def image_distances(distance_function, image1, image2):
'''Measures the distance between the histogram of corresponding bands in
two images. '''
bands1 = cv2.split(image1)
bands2 = cv2.split(image2)
assert len(bands1) == len(bands2)
dist = []
for band1, band2 in zip(bands1, bands2):
dist.append(distance_function(
ci.get_histogram(band1), ci.get_histogram(band2)))
return dist
def test_get_histogram(self):
test_band = numpy.array([[1, 1], [1, 1]], dtype=numpy.uint8)
test_mask = numpy.array([[255, 0], [255, 0]], dtype=numpy.uint8)
# All entries at intensity 1
expected = numpy.zeros((256), dtype=numpy.int)
expected[1] = 4
hist = colorimage.get_histogram(test_band)
numpy.testing.assert_array_equal(hist, expected)
# Two values masked, count should drop by two
expected = numpy.zeros((256), dtype=numpy.int)
expected[1] = 2
hist = colorimage.get_histogram(test_band, mask=test_mask)
numpy.testing.assert_array_equal(hist, expected)
def test_get_histogram(self):
test_band = numpy.array([[1, 1], [1, 1]], dtype=numpy.uint8)
test_mask = numpy.array([[255, 0], [255, 0]], dtype=numpy.uint8)
# All entries at intensity 1
expected = numpy.zeros((256), dtype=numpy.int)
expected[1] = 4
hist = colorimage.get_histogram(test_band)
numpy.testing.assert_array_equal(hist, expected)
# Two values masked, count should drop by two
expected = numpy.zeros((256), dtype=numpy.int)
expected[1] = 2
hist = colorimage.get_histogram(test_band, mask=test_mask)
numpy.testing.assert_array_equal(hist, expected)
def image_distances(distance_function, image1, image2):
"""
Measures the distance between the histogram of corresponding bands in
two images.
"""
shape1 = image1.shape
shape2 = image2.shape
assert shape1[2] == shape2[2]
bands1 = [image1[:, :, bidx] for bidx in range(shape1[2])]
bands2 = [image2[:, :, bidx] for bidx in range(shape2[2])]
dist = []
for band1, band2 in zip(bands1, bands2):
dist.append(distance_function(ci.get_histogram(band1), ci.get_histogram(band2)))
return dist
def image_distances(distance_function, image1, image2):
"""
Measures the distance between the histogram of corresponding bands in
two images.
"""
shape1 = image1.shape
shape2 = image2.shape
assert shape1[2] == shape2[2]
bands1 = [ image1[:, :, bidx] for bidx in range(shape1[2]) ]
bands2 = [ image2[:, :, bidx] for bidx in range(shape2[2]) ]
dist = []
for band1, band2 in zip(bands1, bands2):
dist.append(distance_function(
ci.get_histogram(band1), ci.get_histogram(band2)))
return dist
def test_get_histogram(self):
test_band = np.array([
[1, 1],
[1, 1]
], dtype=np.uint8)
test_mask = np.array([
[255, 0],
[255, 0]
], dtype=np.uint8)
# All entries at intensity 1
expected = np.zeros(255, dtype=np.int)
expected[1] = 4
hist = colorimage.get_histogram(test_band)
np.testing.assert_array_equal(hist, expected)
expected = np.zeros(255, dtype=np.int)
expected[1] = 2
hist = colorimage.get_histogram(test_band, mask=test_mask)
np.testing.assert_array_equal(hist, expected)
test_band = np.array([
[0, 1],
[2, 3]
], dtype=np.uint8)
test_mask = np.array([
[False, True],
[False, True]
], dtype=bool)
expected = np.zeros(255, dtype=np.int)
expected[0] = 1
expected[2] = 1
hist = colorimage.get_histogram(test_band, mask=test_mask)
np.testing.assert_array_equal(expected, hist)
def test_get_histogram(self):
test_band = np.array([[1, 1], [1, 1]], dtype=np.uint8)
test_mask = np.array([[255, 0], [255, 0]], dtype=np.uint8)
# All entries at intensity 1
expected = np.zeros(255, dtype=np.int)
expected[1] = 4
hist = colorimage.get_histogram(test_band)
np.testing.assert_array_equal(hist, expected)
expected = np.zeros(255, dtype=np.int)
expected[1] = 2
hist = colorimage.get_histogram(test_band, mask=test_mask)
np.testing.assert_array_equal(hist, expected)
test_band = np.array([[0, 1], [2, 3]], dtype=np.uint8)
test_mask = np.array([[False, True], [False, True]], dtype=bool)
expected = np.zeros(255, dtype=np.int)
expected[0] = 1
expected[2] = 1
hist = colorimage.get_histogram(test_band, mask=test_mask)
np.testing.assert_array_equal(expected, hist)
