def test_get_block_image(self):
chromosome1 = image_utils.read_image(
data_dir + "/chromosome/1/xx_karyotype_001_0.bmp")
chromosome2 = image_utils.read_image(
data_dir + "/chromosome/1/xx_karyotype_001_1.bmp")
image = image_utils.get_block_image([chromosome1, chromosome2], "1")
image_utils.show_image(image)
def image_files_to_bounding_box_csv(image_files,
labels,
csv_dir,
prefix="",
verbose=False):
general_utils.create_directory(csv_dir)
boxes = list()
for image_file in image_files:
image = image_utils.read_image(image_file, cmap="rgb")
box = image_utils.get_chromosome_bounding_box(image)
boxes.append(box)
train_data, val_data, test_data = data_utils.split_multiple_data_lists(
[image_files, boxes, labels])
annotations_train_file = csv_dir + "/" + prefix + "annotations_train.csv"
image_and_bounding_boxes_to_csv(*train_data, annotations_train_file)
annotations_val_file = csv_dir + "/" + prefix + "annotations_val.csv"
image_and_bounding_boxes_to_csv(*val_data, annotations_val_file)
annotations_test_file = csv_dir + "/" + prefix + "annotations_test.csv"
image_and_bounding_boxes_to_csv(*test_data, annotations_test_file)
class_mapping = [[str(i), i] for i in range(len(labels))]
class_mapping_file = csv_dir + "/" + prefix + "class_mapping.csv"
general_utils.write_list_to_csv(class_mapping, class_mapping_file)
if verbose:
print("Train: ", annotations_train_file)
print("Validation: ", annotations_val_file)
print("Test: ", annotations_test_file)
print("Class mapping:", class_mapping_file)
def images_and_centers_to_csv(image_files,
points_list,
annotations_file,
class_mapping_file,
window_radius=1):
temp_image = image_utils.read_image(image_files[0], 0)
image_shape = temp_image.shape[0]
center_points = [[
int(points[0][0] * image_shape),
int(points[0][1] * image_shape)
] for points in points_list]
rect_center_points = [[
x - window_radius, y - window_radius, x + window_radius,
y + window_radius
] for x, y in center_points]
annotations = [[
image_files[idx], rect_center_points[idx][0],
rect_center_points[idx][1], rect_center_points[idx][2],
rect_center_points[idx][3], "center"
] for idx in range(len(image_files))]
class_mapping = [["center", 0]]
general_utils.write_list_to_csv(annotations, annotations_file)
general_utils.write_list_to_csv(class_mapping, class_mapping_file)
def test_rewrite_image(self):
idx = 12
image = image_utils.read_image(
"/home/lntk/Desktop/Karyotype/data/pipeline/karyotype_" +
str(idx) + ".bmp")
cv2.imwrite(
"/home/lntk/Desktop/Karyotype/data/pipeline/karyotype_" +
str(idx) + "_clone.bmp", image)
def _on_file_drop(self, window, file_path):
print("Dropping file ...")
if self.collide_point(*self.mouse_pos):
filePath = file_path.decode("utf-8")
if self.debug:
print(file_path)
self.image.source = filePath
self.image.reload()
self.source = filePath
if self.data is not None:
self.data["image"] = image_utils.read_image(filePath)
print(self.data["image"].shape)
def test_generate_chromosome_cluster(self):
image_dir = data_dir + "/chromosome/1"
image_files = general_utils.get_all_files(image_dir)
num_chromosome = 15
contours = list()
chromosomes = list()
chosen_files = list()
# error_case = ['/home/lntk/Desktop/Karyotype/data/chromosome/1/xx_karyotype_225_0.bmp',
# '/home/lntk/Desktop/Karyotype/data/chromosome/1/xy_karyotype_213_1.bmp',
# '/home/lntk/Desktop/Karyotype/data/chromosome/1/xy_karyotype_190_1.bmp',
# '/home/lntk/Desktop/Karyotype/data/chromosome/1/xx_karyotype_064_0.bmp',
# '/home/lntk/Desktop/Karyotype/data/chromosome/1/xx_karyotype_017_0.bmp',
# '/home/lntk/Desktop/Karyotype/data/chromosome/1/xy_karyotype_055_0.bmp',
# '/home/lntk/Desktop/Karyotype/data/chromosome/1/xy_karyotype_208_0.bmp',
# '/home/lntk/Desktop/Karyotype/data/chromosome/1/xy_karyotype_266_1.bmp',
# '/home/lntk/Desktop/Karyotype/data/chromosome/1/xy_karyotype_132_0.bmp',
# '/home/lntk/Desktop/Karyotype/data/chromosome/1/xy_karyotype_233_1.bmp']
for _ in range(num_chromosome):
""" Randomly get chromosome image from directory """
idx = np.random.randint(len(image_files))
chromosome = image_utils.read_image(image_dir + "/" +
image_files[idx])
chosen_files.append(image_dir + "/" + image_files[idx])
# for image_file in error_case:
# chromosome = image_utils.read_image(image_file)
""" Resize """
chromosome = cv2.resize(chromosome, (64, 64))
""" Rotate """
angle = np.random.randint(90)
rotated_chromosome = image_utils.rotate_image(chromosome, angle)
""" Extract contour """
contour = image_utils.get_chromosome_contour(rotated_chromosome)
contours.append(contour)
chromosomes.append(rotated_chromosome)
print(chosen_files)
contours, boxes, initial_boxes = chromosome_utils.generate_chromosome_cluster(
contours)
for contour in contours:
print(contour.shape)
# silhouette_image = chromosome_utils.get_chromosome_silhouette(contours, boxes)
cluster_image = chromosome_utils.get_chromosome_cluster_image(
boxes, initial_boxes, chromosomes)
image_utils.show_multiple_images([cluster_image])
def images_and_points_to_csv(image_files,
points_list,
annotations_file,
class_mapping_file,
window_radius=1):
num_point = 6
temp_image = image_utils.read_image(image_files[0], 0)
image_shape = temp_image.shape[0]
points = [list() for _ in range(num_point)]
rect_points = [list() for _ in range(num_point)]
for i in range(num_point):
points[i] = [[
int(points[i][0] * image_shape),
int(points[i][1] * image_shape)
] for points in points_list]
rect_points[i] = [[
x - window_radius, y - window_radius, x + window_radius,
y + window_radius
] for x, y in points[i]]
annotations = list()
for image_id in range(len(image_files)):
for point_id in range(6):
annotations.append([
image_files[image_id], rect_points[point_id][image_id][0],
rect_points[point_id][image_id][1],
rect_points[point_id][image_id][2],
rect_points[point_id][image_id][3],
str(point_id)
])
class_mapping = [[str(i), i] for i in range(num_point)]
general_utils.write_list_to_csv(annotations, annotations_file)
general_utils.write_list_to_csv(class_mapping, class_mapping_file)
def read_image(image_file):
return image_utils.read_image(image_file)
def test_remove_chromosomes(self):
image = image_utils.read_image(data_dir + "/test/karyotyping_1.bmp")
image = data_utils.remove_chromosomes(image)
cv2.imwrite(data_dir + "/test/karyotyping_frame.bmp", image)