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Optimize Docs images (#15900)

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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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docs/en/datasets/segment/coco.md
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@ -76,7 +76,7 @@ To train a YOLOv8n-seg model on the COCO-Seg dataset for 100 epochs with an imag
COCO-Seg, like its predecessor COCO, contains a diverse set of images with various object categories and complex scenes. However, COCO-Seg introduces more detailed instance segmentation masks for each object in the images. Here are some examples of images from the dataset, along with their corresponding instance segmentation masks:
![Dataset sample image](https://user-images.githubusercontent.com/26833433/239690696-93fa8765-47a2-4b34-a6e5-516d0d1c725b.jpg)
![Dataset sample image](https://github.com/ultralytics/docs/releases/download/0/mosaiced-training-batch-3.avif)
- **Mosaiced Image**: This image demonstrates a training batch composed of mosaiced dataset images. Mosaicing is a technique used during training that combines multiple images into a single image to increase the variety of objects and scenes within each training batch. This aids the model's ability to generalize to different object sizes, aspect ratios, and contexts.