def update_chromosome_orientation(self):
rotate_image_object = rotate_image.RotateImage()
compute_projection_vector_object = compute_projection_vector.ComputeProjectionVector(
)
rotate_image_object.rotate_image(self.img_path, self.current_angle)
self.best_image_path = rotate_image_object.get_output_image_path()
self.best_horizontal_projection_vector = \
compute_projection_vector_object.get_horizontal_projection_vector(self.img_path)
self.best_vertical_projection_vector = \
compute_projection_vector_object.get_vertical_projection_vector(self.img_path)
self.best_score = \
self.get_orientation_score(self.best_horizontal_projection_vector, self.best_vertical_projection_vector)
for self.current_angle in range(10, 180, 5):
rotate_image_object.rotate_image(self.img_path, self.current_angle)
rotated_image_path = rotate_image_object.get_output_image_path()
horizontal_projection_vector = \
compute_projection_vector_object.get_horizontal_projection_vector(rotated_image_path)
vertical_projection_vector = \
compute_projection_vector_object.get_vertical_projection_vector(rotated_image_path)
score = self.get_orientation_score(horizontal_projection_vector,
vertical_projection_vector)
if score < self.best_score:
self.best_horizontal_projection_vector = horizontal_projection_vector
self.best_vertical_projection_vector = vertical_projection_vector
self.best_score = score
self.best_image_path = rotated_image_path
self.best_angle = self.current_angle
def handle_one_image(self, image_path, straighten=True):
self.ready_dir = self.get_or_create_ready_dir(image_path)
if self.check_if_curved.is_curved(image_path):
for self.current_angle in range(0, 180, 5):
rotate_image_obj = rotate_image.RotateImage()
rotate_image_obj.rotate_image(image_path, self.current_angle)
rotated_image_path = rotate_image_obj.get_output_image_path()
compute_projection_vector_obj = compute_projection_vector.ComputeProjectionVector(
)
h_vector = compute_projection_vector_obj.get_horizontal_projection_vector(
rotated_image_path)
score, min_position = self.__compute_horizontal_vector_score(
h_vector)
if score < self.best_score:
self.best_score = score
self.best_angle = self.current_angle
self.best_min_position = min_position
self.best_image_path = rotated_image_path
if straighten:
self.straighten_curved_chromosome.straight_curved_chromosome(
self.best_image_path, self.best_min_position,
self.ready_dir)
else:
shutil.copy2(self.best_image_path, self.ready_dir)
return True
else:
shutil.copy2(image_path, self.ready_dir)
return False
def straight_half_chromosome(self, img_path):
rotate_image_object = rotate_image.RotateImage()
compute_projection_vector_object = compute_projection_vector.ComputeProjectionVector(
)
best_angle = 0
rotate_image_object.rotate_image(img_path, best_angle)
best_image_path = rotate_image_object.get_output_image_path()
best_horizontal_projection_vector = compute_projection_vector_object.get_horizontal_projection_vector(
img_path)
best_vertical_projection_vector = compute_projection_vector_object.get_vertical_projection_vector(
img_path)
best_score = self.get_orientation_score(
best_horizontal_projection_vector, best_vertical_projection_vector)
for current_angle in range(0, 180, 5):
rotate_image_object.rotate_image(img_path, current_angle)
rotated_image_path = rotate_image_object.get_output_image_path()
horizontal_projection_vector = \
compute_projection_vector_object.get_horizontal_projection_vector(rotated_image_path)
vertical_projection_vector = \
compute_projection_vector_object.get_vertical_projection_vector(rotated_image_path)
score = self.get_orientation_score(horizontal_projection_vector,
vertical_projection_vector)
if score < best_score:
best_score = score
best_image_path = rotated_image_path
best_angle = current_angle
print("Best angle = %d" % best_angle)
if best_score < math.inf:
print("Best score = %d" % best_score)
print("Best image path = %s" % best_image_path)
return best_image_path, best_angle
def __extract_short_chromatid_ratio_feature_old(self):
for file in self.get_all_images():
compute_projection_vector_obj = compute_projection_vector.ComputeProjectionVector(
)
h_vector = compute_projection_vector_obj.get_horizontal_projection_vector(
file)
min_position = self.__compute_horizontal_vector_score(h_vector)
chromosome_len = self.features[file][CHROMOSOME_LEN_KEY]
short_chromatid_len = min(min_position,
chromosome_len - min_position)
self.features[file][
SHORT_CHROMATID_RATIO_KEY] = short_chromatid_len / chromosome_len
self.features[file][CENTROMERE_POSITION_KEY] = min_position
def is_curved(self, image_to_check_path):
self.image_path = image_to_check_path
image = common_operations.read_image(self.image_path)
compute_projection_vector_obj = compute_projection_vector.ComputeProjectionVector(
)
h_vector = compute_projection_vector_obj.get_horizontal_projection_vector(
self.image_path)
ch_area = sum(h_vector)
total_area = image.shape[0] * image.shape[1]
proc = ch_area / total_area
if proc < 0.6:
return True
return False
def __compute_centromere_position(self):
for self.current_angle in range(0, 180, 5):
rotate_image_obj = rotate_image.RotateImage()
rotate_image_obj.rotate_image(self.image_path, self.current_angle)
rotated_image_path = rotate_image_obj.get_output_image_path()
compute_projection_vector_obj = compute_projection_vector.ComputeProjectionVector(
)
h_vector = compute_projection_vector_obj.get_horizontal_projection_vector(
rotated_image_path)
score, min_position = self.__compute_horizontal_vector_score(
h_vector)
if score < self.best_score:
self.best_score = score
self.best_angle = self.current_angle
self.best_min_position = min_position
self.best_image_path = rotated_image_path
def __init__(self):
self.compute_projection_vector_obj = compute_projection_vector.ComputeProjectionVector(
)