def test_black_white_conversion_2x3dshape():
lung = ami.load_images(image_path,
convert_to_grey=True,
image_size=30,
keep_3d_shape=True)[0]
assert lung.shape == (30, 30, 1)
lung = conv.to_blackwhite([lung], keep_3d_shape=True, threshold=200)
assert lung[0].shape == (30, 30, 1)
def test_black_white_conversion_double_arrays():
image_list = ami.load_images(image_path)
test_list = list()
for img in image_list:
test_list.append(img / 255)
ls = conv.to_blackwhite(np.array(test_list))
pixel_value = ls[0][0][0]
assert pixel_value == 0 or pixel_value == 1
def test_black_white_conversion_3dshape():
image_list = ami.load_images(image_path)
ls = conv.to_blackwhite(image_list, keep_3d_shape=True)
pixel_value = ls[0][0][0]
assert pixel_value == 0 or pixel_value == 1
assert len(ls[0].shape) == 3
def test_crop_image():
image = ami.load_images(image_path, max_images=1, image_size=50)[0]
crop = conv.crop(image, 10, 20, 20, 10)
assert crop.shape == (10, 20, 3)
def test_load_images_extensions():
image_list = ami.load_images(image_path, valid_extensions=['.gif'])
assert len(image_list) == 0
def test_load_images_grey():
image_list = ami.load_images(image_path, image_size=40, max_images=1, convert_to_grey=True)
assert image_list[0].shape == (40, 40)
assert len(image_list) == 1
def test_load_images_grey_dont_keep_shape():
image_list = ami.load_images(image_path, image_size=40, max_images=1, convert_to_grey=True, keep_3d_shape=False)
assert image_list[0].shape == (40, 40)
assert len(image_list) == 1
def test_load_images_max_number():
image_list = ami.load_images(image_path, max_images=4)
assert len(image_list) == 4
def test_load_images_resize_tuple():
image_list = ami.load_images(image_path, image_size=(40, 30), max_images=1)
assert len(image_list) == 1
assert image_list[0].shape == (40, 30, 3)
def test_load_images_defaults():
image_list = ami.load_images(image_path)
assert len(image_list) == 11
def test_show_3d_shape_image():
lungs = imgio.load_images(image_path_1, convert_to_grey=True, keep_3d_shape=True)
#X = conversion.to_blackwhite(X, keep_3d_shape=True, threshold=200)
exp.show_image(lungs[1])
def test_visualize_oneset_images():
lungs = imgio.load_images(image_path_1)
exp.visualize({'lungs': lungs}, image_count = 6, randomize=True)
def test_visualize_3d_shape_images():
lungs = imgio.load_images(image_path_1, convert_to_grey=True, keep_3d_shape=True)
masks = imgio.load_images(image_path_2, convert_to_grey=True, keep_3d_shape=True)
exp.visualize({'lungs': lungs, 'masks': masks}, image_count = 6, randomize=True)
def test_visualize_first_images():
lungs = imgio.load_images(image_path_1)
masks = imgio.load_images(image_path_2)
exp.visualize({'lungs': lungs, 'masks': masks}, image_count = 6, randomize=False)