Image Statistics

The imagestats function assists with understanding the dataset. This function can be used in conjunction with the Linter class to determine if there are any issues with any of the images in the dataset.

This class can be used to get a big picture view of the dataset and it’s underlying distribution.

The stats delivered by the class is broken down into 3 main categories:

  • statistics covering image properties,

  • statistics covering the visual aspect of images,

  • and normal statistics about pixel values.

Below shows the statistics each category calculates.

  • Image Properties

    • height (uint16)

    • width (uint16)

    • channels (uint8)

    • size (uint32)

    • aspect ratio (float16)

    • pixel value range (uint8)

  • Image Visuals

    • image brightness (float16)

    • image blurriness (float16)

    • missing values (NaNs) (float16)

    • number of 0 value pixels (float16)

  • Pixel Statistics

    • mean pixel value (float16)

    • pixel value standard deviation (float16)

    • pixel value variance (float16)

    • pixel value skew (float16)

    • pixel value kurtosis (float16)

    • entropy of the image (float16)

    • pixel percentiles (min, max, 25th, 50th, and 75th percentile values) (float16)

    • histogram of pixel values (uint32)

In addition to the above stats, the imagestats function also defines a hash for each image to be used in conjunction with the Duplicates class in order to identify duplicate images.

Tutorials

To see how the imagestats function can be used while doing exploratory data analysis, check out the EDA Part 1 tutorial.

Exploratory Data Analysis Part 1

How To Guides

There is a how-to guide that applies to the imagestats function.

DataEval API

dataeval.metrics.imagestats(images: Iterable[_SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | bool | int | float | complex | str | bytes | _NestedSequence[bool | int | float | complex | str | bytes]], flags: ImageStat = ImageStat.ALL_STATS) → StatsOutput

Calculates image and pixel statistics for each image

Parameters:

  • images (Iterable[ArrayLike]) – Images to run statistical tests on

  • flags (ImageStat, default ImageStat.ALL_STATS) – Metric(s) to calculate for each image

Return type:

Dict[str, Any]