def test_wavelet_transformations(self):
""" Test all the registered transformations.
"""
for image in self.images:
print("Process test with image '{0}'...".format(
image.metadata["path"]))
for nb_scale in self.nb_scales:
print("- Number of scales: {0}".format(nb_scale))
for transform in self.transforms:
print(" Transform: {0}".format(transform))
transform = transform(nb_scale=nb_scale, verbose=0)
self.assertFalse(transform.use_wrapping)
transform.info
transform.data = image
transform.analysis()
# transform.show()
recim = transform.synthesis()
# recim.show()
mismatch = (1. - numpy.mean(
numpy.isclose(
recim.data, image.data, atol=1e-8, rtol=1e-5)))
print(" mismatch = ", mismatch)
print(" analysis = ",
[band.shape for band in transform.analysis_data],
len(transform.analysis_data))
print(" bands = ", transform.nb_band_per_scale)
print(" synthesis = ", recim.shape)
def test_speed(self):
""" Test the bindings time advantages.
"""
# With/without bindings
for strategy, name in ((True, "Without"), (False, "With")):
tic = time.time()
transform = pysap.load_transform(
"LinearWaveletTransformATrousAlgorithm")
transform = transform(nb_scale=4, verbose=0)
transform.use_wrapping = strategy
transform.data = self.images[0]
for i in range(self.nb_iter):
transform.analysis()
recim = transform.synthesis()
toc = time.time()
print("[result] {0} bindings execution time: {1}.".format(
name, toc - tic))
def test_wavelet_transformations(self):
""" Test all the registered transformations.
"""
for image_i in self.images:
print("Process test with image '{0}'...".format(
image_i.metadata["path"]))
for nb_scale in self.nb_scales:
print("- Number of scales: {0}".format(nb_scale))
for transform in self.transforms:
print(" Transform: {0}".format(transform))
if transform.__family__ == "isap-2d":
transform = transform(nb_scale=nb_scale,
verbose=0,
padding_mode="symmetric")
else:
transform = transform(nb_scale=nb_scale, verbose=0)
image = numpy.copy(image_i)
if transform.data_dim == 3:
image = image[64:192, 64:192]
image = numpy.tile(image, (image.shape[0], 1, 1))
transform.data = image
else:
transform.data = image
self.assertFalse(transform.use_wrapping)
transform.info
transform.analysis()
# transform.show()
recim = transform.synthesis()
# recim.show()
mismatch = (1. - numpy.mean(
numpy.isclose(recim.data, image, atol=1e-8,
rtol=1e-5)))
print(" mismatch = ", mismatch)
print(" analysis = ",
[band.shape for band in transform.analysis_data],
len(transform.analysis_data))
print(" bands = ", transform.nb_band_per_scale)
print(" synthesis = ", recim.shape)
