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)