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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/detect/roboflow-100.md
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@ -9,7 +9,7 @@ keywords: Roboflow 100, Ultralytics, object detection, dataset, benchmarking, ma
Roboflow 100, developed by [Roboflow](https://roboflow.com/?ref=ultralytics) and sponsored by Intel, is a groundbreaking [object detection](../../tasks/detect.md) benchmark. It includes 100 diverse datasets sampled from over 90,000 public datasets. This benchmark is designed to test the adaptability of models to various domains, including healthcare, aerial imagery, and video games.
<p align="center">
<img width="640" src="https://user-images.githubusercontent.com/15908060/202452898-9ca6b8f7-4805-4e8e-949a-6e080d7b94d2.jpg" alt="Roboflow 100 Overview">
<img width="640" src="https://github.com/ultralytics/docs/releases/download/0/roboflow-100-overview.avif" alt="Roboflow 100 Overview">
</p>
## Key Features
@ -104,7 +104,7 @@ You can access it directly from the Roboflow 100 GitHub repository. In addition,
Roboflow 100 consists of datasets with diverse images and videos captured from various angles and domains. Here's a look at examples of annotated images in the RF100 benchmark.
<p align="center">
<img width="640" src="https://blog.roboflow.com/content/images/2022/11/image-2.png" alt="Sample Data and Annotations">
<img width="640" src="https://github.com/ultralytics/docs/releases/download/0/sample-data-annotations.avif" alt="Sample Data and Annotations">
</p>
The diversity in the Roboflow 100 benchmark that can be seen above is a significant advancement from traditional benchmarks which often focus on optimizing a single metric within a limited domain.