def test_random_choice_exception_random_crop_badinput():
"""
Test RandomChoice: hit error in RandomCrop with greater crop size,
expected to raise error
"""
logger.info("test_random_choice_exception_random_crop_badinput")
# define map operations
# note: crop size[5000, 5000] > image size[4032, 2268]
transforms_list = [py_vision.RandomCrop(5000)]
transforms = [
py_vision.Decode(),
py_vision.RandomChoice(transforms_list),
py_vision.ToTensor()
]
transform = py_vision.ComposeOp(transforms)
# Generate dataset
data = ds.TFRecordDataset(DATA_DIR,
SCHEMA_DIR,
columns_list=["image"],
shuffle=False)
data = data.map(input_columns=["image"], operations=transform())
try:
_ = data.create_dict_iterator().get_next()
except RuntimeError as e:
logger.info("Got an exception in DE: {}".format(str(e)))
assert "Crop size" in str(e)
def test_random_choice_comp(plot=False):
"""
Test RandomChoice and compare with single CenterCrop results
"""
logger.info("test_random_choice_comp")
# define map operations
transforms_list = [py_vision.CenterCrop(64)]
transforms1 = [
py_vision.Decode(),
py_vision.RandomChoice(transforms_list),
py_vision.ToTensor()
]
transform1 = py_vision.ComposeOp(transforms1)
transforms2 = [
py_vision.Decode(),
py_vision.CenterCrop(64),
py_vision.ToTensor()
]
transform2 = py_vision.ComposeOp(transforms2)
# First dataset
data1 = ds.TFRecordDataset(DATA_DIR,
SCHEMA_DIR,
columns_list=["image"],
shuffle=False)
data1 = data1.map(input_columns=["image"], operations=transform1())
# Second dataset
data2 = ds.TFRecordDataset(DATA_DIR,
SCHEMA_DIR,
columns_list=["image"],
shuffle=False)
data2 = data2.map(input_columns=["image"], operations=transform2())
image_choice = []
image_original = []
for item1, item2 in zip(data1.create_dict_iterator(),
data2.create_dict_iterator()):
image1 = (item1["image"].transpose(1, 2, 0) * 255).astype(np.uint8)
image2 = (item2["image"].transpose(1, 2, 0) * 255).astype(np.uint8)
image_choice.append(image1)
image_original.append(image2)
mse = diff_mse(image1, image2)
assert mse == 0
if plot:
visualize_list(image_original, image_choice)