CVAT YOLOv5 annotation format support

[husia777]

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hi, how do I add YOLOv5 support to cvat? There is a tutorial here https://opencv.github.io/cvat/docs/contributing/new-annotation-format/ but I do not know what to do , I am a backend developer

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[github-actions]

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[glenn-jocher]

@husia777 hello! Thanks for reaching out. To add YOLOv5 support to CVAT, you'll need to create a new annotation format definition following the guide you mentioned. Since you're a backend developer, you might be familiar with the process of integrating APIs or modifying codebases.

Here's a brief outline of the steps you'd typically follow:

1. Fork the CVAT repository.
2. Create a new annotation format specification for YOLOv5 in the CVAT format registry.
3. Implement the conversion code to support importing and exporting YOLOv5 annotations.
4. Test your implementation thoroughly to ensure compatibility.
5. Submit a pull request to the CVAT repository with your changes.

Since YOLOv5 uses a specific format for annotations (class index, x_center, y_center, width, height), ensure that your implementation correctly translates between the CVAT format and the YOLOv5 format.

For detailed instructions and code examples, please refer to the CVAT documentation and the contribution guide you've found. If you encounter any issues specific to YOLOv5 during this process, feel free to open an issue on the YOLOv5 repository, and we'll do our best to assist you.

Good luck with your integration, and thank you for contributing to the community! 🚀

[husia777]

cvat uses the datumaro library, but I can't find where it is installed to specify my version of datumaro

[glenn-jocher]

Hello @husia777! CVAT indeed uses the Datumaro library for handling various annotation formats. When you install CVAT, Datumaro is typically installed as a dependency within the CVAT environment.

If you need to specify a particular version of Datumaro or work with it directly, you would usually do this within the Python environment where CVAT is running. Here's a general approach:

1. Activate the Python virtual environment used by CVAT if it's using one.
2. Use pip to install your specific version of Datumaro with pip install datumaro==<version>.

If you're working with a Docker installation of CVAT, you might need to enter the Docker container to access the correct environment.

For CVAT installations not using Docker:

• Locate the CVAT directory.
• Look for a requirements.txt or a Python virtual environment to identify where Datumaro might be installed.

For Docker installations:

• Access the container with docker exec -it <container_name> /bin/bash.
• Once inside, you can use pip to manage Python packages.

Remember to check the compatibility of your Datumaro version with the CVAT version you are using to avoid any conflicts.

If you need further assistance, the CVAT GitHub issues page is a good place to ask for help specific to their platform. Good luck with your setup! 🛠️

[github-actions]

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