docs: make Chinese README the default

2026-07-13 10:42:43 +00:00
parent 492b51264f
commit a1fe9b0212
1 changed files with 119 additions and 119 deletions
@@ -1,5 +1,11 @@
+<!-- WEHUB_ZH_README -->
+> [!NOTE]
+> 本文档由 WeHub 基于上游 README 翻译整理，属于社区翻译，非官方中文文档。  
+> [English](./README.en.md) · [原始项目](https://github.com/cvat-ai/cvat) · [上游 README](https://github.com/cvat-ai/cvat/blob/HEAD/README.md)  
+> 原作者、版权与许可证归属以原始项目及本仓库 LICENSE 文件为准。
+
 [![CVAT Community header](site/content/en/images/cvat_github_header.webp)](https://app.cvat.ai)
-# CVAT: Computer Vision Annotation Tool
+# CVAT：计算机视觉标注工具（Computer Vision Annotation Tool）

 [![Release][release-img]][release-url]
 [![GitHub stars][stars-img]][stars-url]
@@ -20,61 +26,61 @@
 [Academy](https://www.cvat.ai/resources/academy) ·
 [Blog](https://www.cvat.ai/resources/blog)

-## What is CVAT Community?
+## 什么是 CVAT Community？

-**CVAT Community** is the free, self-hosted open-source edition of [CVAT](https://www.cvat.ai/) — one of
-the most widely used data annotation platforms for building high-quality visual datasets for
-computer vision and visual AI.
-Since 2018, CVAT has become one of the best-known data annotation tools in computer vision, with a
-large open-source community, millions of Docker pulls, and broad adoption across research and
-production AI teams.
+**CVAT Community** 是 [CVAT](https://www.cvat.ai/) 的免费、可自托管开源版本，也是
+面向计算机视觉与视觉 AI 构建高质量视觉数据集时
+最广泛使用的数据标注平台之一。
+自 2018 年以来，CVAT 已成为计算机视觉领域最知名的数据标注工具之一，拥有
+庞大的开源社区、数百万次 Docker 拉取，并在科研与
+生产 AI 团队中得到广泛采用。

-CVAT Community supports image, video, and 3D annotation, dataset management, team collaboration, cloud storage
-integration, developer-friendly SDKs and APIs, and gives your team full control over your data
-and annotation infrastructure.
-The platform serves as the foundation of
-[CVAT Online](https://www.cvat.ai/pricing/cvat-online) and
-[CVAT Enterprise](https://www.cvat.ai/enterprise), and is actively maintained by the CVAT engineering team.
+CVAT Community 支持图像、视频和 3D 标注、数据集管理、团队协作、云存储
+集成、对开发者友好的 SDK 与 API，让你的团队完全掌控数据
+与标注基础设施。
+该平台是
+[CVAT Online](https://www.cvat.ai/pricing/cvat-online) 与
+[CVAT Enterprise](https://www.cvat.ai/enterprise), 的基础，并由 CVAT 工程团队积极维护。

-Why teams choose CVAT Community:
+团队为何选择 CVAT Community：

- **Own your data:** Run entirely within your own infrastructure. No data leaves your environment.
- **AI-powered annotation:** Connect your own ML models for detection, segmentation, and tracking to speed up labeling.
- **Team collaboration:** Multi-user and multi-organization support with roles, task assignments,
-  and review workflows.
- **MIT-licensed core:** Use, modify, and distribute CVAT Community under the permissive MIT License. Some serverless
-assets and dependencies may have separate licenses.
- **Production-grade:** The foundation of all CVAT commercial products — battle-tested at scale.
- **True open-source:** Transparent development, active community, on GitHub since 2018.
+- **掌控你的数据：** 完全在你的自有基础设施中运行。数据不会离开你的环境。
+- **AI 驱动的标注：** 接入你自己的 ML 模型，用于检测、分割和跟踪，以加快标注速度。
+- **团队协作：** 支持多用户与多组织，提供角色、任务分配
+  与审核工作流。
+- **MIT 许可的核心：** 在宽松的 MIT License 下使用、修改和分发 CVAT Community。部分 serverless
+  资产与依赖可能适用单独许可证。
+- **生产级：** 所有 CVAT 商业产品的基础——经大规模实战检验。
+- **真正的开源：** 开发过程透明、社区活跃，自 2018 年起托管于 GitHub。

-This repository contains the source code and deployment assets for CVAT Community.
+本仓库包含 CVAT Community 的源代码与部署资源。

-For a fully managed setup, annotation services, or enterprise features, see
+如需全托管部署、标注服务或企业级功能，请参阅
 [CVAT Online](https://www.cvat.ai/pricing/cvat-online),
-[CVAT Enterprise](https://www.cvat.ai/enterprise) and
+[CVAT Enterprise](https://www.cvat.ai/enterprise) 与
 [CVAT Labeling Services](https://www.cvat.ai/annotation-services).

-## Getting Started
+## 快速开始

-> 💡 Want to explore CVAT before deploying anything?
-> **[Try CVAT Online (Free plan)](https://app.cvat.ai)** directly in your browser.
-> Feature availability and usage limits vary by plan; see
-> [CVAT Online pricing](https://www.cvat.ai/pricing/cvat-online) for details.
+> 💡 想在部署任何东西之前先体验 CVAT 吗？
+> **[免费试用 CVAT Online](https://app.cvat.ai)**，直接在浏览器中使用。
+> 功能可用性与使用限制因套餐而异；详见
+> [CVAT Online 定价](https://www.cvat.ai/pricing/cvat-online)。

-### Installation
+### 安装

-**Prerequisites:**
+**前置条件：**

 - [Docker Engine](https://docs.docker.com/engine/install/)
 - [Docker Compose](https://docs.docker.com/compose/install/)
 - [Git](https://git-scm.com/)

-> 💡 CVAT is primarily tested with Chromium-based browsers (Google Chrome, Microsoft Edge).
-> Firefox may work with some caveats; Safari/WebKit is not supported.
+> 💡 CVAT 主要在基于 Chromium 的浏览器（Google Chrome、Microsoft Edge）上测试。
+> Firefox 可能可用，但存在一些限制；不支持 Safari/WebKit。

-**1. Start the default stack**
+**1. 启动默认技术栈**

-Clone the repository and launch the services.
+克隆仓库并启动服务。

 ```bash
 git clone https://github.com/cvat-ai/cvat
@@ -86,69 +92,68 @@ cd cvat
 docker compose up -d
 ```

-**2. Create an admin account**
+**2. 创建管理员账户**

 ```bash
 docker exec -it cvat_server bash -ic 'python3 ~/manage.py createsuperuser'
 ```

-See the [Installation Guide](https://docs.cvat.ai/docs/administration/community/basics/installation/) for full
-instructions and OS-specific setup.
+完整说明与各操作系统专属设置请参阅 [安装指南](https://docs.cvat.ai/docs/administration/community/basics/installation/)。

-**3. Sign in and start labeling**
+**3. 登录并开始标注**

- Open [http://localhost:8080](http://localhost:8080) (or your `CVAT_HOST`) in your browser.
- Log in with your superuser account.
- Create a project or task, upload your data (images, videos, or point clouds), and define labels to start annotating.
+- 在浏览器中打开 [http://localhost:8080](http://localhost:8080)（或你的 `CVAT_HOST`）。
+- 使用超级用户账户登录。
+- 创建项目或任务，上传数据（图像、视频或点云），并定义标签以开始标注。

-Learn more about annotation tools and workflows in the [CVAT Documentation](https://docs.cvat.ai/docs/) or
-take our free course – [CVAT Academy](https://www.cvat.ai/resources/academy).
+在 [CVAT 文档](https://docs.cvat.ai/docs/) 中了解更多标注工具与工作流，或
+参加我们的免费课程——[CVAT Academy](https://www.cvat.ai/resources/academy).

-_For alternative deployments (AWS, Kubernetes, external PostgreSQL, backups, upgrades), see the [Deployment Guides](https://docs.cvat.ai/docs/administration/community/advanced/)._
+_如需其他部署方式（AWS、Kubernetes、外部 PostgreSQL、备份、升级），请参阅 [部署指南](https://docs.cvat.ai/docs/administration/community/advanced/).__

-## Key Capabilities
+## 核心能力

- **[Manual & Auto-labeling](https://docs.cvat.ai/docs/annotation/manual-annotation/):** Annotate images, videos, and
-  3D point clouds with bounding boxes, polygons, masks, keypoints, cuboids, tags, and more. Speed up labeling
-  by connecting your own models for automatic annotation.
- **[Task Management](https://docs.cvat.ai/docs/workspace/):** Organize datasets into projects, split them into tasks
-  and jobs, assign work to annotators, and track progress in real time.
- **[Collaboration](https://docs.cvat.ai/docs/account_management/user-roles/):** Create organizations, invite teammates,
-  assign roles, and collaborate on annotations with comments and issues.
- **[Quality Control](https://docs.cvat.ai/docs/qa-analytics/manual-qa/):** Review annotations, flag issues, compare
-  results across annotators with consensus, and run Ground Truth and Honeypot checks through the server API.
- **[Analytics](https://docs.cvat.ai/docs/administration/community/advanced/analytics/):** Monitor user activity,
-  working time by job, events, and server logs with Grafana dashboards.
- **[Data Ops & Integrations](https://docs.cvat.ai/docs/dataset_management/export-datasets/):** Export/import in 20+
-  formats (COCO, YOLO, Pascal VOC, KITTI, etc.), connect to cloud storage (S3, Azure, Google Cloud), and automate
-  via REST API and Python SDK.
+- **[手动与自动标注](https://docs.cvat.ai/docs/annotation/manual-annotation/):** 对图像、视频和
+  3D 点云进行边界框、多边形、掩码、关键点、立方体、标签等标注。接入你自己的模型进行自动标注，
+  以加快标注速度。
+- **[任务管理](https://docs.cvat.ai/docs/workspace/):** 将数据集组织为项目，拆分为任务
+  与作业，分配给标注员，并实时跟踪进度。
+- **[协作](https://docs.cvat.ai/docs/account_management/user-roles/):** 创建组织、邀请队友、
+  分配角色，并通过评论与 issue 协作完成标注。
+- **[质量控制](https://docs.cvat.ai/docs/qa-analytics/manual-qa/):** 审核标注、标记问题，通过共识（consensus）比较
+  不同标注员的结果，并通过服务器 API 运行 Ground Truth 与 Honeypot 检查。
+- **[分析](https://docs.cvat.ai/docs/administration/community/advanced/analytics/):** 通过 Grafana 仪表板监控用户活动、
+  各作业工时、事件与服务器日志。
+- **[数据运维与集成](https://docs.cvat.ai/docs/dataset_management/export-datasets/):** 支持 20+
+  种格式导入/导出（COCO、YOLO、Pascal VOC、KITTI 等），连接云存储（S3、Azure、Google Cloud），并通过
+  REST API 与 Python SDK 实现自动化。

-Advanced capabilities such as advanced project analytics, quality control UI, built-in auto-labeling with SAM 2
- and SAM 3, AI agents, SSO, and more are available in [CVAT Online](https://www.cvat.ai/pricing/cvat-online)
- paid plans (Solo, Team) and [CVAT Enterprise](https://www.cvat.ai/enterprise).
+高级项目分析、质量控制 UI、内置 SAM 2
+ 与 SAM 3 自动标注、AI agents、SSO 等高级能力可在 [CVAT Online](https://www.cvat.ai/pricing/cvat-online)
+ 付费套餐（Solo、Team）与 [CVAT Enterprise](https://www.cvat.ai/enterprise). 中获取。

-## Developer Tools
+## 开发者工具

-CVAT is designed for automation. Beyond the Web UI, you can integrate it into your pipelines using:
+CVAT 面向自动化而设计。除 Web UI 外，你还可以通过以下方式将其集成到流水线中：

- [Python SDK](https://docs.cvat.ai/docs/api_sdk/sdk/): install with `pip install cvat-sdk` and automate task creation,
-uploads, and exports from Python.
- [Command line tool](https://docs.cvat.ai/docs/api_sdk/cli/): install with `pip install cvat-cli`
-and script common CVAT workflows from the terminal.
- [REST API](https://docs.cvat.ai/docs/api_sdk/api/): full programmatic control over CVAT.
+- [Python SDK](https://docs.cvat.ai/docs/api_sdk/sdk/): 使用 `pip install cvat-sdk` 安装，从 Python 自动化创建任务、
+  上传与导出。
+- [命令行工具](https://docs.cvat.ai/docs/api_sdk/cli/): 使用 `pip install cvat-cli`
+  安装，在终端中编写常见 CVAT 工作流脚本。
+- [REST API](https://docs.cvat.ai/docs/api_sdk/api/): 对 CVAT 进行完整的程序化控制。

-## Data and Formats
+## 数据与格式

-CVAT Community supports image, video, and 3D (point cloud) annotation workflows. You can move data in and out using 20+
-industry-standard formats: CVAT (XML), COCO (JSON), YOLO (TXT), Ultralytics YOLO (TXT/YAML), Pascal VOC (XML),
-KITTI (TXT), MOT (TXT), and more.
+CVAT Community 支持图像、视频和 3D（点云）标注工作流。你可以使用 20+
+  种行业标准格式导入和导出数据：CVAT (XML)、COCO (JSON)、YOLO (TXT)、Ultralytics YOLO (TXT/YAML)、Pascal VOC (XML)、
+  KITTI (TXT)、MOT (TXT) 等。

-[Full list of supported formats.](https://docs.cvat.ai/docs/dataset_management/formats/)
+[支持格式的完整列表。](https://docs.cvat.ai/docs/dataset_management/formats/)

-## ML and AI Models
+## ML 与 AI 模型

-CVAT Community supports automatic annotation via pre-built serverless models powered by Nuclio,
-covering detection, segmentation, pose estimation, and tracking:
+CVAT Community 通过由 Nuclio 驱动的预构建 serverless 模型支持自动标注，
+涵盖检测、分割、姿态估计与跟踪：

 | Model | Framework | Type |
 | --- | --- | --- |
@@ -162,69 +167,64 @@ covering detection, segmentation, pose estimation, and tracking:
 | [Face Detection 0205](https://github.com/cvat-ai/cvat/tree/develop/serverless/openvino/omz/intel/face-detection-0205/nuclio) | OpenVINO | Detector |
 | [Faster RCNN Inception v2](https://github.com/cvat-ai/cvat/tree/develop/serverless/tensorflow/faster_rcnn_inception_v2_coco/nuclio) | TensorFlow | Detector |

-To enable automatic annotation, add the serverless component to your deployment:
+要启用自动标注，请在你的部署中添加 serverless 组件：

 ```bash
 docker compose -f docker-compose.yml -f components/serverless/docker-compose.serverless.yml up -d
 ```

-This starts the serverless infrastructure. To make models available in CVAT, install `nuctl` and deploy
-the functions you need, for example SAM or YOLO, as described in the [Automatic Annotation Guide](https://docs.cvat.ai/docs/annotation/auto-annotation/automatic-annotation/).
+这将启动 serverless 基础设施。若要让模型在 CVAT 中可用，请安装 `nuctl` 并部署
+你所需的函数，例如 SAM 或 YOLO，详见[自动标注指南](https://docs.cvat.ai/docs/annotation/auto-annotation/automatic-annotation/).

-## Which CVAT edition should I choose?
+## 我应该选择哪个 CVAT 版本？

- **CVAT Online**: the fastest way to try CVAT and start labeling without deployment. Use it to evaluate CVAT in
-the browser, explore managed features, and move to cost-efficient paid plans when you need more capacity or team
-workflows.
- **CVAT Community**: the MIT-licensed self-hosted edition for teams that want to run CVAT themselves, customize the
-stack, and control their infrastructure.
- **CVAT Enterprise**: for organizations that need CVAT in their own cloud or internal environment, enterprise support,
-security controls such as SSO, paid platform features, and SLAs.
- **Labeling Services**: for teams that want to outsource annotation work to CVAT.ai’s experienced labeling team instead
-of building an internal labeling operation. Customers get trial access to CVAT Online during the project.
+- **CVAT Online**：无需部署即可最快试用 CVAT 并开始标注的方式。可用于在浏览器中评估 CVAT、探索托管功能，并在需要更大容量或团队协作工作流时迁移到高性价比的付费方案。
+- **CVAT Community**：采用 MIT 许可证的自托管版本，适合希望自行运行 CVAT、定制技术栈并掌控基础设施的团队。
+- **CVAT Enterprise**：面向需要在自有云或内部环境运行 CVAT 的组织，提供企业级支持、SSO 等安全控制、付费平台功能以及 SLA。
+- **Labeling Services（标注服务）**：面向希望将标注工作外包给 CVAT.ai 经验丰富的标注团队、而非自建内部标注团队的客户。客户在项目期间可获得 CVAT Online 的试用访问权限。

-For detailed plan limits and feature availability, see [CVAT Online pricing](https://www.cvat.ai/pricing/cvat-online),
- [CVAT Enterprise](https://www.cvat.ai/enterprise), and [Labeling Services](https://www.cvat.ai/annotation-services).
+有关各方案的详细额度限制与功能可用性，请参阅 [CVAT Online 定价](https://www.cvat.ai/pricing/cvat-online),
+ [CVAT Enterprise](https://www.cvat.ai/enterprise), 和 [Labeling Services（标注服务）](https://www.cvat.ai/annotation-services).

-## Support
+## 支持

- **Usage questions:** ask the community on [Discord](https://discord.com/invite/fNR3eXfk6C) or
-Stack Overflow with the `cvat` tag.
- **Bugs and feature requests:** use [GitHub Issues](https://github.com/cvat-ai/cvat/issues).
- **FAQ:** [Installation, upgrades, troubleshooting](https://docs.cvat.ai/docs/faq/).
+- **使用问题：** 可在 [Discord](https://discord.com/invite/fNR3eXfk6C) 向社区提问，或在
+Stack Overflow 上使用 `cvat` 标签提问。
+- **缺陷与功能请求：** 请使用 [GitHub Issues](https://github.com/cvat-ai/cvat/issues).
+- **常见问题：** [安装、升级、故障排除](https://docs.cvat.ai/docs/faq/).

-For dedicated support, SLAs, or advanced deployments, consider [CVAT Enterprise](https://www.cvat.ai/enterprise).
+如需专属支持、SLA 或高级部署，请考虑 [CVAT Enterprise](https://www.cvat.ai/enterprise).

-## Contributing
+## 贡献

-We welcome all contributions: bug reports, documentation fixes, integrations, and code.
+我们欢迎各类贡献：缺陷报告、文档修复、集成与代码。

- If you'd like to contribute to CVAT, please refer to our
-  [contribution documentation](https://docs.cvat.ai/docs/contributing/).
- For bug reports or feature requests, please use the [GitHub Issues](https://github.com/cvat-ai/cvat/issues) tracker.
+- 若要为 CVAT 做贡献，请参阅我们的
+  [贡献文档](https://docs.cvat.ai/docs/contributing/).
+- 缺陷报告或功能请求请使用 [GitHub Issues](https://github.com/cvat-ai/cvat/issues) 跟踪器。

-## Security
+## 安全

- Please review our [Security Policy](https://github.com/cvat-ai/cvat/security/policy) before reporting vulnerabilities.
- For sensitive issues, contact: [secure@cvat.ai](mailto:secure@cvat.ai).
+- 在报告漏洞前，请先阅读我们的[安全政策](https://github.com/cvat-ai/cvat/security/policy)。
+- 敏感问题请联系：[secure@cvat.ai](mailto:secure@cvat.ai)。

-## License
+## 许可证

-CVAT Community is released under the MIT License.
+CVAT Community 在 MIT 许可证下发布。

- Code in `/serverless` is also MIT-licensed, but may use third-party assets under separate licenses (including
-  non-commercial). Review those licenses before use.
- This software uses FFmpeg libraries under LGPL/GPL. See the Dockerfile and
-  [FFmpeg legal info](https://www.ffmpeg.org/legal.html) for details.
+- `/serverless` 中的代码同样采用 MIT 许可证，但可能包含依据单独许可证（包括
+  非商业用途限制）的第三方资源。使用前请查阅相关许可证。
+- 本软件在 LGPL/GPL 下使用 FFmpeg 库。详见 Dockerfile 与
+  [FFmpeg 法律信息](https://www.ffmpeg.org/legal.html)。

-## Additional Resources
+## 更多资源

-For the latest product releases, feature walkthroughs, and all things CVAT see:
+要了解最新产品发布、功能演示及 CVAT 相关资讯，请参阅：

 <table cellspacing="10" border="0"><tr>
-  <td><a href="https://www.cvat.ai/resources/blog"><img src="site/content/en/images/badge-blog.png" alt="CVAT Blog" height="120"/></a></td>
+  <td><a href="https://www.cvat.ai/resources/blog"><img src="site/content/en/images/badge-blog.png" alt="CVAT 博客" height="120"/></a></td>
  <td><a href="https://www.cvat.ai/resources/academy"><img src="site/content/en/images/badge-academy.png" alt="CVAT Academy" height="120"/></a></td>
-  <td><a href="https://www.cvat.ai/resources/case-studies"><img src="site/content/en/images/badge-case-studies.png" alt="Case Studies" height="120"/></a></td>
+  <td><a href="https://www.cvat.ai/resources/case-studies"><img src="site/content/en/images/badge-case-studies.png" alt="案例研究" height="120"/></a></td>
  <td><a href="https://www.youtube.com/@cvat-ai"><img src="site/content/en/images/badge-youtube.png" alt="YouTube" height="120"/></a></td>
  <td><a href="https://www.linkedin.com/company/cvat-ai"><img src="site/content/en/images/badge-linkedin.png" alt="LinkedIn" height="120"/></a></td>
 </tr></table>