Update URLs to redirects (#16048)

docs/en/integrations/roboflow.md

@@ -12,10 +12,10 @@ keywords: Roboflow, YOLOv8, data labeling, computer vision, model training, mode
 
     Ultralytics offers two licensing options:
 
-    - The [AGPL-3.0 License](https://github.com/ultralytics/ultralytics/blob/main/LICENSE), an [OSI-approved](https://opensource.org/licenses/) open-source license ideal for students and enthusiasts.
-    - The [Enterprise License](https://ultralytics.com/license) for businesses seeking to incorporate our AI models into their products and services.
+    - The [AGPL-3.0 License](https://github.com/ultralytics/ultralytics/blob/main/LICENSE), an [OSI-approved](https://opensource.org/license) open-source license ideal for students and enthusiasts.
+    - The [Enterprise License](https://www.ultralytics.com/license) for businesses seeking to incorporate our AI models into their products and services.
 
-    For more details see [Ultralytics Licensing](https://ultralytics.com/license).
+    For more details see [Ultralytics Licensing](https://www.ultralytics.com/license).
 
 In this guide, we are going to showcase how to find, label, and organize data for use in training a custom Ultralytics YOLOv8 model. Use the table of contents below to jump directly to a specific section:
 
@@ -27,7 +27,7 @@ In this guide, we are going to showcase how to find, label, and organize data fo
 - Upload custom YOLOv8 model weights for testing and deployment
 - Gather Data for Training a Custom YOLOv8 Model
 
-Roboflow provides two services that can help you collect data for YOLOv8 models: [Universe](https://universe.roboflow.com/?ref=ultralytics) and [Collect](https://roboflow.com/collect?ref=ultralytics).
+Roboflow provides two services that can help you collect data for YOLOv8 models: [Universe](https://universe.roboflow.com/?ref=ultralytics) and [Collect](https://github.com/roboflow/roboflow-collect?ref=ultralytics).
 
 Universe is an online repository with over 250,000 vision datasets totalling over 100 million images.
 
@@ -47,13 +47,13 @@ For YOLOv8, select "YOLOv8" as the export format:
 <img src="https://github.com/ultralytics/docs/releases/download/0/roboflow-universe-dataset-export-1.avif" alt="Roboflow Universe dataset export" width="800">
 </p>
 
-Universe also has a page that aggregates all [public fine-tuned YOLOv8 models uploaded to Roboflow](https://universe.roboflow.com/search?q=model:yolov8). You can use this page to explore pre-trained models you can use for testing or [for automated data labeling](https://docs.roboflow.com/annotate/use-roboflow-annotate/model-assisted-labeling) or to prototype with [Roboflow inference](https://roboflow.com/inference?ref=ultralytics).
+Universe also has a page that aggregates all [public fine-tuned YOLOv8 models uploaded to Roboflow](https://universe.roboflow.com/search?q=model%3Ayolov8&ref=ultralytics). You can use this page to explore pre-trained models you can use for testing or [for automated data labeling](https://docs.roboflow.com/annotate/use-roboflow-annotate/model-assisted-labeling?ref=ultralytics) or to prototype with [Roboflow inference](https://github.com/roboflow/inference?ref=ultralytics).
 
 If you want to gather images yourself, try [Collect](https://github.com/roboflow/roboflow-collect), an open source project that allows you to automatically gather images using a webcam on the edge. You can use text or image prompts with Collect to instruct what data should be collected, allowing you to capture only the useful data you need to build your vision model.
 
 ## Upload, Convert and Label Data for YOLOv8 Format
 
-[Roboflow Annotate](https://docs.roboflow.com/annotate/use-roboflow-annotate) is an online annotation tool for use in labeling images for object detection, classification, and segmentation.
+[Roboflow Annotate](https://docs.roboflow.com/annotate/use-roboflow-annotate?ref=ultralytics) is an online annotation tool for use in labeling images for object detection, classification, and segmentation.
 
 To label data for a YOLOv8 object detection, instance segmentation, or classification model, first create a project in Roboflow.
 
@@ -127,7 +127,7 @@ You can narrow your search to images with a particular tag using the "Tags" sele
 <img src="https://github.com/ultralytics/docs/releases/download/0/filter-images-by-tag.avif" alt="Filter images by tag" width="350">
 </p>
 
-Before you start training a model with your dataset, we recommend using Roboflow [Health Check](https://docs.roboflow.com/datasets/dataset-health-check), a web tool that provides an insight into your dataset and how you can improve the dataset prior to training a vision model.
+Before you start training a model with your dataset, we recommend using Roboflow [Health Check](https://docs.roboflow.com/datasets/dataset-health-check?ref=ultralytics), a web tool that provides an insight into your dataset and how you can improve the dataset prior to training a vision model.
 
 To use Health Check, click the "Health Check" sidebar link. A list of statistics will appear that show the average size of images in your dataset, class balance, a heatmap of where annotations are in your images, and more.
 
@@ -157,7 +157,7 @@ When your dataset version has been generated, you can export your data into a ra
 <img src="https://github.com/ultralytics/docs/releases/download/0/exporting-dataset.avif" alt="Exporting a dataset" width="800">
 </p>
 
-You are now ready to train YOLOv8 on a custom dataset. Follow this [written guide](https://blog.roboflow.com/how-to-train-yolov8-on-a-custom-dataset/) and [YouTube video](https://www.youtube.com/watch?v=wuZtUMEiKWY) for step-by-step instructions or refer to the [Ultralytics documentation](../modes/train.md).
+You are now ready to train YOLOv8 on a custom dataset. Follow this [written guide](https://blog.roboflow.com/how-to-train-yolov8-on-a-custom-dataset/?ref=ultralytics) and [YouTube video](https://www.youtube.com/watch?v=wuZtUMEiKWY) for step-by-step instructions or refer to the [Ultralytics documentation](../modes/train.md).
 
 ## Upload Custom YOLOv8 Model Weights for Testing and Deployment
 
@@ -178,7 +178,7 @@ dataset = project.version(VERSION).download("yolov8")
 project.version(dataset.version).deploy(model_type="yolov8", model_path=f"{HOME}/runs/detect/train/")
 ```
 
-In this code, replace the project ID and version ID with the values for your account and project. [Learn how to retrieve your Roboflow API key](https://docs.roboflow.com/api-reference/authentication#retrieve-an-api-key).
+In this code, replace the project ID and version ID with the values for your account and project. [Learn how to retrieve your Roboflow API key](https://docs.roboflow.com/api-reference/authentication?ref=ultralytics#retrieve-an-api-key).
 
 When you run the code above, you will be asked to authenticate. Then, your model will be uploaded and an API will be created for your project. This process can take up to 30 minutes to complete.
 
@@ -188,7 +188,7 @@ To test your model and find deployment instructions for supported SDKs, go to th
 <img src="https://github.com/ultralytics/docs/releases/download/0/running-inference-example-image.avif" alt="Running inference on an example image" width="800">
 </p>
 
-You can also use your uploaded model as a [labeling assistant](https://docs.roboflow.com/annotate/use-roboflow-annotate/model-assisted-labeling). This feature uses your trained model to recommend annotations on images uploaded to Roboflow.
+You can also use your uploaded model as a [labeling assistant](https://docs.roboflow.com/annotate/use-roboflow-annotate/model-assisted-labeling?ref=ultralytics). This feature uses your trained model to recommend annotations on images uploaded to Roboflow.
 
 ## How to Evaluate YOLOv8 Models
 
@@ -227,9 +227,9 @@ You can use Vector Analysis to:
 Want to learn more about using Roboflow for creating YOLOv8 models? The following resources may be helpful in your work.
 
 - [Train YOLOv8 on a Custom Dataset](https://github.com/roboflow/notebooks/blob/main/notebooks/train-yolov8-object-detection-on-custom-dataset.ipynb): Follow our interactive notebook that shows you how to train a YOLOv8 model on a custom dataset.
-- [Autodistill](https://autodistill.github.io/autodistill/): Use large foundation vision models to label data for specific models. You can label images for use in training YOLOv8 classification, detection, and segmentation models with Autodistill.
-- [Supervision](https://roboflow.github.io/supervision/): A Python package with helpful utilities for use in working with computer vision models. You can use supervision to filter detections, compute confusion matrices, and more, all in a few lines of Python code.
-- [Roboflow Blog](https://blog.roboflow.com/): The Roboflow Blog features over 500 articles on computer vision, covering topics from how to train a YOLOv8 model to annotation best practices.
+- [Autodistill](https://docs.autodistill.com/): Use large foundation vision models to label data for specific models. You can label images for use in training YOLOv8 classification, detection, and segmentation models with Autodistill.
+- [Supervision](https://supervision.roboflow.com/?ref=ultralytics): A Python package with helpful utilities for use in working with computer vision models. You can use supervision to filter detections, compute confusion matrices, and more, all in a few lines of Python code.
+- [Roboflow Blog](https://blog.roboflow.com/?ref=ultralytics): The Roboflow Blog features over 500 articles on computer vision, covering topics from how to train a YOLOv8 model to annotation best practices.
 - [Roboflow YouTube channel](https://www.youtube.com/@Roboflow): Browse dozens of in-depth computer vision guides on our YouTube channel, covering topics from training YOLOv8 models to automated image labeling.
 
 ## Project Showcase
@@ -250,7 +250,7 @@ Labeling data for YOLOv8 models using Roboflow is straightforward with Roboflow
 
 ### What services does Roboflow offer for collecting YOLOv8 training data?
 
-Roboflow provides two key services for collecting YOLOv8 training data: [Universe](https://universe.roboflow.com/?ref=ultralytics) and [Collect](https://roboflow.com/collect?ref=ultralytics). Universe offers access to over 250,000 vision datasets, while Collect helps you gather images using a webcam and automated prompts.
+Roboflow provides two key services for collecting YOLOv8 training data: [Universe](https://universe.roboflow.com/?ref=ultralytics) and [Collect](https://github.com/roboflow/roboflow-collect?ref=ultralytics). Universe offers access to over 250,000 vision datasets, while Collect helps you gather images using a webcam and automated prompts.
 
 ### How can I manage and analyze my YOLOv8 dataset using Roboflow?