Convert the COCO RLE format to YOLOv5/v8 segmentation format. (Sourcery refactored)

[sourcery-ai]

Pull Request #61 refactored by Sourcery.

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   git fetch https://github.com/ultralytics/JSON2YOLO pull/61/head
   git merge --ff-only FETCH_HEAD
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🛠️ PR Summary

_{Made with ❤️ by Ultralytics Actions}

📊 Key Changes

• Added the ability to convert COCO RLE (Run Length Encoding) formatted annotations to YOLOv5/v8 segmentation format.
• Implemented functions to support keypoints in annotations, including flip indices and merging multiple contours.
• Introduced utility functions for various transformations like converting masks to polygons, RLE to polygon, and more.

🎯 Purpose & Impact

The purpose of these changes is to enhance the JSON2YOLO conversion tool to support more complex annotation formats used in computer vision datasets, especially keypoints and segmentation masks. 🌐 This will allow developers and researchers who use the YOLO format for object detection and instance segmentation tasks to work with a broader range of datasets that may contain different types of annotations. For non-experts, these features make it easier to convert datasets without needing an in-depth understanding of annotation formats, potentially accelerating their AI/ML projects.

🌟 Summary

Now you can convert COCO dataset annotations with keypoints and segmentation to the YOLO format in a snap! 🎉 This update makes your data transformation tasks much simpler and supports more types of computer vision training escapades. 🚀