NormalizeQuantile#

class deeptrack.math.NormalizeQuantile(quantiles=(0.25, 0.75), featurewise=True, **kwargs)#

Image normalization.

Center the image to the median, and divide by the difference between the quantiles defined by q_max and q_min

Parameters#

quantilestuple (q_min, q_max), 0.0 < q_min < q_max < 1.0: Quantile range to calculate scaling factor
featurewisebool: Whether to normalize each feature independently

Methods Summary

get(image, quantiles, **kwargs)

Transform an image [abstract method].

Methods Documentation

get(image, quantiles, **kwargs)#

Transform an image [abstract method].

Abstract method that defines how the feature transforms the input. The current value of all properties will be passed as keyword arguments.

image‘Image’ or List[‘Image’]: The Image or list of images to transform.
**kwargsDict[str, Any]: The current value of all properties in properties as well as any global arguments.