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This page lists the datasets which are commonly used in text detection, text recognition and key information extraction, and their download links. This page lists the datasets which are commonly used in text detection, text recognition and key information extraction, and their download links.
<!-- TOC --> <!-- TOC -->
- [Datasets Preparation](#datasets-preparation) - [Datasets Preparation](#datasets-preparation)
- [Text Detection](#text-detection) - [Text Detection](#text-detection)
- [Text Recognition](#text-recognition) - [Text Recognition](#text-recognition)
- [Key Information Extraction](#key-information-extraction) - [Key Information Extraction](#key-information-extraction)
<!-- /TOC --> <!-- /TOC -->
## Text Detection ## Text Detection
The structure of the text detection dataset directory is organized as follows. The structure of the text detection dataset directory is organized as follows.
@ -31,13 +33,13 @@ The structure of the text detection dataset directory is organized as follows.
│   └── instances_training.lmdb │   └── instances_training.lmdb
``` ```
| Dataset | | Images | | | Annotation Files | | | | Dataset | Images | | | Annotation Files | |
| :-------: | :---: | :------------------------------------------------------------: | :----------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------: | :-------------------------------------: | :--------------------------------------------------------------------------------------------: | :---: | | :-------: | :------------------------------------------------------------: | :----------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------: | :-------------------------------------: | :--------------------------------------------------------------------------------------------: |
| | | | | training | validation | testing | | | | | | training | validation | testing | |
| CTW1500 | | [homepage](https://github.com/Yuliang-Liu/Curve-Text-Detector) | | [instances_training.json](https://download.openmmlab.com/mmocr/data/ctw1500/instances_training.json) | - | [instances_test.json](https://download.openmmlab.com/mmocr/data/ctw1500/instances_test.json) | | | CTW1500 | [homepage](https://github.com/Yuliang-Liu/Curve-Text-Detector) | | [instances_training.json](https://download.openmmlab.com/mmocr/data/ctw1500/instances_training.json) | - | [instances_test.json](https://download.openmmlab.com/mmocr/data/ctw1500/instances_test.json) |
| ICDAR2015 | | [homepage](https://rrc.cvc.uab.es/?ch=4&com=downloads) | | [instances_training.json](https://download.openmmlab.com/mmocr/data/icdar2015/instances_training.json) | - | [instances_test.json](https://download.openmmlab.com/mmocr/data/icdar2015/instances_test.json) | | | ICDAR2015 | [homepage](https://rrc.cvc.uab.es/?ch=4&com=downloads) | | [instances_training.json](https://download.openmmlab.com/mmocr/data/icdar2015/instances_training.json) | - | [instances_test.json](https://download.openmmlab.com/mmocr/data/icdar2015/instances_test.json) |
| ICDAR2017 | | [homepage](https://rrc.cvc.uab.es/?ch=8&com=downloads) | [renamed_imgs](https://download.openmmlab.com/mmocr/data/icdar2017/renamed_imgs.tar) | [instances_training.json](https://download.openmmlab.com/mmocr/data/icdar2017/instances_training.json) | [instances_val.json](https://openmmlab) | [instances_test.json](https://download.openmmlab.com/mmocr/data/icdar2017/instances_test.json) | | | | | ICDAR2017 | [homepage](https://rrc.cvc.uab.es/?ch=8&com=downloads) | [renamed_imgs](https://download.openmmlab.com/mmocr/data/icdar2017/renamed_imgs.tar) | [instances_training.json](https://download.openmmlab.com/mmocr/data/icdar2017/instances_training.json) | [instances_val.json](https://openmmlab) | [instances_test.json](https://download.openmmlab.com/mmocr/data/icdar2017/instances_test.json) | | |
| Synthtext | | [homepage](https://www.robots.ox.ac.uk/~vgg/data/scenetext/) | | [instances_training.lmdb](https://download.openmmlab.com/mmocr/data/synthtext/instances_training.lmdb) | - | | | Synthtext | [homepage](https://www.robots.ox.ac.uk/~vgg/data/scenetext/) | | [instances_training.lmdb](https://download.openmmlab.com/mmocr/data/synthtext/instances_training.lmdb) | - |
- For `icdar2015`: - For `icdar2015`:
- Step1: Download `ch4_training_images.zip` and `ch4_test_images.zip` from [homepage](https://rrc.cvc.uab.es/?ch=4&com=downloads) - Step1: Download `ch4_training_images.zip` and `ch4_test_images.zip` from [homepage](https://rrc.cvc.uab.es/?ch=4&com=downloads)
@ -112,16 +114,16 @@ The structure of the text detection dataset directory is organized as follows.
| :--------: | :-----------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------: | | :--------: | :-----------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------: |
| | | training | test | | | | training | test |
| coco_text | [homepage](https://rrc.cvc.uab.es/?ch=5&com=downloads) | [train_label.txt](https://download.openmmlab.com/mmocr/data/mixture/coco_text/train_label.txt) | - | | | coco_text | [homepage](https://rrc.cvc.uab.es/?ch=5&com=downloads) | [train_label.txt](https://download.openmmlab.com/mmocr/data/mixture/coco_text/train_label.txt) | - | |
| icdar_2011 | | [homepage](http://www.cvc.uab.es/icdar2011competition/?com=downloads) | [train_label.txt](https://download.openmmlab.com/mmocr/data/mixture/icdar_2015/train_label.txt) | - | | | icdar_2011 | [homepage](http://www.cvc.uab.es/icdar2011competition/?com=downloads) | [train_label.txt](https://download.openmmlab.com/mmocr/data/mixture/icdar_2015/train_label.txt) | - | |
| icdar_2013 | | [homepage](https://rrc.cvc.uab.es/?ch=2&com=downloads) | [train_label.txt](https://download.openmmlab.com/mmocr/data/mixture/icdar_2013/train_label.txt) | [test_label_1015.txt](https://download.openmmlab.com/mmocr/data/mixture/icdar_2013/test_label_1015.txt) | | | icdar_2013 | [homepage](https://rrc.cvc.uab.es/?ch=2&com=downloads) | [train_label.txt](https://download.openmmlab.com/mmocr/data/mixture/icdar_2013/train_label.txt) | [test_label_1015.txt](https://download.openmmlab.com/mmocr/data/mixture/icdar_2013/test_label_1015.txt) | |
| icdar_2015 | | [homepage](https://rrc.cvc.uab.es/?ch=4&com=downloads) | [train_label.txt](https://download.openmmlab.com/mmocr/data/mixture/icdar_2015/train_label.txt) | [test_label.txt](https://download.openmmlab.com/mmocr/data/mixture/icdar_2015/test_label.txt) | | | icdar_2015 | [homepage](https://rrc.cvc.uab.es/?ch=4&com=downloads) | [train_label.txt](https://download.openmmlab.com/mmocr/data/mixture/icdar_2015/train_label.txt) | [test_label.txt](https://download.openmmlab.com/mmocr/data/mixture/icdar_2015/test_label.txt) | |
| IIIT5K | | [homepage](http://cvit.iiit.ac.in/projects/SceneTextUnderstanding/IIIT5K.html) | [train_label.txt](https://download.openmmlab.com/mmocr/data/mixture/IIIT5K/train_label.txt) | [test_label.txt](https://download.openmmlab.com/mmocr/data/mixture/IIIT5K/test_label.txt) | | | IIIT5K | [homepage](http://cvit.iiit.ac.in/projects/SceneTextUnderstanding/IIIT5K.html) | [train_label.txt](https://download.openmmlab.com/mmocr/data/mixture/IIIT5K/train_label.txt) | [test_label.txt](https://download.openmmlab.com/mmocr/data/mixture/IIIT5K/test_label.txt) | |
| ct80 | | - | - | [test_label.txt](https://download.openmmlab.com/mmocr/data/mixture/ct80/test_label.txt) | | | ct80 | - | - | [test_label.txt](https://download.openmmlab.com/mmocr/data/mixture/ct80/test_label.txt) | |
| svt | | [homepage](http://www.iapr-tc11.org/mediawiki/index.php/The_Street_View_Text_Dataset) | - | [test_label.txt](https://download.openmmlab.com/mmocr/data/mixture/svt/test_label.txt) | | | svt |[homepage](http://www.iapr-tc11.org/mediawiki/index.php/The_Street_View_Text_Dataset) | - | [test_label.txt](https://download.openmmlab.com/mmocr/data/mixture/svt/test_label.txt) | |
| svtp | | - | - | [test_label.txt](https://download.openmmlab.com/mmocr/data/mixture/svtp/test_label.txt) | | | svtp | - | - | [test_label.txt](https://download.openmmlab.com/mmocr/data/mixture/svtp/test_label.txt) | |
| Synth90k | | [homepage](https://www.robots.ox.ac.uk/~vgg/data/text/) | [shuffle_labels.txt](https://download.openmmlab.com/mmocr/data/mixture/Synth90k/shuffle_labels.txt) \| [label.lmdb](https://download.openmmlab.com/mmocr/data/mixture/Synth90k/label.lmdb) | - | | | Synth90k | [homepage](https://www.robots.ox.ac.uk/~vgg/data/text/) | [shuffle_labels.txt](https://download.openmmlab.com/mmocr/data/mixture/Synth90k/shuffle_labels.txt) \| [label.lmdb](https://download.openmmlab.com/mmocr/data/mixture/Synth90k/label.lmdb) | - | |
| SynthText | | [homepage](https://www.robots.ox.ac.uk/~vgg/data/scenetext/) | [shuffle_labels.txt](https://download.openmmlab.com/mmocr/data/mixture/SynthText/shuffle_labels.txt) \| [instances_train.txt](https://download.openmmlab.com/mmocr/data/mixture/SynthText/instances_train.txt) \| [label.lmdb](https://download.openmmlab.com/mmocr/data/mixture/SynthText/label.lmdb) | - | | | SynthText | [homepage](https://www.robots.ox.ac.uk/~vgg/data/scenetext/) | [shuffle_labels.txt](https://download.openmmlab.com/mmocr/data/mixture/SynthText/shuffle_labels.txt) \| [instances_train.txt](https://download.openmmlab.com/mmocr/data/mixture/SynthText/instances_train.txt) \| [label.lmdb](https://download.openmmlab.com/mmocr/data/mixture/SynthText/label.lmdb) | - | |
| SynthAdd | | [SynthText_Add.zip](https://pan.baidu.com/s/1uV0LtoNmcxbO-0YA7Ch4dg) (code:627x) | [label.txt](https://download.openmmlab.com/mmocr/data/mixture/SynthAdd/label.txt) | - | | | SynthAdd | [SynthText_Add.zip](https://pan.baidu.com/s/1uV0LtoNmcxbO-0YA7Ch4dg) (code:627x) | [label.txt](https://download.openmmlab.com/mmocr/data/mixture/SynthAdd/label.txt) | - | |
- For `icdar_2013`: - For `icdar_2013`:
- Step1: Download `Challenge2_Test_Task3_Images.zip` and `Challenge2_Training_Task3_Images_GT.zip` from [homepage](https://rrc.cvc.uab.es/?ch=2&com=downloads) - Step1: Download `Challenge2_Test_Task3_Images.zip` and `Challenge2_Training_Task3_Images_GT.zip` from [homepage](https://rrc.cvc.uab.es/?ch=2&com=downloads)

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docs/getting_started.md
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@ -37,7 +37,7 @@ It will save both the prediction results and visualized images to `${RESULTS_DIR
### Test a Dataset ### Test a Dataset
MMOCR implements **distributed** testing with `MMDistributedDataParallel`. (Please refer to [dataset.md](dataset.md) to prepare your datasets) MMOCR implements **distributed** testing with `MMDistributedDataParallel`. (Please refer to [datasets.md](datasets.md) to prepare your datasets)
#### Test with Single/Multiple GPUs #### Test with Single/Multiple GPUs
@ -78,7 +78,7 @@ You can check [slurm_test.sh](https://github.com/open-mmlab/mmocr/blob/master/to
## Train a Model ## Train a Model
MMOCR implements **distributed** training with `MMDistributedDataParallel`. (Please refer to [dataset.md](dataset.md) to prepare your datasets) MMOCR implements **distributed** training with `MMDistributedDataParallel`. (Please refer to [datasets.md](datasets.md) to prepare your datasets)
All outputs (log files and checkpoints) will be saved to a working directory specified by `work_dir` in the config file. All outputs (log files and checkpoints) will be saved to a working directory specified by `work_dir` in the config file.

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docs/index.rst
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@ -7,8 +7,6 @@ Welcome to MMOCR's documentation!
install.md install.md
getting_started.md getting_started.md
technical_details.md
contributing.md
.. toctree:: .. toctree::
:maxdepth: 2 :maxdepth: 2
@ -23,14 +21,13 @@ Welcome to MMOCR's documentation!
:maxdepth: 2 :maxdepth: 2
:caption: Datasets :caption: Datasets
dataset.md datasets.md
.. toctree:: .. toctree::
:maxdepth: 2 :maxdepth: 2
:caption: Notes :caption: Notes
changelog.md changelog.md
faq.md
.. toctree:: .. toctree::
:caption: API Reference :caption: API Reference

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@ -129,7 +129,7 @@ docker run --gpus all --shm-size=8g -it -v {DATA_DIR}:/mmocr/data mmocr
## Prepare Datasets ## Prepare Datasets
It is recommended to symlink the dataset root to `mmocr/data`. Please refer to [dataset.md](dataset.md) to prepare your datasets. It is recommended to symlink the dataset root to `mmocr/data`. Please refer to [datasets.md](datasets.md) to prepare your datasets.
If your folder structure is different, you may need to change the corresponding paths in config files. If your folder structure is different, you may need to change the corresponding paths in config files.
The `mmocr` folder is organized as follows: The `mmocr` folder is organized as follows:

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docs/stats.py
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@ -85,7 +85,7 @@ modelzoo = f"""
* Number of papers: {len(allpapers)} * Number of papers: {len(allpapers)}
{countstr} {countstr}
For supported datasets, see [datasets overview](dataset.md). For supported datasets, see [datasets overview](datasets.md).
{msglist} {msglist}
""" """