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