Data conventionsΒΆ

datadings is built around two basic principles:

Datasets are collections of individual data samples.

Each sample is a dictionary with descriptive keys.

E.g., for supervised training with images each sample is a dictionary {'key': unique_key, 'image': imagedata, 'label': label). Depending on the type of dataset different keys are used. There is no schema to dictate which keys are allowed and what they stand for, with the exception of the "key" which is always a unique identifier of that sample in the dataset. datadings follows the best-effort principle that the kind of data associated with a certain key remains the same across datasets. These are some common keys and their meanings:

  • "key": Unique identifier of this sample.

  • "image": Contents of an image file. Use any standard image library to get pixel data.

  • "label": Numerical label for the whole sample.

  • "*_image": Same as image, but different semantics. For example, "label_image" with per-pixel segmentation labels, or "instance_image" for instance segmentation.

  • "experiments": A list of experiments, usually saliency. Type depends on dataset.

  • "locations": List of (x,y) coordinates.

  • "map": Fixation map as image.

  • "fixations": List of (x,y) fixation points.