scikit-image

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import numpy as np
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from skimage import data, filters, measure
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try:
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    from skimage.measure._regionprops import PROP_VALS
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except ImportError:
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    PROP_VALS = []
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def init_regionprops_data():
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    image = filters.gaussian(data.coins().astype(float), sigma=3)
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    # increase size to (2048, 2048) by tiling
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    image = np.tile(image, (4, 4))
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    label_image = measure.label(image > 130, connectivity=image.ndim)
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    intensity_image = image
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    return label_image, intensity_image
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class RegionpropsTableIndividual:
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    param_names = ['prop']
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    params = sorted(list(PROP_VALS))
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    def setup(self, prop):
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        try:
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            from skimage.measure import regionprops_table  # noqa
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        except ImportError:
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            # regionprops_table was introduced in scikit-image v0.16.0
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            raise NotImplementedError("regionprops_table unavailable")
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        self.label_image, self.intensity_image = init_regionprops_data()
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    def time_single_region_property(self, prop):
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        measure.regionprops_table(
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            self.label_image, self.intensity_image, properties=[prop], cache=True
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        )
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    # omit peakmem tests to save time (memory usage was minimal)
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class RegionpropsTableAll:
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    param_names = ['cache']
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    params = (False, True)
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    def setup(self, cache):
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        try:
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            from skimage.measure import regionprops_table  # noqa
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        except ImportError:
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            # regionprops_table was introduced in scikit-image v0.16.0
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            raise NotImplementedError("regionprops_table unavailable")
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        self.label_image, self.intensity_image = init_regionprops_data()
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    def time_regionprops_table_all(self, cache):
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        measure.regionprops_table(
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            self.label_image, self.intensity_image, properties=PROP_VALS, cache=cache
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        )
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    # omit peakmem tests to save time (memory usage was minimal)
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class MomentsSuite:
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    params = (
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        [(64, 64), (4096, 2048), (32, 32, 32), (256, 256, 192)],
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        [np.uint8, np.float32, np.float64],
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        [1, 2, 3],
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    )
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    param_names = ['shape', 'dtype', 'order']
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    """Benchmark for filter routines in scikit-image."""
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    def setup(self, shape, dtype, *args):
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        rng = np.random.default_rng(1234)
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        if np.dtype(dtype).kind in 'iu':
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            self.image = rng.integers(0, 256, shape, dtype=dtype)
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        else:
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            self.image = rng.standard_normal(shape, dtype=dtype)
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    def time_moments_raw(self, shape, dtype, order):
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        measure.moments(self.image)
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    def time_moments_central(self, shape, dtype, order):
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        measure.moments_central(self.image)
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    def peakmem_reference(self, shape, dtype, order):
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        pass
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    def peakmem_moments_central(self, shape, dtype, order):
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        measure.moments_central(self.image)
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