diff --git a/docs/en/hub/models.md b/docs/en/hub/models.md index bbfa313f..265b4b47 100644 --- a/docs/en/hub/models.md +++ b/docs/en/hub/models.md @@ -76,6 +76,17 @@ By default, your model will use a pre-trained model (trained on the [COCO](https You can easily change the most common model configuration options (such as the number of epochs) but you can also use the **Custom** option to access all [Train Settings](https://docs.ultralytics.com/modes/train/#train-settings) relevant to [Ultralytics HUB](https://bit.ly/ultralytics_hub). +

+
+ +
+ Watch: How to Configure Ultralytics YOLOv8 Training Parameters in Ultralytics HUB +

+ Alternatively, you start training from one of your previously trained models by clicking on the **Custom** tab. ![Ultralytics HUB screenshot of the Train Model dialog with an arrow pointing to the Custom tab](https://raw.githubusercontent.com/ultralytics/assets/main/docs/hub/models/hub_train_model_6.jpg) diff --git a/docs/en/integrations/gradio.md b/docs/en/integrations/gradio.md index f619457b..a80dba18 100644 --- a/docs/en/integrations/gradio.md +++ b/docs/en/integrations/gradio.md @@ -10,6 +10,17 @@ keywords: Ultralytics, YOLOv8, Gradio, object detection, interactive, real-time, This Gradio interface provides an easy and interactive way to perform object detection using the [Ultralytics YOLOv8](https://github.com/ultralytics/ultralytics/) model. Users can upload images and adjust parameters like confidence threshold and intersection-over-union (IoU) threshold to get real-time detection results. +

+
+ +
+ Watch: Gradio Integration with Ultralytics YOLOv8 +

+ ## Why Use Gradio for Object Detection? * **User-Friendly Interface:** Gradio offers a straightforward platform for users to upload images and visualize detection results without any coding requirement.