def test_vessel_number(self):
self.image.reshape_for_landmarks(2)
self.image.threshold_image()
threshold = self.image.get_uint_image()
self.image.skeletonization()
skeleton = self.image.get_uint_image()
self.image.bin_to_bgr()
skeleton_rgb = self.image.get_uint_image()
landmarks, segments = l.potential_landmarks(skeleton, 3)
widths = l.vessel_width(threshold, landmarks)
vessels = l.finding_landmark_vessels(widths, landmarks, skeleton,
skeleton_rgb)
marked_skeleton, final_landmarks = l.vessel_number(
vessels, landmarks, skeleton_rgb)
result_skeleton = np.genfromtxt(self._test_path +
"vessel_number_skeleton_test.csv",
delimiter=',')
result_landmarks = np.genfromtxt(self._test_path +
"vessel_number_filter_test.csv",
delimiter=',')
assert_array_equal(result_skeleton, marked_skeleton[20, :],
"Vessel skeleton does not match")
assert_array_equal(result_landmarks, final_landmarks,
"Vessel final landmarks does not match")
def test_principal_boxes(self):
self.image.reshape_for_landmarks(2)
self.image.threshold_image()
threshold = self.image.get_uint_image()
self.image.skeletonization()
skeleton = self.image.get_uint_image()
self.image.bin_to_bgr()
skeleton_rgb = self.image.get_uint_image()
landmarks, segments = l.potential_landmarks(skeleton, 3)
widths = l.vessel_width(threshold, landmarks)
vessels = l.finding_landmark_vessels(widths, landmarks, skeleton,
skeleton_rgb)
marked_skeleton, final_landmarks = l.vessel_number(
vessels, landmarks, skeleton_rgb)
bifurcations, crossings = l.principal_boxes(marked_skeleton,
final_landmarks, 2)
result = np.genfromtxt(self._test_path + "boxes_bifurcations_test.csv",
delimiter=',')
result2 = np.genfromtxt(self._test_path + "boxes_crossings_test.csv",
delimiter=',')
assert_array_equal(result, bifurcations[0],
"Bifurcation points does not match")
assert_array_equal(result2, crossings[0],
"Crossing points does not match")
def test_vessel_width(self):
self.image.reshape_for_landmarks(2)
self.image.threshold_image()
threshold = self.image.get_uint_image()
self.image.skeletonization()
skeleton = self.image.get_uint_image()
landmarks, segments = l.potential_landmarks(skeleton, 3)
widths = l.vessel_width(threshold, landmarks)
result = np.genfromtxt(self._test_path + "vessel_widths_test.csv",
delimiter=',')
assert_array_equal(result, widths, "Vessel widths does not match")
def _average_width(connected_matrix: np.ndarray, connected: list,
thr_img: np.ndarray, final_image: np.ndarray):
connected_avg = []
for c in connected:
formatted_indexes = _normalize_indexes(connected_matrix, c)
label_widths = l.vessel_width(thr_img, formatted_indexes)
index = int(len(formatted_indexes) / 2)
connected_avg.extend([
_average(label_widths), final_image[formatted_indexes[index][0],
formatted_indexes[index][1]]
])
return connected_avg
def test_finding_landmark_vessels(self):
self.image.reshape_for_landmarks(2)
self.image.threshold_image()
threshold = self.image.get_uint_image()
self.image.skeletonization()
skeleton = self.image.get_uint_image()
self.image.bin_to_bgr()
skeleton_rgb = self.image.get_uint_image()
landmarks, segments = l.potential_landmarks(skeleton, 3)
widths = l.vessel_width(threshold, landmarks)
vessels = l.finding_landmark_vessels(widths, landmarks, skeleton,
skeleton_rgb)
result = np.genfromtxt(self._test_path +
"finding_landmark_vessels_test.csv",
delimiter=',')
assert_array_equal(result, vessels[0],
"Landmark vessels does not match")