def test_make_plot(color_space: str, image_channels: str, source_path: str,
reference_path: str) -> None:
params = Params(
{
'color_space': color_space,
'channels': image_channels,
'match_proportion': 0.8,
'src_path': source_path,
'ref_path': reference_path
}
)
converter = build_cs_converter(params.color_space)
source = read_image(params.src_path)
reference = read_image(params.ref_path)
source = converter.convert(source)
reference = converter.convert(reference)
channels = tuple(int(c) for c in params.channels.split(','))
hist_match = HistogramMatching(channels, params.match_proportion)
result = hist_match(source, reference)
file_name = os.path.join(TEST_DIR, 'histogram_matching_plot.png')
images = hm_plot.Images(source, reference, result)
hm_plot.make_plot(file_name, images, converter, params.color_space,
params.channels)
assert os.path.exists(file_name) is True
os.remove(file_name)
def test_read_image() -> None:
expected = np.asarray(Image.open(MUNICH_1_PATH)).astype(
np.float32) / MAX_VALUE_8_BIT
result = read_image(MUNICH_1_PATH)
np.testing.assert_array_equal(result, expected)
with pytest.raises(ValueError):
read_image('no_image.png')
def test_apply_images(source_path: str, reference_path: str,
feature_dist_matching: FeatureDistMatching) -> \
None:
source = read_image(source_path)
reference = read_image(reference_path)
result = feature_dist_matching._apply(source, reference)
assert result.shape == source.shape
assert np.max(result) <= 1.
assert 0.1 < np.mean(result) < 0.9
assert np.min(result) >= 0.
assert result.dtype == np.float32
with np.testing.assert_raises(AssertionError):
np.testing.assert_array_equal(result, source)
with np.testing.assert_raises(AssertionError):
np.testing.assert_array_equal(result, reference)
def test_image_histogram_gray() -> None:
# pylint: disable=protected-access (W0212)
img = read_image(MUNICH_1_GRAY_PATH)
gray_hist = hm_plot._image_histogram_gray(img)
expected_hist = np.histogram(img[:, :, 0], bins=hm_plot._BINS,
range=hm_plot._HIST_RANGE)[0]
assert gray_hist.name == hm_plot._GRAY
np.testing.assert_array_equal(gray_hist.hist, expected_hist)
def test_cdf() -> None:
# pylint: disable=protected-access (W0212)
img = read_image(MUNICH_1_PATH)
expected_values, counts = np.unique(img, return_counts=True)
expected_cdf = np.cumsum(counts).astype(float) / img.size
values, cdf = hm_plot._cdf(img)
np.testing.assert_array_equal(values, expected_values)
np.testing.assert_array_equal(cdf, expected_cdf)
def test_image_histogram_rgb() -> None:
# pylint: disable=protected-access (W0212)
img = read_image(MUNICH_1_PATH)
hist = hm_plot._image_histogram_rgb(img)
assert len(hist) == img.shape[-1]
for channel in range(img.shape[-1]):
expected_hist = np.histogram(img[:, :, channel], bins=hm_plot._BINS,
range=hm_plot._HIST_RANGE)[0]
assert hist[channel].name == hm_plot._HIST_RGB_COLORS[channel]
np.testing.assert_array_equal(hist[channel].hist, expected_hist)
def test_read_image_gray() -> None:
expected = np.asarray(Image.open(MUNICH_1_GRAY_PATH))[:, :, np.newaxis]
expected = expected.astype(np.float32) / MAX_VALUE_8_BIT
result = read_image(MUNICH_1_GRAY_PATH)
np.testing.assert_array_equal(result, expected)
def test_color_check_fail(color_space: str, source: str,
reference: str) -> None:
source_image = read_image(source)
reference_image = read_image(reference)
with pytest.raises(ValueError):
app.color_check(color_space, source_image, reference_image)