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.travis.yml

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language: node_js
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node_js:
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- "stable"
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cache:
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directories:
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- node_modules
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script:
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- npm test
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- npm run test:coverage
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- npm run build

README.md

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[![Build Status](https://travis-ci.org/SkalskiP/make-sense.svg?branch=develop)](https://travis-ci.org/SkalskiP/make-sense)
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![GitHub release (latest by date including pre-releases)](https://img.shields.io/github/v/release/SkalskiP/make-sense?include_prereleases)
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[![Gitter](https://badges.gitter.im/make-sense-ai/community.svg)](https://gitter.im/make-sense-ai/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
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<h1 align="center">makesense.ai</h1>
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[makesense.ai][1] is a free to use online tool for labelling photos. Thanks to the use of a browser it does not require any complicated installation - just visit the website and you are ready to go. It also doesn't matter which operating system you're running on - we do our best to be truly cross-platform. It is perfect for small computer vision deeplearning projects, making the process of preparing a dataset much easier and faster. Prepared labels can be downloaded in one of multiple supported formats. The application was written in TypeScript and is based on React/Redux duo.
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## Road Map
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## Motto
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Our application is being actively developed. If you have an idea for a new functionality, please hit us on [Twitter][3] or create an issue where you can describe your concept. In the meantime, see what improvements we are planning for you in the future.
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> For AI to be free we need not just Open Source, but also a strong Open Data movement.
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- [X] Export labels in Pascal VOC XML format
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- [ ] Optimization of the process of loading photos from disk - queuing
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- [ ] Labelling objects using polygons and Bézier curves
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- [ ] Labelling objects using lines
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- [ ] Export labels in COCO JSON format
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- [ ] Separate tab with settings
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- [ ] Support basic image operations like crop and resize
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- [ ] Converting video to image frames
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- [ ] Keyboard shortcuts to improve productivity
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- [ ] Automatic detection of objects in a photo - all you have to do is to label them
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- [ ] OCR labelling
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- [ ] Integration with external storage - Amazon S3, Google Drive, Dropbox
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- [ ] Copy annotations from previous image into the next one
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Andrew Ng
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## Sneak Peek
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### Bounding boxes
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<p align="center">
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<img width="1000" src=".//examples/bbox-demo.gif" alt="bbox">
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</p>
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### Points
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<p align="center">
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<img width="1000" src=".//examples/alfa-demo.gif" alt="Logo">
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<img width="1000" src=".//examples/points-demo.gif" alt="points">
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</p>
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### Polygons
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<p align="center">
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<img width="1000" src=".//examples/polygon-demo.gif" alt="polygon">
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</p>
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## Set Up the Project Locally
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## Supported Output Formats
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* A .zip package containing files in YOLO format
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| | CSV | YOLO | VOC XML | VGG JSON | COCO | PIXEL MASK |
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|:-------------:|:---:|:----:|:-------:|:--------:|:----:|:----------:|
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| **Point** |||||||
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| **Rect** |||||||
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| **Polygon** |||||||
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**Table 1.** The matrix of supported labels export format, where:
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* ☑ - supported format
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* ☐ - not yet supported format
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* ☒ - format does not make sense for a given label type
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**A .zip package containing files in YOLO format**
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<details><summary><i>example of file in YOLO format</i></summary><p>
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```
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</p></details>
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* A .zip package containing files in Pascal VOC XML format
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**A .zip package containing files in Pascal VOC XML format**
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<details><summary><i>example of file in Pascal VOC XML format</i></summary><p>
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```
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</p></details>
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* Single CSV file
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**Single CSV file**
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<details><summary><i>example of CSV file</i></summary><p>
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We don't store your images, because we don't send them anywhere in the first place.
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## Road Map
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Our application is being actively developed. If you have an idea for a new functionality, please hit us on [Twitter][3] and [Gitter][5] or create an issue where you can describe your concept. In the meantime, see what improvements we are planning for you in the future.
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- [X] Export rect labels in Pascal VOC XML format
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- [X] Labelling objects using polygons
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- [X] Export polygon labels in VGG JSON format
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- [ ] Optimization of the process of loading photos from disk - queuing
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- [ ] Labelling objects using lines
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- [ ] Autofill in label selection dropdown
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- [ ] Export labels in COCO JSON format
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- [ ] Export segmentation labels as image mask
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- [ ] Separate tab with settings
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- [ ] Support basic image operations like crop and resize
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- [ ] Converting video to image frames
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- [ ] Keyboard shortcuts to improve productivity
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- [ ] Automatic detection of objects in a photo - all you have to do is to label them
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- [ ] OCR labelling
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- [ ] Integration with external storage - Amazon S3, Google Drive, Dropbox
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- [ ] Copy annotations from previous image into the next one
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## License
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This project is licensed under the GPL-3.0 License - see the [LICENSE][2] file for details
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[2]: ./LICENSE
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[3]: https://twitter.com/PiotrSkalski92
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[4]: https://github.com/SkalskiP/make-sense/issues/16
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[5]: https://gitter.im/make-sense-ai/community?utm_source=share-link&utm_medium=link&utm_campaign=share-link

examples/bbox-demo.gif

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package.json

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"scripts": {
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"start": "react-scripts start",
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"build": "react-scripts build",
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"test": "react-scripts test",
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"test": "CI=true react-scripts test --env=jsdom",
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"test:coverage": "npm test -- --coverage",
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"eject": "react-scripts eject"
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},
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"eslintConfig": {

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