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>

docs/en/datasets/segment/carparts-seg.md

@@ -72,7 +72,7 @@ To train Ultralytics YOLOv8n model on the Carparts Segmentation dataset for 100
 
 The Carparts Segmentation dataset includes a diverse array of images and videos taken from various perspectives. Below, you'll find examples of data from the dataset along with their corresponding annotations:
 
-![Dataset sample image](https://github.com/RizwanMunawar/RizwanMunawar/assets/62513924/55da8284-a637-4858-aa1c-fc22d33a9c43)
+![Dataset sample image](https://github.com/ultralytics/docs/releases/download/0/dataset-sample-image.avif)
 
 - This image illustrates object segmentation within a sample, featuring annotated bounding boxes with masks surrounding identified objects. The dataset consists of a varied set of images captured in various locations, environments, and densities, serving as a comprehensive resource for crafting models specific to this task.
 - This instance highlights the diversity and complexity inherent in the dataset, emphasizing the crucial role of high-quality data in computer vision tasks, particularly in the realm of car parts segmentation.

docs/en/datasets/segment/coco.md

@@ -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.
 

docs/en/datasets/segment/coco8-seg.md

@@ -51,7 +51,7 @@ To train a YOLOv8n-seg model on the COCO8-Seg dataset for 100 epochs with an ima
 
 Here are some examples of images from the COCO8-Seg dataset, along with their corresponding annotations:
 
-<img src="https://user-images.githubusercontent.com/26833433/236818387-f7bde7df-caaa-46d1-8341-1f7504cd11a1.jpg" alt="Dataset sample image" width="800">
+<img src="https://github.com/ultralytics/docs/releases/download/0/mosaiced-training-batch-2.avif" alt="Dataset sample image" width="800">
 
 - **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 helps improve the model's ability to generalize to different object sizes, aspect ratios, and contexts.
 

docs/en/datasets/segment/crack-seg.md

@@ -61,7 +61,7 @@ To train Ultralytics YOLOv8n model on the Crack Segmentation dataset for 100 epo
 
 The Crack Segmentation dataset comprises a varied collection of images and videos captured from multiple perspectives. Below are instances of data from the dataset, accompanied by their respective annotations:
 
-![Dataset sample image](https://github.com/RizwanMunawar/RizwanMunawar/assets/62513924/40ccc20a-9593-412f-b028-643d4a904d0e)
+![Dataset sample image](https://github.com/ultralytics/docs/releases/download/0/crack-segmentation-sample.avif)
 
 - This image presents an example of image object segmentation, featuring annotated bounding boxes with masks outlining identified objects. The dataset includes a diverse array of images taken in different locations, environments, and densities, making it a comprehensive resource for developing models designed for this particular task.
 

docs/en/datasets/segment/package-seg.md

@@ -61,7 +61,7 @@ To train Ultralytics YOLOv8n model on the Package Segmentation dataset for 100 e
 
 The Package Segmentation dataset comprises a varied collection of images and videos captured from multiple perspectives. Below are instances of data from the dataset, accompanied by their respective annotations:
 
-![Dataset sample image](https://github.com/RizwanMunawar/RizwanMunawar/assets/62513924/55bdf5c8-4ae4-4824-8d08-63c15bdd9a92)
+![Dataset sample image](https://github.com/ultralytics/docs/releases/download/0/dataset-sample-image-1.avif)
 
 - This image displays an instance of image object detection, featuring annotated bounding boxes with masks outlining recognized objects. The dataset incorporates a diverse collection of images taken in different locations, environments, and densities. It serves as a comprehensive resource for developing models specific to this task.
 - The example emphasizes the diversity and complexity present in the VisDrone dataset, underscoring the significance of high-quality sensor data for computer vision tasks involving drones.