dataeval.metrics.stats.imagestats¶
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dataeval.metrics.stats.imagestats(dataset: dataeval.typing.Dataset[dataeval.typing.ArrayLike] | dataeval.typing.Dataset[tuple[dataeval.typing.ArrayLike, Any, Any]], *, per_box: bool =
False, per_channel: True) dataeval.outputs.ChannelStatsOutput¶ -
dataeval.metrics.stats.imagestats(dataset: dataeval.typing.Dataset[dataeval.typing.ArrayLike] | dataeval.typing.Dataset[tuple[dataeval.typing.ArrayLike, Any, Any]], *, per_box: bool =
False, per_channel: False =False) dataeval.outputs.ImageStatsOutput Calculates various statistics for each image.
This function computes dimension, pixel and visual metrics on the images or individual bounding boxes for each image as well as label statistics if provided.
See also
dimensionstats,labelstats,pixelstats,visualstats,OutliersExamples
Calculate dimension, pixel and visual statistics for a dataset containing 8 images.
>>> stats = imagestats(dataset) >>> print(stats.aspect_ratio) [1. 1. 1.333 1. 0.667 1. 1. 1. ]>>> print(stats.sharpness) [20.23 20.23 23.33 20.23 77.06 20.23 20.23 20.23]Calculate the pixel and visual stats for a dataset containing 6 3-channel images and 2 1-channel images for a total of 20 channels.
>>> ch_stats = imagestats(dataset, per_channel=True) >>> print(ch_stats.brightness) [0.027 0.152 0.277 0.127 0.135 0.142 0.259 0.377 0.385 0.392 0.508 0.626 0.634 0.642 0.751 0.759 0.767 0.876 0.884 0.892]