def test_return_type(self, img, pipeline_):
r = pipeline_.run(img)
assert isinstance(r, tuple)
assert len(r) == 2
out, ctx = r
assert is_image(out)
assert isinstance(ctx, PipelineContext)
def _raise_if_invalid_img(img: Image, returned_from: Optional[str] = None):
if not utils.is_image(img):
message = 'Invalid image'
if returned_from is not None:
message += f' returned from "{returned_from}"'
message += f': {img}'
raise BadImageError(message)
def __init__(self, original_img: Image):
if not is_image(original_img):
raise ValueError('Invalid original image')
self.original_img = original_img.copy()
self.original_img.flags.writeable = False
self._scopes = list()
self.info = dict()
def img2QImage(img: np.ndarray) -> QImage:
if not is_image(img):
raise ValueError('Invalid image')
# Using straight numpy here just so we don't have a direct dependency on opencv
if img.ndim == 2:
img = np.repeat(img[..., None], 3, axis=2)
else:
img = img[..., ::-1].copy(
) # QImage doesn't accept a memoryview. So we make a copy
height, width, _ = img.shape
bytes_per_line = 3 * width
qimg = QImage(img.data, width, height, bytes_per_line,
QImage.Format_RGB888)
return qimg
def test_is_image_valid(img):
assert is_image(img)
def test_is_image_random_object():
assert not is_image(object())
def test_is_image_none():
assert not is_image(None)
def test_is_image_invalid(img):
assert not is_image(img)