def test_load_image_data():
dataset = io_utils.image_dataset_from_directory(
IMG_DATA_DIR,
image_size=(180, 180),
validation_split=0.2,
subset="training",
seed=test_utils.SEED,
)
val_dataset = io_utils.image_dataset_from_directory(
IMG_DATA_DIR,
image_size=(180, 180),
validation_split=0.2,
subset="validation",
seed=test_utils.SEED,
)
for data in dataset:
assert data[0].numpy().shape == (32, 180, 180, 3)
assert data[1].dtype == tf.string
break
for data in val_dataset:
assert data[0].numpy().shape == (32, 180, 180, 3)
assert data[1].dtype == tf.string
break
def test_load_image_data_raise_subset_error():
with pytest.raises(ValueError) as info:
io_utils.image_dataset_from_directory(
IMG_DATA_DIR,
image_size=(180, 180),
validation_split=0.2,
subset="abcd",
seed=test_utils.SEED,
)
assert "`subset` must be either" in str(info.value)
def test_load_image_data_raise_color_mode_error():
with pytest.raises(ValueError) as info:
io_utils.image_dataset_from_directory(IMG_DATA_DIR,
image_size=(180, 180),
color_mode="abcd")
assert "`color_mode` must be one of" in str(info.value)
def test_load_image_data_grey_scale():
io_utils.image_dataset_from_directory(IMG_DATA_DIR,
image_size=(180, 180),
color_mode="grayscale")
def test_load_image_data_rgba():
io_utils.image_dataset_from_directory(IMG_DATA_DIR,
image_size=(180, 180),
color_mode="rgba")
