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Add https://youtu.be/ie3vLUDNYZo and other YT videos in Docs (#8551)

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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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11
docs/en/guides/distance-calculation.md
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@ -10,6 +10,17 @@ keywords: Ultralytics, YOLOv8, Object Detection, Distance Calculation, Object Tr
Measuring the gap between two objects is known as distance calculation within a specified space. In the case of [Ultralytics YOLOv8](https://github.com/ultralytics/ultralytics), the bounding box centroid is employed to calculate the distance for bounding boxes highlighted by the user.
<p align="center">
<br>
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/LE8am1QoVn4"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br>
<strong>Watch:</strong> Distance Calculation using Ultralytics YOLOv8
</p>
## Visuals
| Distance Calculation using Ultralytics YOLOv8 |

11
docs/en/guides/instance-segmentation-and-tracking.md
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@ -16,6 +16,17 @@ There are two types of instance segmentation tracking available in the Ultralyti
- **Instance Segmentation with Object Tracks:** Every track is represented by a distinct color, facilitating easy identification and tracking.
<p align="center">
<br>
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/75G_S1Ngji8"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br>
<strong>Watch:</strong> Instance Segmentation with Object Tracking using Ultralytics YOLOv8
</p>
## Samples
| Instance Segmentation | Instance Segmentation + Object Tracking |

11
docs/en/hub/app/android.md
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@ -31,6 +31,17 @@ keywords: Ultralytics, Android App, real-time object detection, YOLO models, Ten
The Ultralytics Android App is a powerful tool that allows you to run YOLO models directly on your Android device for real-time object detection. This app utilizes TensorFlow Lite for model optimization and various hardware delegates for acceleration, enabling fast and efficient object detection.
<p align="center">
<br>
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/AIvrQ7y0aLo"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br>
<strong>Watch:</strong> Getting Started with the Ultralytics HUB App (IOS & Android)
</p>
## Quantization and Acceleration
To achieve real-time performance on your Android device, YOLO models are quantized to either FP16 or INT8 precision. Quantization is a process that reduces the numerical precision of the model's weights and biases, thus reducing the model's size and the amount of computation required. This results in faster inference times without significantly affecting the model's accuracy.

11
docs/en/hub/app/ios.md
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@ -31,6 +31,17 @@ keywords: Ultralytics, iOS app, object detection, YOLO models, real time, Apple
The Ultralytics iOS App is a powerful tool that allows you to run YOLO models directly on your iPhone or iPad for real-time object detection. This app utilizes the Apple Neural Engine and Core ML for model optimization and acceleration, enabling fast and efficient object detection.
<p align="center">
<br>
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/AIvrQ7y0aLo"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br>
<strong>Watch:</strong> Getting Started with the Ultralytics HUB App (IOS & Android)
</p>
## Quantization and Acceleration
To achieve real-time performance on your iOS device, YOLO models are quantized to either FP16 or INT8 precision. Quantization is a process that reduces the numerical precision of the model's weights and biases, thus reducing the model's size and the amount of computation required. This results in faster inference times without significantly affecting the model's accuracy.

11
docs/en/hub/cloud-training.md
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@ -12,6 +12,17 @@ keywords: Ultralytics, HUB Models, AI model training, model creation, model trai
Read more about creating and other details of a Model at our [HUB Models page](models.md)
<p align="center">
<br>
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/ie3vLUDNYZo"
title="YouTube video player" frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
allowfullscreen>
</iframe>
<br>
<strong>Watch:</strong> New Feature 🌟 Introducing Ultralytics HUB Cloud Training
</p>
## Selecting an Instance
For details on picking a model and instances for it, please read our [Instances guide Page](models.md)