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deep-text-recognition-benchmark
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@ -16,6 +16,7 @@ pip3 install lmdb pillow torchvision nltk torch-baidu-ctc
### Download lmdb dataset for traininig and evaluation from [here](https://drive.google.com/drive/folders/192UfE9agQUMNq6AgU3_E05_FcPZK4hyt)
data_lmdb_release.zip contains below. <br>
training datasets : [MJSynth (MJ)](http://www.robots.ox.ac.uk/~vgg/data/text/)[1] and [SynthText (ST)](http://www.robots.ox.ac.uk/~vgg/data/scenetext/)[2] \
validation datasets : the union of the training sets [IC13](http://rrc.cvc.uab.es/?ch=2)[3], [IC15](http://rrc.cvc.uab.es/?ch=4)[4], [IIIT](http://cvit.iiit.ac.in/projects/SceneTextUnderstanding/IIIT5K.html)[5], and [SVT](http://www.iapr-tc11.org/mediawiki/index.php/The_Street_View_Text_Dataset)[6].\
evaluation datasets : benchmark evaluation datasets, consist of [IIIT](http://cvit.iiit.ac.in/projects/SceneTextUnderstanding/IIIT5K.html)[5], [SVT](http://www.iapr-tc11.org/mediawiki/index.php/The_Street_View_Text_Dataset)[6], [IC03](http://www.iapr-tc11.org/mediawiki/index.php/ICDAR_2003_Robust_Reading_Competitions)[7], [IC13](http://rrc.cvc.uab.es/?ch=2)[3], [IC15](http://rrc.cvc.uab.es/?ch=4)[4], [SVTP](http://openaccess.thecvf.com/content_iccv_2013/papers/Phan_Recognizing_Text_with_2013_ICCV_paper.pdf)[8], and [CUTE](http://cs-chan.com/downloads_CUTE80_dataset.html)[9].
@ -64,7 +65,7 @@ CUDA_VISIBLE_DEVICES=0 python3 test.py \
* `--benchmark_all_eval`: evaluate with 10 evaluation dataset versions, same with Table 1 in our paper.
## Download failure cases and cleansed label from [here](https://drive.google.com/drive/folders/1W84gS9T5GU5l5Wp3VV1aeXIIKV87yjRm)
This contains failure case images and benchmark evaluation images with cleansed label.
image_release.zip contains failure case images and benchmark evaluation images with cleansed label.
<img src="./figures/failure-case.jpg" width="1000" title="failure cases">
## When you need to create lmdb dataset