Optimize Docs images (#15900)

Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Muhammad Rizwan Munawar 2024-08-30 05:52:10 +05:00 committed by GitHub
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@ -7,7 +7,7 @@ keywords: Ultralytics, utilities, data processing, auto annotation, YOLO, datase
# Simple Utilities
<p align="center">
<img src="https://github.com/ultralytics/ultralytics/assets/62214284/516112de-4567-49f8-b93f-b55a10b79dd7" alt="code with perspective">
<img src="https://github.com/ultralytics/docs/releases/download/0/code-with-perspective.avif" alt="code with perspective">
</p>
The `ultralytics` package comes with a myriad of utilities that can support, enhance, and speed up your workflows. There are many more available, but here are some that will be useful for most developers. They're also a great reference point to use when learning to program.
@ -53,7 +53,7 @@ auto_annotate( # (1)!
### Convert Segmentation Masks into YOLO Format
![Segmentation Masks to YOLO Format](https://github.com/user-attachments/assets/1a823fc1-f3a1-4dd5-83e7-0b209df06fc3)
![Segmentation Masks to YOLO Format](https://github.com/ultralytics/docs/releases/download/0/segmentation-masks-to-yolo-format.avif)
Use to convert a dataset of segmentation mask images to the `YOLO` segmentation format.
This function takes the directory containing the binary format mask images and converts them into YOLO segmentation format.