Generate Datasets

Autogenerated datasets consist of randomly generated noise in images for testing purposes and do not include annotations. Below is an example of a noise image:


NOTE: Generated datasets are only in the ImageNet format and suitable only for generic or classification type models.

NOTE: Because autogenerated datasets are made of noise images and do not contain annotations, they cannot be used for accuracy measurement and calibration.

On the One-Page Wizard screen, find the table with datasets:


To generate a new dataset, click the Autogenerate Dataset in ImageNet format button. Fill out the Autogenerate Dataset form that appears on a new page:

Parameter Values Explanation
Number of Images to Generate [1; 2000]A number of .npy images to generate for the dataset
Image Dimensions [1; 1920] Image height and width in pixels

After you have entered all the required parameters, click the Generate button to generate a dataset. You are automatically directed back to the datasets table, where the Status column shows the progress bar and status of the generation.


To cancel the generation process, press a red stop sign in the Action column.

Once the generation completes, the dataset indicates a green tick sign.

To remove an imported dataset from the list, click the bin icon in the Action column.

Select dataset in the list and proceed to select an environment.