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Fix readthedocs generation (#14)
* Fix readthedocs * Fix doc * md format
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@ -32,6 +32,6 @@
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## Results and models
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## Results and models
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| methods | | Regular Text | | | | Irregular Text | | download |
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| methods | | Regular Text | | | | Irregular Text | | download |
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| :-----: | :----: | :----------: | :--: | :-: | :--: | :------------: | :--: | :------------------: |
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| :-----: | :----: | :----------: | :---: | :---: | :---: | :------------: | :---: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
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| methods | IIIT5K | SVT | IC13 | | IC15 | SVTP | CT80 |
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| methods | IIIT5K | SVT | IC13 | | IC15 | SVTP | CT80 |
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| CRNN | 80.5 | 81.5 | 86.5 | | - | - | - | [model](https://download.openmmlab.com/mmocr/textrecog/crnn/crnn_academic-a723a1c5.pth) \| [log](https://download.openmmlab.com/mmocr/textrecog/crnn/20210326_111035.log.json) |
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| CRNN | 80.5 | 81.5 | 86.5 | | - | - | - | [model](https://download.openmmlab.com/mmocr/textrecog/crnn/crnn_academic-a723a1c5.pth) \| [log](https://download.openmmlab.com/mmocr/textrecog/crnn/20210326_111035.log.json) |
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## Results and Models
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## Results and Models
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| Methods | GPUs | | Regular Text | | | | Irregular Text | | download |
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| Methods | GPUs | | Regular Text | | | | Irregular Text | | download |
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| :-----------------------------------------------------------------: | :---------: | :----: | :----------: | :--: | :-: | :--: | :------------: | :--: | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
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| :-----------------------------------------------------------------------------: | :---: | :----: | :----------: | :---: | :---: | :---: | :------------: | :---: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
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| | | IIIT5K | SVT | IC13 | | IC15 | SVTP | CT80 |
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| | | IIIT5K | SVT | IC13 | | IC15 | SVTP | CT80 |
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| [RobustScanner](configs/textrecog/robust_scanner/robustscanner_r31_academic.py) | 16 | 95.1 | 89.2 | 93.1 | | 77.8 | 80.3 | 90.3 | [model](https://download.openmmlab.com/mmocr/textrecog/robustscanner/robustscanner_r31_academic-5f05874f.pth) \| [log](https://download.openmmlab.com/mmocr/textrecog/robustscanner/20210401_170932.log.json) |
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| [RobustScanner](configs/textrecog/robust_scanner/robustscanner_r31_academic.py) | 16 | 95.1 | 89.2 | 93.1 | | 77.8 | 80.3 | 90.3 | [model](https://download.openmmlab.com/mmocr/textrecog/robustscanner/robustscanner_r31_academic-5f05874f.pth) \| [log](https://download.openmmlab.com/mmocr/textrecog/robustscanner/20210401_170932.log.json) |
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## Results and Models
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## Results and Models
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| Methods | Backbone | Decoder | | Regular Text | | | | Irregular Text | | download |
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| Methods | Backbone | Decoder | | Regular Text | | | | Irregular Text | | download |
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| :-----------------------------------------------------------------: | :---------: | :------------------: | :----: | :----------: | :--: | :-: | :--: | :------------: | :--: | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
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| :-----------------------------------------------------------------: | :---------: | :------------------: | :----: | :----------: | :---: | :---: | :---: | :------------: | :---: | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
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| | | | IIIT5K | SVT | IC13 | | IC15 | SVTP | CT80 |
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| | | | IIIT5K | SVT | IC13 | | IC15 | SVTP | CT80 |
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| [SAR](/configs/textrecog/sar/sar_r31_parallel_decoder_academic.py) | R31-1/8-1/4 | ParallelSARDecoder | 95.0 | 89.6 | 93.7 | | 79.0 | 82.2 | 88.9 | [model](https://download.openmmlab.com/mmocr/textrecog/sar/sar_r31_parallel_decoder_academic-dba3a4a3.pth) \| [log](https://download.openmmlab.com/mmocr/textrecog/sar/20210327_154129.log.json) |
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| [SAR](/configs/textrecog/sar/sar_r31_parallel_decoder_academic.py) | R31-1/8-1/4 | ParallelSARDecoder | 95.0 | 89.6 | 93.7 | | 79.0 | 82.2 | 88.9 | [model](https://download.openmmlab.com/mmocr/textrecog/sar/sar_r31_parallel_decoder_academic-dba3a4a3.pth) \| [log](https://download.openmmlab.com/mmocr/textrecog/sar/20210327_154129.log.json) |
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| [SAR](configs/textrecog/sar/sar_r31_sequential_decoder_academic.py) | R31-1/8-1/4 | SequentialSARDecoder | 95.2 | 88.7 | 92.4 | | 78.2 | 81.9 | 89.6 | [model](https://download.openmmlab.com/mmocr/textrecog/sar/sar_r31_sequential_decoder_academic-d06c9a8e.pth) \| [log](https://download.openmmlab.com/mmocr/textrecog/sar/20210330_105728.log.json) |
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| [SAR](configs/textrecog/sar/sar_r31_sequential_decoder_academic.py) | R31-1/8-1/4 | SequentialSARDecoder | 95.2 | 88.7 | 92.4 | | 78.2 | 81.9 | 89.6 | [model](https://download.openmmlab.com/mmocr/textrecog/sar/sar_r31_sequential_decoder_academic-d06c9a8e.pth) \| [log](https://download.openmmlab.com/mmocr/textrecog/sar/20210330_105728.log.json) |
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## Results and Models
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## Results and Models
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|Backbone|Neck|Head|||Regular Text|||Irregular Text|download
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| Backbone | Neck | Head | | | Regular Text | | | Irregular Text | download |
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| :-------------: | :-----: | :-----: | :------: | :-----: | :----: | :-----: | :-----: | :-----: | :-----: |
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| :------: | :----: | :---: | :---: | :----: | :----------: | :---: | :---: | :------------: | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
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| | | | | IIIT5K | SVT | IC13 | | CT80 |
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| | | | | IIIT5K | SVT | IC13 | | CT80 |
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| R31-1/16 | FPNOCR | 1x | | 90.9 | 81.8 | 90.7 | | 80.9 | [model](https://download.openmmlab.com/mmocr/textrecog/seg/seg_r31_1by16_fpnocr_academic-72235b11.pth) \| [log](https://download.openmmlab.com/mmocr/textrecog/seg/20210325_112835.log.json) |
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| R31-1/16 | FPNOCR | 1x | | 90.9 | 81.8 | 90.7 | | 80.9 | [model](https://download.openmmlab.com/mmocr/textrecog/seg/seg_r31_1by16_fpnocr_academic-72235b11.pth) \| [log](https://download.openmmlab.com/mmocr/textrecog/seg/20210325_112835.log.json) |
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# Datasets Preparation
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# Datasets Preparation
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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.
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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.
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<!-- TOC -->
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- [Datasets Preparation](#datasets-preparation)
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- [Text Detection](#text-detection)
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- [Text Recognition](#text-recognition)
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- [Key Information Extraction](#key-information-extraction)
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<!-- /TOC -->
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## Text Detection
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## Text Detection
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**The structure of the text detection dataset directory is organized as follows.**
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```
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The structure of the text detection dataset directory is organized as follows.
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```text
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├── ctw1500
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├── ctw1500
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│ ├── imgs
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│ ├── imgs
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│ ├── instances_test.json
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│ ├── instances_test.json
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│ ├── imgs
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│ ├── imgs
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│ └── instances_training.lmdb
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│ └── instances_training.lmdb
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```
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```
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| Dataset | | Images | | | Annotation Files | | | Note | |
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| Dataset | | Images | | | Annotation Files | | | Note | |
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|:---------:|:-:|:--------------------------:|:-:|:--------------------------------------------:|:---------------------------------------:|:----------------------------------------:|:-:|:----:|---|
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| :-------: | :---: | :------------------------------------------------------------: | :----------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------: | :-------------------------------------: | :--------------------------------------------------------------------------------------------: | :---: | :---: | --- |
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| | | | | training | validation | testing | | | |
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| | | | | training | validation | testing | | | |
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| 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) | | | |
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| 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) | | | |
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| 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) | | | |
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| 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) | | | |
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@ -32,6 +43,7 @@ This page lists the datasets which are commonly used in text detection, text rec
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- Step1: Download `ch4_training_images.zip` and `ch4_test_images.zip` from [homepage](https://rrc.cvc.uab.es/?ch=4&com=downloads)
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- Step1: Download `ch4_training_images.zip` and `ch4_test_images.zip` from [homepage](https://rrc.cvc.uab.es/?ch=4&com=downloads)
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- Step2: Download [instances_training.json](https://download.openmmlab.com/mmocr/data/icdar2015/instances_training.json) and [instances_test.json](https://download.openmmlab.com/mmocr/data/icdar2015/instances_test.json)
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- Step2: Download [instances_training.json](https://download.openmmlab.com/mmocr/data/icdar2015/instances_training.json) and [instances_test.json](https://download.openmmlab.com/mmocr/data/icdar2015/instances_test.json)
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- Step3:
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- Step3:
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```bash
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```bash
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mkdir icdar2015 && cd icdar2015
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mkdir icdar2015 && cd icdar2015
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mv /path/to/instances_training.json .
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mv /path/to/instances_training.json .
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ln -s /path/to/ch4_training_images training
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ln -s /path/to/ch4_training_images training
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ln -s /path/to/ch4_test_images test
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ln -s /path/to/ch4_test_images test
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```
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```
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- For `icdar2017`:
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- For `icdar2017`:
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- To avoid the effect of rotation when load `jpg` with opencv, We provide re-saved `png` format image in [renamed_images](https://download.openmmlab.com/mmocr/data/icdar2017/renamed_imgs.tar). You can copy these images to `imgs`.
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- To avoid the effect of rotation when load `jpg` with opencv, We provide re-saved `png` format image in [renamed_images](https://download.openmmlab.com/mmocr/data/icdar2017/renamed_imgs.tar). You can copy these images to `imgs`.
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## Text Recognition
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## Text Recognition
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**The structure of the text recognition dataset directory is organized as follows.**
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**The structure of the text recognition dataset directory is organized as follows.**
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```
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```text
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├── mixture
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├── mixture
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│ ├── coco_text
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│ ├── coco_text
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│ │ ├── train_label.txt
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│ │ ├── train_label.txt
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│ ├── SynthAdd
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│ ├── SynthAdd
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│ │ ├── label.txt
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│ │ ├── label.txt
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│ │ ├── SynthText_Add
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│ │ ├── SynthText_Add
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```
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```
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| Dataset | | images | annotation file | annotation file | Note |
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| Dataset | | images | annotation file | annotation file | Note |
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|:----------:|:-:|:---------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------:|:----:|
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| :--------: | :---: | :-----------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------: | :---: |
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| | | | training | test | |
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| | | | training | test | |
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| 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) | - | |
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| 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) | - | |
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| 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) | - | |
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| 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) | - | |
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- For `coco_text`:
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- For `coco_text`:
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- Step1: Download from [homepage](https://rrc.cvc.uab.es/?ch=5&com=downloads)
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- Step1: Download from [homepage](https://rrc.cvc.uab.es/?ch=5&com=downloads)
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- Step2: Download [train_label.txt](https://download.openmmlab.com/mmocr/data/mixture/coco_text/train_label.txt)
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- Step2: Download [train_label.txt](https://download.openmmlab.com/mmocr/data/mixture/coco_text/train_label.txt)
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- For `Syn90k`:
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- For `Syn90k`:
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- Step1: Download `mjsynth.tar.gz` from [homepage](https://www.robots.ox.ac.uk/~vgg/data/text/)
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- Step1: Download `mjsynth.tar.gz` from [homepage](https://www.robots.ox.ac.uk/~vgg/data/text/)
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- Step2: Download [shuffle_labels.txt](https://download.openmmlab.com/mmocr/data/mixture/Synth90k/shuffle_labels.txt)
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- Step2: Download [shuffle_labels.txt](https://download.openmmlab.com/mmocr/data/mixture/Synth90k/shuffle_labels.txt)
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- Step3:
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- Step3:
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```bash
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```bash
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mkdir Syn90k && cd Syn90k
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mkdir Syn90k && cd Syn90k
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ln -s /path/to/Syn90k Syn90k
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ln -s /path/to/Syn90k Syn90k
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```
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```
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- For `SynthText`:
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- For `SynthText`:
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- Step1: Download `SynthText.zip` from [homepage](https://www.robots.ox.ac.uk/~vgg/data/scenetext/)
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- Step1: Download `SynthText.zip` from [homepage](https://www.robots.ox.ac.uk/~vgg/data/scenetext/)
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- Step2: Download [shuffle_labels.txt](https://download.openmmlab.com/mmocr/data/mixture/SynthText/shuffle_labels.txt)
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- Step2: Download [shuffle_labels.txt](https://download.openmmlab.com/mmocr/data/mixture/SynthText/shuffle_labels.txt)
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- Step3: Download [instances_train.txt](https://download.openmmlab.com/mmocr/data/mixture/SynthText/instances_train.txt)
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- Step3: Download [instances_train.txt](https://download.openmmlab.com/mmocr/data/mixture/SynthText/instances_train.txt)
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- Step4:
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- Step4:
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```bash
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```bash
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unzip SynthText.zip
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unzip SynthText.zip
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ln -s /path/to/SynthText SynthText
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ln -s /path/to/SynthText SynthText
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```
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```
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- For `SynthAdd`:
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- For `SynthAdd`:
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- Step1: Download `SynthText_Add.zip` from [SynthAdd](https://pan.baidu.com/s/1uV0LtoNmcxbO-0YA7Ch4dg) (code:627x))
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- Step1: Download `SynthText_Add.zip` from [SynthAdd](https://pan.baidu.com/s/1uV0LtoNmcxbO-0YA7Ch4dg) (code:627x))
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- Step2: Download [label.txt](https://download.openmmlab.com/mmocr/data/mixture/SynthAdd/label.txt)
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- Step2: Download [label.txt](https://download.openmmlab.com/mmocr/data/mixture/SynthAdd/label.txt)
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- Step3:
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- Step3:
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```bash
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```bash
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mkdir SynthAdd && cd SynthAdd
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mkdir SynthAdd && cd SynthAdd
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```
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```
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## Key Information Extraction
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## Key Information Extraction
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**The structure of the key information extraction dataset directory is organized as follows.**
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```
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The structure of the key information extraction dataset directory is organized as follows.
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```text
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└── wildreceipt
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└── wildreceipt
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├── anno_files
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├── anno_files
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├── class_list.txt
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├── class_list.txt
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├── test.txt
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├── test.txt
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└── train.txt
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└── train.txt
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```
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```
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- Download [wildreceipt.tar](https://download.openmmlab.com/mmocr/data/wildreceipt.tar)
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- Download [wildreceipt.tar](https://download.openmmlab.com/mmocr/data/wildreceipt.tar)
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imgaug
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kwarray
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lmdb
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matplotlib
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mmcv
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mmcv
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numpy
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Pillow<=6.2.2
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Polygon3
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pyclipper
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pycocotools
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python-Levenshtein
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scikit-image
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scipy
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shapely
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skimage
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titlecase
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torch
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torch
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torchvision
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torchvision
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