Replace 'supervise.ly' with 'supervisely.com'

README.md

@@ -11,19 +11,19 @@
   <a href="#Related-apps">Related apps</a>
 </p>
 
-[![](https://img.shields.io/badge/supervisely-ecosystem-brightgreen)](https://ecosystem.supervise.ly/apps/supervisely-ecosystem/export-to-yolov8)
-[![](https://img.shields.io/badge/slack-chat-green.svg?logo=slack)](https://supervise.ly/slack)
+[![](https://img.shields.io/badge/supervisely-ecosystem-brightgreen)](https://ecosystem.supervisely.com/apps/supervisely-ecosystem/export-to-yolov8)
+[![](https://img.shields.io/badge/slack-chat-green.svg?logo=slack)](https://supervisely.com/slack)
 ![GitHub release (latest SemVer)](https://img.shields.io/github/v/release/supervisely-ecosystem/export-to-yolov8)
-[![views](https://app.supervise.ly/img/badges/views/supervisely-ecosystem/export-to-yolov8.png)](https://supervise.ly)
-[![runs](https://app.supervise.ly/img/badges/runs/supervisely-ecosystem/export-to-yolov8.png)](https://supervise.ly)
+[![views](https://app.supervisely.com/img/badges/views/supervisely-ecosystem/export-to-yolov8.png)](https://supervisely.com)
+[![runs](https://app.supervisely.com/img/badges/runs/supervisely-ecosystem/export-to-yolov8.png)](https://supervisely.com)
 
 </div>
 
 # Overview
 
 This application is designed specifically for instance segmentation and pose estimation tasks.
 
-It transforms datasets from the [Supervisely format](https://docs.supervise.ly/data-organization/00_ann_format_navi) to the YOLOv8 **segmentation format** or **pose estimation format**. 
+It transforms datasets from the [Supervisely format](https://docs.supervisely.com/data-organization/00_ann_format_navi) to the YOLOv8 **segmentation format** or **pose estimation format**. 
 By using this application, you can effortlessly convert your dataset and download as `tar` archive.
 
 **Changelog**:
@@ -59,7 +59,7 @@ Learn more about Yolov8 segmentation format [here](https://docs.ultralytics.com/
 
 **Detection**:
 
-- To convert Supervisely project to YOLOv8 format for object detection tasks, you can use the [Convert Supervisely to YOLO v5 format ](https://ecosystem.supervise.ly/apps/convert-supervisely-to-yolov5-format) app.
+- To convert Supervisely project to YOLOv8 format for object detection tasks, you can use the [Convert Supervisely to YOLO v5 format ](https://ecosystem.supervisely.com/apps/convert-supervisely-to-yolov5-format) app.
 
     <img data-key="sly-module-link" data-module-slug="supervisely-ecosystem/convert-supervisely-to-yolov5-format" src="https://github.com/supervisely-ecosystem/export-to-yolov8/releases/download/untagged-6331ae231a8468233aab/yolo_det.jpg" height="70px" margin-bottom="20px"/>
 
@@ -91,18 +91,18 @@ Learn more about Yolov8 pose estimation format [here](https://docs.ultralytics.c
 Supervisely project has to contain only classes with shape `Polygon`, `Bitmap`, `AlphaMask` for segmentation tasks or `Graph` for pose estimation tasks. 
 If your project has classes with other shapes, labels with other types of shapes will be skipped. We recommend you to use `Convert Class Shape` app to convert class shapes (supported for segmentation tasks only).
 
-- The [Convert Class Shape](https://ecosystem.supervise.ly/apps/convert-class-shape) app allows to convert labels to different class shapes.  
+- The [Convert Class Shape](https://ecosystem.supervisely.com/apps/convert-class-shape) app allows to convert labels to different class shapes.  
 
     <img data-key="sly-module-link" data-module-slug="supervisely-ecosystem/convert-class-shape" src="https://user-images.githubusercontent.com/115161827/235643553-d5dd001e-22ef-4e74-a303-b7cfd251b7fd.png" height="70px" margin-bottom="20px"/>
 
 In addition, YOLOv8 format implies the presence of train/val datasets. Thus, to split images on training and validation datasets you should assign  corresponding tags (`train` or `val`) to images. If image doesn't have such tags, it will be treated as `train`. We recommend to use app `Assign train/val tags to images`. 
 
-- [Assign train/val tags to images](https://ecosystem.supervise.ly/apps/tag-train-val-test) - app allows to assign train/val tags to images.  
+- [Assign train/val tags to images](https://ecosystem.supervisely.com/apps/tag-train-val-test) - app allows to assign train/val tags to images.  
 
     <img data-key="sly-module-link" data-module-slug="supervisely-ecosystem/tag-train-val-test" src="https://user-images.githubusercontent.com/115161827/235643549-d0f4ea23-c75e-46f2-8767-3d786eb79207.png" height="70px" margin-bottom="20px"/>
 
 # How to Run 
-1. Add app to your team from [Ecosystem](https://ecosystem.supervise.ly/apps/export-to-yolov8) if it is not there.
+1. Add app to your team from [Ecosystem](https://ecosystem.supervisely.com/apps/export-to-yolov8) if it is not there.
 
 2. Open context menu of project -> `Download as` -> `Export to YOLO v8 format` 
 <img src="https://user-images.githubusercontent.com/115161827/235641219-43f67765-99ff-4ece-803b-3cbbb07011c4.png" />
@@ -145,8 +145,8 @@ kpt_shape: [17, 3]  # number of keypoints, number of dims (2 for x,y or 3 for x,
 
 # Related apps
 
-- [Train YOLOv8](https://ecosystem.supervise.ly/apps/supervisely-ecosystem/yolov8/train) - app allows to create custom YOLOv8 weights through training process.
+- [Train YOLOv8](https://ecosystem.supervisely.com/apps/supervisely-ecosystem/yolov8/train) - app allows to create custom YOLOv8 weights through training process.
     <img data-key="sly-module-link" data-module-slug="supervisely-ecosystem/yolov8/train" src="https://github.com/supervisely-ecosystem/yolov8/assets/115161827/82348f9a-38fc-4736-885c-d6786e37a218" height="70px" margin-bottom="20px"/>
 
-- [Serve YOLOv8](https://ecosystem.supervise.ly/apps/yolov8/serve) - app allows to deploy YOLOv8 model as REST API service.   
+- [Serve YOLOv8](https://ecosystem.supervisely.com/apps/yolov8/serve) - app allows to deploy YOLOv8 model as REST API service.   
     <img data-key="sly-module-link" data-module-slug="supervisely-ecosystem/yolov8/serve" src="https://github.com/supervisely-ecosystem/yolov8/assets/115161827/721f5344-013c-4466-bc05-88cc3efef5ca" height="70px" margin-bottom="20px"/>