def test_create_alpha(self):
shape = (5, 5)
expected_alpha = 255 * np.ones((5, 5), dtype=np.uint8)
alpha_from_shape_cimage = io.CImage()
alpha_from_shape_cimage.create_alpha(shape)
np.testing.assert_array_equal(alpha_from_shape_cimage.alpha,
expected_alpha)
band = np.ones((5, 5), dtype=np.uint8)
alpha_from_band_cimage = io.CImage()
alpha_from_band_cimage.bands = [band]
alpha_from_band_cimage.create_alpha()
np.testing.assert_array_equal(alpha_from_band_cimage.alpha,
expected_alpha)
def test_load(self):
input_file = 'test_file.tif'
self._create_image_with_geotransform(input_file)
test_cimage = io.CImage()
test_cimage.load(input_file)
test_geotransform = test_cimage.metadata['geotransform']
self.assertEquals(test_geotransform, (-1.0, 1.0, 0.0, 1.0, 0.0, -1.0))
os.unlink(input_file)
def test_save(self):
output_file = 'test_file.tif'
test_band = 255 * np.ones((5, 5), dtype=np.uint8)
test_cimage = io.CImage()
test_cimage.bands = [test_band]
test_cimage.save(output_file)
test_ds = gdal.Open(output_file)
saved_number_of_bands = test_ds.RasterCount
self.assertEquals(saved_number_of_bands, 1)
saved_band = test_ds.GetRasterBand(1).ReadAsArray()
np.testing.assert_array_equal(saved_band, test_band)
os.unlink(output_file)
def test_convert_to_colorimage(self):
# Create 4-band, 8-bit CImage. Each band has intensity values equal to
# the band number
test_bands = [i * numpy.ones((5, 5), dtype=numpy.uint8) \
for i in range(4)]
test_cimage = io.CImage()
test_cimage.bands = test_bands
# Trying to load a 4-band image should raise an exception
self.assertRaises(colorimage.ImagePropertyException,
colorimage.convert_to_colorimage, test_cimage)
# Specifying 3 bands should allow the 4-band image to be converted
band_indices = [0, 2, 3]
test_colorimage, test_colormask = colorimage.convert_to_colorimage(
test_cimage, band_indices)
# The band indices are read in as RGB but the colorimage is BGR
# so the expected image should have band order that is the reverse
# order of band_indices.
expected_bands = [i * numpy.ones((5, 5), dtype=numpy.uint8) \
for i in reversed(band_indices)]
expected_image = cv2.merge(expected_bands)
numpy.testing.assert_array_equal(test_colorimage, expected_image)
# CImage has no alpha channel so mask should be blank
expected_mask = 255 * numpy.ones((5, 5), dtype=numpy.uint8)
numpy.testing.assert_array_equal(test_colormask, expected_mask)
# Change CImage alpha mask and confirm colorimage mask matches
test_cimage.create_alpha()
test_cimage.alpha[2, 2] = 0
_, test_colormask = colorimage.convert_to_colorimage(
test_cimage, band_indices=band_indices)
expected_mask = 255 * numpy.ones((5, 5), dtype=numpy.uint8)
expected_mask[2, 2] = 0
numpy.testing.assert_array_equal(test_colormask, expected_mask)
# Check that curve_function is applied to image
def test_curve(r, g, b):
return r / 2, g / 2, b / 2
test_colorimage, _ = colorimage.convert_to_colorimage(
test_cimage, band_indices=band_indices, curve_function=test_curve)
expected_bands = [i/2 * numpy.ones((5, 5), dtype=numpy.uint8) \
for i in reversed(band_indices)]
expected_image = cv2.merge(expected_bands)
numpy.testing.assert_array_equal(test_colorimage, expected_image)
# Create 3-band, 16-bit cimage
def numpy_1d_to_3d(numpy_1d):
band = numpy.reshape(numpy_1d, (2, 2))
return [band, band, band]
test_bands = numpy_1d_to_3d(
numpy.array([0, 256, 4095, 65535], dtype=numpy.uint16))
test_cimage = io.CImage()
test_cimage.bands = test_bands
# No bit depth provided, should assume all 16 bits are used and divide
# by 256 and mask should be blank
test_colorimage, test_colormask = colorimage.convert_to_colorimage(
test_cimage)
expected = numpy_1d_to_3d(
numpy.array([0, 1, 15, 255], dtype=numpy.uint8))
expected_image = cv2.merge(expected)
numpy.testing.assert_array_equal(test_colorimage, expected_image)
expected_mask = 255 * numpy.ones((2, 2), dtype=numpy.uint8)
numpy.testing.assert_array_equal(test_colormask, expected_mask)
# If bit depth of 12 is provided, the values should be scaled by 2**4
# and pixels with values above 2**12 should be masked
test_colorimage, test_colormask = colorimage.convert_to_colorimage(
test_cimage, bit_depth=2**12)
expected = numpy_1d_to_3d(
numpy.array([0, 16, 255, 255], dtype=numpy.uint8))
expected_image = cv2.merge(expected)
numpy.testing.assert_array_equal(test_colorimage, expected_image)
expected_mask = numpy.reshape(
numpy.array([255, 255, 255, 0], dtype=numpy.uint8), (2, 2))
numpy.testing.assert_array_equal(test_colormask, expected_mask)
# Check that curve_function downsampling is applied to bands and avoids
# further bit decimation
def test_curve(r, g, b):
r = (r / 2**8).astype(numpy.uint8)
g = (g / 2**8).astype(numpy.uint8)
b = (b / 2**8).astype(numpy.uint8)
return r, g, b
test_colorimage, _ = colorimage.convert_to_colorimage(
test_cimage, curve_function=test_curve)
expected_bands = numpy_1d_to_3d(
numpy.array([0, 1, 15, 255], dtype=numpy.uint8))
expected_image = cv2.merge(expected_bands)
numpy.testing.assert_array_equal(test_colorimage, expected_image)