Export labeled datasets to use in projects
- 1.Navigate to the "Review" tab
- 2.Click "Export Labels"
- 3.Select desired export type
- 4.If an option, select what label types to export
- 5.Click "Export Now"
Once the project is done exporting a notification will appear.
HyperLabel supports several popular formats for exporting labeled datasets.
After you've finished labeling and have submitted your labels, go to the "Review" tab. There you can scroll and review a list of your images and their label statuses to ensure that you haven't missed an image that needs labeling.
From there, "Export Labels" button will allow you to export your labels into these formats:
- HyperLabel's own JSON format, used to import project data into another HyperLabel install on a different machine.
- Create ML - Apple's machine learning model creation and training framework. This format is now supported in the 1.1.9 release. Only Rectangles, Polygons, and Select label types can be exported to this format.
- COCO - a large-scale object detection, segmentation, and captioning dataset. All label types supported by HyperLabel can be exported to this format.
- YOLO - a real-time object detection algorithm. Only Rectangles and Polygons can be exported to this format.
- Pascal VOC - “Pattern Analysis, Statistical Modeling and Computational Learning Visual Object Classes” format is the input to the Pascal object detector. Rectangle and Polygon (converted to Rectangle) are supported.