def test_random_grayscale_valid_prob(plot=False):
"""
Test RandomGrayscale Op: valid input, expect to pass
"""
logger.info("test_random_grayscale_valid_prob")
# First dataset
data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
transforms1 = [
py_vision.Decode(),
# Note: prob is 1 so the output should always be grayscale images
py_vision.RandomGrayscale(1),
py_vision.ToTensor()
]
transform1 = py_vision.ComposeOp(transforms1)
data1 = data1.map(input_columns=["image"], operations=transform1())
# Second dataset
data2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
transforms2 = [
py_vision.Decode(),
py_vision.ToTensor()
]
transform2 = py_vision.ComposeOp(transforms2)
data2 = data2.map(input_columns=["image"], operations=transform2())
image_gray = []
image = []
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_gray.append(image1)
image.append(image2)
if plot:
visualize_list(image, image_gray)
def test_random_grayscale_md5_no_param():
"""
Test RandomGrayscale with md5 comparison: no parameter given, expect to pass
"""
logger.info("test_random_grayscale_md5_no_param")
original_seed = config_get_set_seed(0)
original_num_parallel_workers = config_get_set_num_parallel_workers(1)
# Generate dataset
data = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
transforms = [
py_vision.Decode(),
py_vision.RandomGrayscale(),
py_vision.ToTensor()
]
transform = py_vision.ComposeOp(transforms)
data = data.map(input_columns=["image"], operations=transform())
# Check output images with md5 comparison
filename = "random_grayscale_02_result.npz"
save_and_check_md5(data, filename, generate_golden=GENERATE_GOLDEN)
# Restore config
ds.config.set_seed(original_seed)
ds.config.set_num_parallel_workers(original_num_parallel_workers)
def test_random_grayscale_input_grayscale_images():
"""
Test RandomGrayscale Op: valid parameter with grayscale images as input, expect to pass
"""
logger.info("test_random_grayscale_input_grayscale_images")
original_seed = config_get_set_seed(0)
original_num_parallel_workers = config_get_set_num_parallel_workers(1)
# First dataset
data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
transforms1 = [
py_vision.Decode(),
py_vision.Grayscale(1),
# Note: If the input images is grayscale image with 1 channel.
py_vision.RandomGrayscale(0.5),
py_vision.ToTensor()
]
transform1 = py_vision.ComposeOp(transforms1)
data1 = data1.map(input_columns=["image"], operations=transform1())
# Second dataset
data2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
transforms2 = [
py_vision.Decode(),
py_vision.ToTensor()
]
transform2 = py_vision.ComposeOp(transforms2)
data2 = data2.map(input_columns=["image"], operations=transform2())
image_gray = []
image = []
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_gray.append(image1)
image.append(image2)
assert len(image1.shape) == 3
assert image1.shape[2] == 1
assert len(image2.shape) == 3
assert image2.shape[2] == 3
# Restore config
ds.config.set_seed(original_seed)
ds.config.set_num_parallel_workers(original_num_parallel_workers)
def test_random_grayscale_invalid_param():
"""
Test RandomGrayscale: invalid parameter given, expect to raise error
"""
logger.info("test_random_grayscale_invalid_param")
# Generate dataset
data = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
try:
transforms = [
py_vision.Decode(),
py_vision.RandomGrayscale(1.5),
py_vision.ToTensor()
]
transform = py_vision.ComposeOp(transforms)
data = data.map(input_columns=["image"], operations=transform())
except ValueError as e:
logger.info("Got an exception in DE: {}".format(str(e)))
assert "Input is not within the required range" in str(e)
