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https://github.com/open-mmlab/ecosystem


https://github.com/open-mmlab/ecosystem

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README

        

# Ecosystem

English | [简体中文](/README_zh-CN.md)

This project is used to collect the information of all open-source projects built with the OpenMMLab projects. The collected projects will be displayed in the official [OpenMMLab Ecosystem Page](https://openmmlab.com/ecosystem).

## File Structure

The data collected in this repo is used for internal analysis and homepage display. The repo has the following file structure:

```python
ecosystem
|-----.pre-commit-config.yaml # configuration of the pre-commit hooks
|-----LICENSE # license of the project
|-----projects_index.yaml # store the detailed information of each project
|-----README.md # readme file
```

## How to Contribute

We appreciate all contributions to add new projects into OpenMMLab ecosystem.

### Workflow

1. fork and pull the latest OpenMMLab repository (ecosystem)
2. checkout a new branch (do not use master branch for PRs)
3. commit your changes
4. create a PR

### Add New Project into YAML

If you want to add one project into the ecosystem, please edit the `project_index.yaml` and add the related information of the specific project.

The following keys are required to :

- `repo_url`: Github link of the project
- `paper_url`: Paper link of the project(Only add one if have > 1 papers, use `""` if no paper)
- `type`: Type of the ecosystem projects(Choose **one** from Type Table)
- `mmrepos`: Which OpenMMLab projects have been adopted in this project(Choose **one or more** from the MMRepos Table, please pay attention to capitalization)
- `tags`: Tags of this project(\<= 5 item)
- `summary`: One sentence summary of the project(English and Chinese)

Please add the information of the specific project with the following example:

```yaml
- repo_url: https://github.com/NVlabs/FAN # repo url
paper_url: https://arxiv.org/abs/2204.12451 # paper url
type: Official Implementation # type of the projects
mmrepos: # used projects of OpenMMLab
- MMDetection
- MMSegmentation
tags: # tags of this projects
- ICML
- Vision Transformer
summary: # Engish/Chinese summary of this projects with one sentence
zh: Official PyTorch implementation of Fully Attentional Networks
en: 基于PyTorch的Fully Attentional Networks官方实现
```

### Validity Check

We use [pre-commit hook](https://pre-commit.com/) that checks and formats for `trailing whitespaces`, `check-yaml`, and use our [openmmlab pre-commit hook](https://github.com/open-mmlab/pre-commit-hooks) for `check-ecosystem-validity`.
The config for a pre-commit hook is stored in [.pre-commit-config](https://github.com/open-mmlab/ecosystem/blob/master/.pre-commit-config.yaml).

After you clone the repository, you will need to install initialize pre-commit hook.

```shell
pip install -U pre-commit
```

From the repository folder

```shell
pre-commit install
```

After this on every commit check code linters and formatter will be enforced.

```{important}
Before you create a PR, make sure that your code lints and is formatted by yapf.
```

### Type Table


Chinese
English
含义
Meaning


官方实现
Official Implementation
论文的官方实现
Official Implementation of the Research Work


第三方实现
Community Implementation
论文的第三方实现
Community Implementation of the Research Work


比赛代码
Competition
比赛代码
Open-source Code of the Competition


算法框架
Library
在 OpenMMLab 之上开发的第三方代码库
Algorithm Library Built on OpenMMLab


服务
Service
第三方服务项目,例如 wandb
Service Project, e.g., wandb


教程
Tutorial  
基于OpenMMLab开发的教程
Tutorial Built on OpenMMLab


示例
Demo
基于OpenMMLab设计的Demo
Demo Built on OpenMMLab


其他
Others
不在以上分类中的其他项目
Projects not in the above Types

### MMRepos

- [MMCV](https://github.com/open-mmlab/mmcv): OpenMMLab foundational library for computer vision.
- [MMClassification](https://github.com/open-mmlab/mmclassification): OpenMMLab image classification toolbox and benchmark.
- [MMDetection](https://github.com/open-mmlab/mmdetection): OpenMMLab detection toolbox and benchmark.
- [MMDetection3D](https://github.com/open-mmlab/mmdetection3d): OpenMMLab's next-generation platform for general 3D object detection.
- [MMRotate](https://github.com/open-mmlab/mmrotate): OpenMMLab rotated object detection toolbox and benchmark.
- [MMSegmentation](https://github.com/open-mmlab/mmsegmentation): OpenMMLab semantic segmentation toolbox and benchmark.
- [MMOCR](https://github.com/open-mmlab/mmocr): OpenMMLab text detection, recognition, and understanding toolbox.
- [MMPose](https://github.com/open-mmlab/mmpose): OpenMMLab pose estimation toolbox and benchmark.
- [MMHuman3D](https://github.com/open-mmlab/mmhuman3d): OpenMMLab 3D human parametric model toolbox and benchmark.
- [MMSelfSup](https://github.com/open-mmlab/mmselfsup): OpenMMLab self-supervised learning toolbox and benchmark.
- [MMRazor](https://github.com/open-mmlab/mmrazor): OpenMMLab model compression toolbox and benchmark.
- [MMFewShot](https://github.com/open-mmlab/mmfewshot): OpenMMLab fewshot learning toolbox and benchmark.
- [MMAction2](https://github.com/open-mmlab/mmaction2): OpenMMLab's next-generation action understanding toolbox and benchmark.
- [MMTracking](https://github.com/open-mmlab/mmtracking): OpenMMLab video perception toolbox and benchmark.
- [MMFlow](https://github.com/open-mmlab/mmflow): OpenMMLab optical flow toolbox and benchmark.
- [MMEditing](https://github.com/open-mmlab/mmediting): OpenMMLab image and video editing toolbox.
- [MMGeneration](https://github.com/open-mmlab/mmgeneration): OpenMMLab image and video generative models toolbox.
- [MMDeploy](https://github.com/open-mmlab/mmdeploy): OpenMMLab model deployment framework.

## License

This project is released under the [Apache 2.0 license](LICENSE).