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#

quantiles: tuple (q_min, q_max), 0.0 < q_min < q_max < 1.0: Quantile range to calculate scaling factor
featurewise: bool: 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: np.ndarray or list of np.ndarray or Image or list of Images: The image or list of images to transform.
**kwargs: dict of str to Any: The current value of all properties in properties, as well as any global arguments passed to the feature.