def test_img_conversion():
img = load_image(data_path("example.jpeg"))
annotation = AnnotatedImage.from_image(img)
image_np = annotation.to_numpy()
assert isinstance(image_np, np.ndarray)
assert image_np.shape == (375, 500, 3)
image_pil = annotation.to_pillow()
assert image_pil.width == 500
assert image_pil.height == 375
def check_image_equality(image: np.ndarray,
path: str,
color_mode="rgb",
delta=None):
reference = load_image(data_path(path), color_mode=color_mode)
if delta is None:
assert (image == reference).all()
else:
assert np.allclose(image[:, :], reference[:, :], rtol=delta)
def test_image_loader():
images = [
data_path("dataset/1.jpeg"),
data_path("dataset/2.jpeg"),
data_path("dataset/3.jpeg"),
]
loader = ImageLoader(images)
assert len(loader) == len(images)
for (image_path, (path, img)) in zip(images, loader):
assert image_path == path
assert np.all(load_image(path) == img)
def test_overlay_masks():
masks = [
load_image(data_path(f"segmentation/color_masks/mask-{i}.png"))
for i in range(4)
]
background = np.zeros((100, 100, 3), dtype=np.uint8)
check_image_equality(
overlay_masks(background, masks, alpha=1.0),
data_path("segmentation/color_masks/overlay-alpha-1.0.png"),
delta=0.001,
)
check_image_equality(
overlay_masks(background, masks, alpha=0.5),
data_path("segmentation/color_masks/overlay-alpha-0.5.png"),
delta=0.001,
)
def test_annotated_image_wrong_image_shape():
img = load_image(data_path("example.jpeg"))
with pytest.raises(Exception):
AnnotatedImage(image=img, size=(100, 100))
def test_annotated_image_shape_from_image():
img = load_image(data_path("example.jpeg"))
annotation = AnnotatedImage.from_image(img)
assert annotation.width == 500
assert annotation.height == 375
def test_load_image_normalize():
img = load_image(data_path("example.jpeg"), normalize=True)
assert np.max(img) <= 1.0
def test_load_image_resize_non_uniform():
img = load_image(data_path("example.jpeg"), target_size=(256, 512))
assert img.shape == (512, 256, 3)
def test_load_image_resize():
img = load_image(data_path("example.jpeg"), target_size=(224, 224))
assert img.shape == (224, 224, 3)
def test_load_image_grayscale():
img = load_image(data_path("example.jpeg"), color_mode="grayscale")
assert img.shape == (375, 500)
def test_load_image_bgr():
img2 = load_image(data_path("example.jpeg"), color_mode="bgr")
check_image_equality(cv2.cvtColor(img2, cv2.COLOR_BGR2RGB),
data_path("example.jpeg"))
def test_load_image_rgb():
img = load_image(data_path("example.jpeg"))
assert img.shape == (375, 500, 3)
assert np.max(img) > 1.0