PreviewSet

class lib.training.data.data_set.PreviewSet(side: str, image_folder: str, input_size: int, output_size: int, color_order: Literal['bgr', 'rgb'], num_images: int = 0)

Bases: _BaseSet

Preview dataset loader. The dataset loader is responsible for loading images from disk and preparing them for inference and display in the model preview

Parameters:

  • side (str) – The side of the model (“A”, “B” etc.)

  • image_folder (str) – Full path to a folder containing training images

  • input_size (int) – The input size to the model

  • output_size (int) – The largest output size of the model

  • color_order (T.Literal['bgr', 'rgb']) – The color order the model expects data in

  • num_images (int) – Set to 0 for random previews from the image folder. Set to a positive integer for this number of images to use for a static timelapse. Default: 0