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README.md
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<div align="center">
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<article style="display: flex; flex-direction: column; align-items: center; justify-content: center;">
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<p align="center"><img width="300" src="https://
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</article>
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<a href="./README_zh-CN.md" >简体中文</a> | English
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<p align="center">
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<img style="width: 700px" src="./docs/assets/main.png">
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</p>
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</div>
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## Introduction
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LabelU is an open source data annotation tool that supports Chinese. At present, it has image annotation capabilities such as rectangle, polygon, point, line, classification,
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## Getting started
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conda create -n labelu --python=3.10
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conda activate labelu
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```
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### Install labelu
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pip install labelu
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```
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###
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labelu
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```
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## feature
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- Uniform
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- Unlimited
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## Scenes
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## Usage
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- [Guide](./docs/
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## Annotation Format
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[LabelU Annotation Format](./docs/annotation/README.md)
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## Communication
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!
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## Links
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- [labelU-Kit](https://github.com/opendatalab/labelU-Kit)
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## LICENSE
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---
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hello:
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---
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<div align="center">
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<article style="display: flex; flex-direction: column; align-items: center; justify-content: center;">
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<p align="center"><img width="300" src="https://user-images.githubusercontent.com/25022954/209616423-9ab056be-5d62-4eeb-b91d-3b20f64cfcf8.svg" /></p>
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<h1 style="width: 100%; text-align: center;"></h1>
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</p>
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</article>
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<a href="./README_zh-CN.md" >简体中文</a> | English
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</div>
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## Introduction
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LabelU is an open source data annotation tool that supports Chinese. At present, it has image annotation capabilities such as rectangle, polygon, point, line, classification, and caption. It can support detection, classification, segmentation, text transcription, Line detection, key point detection and other computer vision task scenarios. You can customize the annotation task by freely combining tools, and support COCO and MASK format data export.
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## Getting started
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### Install locally with miniconda
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```
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# Download and Install miniconda
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# https://docs.conda.io/en/latest/miniconda.html
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# Create virtual environment(python = 3.7)
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conda create -n labelu python=3.7
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# Activate virtual environment
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conda activate labelu
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# Install labelu
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pip install labelu
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# Start labelu, server: http://localhost:8000
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labelu
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```
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### Install for local development
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```
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# Download and Install miniconda
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# https://docs.conda.io/en/latest/miniconda.html
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# Create virtual environment(python = 3.7)
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conda create -n labelu python=3.7
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# Activate virtual environment
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conda activate labelu
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# Install peotry
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# https://python-poetry.org/docs/#installing-with-the-official-installer
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# Install all package dependencies
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poetry install
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# Start labelu, server: http://localhost:8000
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uvicorn labelu.main:app --reload
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# Update submodule
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git submodule update --remote --merge
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```
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## feature
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- Uniform, Six image annotation tools are provided, which can be configured through simple visualization or Yaml
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- Unlimited, Multiple tools can be freely combined to meet most image annotation requirements
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<p align="center">
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<img style="width: 600px" src="https://user-images.githubusercontent.com/25022954/209318236-79d3a5c3-2700-46c3-b59a-62d9c132a6c3.gif">
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</p>
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- Universal, Support multiple data export formats, including LabelU, COCO, Mask
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## Scenes
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## Usage
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- [Guide](./docs/GUIDE.md)
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## Annotation Format
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- [LabelU Annotation Format](./docs/annotation%20format/README.md)
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## Communication
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Welcome to the Opendatalab Wechat group!
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<p align="center">
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<img style="width: 400px" src="https://user-images.githubusercontent.com/25022954/208374419-2dffb701-321a-4091-944d-5d913de79a15.jpg">
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</p>
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## Links
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- [labelU-Kit](https://github.com/opendatalab/labelU-Kit)(Powered by labelU-Kit)
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## LICENSE
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