Using your own data or built-in samples¶

Your own data¶

RAITAP can load your own data by pointing data.source to a local file or directory.

Supported inputs include:

A directory of images such as .jpg, .png, .bmp, or .webp
A single image file
A CSV, TSV, or Parquet file
A directory containing CSV, TSV, or Parquet files

Example:

data:
  source: "./data/images" # a directory of images
  labels:
    source: "./data/labels.csv"
    id_column: "image"
    column: "label"

If you want to evaluate metrics against ground-truth labels, configure the optional data.labels block as described in Configuration.

Built-in samples¶

RAITAP also includes a few built-in sample datasets that can be referenced by name through data.source.

Available sample names are:

imagenet_samples
isic2018
malaria
UdacitySelfDriving

Example:

data:
  source: "imagenet_samples"

Built-in samples are useful for quickly testing the pipeline without preparing your own dataset first. RAITAP downloads them to a local cache automatically when needed.