.925 --test_size 640 1024 --gpu 1

5.Experiments results

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Comments

Is that anything wrong with pretrained model?

Hello, many thanks to your excellent work!

However, when I tried to use the pretrained model to evaluate total-text dataset, I found the name of pretrained model is "TextGraph_resnet50_550.pth" and it can not be successfully loaded to the model.

So I am wondering if there is anything wrong with the pretrained model?

opened by JingyeChen 2
How to sample vertices from the boundary proposals during the training?

Thank you for your work.

I am confused about how did you sample the vertices from the predicted boundary proposals during the training in a learnable way ?

https://github.com/GXYM/TextBPN/blob/main/network/textnet.py#L74

It seems directly read from the input instead of from the predicted boundary proposal?

Thank you.

opened by smallmax00 1

TextBPN Adaptive Boundary Proposal Network for Arbitrary Shape Text Detection

Related tags

Overview

TextBPN

1.Prerequisites t

2.Dataset Links

3.Models

4.Running Evaluation

5.Experiments results

You might also like...

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Official implementation of "Dynamic Anchor Learning for Arbitrary-Oriented Object Detection" (AAAI2021).

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

ICCV2021 Paper: AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection

[CVPR 2022] Back To Reality: Weak-supervised 3D Object Detection with Shape-guided Label Enhancement

Towards Implicit Text-Guided 3D Shape Generation (CVPR2022)

Comments

Is that anything wrong with pretrained model?

How to sample vertices from the boundary proposals during the training?

Owner

S.X.Zhang

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