diff --git a/docs/en/guides/distance-calculation.md b/docs/en/guides/distance-calculation.md index 8cd064e4..c479d5f6 100644 --- a/docs/en/guides/distance-calculation.md +++ b/docs/en/guides/distance-calculation.md @@ -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. +

+
+ +
+ Watch: Distance Calculation using Ultralytics YOLOv8 +

+ ## Visuals | Distance Calculation using Ultralytics YOLOv8 | diff --git a/docs/en/guides/instance-segmentation-and-tracking.md b/docs/en/guides/instance-segmentation-and-tracking.md index 0339ab90..ac31ac87 100644 --- a/docs/en/guides/instance-segmentation-and-tracking.md +++ b/docs/en/guides/instance-segmentation-and-tracking.md @@ -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. +

+
+ +
+ Watch: Instance Segmentation with Object Tracking using Ultralytics YOLOv8 +

+ ## Samples | Instance Segmentation | Instance Segmentation + Object Tracking | diff --git a/docs/en/hub/app/android.md b/docs/en/hub/app/android.md index 0bff31c1..7a804743 100644 --- a/docs/en/hub/app/android.md +++ b/docs/en/hub/app/android.md @@ -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. +

+
+ +
+ Watch: Getting Started with the Ultralytics HUB App (IOS & Android) +

+ ## 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. diff --git a/docs/en/hub/app/ios.md b/docs/en/hub/app/ios.md index ac939c90..41e4b634 100644 --- a/docs/en/hub/app/ios.md +++ b/docs/en/hub/app/ios.md @@ -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. +

+
+ +
+ Watch: Getting Started with the Ultralytics HUB App (IOS & Android) +

+ ## 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. diff --git a/docs/en/hub/cloud-training.md b/docs/en/hub/cloud-training.md index 0fc850e1..91178ea2 100644 --- a/docs/en/hub/cloud-training.md +++ b/docs/en/hub/cloud-training.md @@ -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) +

+
+ +
+ Watch: New Feature 🌟 Introducing Ultralytics HUB Cloud Training +

+ ## Selecting an Instance For details on picking a model and instances for it, please read our [Instances guide Page](models.md)