README
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Image annotation for Machine Learning
Convolutional Neural Networks require annotated images to learn how to get recognize objects in images, which means that you need to give both the image and bounding boxes of each object to recognize when you train your model. And you will need a lot of annotations to ensure a good train!
Imannotate is a tool to help you to create those kind of dataset by spreading a dataset of non annotated pictures across several users and let them annonate them. Once done, you can export a CSV with all your annotations to train your model.
Features
- Manage multiple project
- Assign multiple users to one or multiple projects
- Annonate (indeed) by drawing bounding boxes and choose a tag
- Support "nothing to tag" on a picture
- Support "Pass" a picture
- S3 connector for the pictures source
- Qwant demo connector included (not suitable for production)
Installation
Since we are including a docker-compose.yaml file, the quickest way to install and start the application is to do a make prod into your terminal, in the project root folder.
However, for the one who like to do it by themself, we have a full Build your own documentation available into the project's wiki.
Contributing
There's just not one way to contribute to a project and you don't have to be a developer to contribute. If you are a developer, you may want to check our documentation regarding setting-up your environment to be able to code. Otherwise you can:
- Filling issues
- Automating Workflows
- Writing documentation & runbooks
- Thinking about long term priorities, doing feature request
- ...
Licence
The license can be seen here. Please note that we'll enforce signed-off commits and DCO.
Opensourced by Smile with ❤️, made by all our wonderfull contributors.
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