def test_pickleable(self):
shape = (16, 16, 3)
image = np.mod(np.arange(int(np.prod(shape))), 256).astype(np.uint8)
image = image.reshape(shape)
with TemporaryDirectory() as folder_path:
path1 = os.path.join(folder_path, "batch_000000.png")
path2 = os.path.join(folder_path, "batch_000010.png")
augmenter = iaa.SaveDebugImageEveryNBatches(folder_path, 10)
augmenter_pkl = pickle.loads(pickle.dumps(augmenter, protocol=-1))
# save two images via augmenter without pickling
for _ in np.arange(20):
_ = augmenter(image=image)
img11 = imageio.imread(path1)
img12 = imageio.imread(path2)
# reset folder content
os.remove(path1)
os.remove(path2)
# save two images via augmenter that was pickled
for _ in np.arange(20):
_ = augmenter_pkl(image=image)
img21 = imageio.imread(path1)
img22 = imageio.imread(path2)
# compare the two images of original/pickled augmenters
assert np.array_equal(img11, img21)
assert np.array_equal(img12, img22)
def chapter_augmenters_savedebugimageeverynbatches():
fn_start = "debug/savedebugimageeverynbatches"
image = ia.quokka_square((128, 128))
bbsoi = ia.quokka_bounding_boxes((128, 128), extract="square")
segmaps = ia.quokka_segmentation_map((128, 128), extract="square")
with tempfile.TemporaryDirectory() as folder_path:
seq = iaa.Sequential([
iaa.Sequential(
[iaa.Fliplr(0.5), iaa.Crop(px=(0, 16))], random_order=True),
iaa.SaveDebugImageEveryNBatches(folder_path, 100)
])
_ = seq(images=[image] * 4,
segmentation_maps=[segmaps] * 4,
bounding_boxes=[bbsoi] * 4)
image_debug_path = os.path.join(folder_path, "batch_latest.png")
image_debug = imageio.imread(image_debug_path)
utils.save("overview_of_augmenters",
fn_start + ".jpg",
image_debug,
quality=95)
def test_temp_directory(self):
with TemporaryDirectory() as folder_path:
image = iarandom.RNG(0).integers(0, 256, size=(256, 256, 3),
dtype=np.uint8)
aug = iaa.SaveDebugImageEveryNBatches(folder_path, 10)
for _ in np.arange(20):
_ = aug(image=image)
expected = iaa.draw_debug_image([image])
path1 = os.path.join(folder_path, "batch_000000.png")
path2 = os.path.join(folder_path, "batch_000010.png")
path_latest = os.path.join(folder_path, "batch_latest.png")
assert len(list(os.listdir(folder_path))) == 3
assert os.path.isfile(path1)
assert os.path.isfile(path2)
assert os.path.isfile(path_latest)
assert np.array_equal(imageio.imread(path1), expected)
assert np.array_equal(imageio.imread(path2), expected)
assert np.array_equal(imageio.imread(path_latest), expected)
def test_mocked(self):
class _DummyDestination(debuglib._IImageDestination):
def __init__(self):
self.received = []
def receive(self, image):
self.received.append(np.copy(image))
image = iarandom.RNG(0).integers(0, 256, size=(256, 256, 3),
dtype=np.uint8)
destination = _DummyDestination()
aug = iaa.SaveDebugImageEveryNBatches(destination, 10)
for _ in np.arange(20):
_ = aug(image=image)
expected = iaa.draw_debug_image([image])
assert len(destination.received) == 2
assert np.array_equal(destination.received[0], expected)
assert np.array_equal(destination.received[1], expected)
def generate_debug():
ia.seed(1)
image = ia.quokka_square((128, 128))
bbsoi = ia.quokka_bounding_boxes((128, 128), extract="square")
segmaps = ia.quokka_segmentation_map((128, 128), extract="square")
with tempfile.TemporaryDirectory() as folder_path:
seq = iaa.Sequential([
iaa.Sequential(
[iaa.Fliplr(0.5), iaa.Crop(px=(0, 16))], random_order=True),
iaa.SaveDebugImageEveryNBatches(folder_path, 100)
])
_ = seq(images=[image] * 4,
segmentation_maps=[segmaps] * 4,
bounding_boxes=[bbsoi] * 4)
image_debug_path = os.path.join(folder_path, "batch_latest.png")
image_debug = imageio.imread(image_debug_path)
_save("savedebugimageeverynbatches.jpg", image_debug)