{"id":13543319,"url":"https://github.com/open-mmlab/mmocr","last_synced_at":"2025-05-14T22:06:47.400Z","repository":{"id":37338534,"uuid":"355559187","full_name":"open-mmlab/mmocr","owner":"open-mmlab","description":"OpenMMLab Text Detection, Recognition and Understanding 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align=\"center\"\u003e\n  \u003cimg src=\"resources/mmocr-logo.png\" width=\"500px\"/\u003e\n  \u003cdiv\u003e\u0026nbsp;\u003c/div\u003e\n  \u003cdiv align=\"center\"\u003e\n    \u003cb\u003e\u003cfont size=\"5\"\u003eOpenMMLab website\u003c/font\u003e\u003c/b\u003e\n    \u003csup\u003e\n      \u003ca href=\"https://openmmlab.com\"\u003e\n        \u003ci\u003e\u003cfont size=\"4\"\u003eHOT\u003c/font\u003e\u003c/i\u003e\n      \u003c/a\u003e\n    \u003c/sup\u003e\n    \u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\n    \u003cb\u003e\u003cfont size=\"5\"\u003eOpenMMLab platform\u003c/font\u003e\u003c/b\u003e\n    \u003csup\u003e\n      \u003ca href=\"https://platform.openmmlab.com\"\u003e\n        \u003ci\u003e\u003cfont size=\"4\"\u003eTRY IT OUT\u003c/font\u003e\u003c/i\u003e\n      \u003c/a\u003e\n    \u003c/sup\u003e\n  \u003c/div\u003e\n  \u003cdiv\u003e\u0026nbsp;\u003c/div\u003e\n\n[![build](https://github.com/open-mmlab/mmocr/workflows/build/badge.svg)](https://github.com/open-mmlab/mmocr/actions)\n[![docs](https://readthedocs.org/projects/mmocr/badge/?version=dev-1.x)](https://mmocr.readthedocs.io/en/dev-1.x/?badge=dev-1.x)\n[![codecov](https://codecov.io/gh/open-mmlab/mmocr/branch/main/graph/badge.svg)](https://codecov.io/gh/open-mmlab/mmocr)\n[![license](https://img.shields.io/github/license/open-mmlab/mmocr.svg)](https://github.com/open-mmlab/mmocr/blob/main/LICENSE)\n[![PyPI](https://badge.fury.io/py/mmocr.svg)](https://pypi.org/project/mmocr/)\n[![Average time to resolve an issue](https://isitmaintained.com/badge/resolution/open-mmlab/mmocr.svg)](https://github.com/open-mmlab/mmocr/issues)\n[![Percentage of issues still open](https://isitmaintained.com/badge/open/open-mmlab/mmocr.svg)](https://github.com/open-mmlab/mmocr/issues)\n\u003ca href=\"https://console.tiyaro.ai/explore?q=mmocr\u0026pub=mmocr\"\u003e \u003cimg src=\"https://tiyaro-public-docs.s3.us-west-2.amazonaws.com/assets/try_on_tiyaro_badge.svg\"\u003e\u003c/a\u003e\n\n[📘Documentation](https://mmocr.readthedocs.io/en/dev-1.x/) |\n[🛠️Installation](https://mmocr.readthedocs.io/en/dev-1.x/get_started/install.html) |\n[👀Model Zoo](https://mmocr.readthedocs.io/en/dev-1.x/modelzoo.html) |\n[🆕Update News](https://mmocr.readthedocs.io/en/dev-1.x/notes/changelog.html) |\n[🤔Reporting Issues](https://github.com/open-mmlab/mmocr/issues/new/choose)\n\n\u003c/div\u003e\n\n\u003cdiv align=\"center\"\u003e\n\nEnglish | [简体中文](README_zh-CN.md)\n\n\u003c/div\u003e\n\u003cdiv align=\"center\"\u003e\n  \u003ca href=\"https://openmmlab.medium.com/\" style=\"text-decoration:none;\"\u003e\n    \u003cimg src=\"https://user-images.githubusercontent.com/25839884/219255827-67c1a27f-f8c5-46a9-811d-5e57448c61d1.png\" width=\"3%\" alt=\"\" /\u003e\u003c/a\u003e\n  \u003cimg src=\"https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png\" width=\"3%\" alt=\"\" /\u003e\n  \u003ca href=\"https://discord.gg/raweFPmdzG\" style=\"text-decoration:none;\"\u003e\n    \u003cimg src=\"https://user-images.githubusercontent.com/25839884/218347213-c080267f-cbb6-443e-8532-8e1ed9a58ea9.png\" width=\"3%\" alt=\"\" /\u003e\u003c/a\u003e\n  \u003cimg src=\"https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png\" width=\"3%\" alt=\"\" /\u003e\n  \u003ca href=\"https://twitter.com/OpenMMLab\" style=\"text-decoration:none;\"\u003e\n    \u003cimg src=\"https://user-images.githubusercontent.com/25839884/218346637-d30c8a0f-3eba-4699-8131-512fb06d46db.png\" width=\"3%\" alt=\"\" /\u003e\u003c/a\u003e\n  \u003cimg src=\"https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png\" width=\"3%\" alt=\"\" /\u003e\n  \u003ca href=\"https://www.youtube.com/openmmlab\" style=\"text-decoration:none;\"\u003e\n    \u003cimg src=\"https://user-images.githubusercontent.com/25839884/218346691-ceb2116a-465a-40af-8424-9f30d2348ca9.png\" width=\"3%\" alt=\"\" /\u003e\u003c/a\u003e\n  \u003cimg src=\"https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png\" width=\"3%\" alt=\"\" /\u003e\n  \u003ca href=\"https://space.bilibili.com/1293512903\" style=\"text-decoration:none;\"\u003e\n    \u003cimg src=\"https://user-images.githubusercontent.com/25839884/219026751-d7d14cce-a7c9-4e82-9942-8375fca65b99.png\" width=\"3%\" alt=\"\" /\u003e\u003c/a\u003e\n  \u003cimg src=\"https://user-images.githubusercontent.com/25839884/218346358-56cc8e2f-a2b8-487f-9088-32480cceabcf.png\" width=\"3%\" alt=\"\" /\u003e\n  \u003ca href=\"https://www.zhihu.com/people/openmmlab\" style=\"text-decoration:none;\"\u003e\n    \u003cimg src=\"https://user-images.githubusercontent.com/25839884/219026120-ba71e48b-6e94-4bd4-b4e9-b7d175b5e362.png\" width=\"3%\" alt=\"\" /\u003e\u003c/a\u003e\n\u003c/div\u003e\n\n## Latest Updates\n\n**The default branch is now `main` and the code on the branch has been upgraded to v1.0.0. The old `main` branch (v0.6.3) code now exists on the `0.x` branch.** If you have been using the `main` branch and encounter upgrade issues, please read the [Migration Guide](https://mmocr.readthedocs.io/en/dev-1.x/migration/overview.html) and notes on [Branches](https://mmocr.readthedocs.io/en/dev-1.x/migration/branches.html) .\n\nv1.0.0 was released in 2023-04-06. Major updates from 1.0.0rc6 include:\n\n1. Support for SCUT-CTW1500, SynthText, and MJSynth datasets in Dataset Preparer\n2. Updated FAQ and documentation\n3. Deprecation of file_client_args in favor of backend_args\n4. Added a new MMOCR tutorial notebook\n\nTo know more about the updates in MMOCR 1.0, please refer to [What's New in MMOCR 1.x](https://mmocr.readthedocs.io/en/dev-1.x/migration/news.html), or\nRead [Changelog](https://mmocr.readthedocs.io/en/dev-1.x/notes/changelog.html) for more details!\n\n## Introduction\n\nMMOCR is an open-source toolbox based on PyTorch and mmdetection for text detection, text recognition, and the corresponding downstream tasks including key information extraction. It is part of the [OpenMMLab](https://openmmlab.com/) project.\n\nThe main branch works with **PyTorch 1.6+**.\n\n\u003cdiv align=\"center\"\u003e\n  \u003cimg src=\"https://user-images.githubusercontent.com/24622904/187838618-1fdc61c0-2d46-49f9-8502-976ffdf01f28.png\"/\u003e\n\u003c/div\u003e\n\n### Major Features\n\n- **Comprehensive Pipeline**\n\n  The toolbox supports not only text detection and text recognition, but also their downstream tasks such as key information extraction.\n\n- **Multiple Models**\n\n  The toolbox supports a wide variety of state-of-the-art models for text detection, text recognition and key information extraction.\n\n- **Modular Design**\n\n  The modular design of MMOCR enables users to define their own optimizers, data preprocessors, and model components such as backbones, necks and heads as well as losses. Please refer to [Overview](https://mmocr.readthedocs.io/en/dev-1.x/get_started/overview.html) for how to construct a customized model.\n\n- **Numerous Utilities**\n\n  The toolbox provides a comprehensive set of utilities which can help users assess the performance of models. It includes visualizers which allow visualization of images, ground truths as well as predicted bounding boxes, and a validation tool for evaluating checkpoints during training.  It also includes data converters to demonstrate how to convert your own data to the annotation files which the toolbox supports.\n\n## Installation\n\nMMOCR depends on [PyTorch](https://pytorch.org/), [MMEngine](https://github.com/open-mmlab/mmengine), [MMCV](https://github.com/open-mmlab/mmcv) and [MMDetection](https://github.com/open-mmlab/mmdetection).\nBelow are quick steps for installation.\nPlease refer to [Install Guide](https://mmocr.readthedocs.io/en/dev-1.x/get_started/install.html) for more detailed instruction.\n\n```shell\nconda create -n open-mmlab python=3.8 pytorch=1.10 cudatoolkit=11.3 torchvision -c pytorch -y\nconda activate open-mmlab\npip3 install openmim\ngit clone https://github.com/open-mmlab/mmocr.git\ncd mmocr\nmim install -e .\n```\n\n## Get Started\n\nPlease see [Quick Run](https://mmocr.readthedocs.io/en/dev-1.x/get_started/quick_run.html) for the basic usage of MMOCR.\n\n## [Model Zoo](https://mmocr.readthedocs.io/en/dev-1.x/modelzoo.html)\n\nSupported algorithms:\n\n\u003cdetails open\u003e\n\u003csummary\u003eBackBone\u003c/summary\u003e\n\n- [x] [oCLIP](configs/backbone/oclip/README.md) (ECCV'2022)\n\n\u003c/details\u003e\n\n\u003cdetails open\u003e\n\u003csummary\u003eText Detection\u003c/summary\u003e\n\n- [x] [DBNet](configs/textdet/dbnet/README.md) (AAAI'2020) / [DBNet++](configs/textdet/dbnetpp/README.md) (TPAMI'2022)\n- [x] [Mask R-CNN](configs/textdet/maskrcnn/README.md) (ICCV'2017)\n- [x] [PANet](configs/textdet/panet/README.md) (ICCV'2019)\n- [x] [PSENet](configs/textdet/psenet/README.md) (CVPR'2019)\n- [x] [TextSnake](configs/textdet/textsnake/README.md) (ECCV'2018)\n- [x] [DRRG](configs/textdet/drrg/README.md) (CVPR'2020)\n- [x] [FCENet](configs/textdet/fcenet/README.md) (CVPR'2021)\n\n\u003c/details\u003e\n\n\u003cdetails open\u003e\n\u003csummary\u003eText Recognition\u003c/summary\u003e\n\n- [x] [ABINet](configs/textrecog/abinet/README.md) (CVPR'2021)\n- [x] [ASTER](configs/textrecog/aster/README.md) (TPAMI'2018)\n- [x] [CRNN](configs/textrecog/crnn/README.md) (TPAMI'2016)\n- [x] [MASTER](configs/textrecog/master/README.md) (PR'2021)\n- [x] [NRTR](configs/textrecog/nrtr/README.md) (ICDAR'2019)\n- [x] [RobustScanner](configs/textrecog/robust_scanner/README.md) (ECCV'2020)\n- [x] [SAR](configs/textrecog/sar/README.md) (AAAI'2019)\n- [x] [SATRN](configs/textrecog/satrn/README.md) (CVPR'2020 Workshop on Text and Documents in the Deep Learning Era)\n- [x] [SVTR](configs/textrecog/svtr/README.md) (IJCAI'2022)\n\n\u003c/details\u003e\n\n\u003cdetails open\u003e\n\u003csummary\u003eKey Information Extraction\u003c/summary\u003e\n\n- [x] [SDMG-R](configs/kie/sdmgr/README.md) (ArXiv'2021)\n\n\u003c/details\u003e\n\n\u003cdetails open\u003e\n\u003csummary\u003eText Spotting\u003c/summary\u003e\n\n- [x] [ABCNet](projects/ABCNet/README.md) (CVPR'2020)\n- [x] [ABCNetV2](projects/ABCNet/README_V2.md) (TPAMI'2021)\n- [x] [SPTS](projects/SPTS/README.md) (ACM MM'2022)\n\n\u003c/details\u003e\n\nPlease refer to [model_zoo](https://mmocr.readthedocs.io/en/dev-1.x/modelzoo.html) for more details.\n\n## Projects\n\n[Here](projects/README.md) are some implementations of SOTA models and solutions built on MMOCR, which are supported and maintained by community users. These projects demonstrate the best practices based on MMOCR for research and product development. We welcome and appreciate all the contributions to OpenMMLab ecosystem.\n\n## Contributing\n\nWe appreciate all contributions to improve MMOCR. Please refer to [CONTRIBUTING.md](.github/CONTRIBUTING.md) for the contributing guidelines.\n\n## Acknowledgement\n\nMMOCR is an open-source project that is contributed by researchers and engineers from various colleges and companies. We appreciate all the contributors who implement their methods or add new features, as well as users who give valuable feedbacks.\nWe hope the toolbox and benchmark could serve the growing research community by providing a flexible toolkit to reimplement existing methods and develop their own new OCR methods.\n\n## Citation\n\nIf you find this project useful in your research, please consider cite:\n\n```bibtex\n@article{mmocr2022,\n    title={MMOCR:  A Comprehensive Toolbox for Text Detection, Recognition and Understanding},\n    author={MMOCR Developer Team},\n    howpublished = {\\url{https://github.com/open-mmlab/mmocr}},\n    year={2022}\n}\n```\n\n## License\n\nThis project is released under the [Apache 2.0 license](LICENSE).\n\n## OpenMMLab Family\n\n- [MMEngine](https://github.com/open-mmlab/mmengine): OpenMMLab foundational library for training deep learning models\n- [MMCV](https://github.com/open-mmlab/mmcv): OpenMMLab foundational library for computer vision.\n- [MIM](https://github.com/open-mmlab/mim): MIM installs OpenMMLab packages.\n- [MMClassification](https://github.com/open-mmlab/mmclassification): OpenMMLab image classification toolbox and benchmark.\n- [MMDetection](https://github.com/open-mmlab/mmdetection): OpenMMLab detection toolbox and benchmark.\n- [MMDetection3D](https://github.com/open-mmlab/mmdetection3d): OpenMMLab's next-generation platform for general 3D object detection.\n- [MMRotate](https://github.com/open-mmlab/mmrotate): OpenMMLab rotated object detection toolbox and benchmark.\n- [MMSegmentation](https://github.com/open-mmlab/mmsegmentation): OpenMMLab semantic segmentation toolbox and benchmark.\n- [MMOCR](https://github.com/open-mmlab/mmocr): OpenMMLab text detection, recognition, and understanding toolbox.\n- [MMPose](https://github.com/open-mmlab/mmpose): OpenMMLab pose estimation toolbox and benchmark.\n- [MMHuman3D](https://github.com/open-mmlab/mmhuman3d): OpenMMLab 3D human parametric model toolbox and benchmark.\n- [MMSelfSup](https://github.com/open-mmlab/mmselfsup): OpenMMLab self-supervised learning toolbox and benchmark.\n- [MMRazor](https://github.com/open-mmlab/mmrazor): OpenMMLab model compression toolbox and benchmark.\n- [MMFewShot](https://github.com/open-mmlab/mmfewshot): OpenMMLab fewshot learning toolbox and benchmark.\n- [MMAction2](https://github.com/open-mmlab/mmaction2): OpenMMLab's next-generation action understanding toolbox and benchmark.\n- [MMTracking](https://github.com/open-mmlab/mmtracking): OpenMMLab video perception toolbox and benchmark.\n- [MMFlow](https://github.com/open-mmlab/mmflow): OpenMMLab optical flow toolbox and benchmark.\n- [MMEditing](https://github.com/open-mmlab/mmediting): OpenMMLab image and video editing toolbox.\n- [MMGeneration](https://github.com/open-mmlab/mmgeneration): OpenMMLab image and video generative models toolbox.\n- [MMDeploy](https://github.com/open-mmlab/mmdeploy): OpenMMLab model deployment framework.\n\n## Welcome to the OpenMMLab community\n\nScan the QR code below to follow the OpenMMLab team's [**Zhihu Official Account**](https://www.zhihu.com/people/openmmlab) and join the OpenMMLab team's [**QQ Group**](https://jq.qq.com/?_wv=1027\u0026k=aCvMxdr3), or join the official communication WeChat group by adding the WeChat, or join our [**Slack**](https://join.slack.com/t/mmocrworkspace/shared_invite/zt-1ifqhfla8-yKnLO_aKhVA2h71OrK8GZw)\n\n\u003cdiv align=\"center\"\u003e\n\u003cimg src=\"https://raw.githubusercontent.com/open-mmlab/mmcv/master/docs/en/_static/zhihu_qrcode.jpg\" height=\"400\" /\u003e  \u003cimg src=\"https://raw.githubusercontent.com/open-mmlab/mmcv/master/docs/en/_static/qq_group_qrcode.jpg\" height=\"400\" /\u003e  \u003cimg src=\"https://raw.githubusercontent.com/open-mmlab/mmcv/master/docs/en/_static/wechat_qrcode.jpg\" height=\"400\" /\u003e\n\u003c/div\u003e\n\nWe will provide you with the OpenMMLab community\n\n- 📢 share the latest core technologies of AI frameworks\n- 💻 Explaining PyTorch common module source Code\n- 📰 News related to the release of OpenMMLab\n- 🚀 Introduction of cutting-edge algorithms developed by OpenMMLab\n  🏃 Get the more efficient answer and feedback\n- 🔥 Provide a platform for communication with developers from all walks of life\n\nThe OpenMMLab community looks forward to your participation! 👬\n","funding_links":[],"categories":["Optical Character Recognition Engines and Frameworks","Computer Vision","Python","Repos","Tools \u0026 Libraries"],"sub_categories":["CTPN [paper:2016](https://arxiv.org/pdf/1609.03605.pdf)","General Purpose CV","Open Source OCR Systems"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fopen-mmlab%2Fmmocr","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fopen-mmlab%2Fmmocr","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fopen-mmlab%2Fmmocr/lists"}