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

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

Owner

S.X.Zhang

Code in conjunction with the publication 'Contrastive Representation Learning for Hand Shape Estimation'

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