def test_create_windows(self):
# test with an empty image
self.assertRaises(ValueError, retina.Window, self._retina_image, 8)
# test with a full data image
self._retina_image.np_image[:, :] = 1
windows = retina.Window(self._retina_image, 8)
self.assertEqual(windows.windows.shape[0], self._image_size, "expected 64 windows")
# test with an image half filled with data
self._retina_image.np_image[:, 0:int(self._image_size/2)] = 0
windows = retina.Window(self._retina_image, 8)
self.assertEqual(windows.windows.shape[0], self._image_size/2, "expected 32 windows")
def test_set_tag_layer(self):
image = retina.Retina(None, _image_path)
image.reshape_by_window(56)
window = retina.Window(image, 56, min_pixels=10)
tags = np.full([window.shape[0], 4], 100)
tags[:, 3] = 50
window.tags = tags
window.set_tag_layer()
def test_mode(self):
window = retina.Window(self._retina_image, 8, min_pixels=0)
assert_array_equal(window.shape, [64, 1, 8, 8], "window shape is incorrect")
window.mode = window.mode_tensorflow
assert_array_equal(window.shape, [64, 8, 8, 1], "window shape is incorrect")
window.mode = window.mode_pytorch
assert_array_equal(window.shape, [64, 1, 8, 8], "window shape is incorrect")
def test_create_windows_combined(self):
windows = retina.Window(self._retina_image, 8, "combined", 0)
# combined should create (width/(dimension/2) - 1) * (height/(dimension/2) -1)
# here is (64/4 -1) * (64/4 -1) = 225
self.assertEqual(windows.windows.shape[0], 225, "there should be 225 windows created")
# fail with no window created
self.assertRaises(ValueError, retina.Window, self._retina_image, 8, "combined")
def test_iterator(self):
image = retina.Retina(None, _image_path)
image.reshape_by_window(56)
windows = retina.Window(image, 56, min_pixels=10)
size = windows.windows.shape[0]
iterated_size = 0
for _ in windows:
iterated_size += 1
self.assertEqual(size, iterated_size, "iterated structure size does not match")
for window in windows:
assert_array_equal(window, windows.windows[0])
break
def density(image: np.ndarray,
window_size: int = 10,
min_pixels: int = 10,
creation_method: str = "separated",
threshold: float = 0.97) -> dict:
image = retina.Retina(image, "tortuosity_density")
dimension = image.reshape_by_window(window_size, True)
image.threshold_image()
image.skeletonization()
windows = retina.Window(image,
dimension,
min_pixels=min_pixels,
method=creation_method)
evaluation = \
{
"uri": "tortuosity_density",
"data": [],
# "image": image.original_base64 # TODO: maybe return a processed image?
}
for i in range(0, windows.shape[0]):
window = windows.windows[i, 0]
w_pos = windows.w_pos[i]
image = retina.Retina(window, "td")
vessels = retina.detect_vessel_border(image)
processed_vessel_count = 0
for vessel in vessels:
if len(vessel[0]) > 10:
processed_vessel_count += 1
tortuosity_density = tortuosity_measures.tortuosity_density(
vessel[0], vessel[1])
if tortuosity_density > threshold:
evaluation["data"].append(
_tortuosity_window(
w_pos[0, 0].item(), w_pos[0, 1].item(),
w_pos[1, 0].item(), w_pos[1, 1].item(),
"{0:.2f}".format(tortuosity_density)))
return evaluation
def test_set_tag_layer_tags_not_set(self):
image = retina.Retina(None, _image_path)
image.reshape_by_window(56)
window = retina.Window(image, 56, min_pixels=10)
with self.assertRaises(ValueError):
window.set_tag_layer()
def test_tags_wrong_input(self):
window = retina.Window(self._retina_image, 8, min_pixels=0)
with self.assertRaises(ValueError):
tags = np.zeros([1, 4])
window.tags = tags
def test_tags(self):
window = retina.Window(self._retina_image, 8, min_pixels=0)
tags = np.zeros([window.shape[0], 4])
window.tags = tags
assert_array_equal(tags, window.tags, "tags does not match")
def test_save_window_wrong_id(self):
self._retina_image.np_image[:, :] = 1
window = retina.Window(self._retina_image, 8, min_pixels=0)
self.assertRaises(ValueError, window.save_window, 80, "./")
def test_save_window(self):
self._retina_image.np_image[:, :] = 1
window = retina.Window(self._retina_image, 8, min_pixels=0)
window.save_window(1, "./")
self.assertTrue(os.path.isfile(window._window_filename(1)), "file not found")
os.unlink(window._window_filename(1))
from retipy import configuration, retina, tortuosity_measures
parser = argparse.ArgumentParser()
parser.add_argument("-c",
"--configuration",
help="the configuration file location",
default="resources/retipy.config")
args = parser.parse_args()
CONFIG = configuration.Configuration(args.configuration)
for filename in sorted(glob.glob(os.path.join(CONFIG.image_directory,
'*.png'))):
print("processing {}...".format(filename))
segmentedImage = retina.Retina(None, filename)
segmentedImage.threshold_image()
segmentedImage.reshape_square()
window_sizes = segmentedImage.get_window_sizes()
window = retina.Window(segmentedImage,
window_sizes[-1],
min_pixels=CONFIG.pixels_per_window)
tortuosity_measures.evaluate_window(window, CONFIG.pixels_per_window,
CONFIG.sampling_size,
CONFIG.r_2_threshold)
hf = h5py.File(
CONFIG.output_folder + "/" + segmentedImage.filename + ".h5", 'w')
hf.create_dataset('windows', data=window.windows)
hf.create_dataset('tags', data=window.tags)
hf.close()
