Add Docs glossary links (#16448)
Signed-off-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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@ -6,7 +6,7 @@ keywords: Carparts Segmentation Dataset, Roboflow, computer vision, automotive A
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# Roboflow Universe Carparts Segmentation Dataset
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The [Roboflow](https://roboflow.com/?ref=ultralytics) [Carparts Segmentation Dataset](https://universe.roboflow.com/gianmarco-russo-vt9xr/car-seg-un1pm?ref=ultralytics) is a curated collection of images and videos designed for computer vision applications, specifically focusing on segmentation tasks related to car parts. This dataset provides a diverse set of visuals captured from multiple perspectives, offering valuable annotated examples for training and testing segmentation models.
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The [Roboflow](https://roboflow.com/?ref=ultralytics) [Carparts Segmentation Dataset](https://universe.roboflow.com/gianmarco-russo-vt9xr/car-seg-un1pm?ref=ultralytics) is a curated collection of images and videos designed for [computer vision](https://www.ultralytics.com/glossary/computer-vision-cv) applications, specifically focusing on segmentation tasks related to car parts. This dataset provides a diverse set of visuals captured from multiple perspectives, offering valuable annotated examples for training and testing segmentation models.
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Whether you're working on automotive research, developing AI solutions for vehicle maintenance, or exploring computer vision applications, the Carparts Segmentation Dataset serves as a valuable resource for enhancing accuracy and efficiency in your projects.
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@ -18,7 +18,7 @@ Whether you're working on automotive research, developing AI solutions for vehic
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allowfullscreen>
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</iframe>
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<br>
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<strong>Watch:</strong> Carparts Instance Segmentation Using Ultralytics HUB
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<strong>Watch:</strong> Carparts [Instance Segmentation](https://www.ultralytics.com/glossary/instance-segmentation) Using Ultralytics HUB
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</p>
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## Dataset Structure
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@ -45,7 +45,7 @@ A YAML (Yet Another Markup Language) file is used to define the dataset configur
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## Usage
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To train Ultralytics YOLOv8n model on the Carparts Segmentation dataset for 100 epochs with an image size of 640, you can use the following code snippets. For a comprehensive list of available arguments, refer to the model [Training](../../modes/train.md) page.
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To train Ultralytics YOLOv8n model on the Carparts Segmentation dataset for 100 [epochs](https://www.ultralytics.com/glossary/epoch) with an image size of 640, you can use the following code snippets. For a comprehensive list of available arguments, refer to the model [Training](../../modes/train.md) page.
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!!! example "Train Example"
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@ -156,6 +156,6 @@ The dataset configuration file for the Carparts Segmentation dataset, `carparts-
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### Why should I use the Carparts Segmentation Dataset?
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The Carparts Segmentation Dataset provides rich, annotated data essential for developing high-accuracy segmentation models in automotive computer vision. This dataset's diversity and detailed annotations improve model training, making it ideal for applications like vehicle maintenance automation, enhancing vehicle safety systems, and supporting autonomous driving technologies. Partnering with a robust dataset accelerates AI development and ensures better model performance.
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The Carparts Segmentation Dataset provides rich, annotated data essential for developing high-[accuracy](https://www.ultralytics.com/glossary/accuracy) segmentation models in automotive computer vision. This dataset's diversity and detailed annotations improve model training, making it ideal for applications like vehicle maintenance automation, enhancing vehicle safety systems, and supporting autonomous driving technologies. Partnering with a robust dataset accelerates AI development and ensures better model performance.
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For more details, visit the [CarParts Segmentation Dataset Page](https://universe.roboflow.com/gianmarco-russo-vt9xr/car-seg-un1pm?ref=ultralytics).
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