def test_cleanup(tmp_dir):
dvclive = Live()
img = np.ones((500, 500, 3), np.uint8)
dvclive.log_image("image.png", img)
assert (tmp_dir / dvclive.dir / LiveImage.subfolder / "image.png").exists()
Live()
assert not (tmp_dir / dvclive.dir / LiveImage.subfolder).exists()
def test_step_formatting(tmp_dir):
dvclive = Live()
img = np.ones((500, 500, 3), np.uint8)
for _ in range(3):
dvclive.log_image("image.png", img)
dvclive.next_step()
for step in range(3):
assert (tmp_dir / dvclive.dir / LiveImage.subfolder / str(step) /
"image.png").exists()
def test_step_rename(tmp_dir, mocker):
from pathlib import Path
rename = mocker.spy(Path, "rename")
dvclive = Live()
img = np.ones((500, 500, 3), np.uint8)
dvclive.log_image("image.png", img)
assert (tmp_dir / dvclive.dir / LiveImage.subfolder / "image.png").exists()
dvclive.next_step()
assert not (tmp_dir / dvclive.dir / LiveImage.subfolder /
"image.png").exists()
assert (tmp_dir / dvclive.dir / LiveImage.subfolder / "0" /
"image.png").exists()
rename.assert_called_once_with(
Path(dvclive.dir) / LiveImage.subfolder / "image.png",
Path(dvclive.dir) / LiveImage.subfolder / "0" / "image.png",
)
def test_get_renderers(tmp_dir, mocker):
live = Live()
for i in range(2):
live.log("foo", i)
img = Image.new("RGB", (10, 10), (i, i, i))
live.log_image("image.png", img)
live.next_step()
live.set_step(None)
live.log_plot("confusion_matrix", [0, 0, 1, 1], [1, 0, 0, 1])
image_renderers = get_image_renderers(tmp_dir / live.dir /
LiveImage.subfolder)
assert len(image_renderers) == 2
image_renderers = sorted(image_renderers,
key=lambda x: x.datapoints[0]["rev"])
for n, renderer in enumerate(image_renderers):
assert renderer.datapoints == [{
"src": mocker.ANY,
"rev": os.path.join(str(n), "image.png")
}]
scalar_renderers = get_scalar_renderers(tmp_dir / live.dir /
Scalar.subfolder)
assert len(scalar_renderers) == 1
assert scalar_renderers[0].datapoints == [
{
"foo": "0",
"rev": "workspace",
"step": "0",
"timestamp": mocker.ANY
},
{
"foo": "1",
"rev": "workspace",
"step": "1",
"timestamp": mocker.ANY
},
]
plot_renderers = get_plot_renderers(tmp_dir / live.dir / Plot.subfolder)
assert len(plot_renderers) == 1
assert plot_renderers[0].datapoints == [
{
"actual": "0",
"rev": "workspace",
"predicted": "1"
},
{
"actual": "0",
"rev": "workspace",
"predicted": "0"
},
{
"actual": "1",
"rev": "workspace",
"predicted": "0"
},
{
"actual": "1",
"rev": "workspace",
"predicted": "1"
},
]
assert plot_renderers[0].properties == ConfusionMatrix.get_properties()
def test_PIL(tmp_dir):
dvclive = Live()
img = Image.new("RGB", (500, 500), (250, 250, 250))
dvclive.log_image("image.png", img)
assert (tmp_dir / dvclive.dir / LiveImage.subfolder / "image.png").exists()
def test_numpy(tmp_dir, shape):
dvclive = Live()
img = np.ones(shape, np.uint8) * 255
dvclive.log_image("image.png", img)
assert (tmp_dir / dvclive.dir / LiveImage.subfolder / "image.png").exists()
def test_invalid_extension(tmp_dir):
dvclive = Live()
img = Image.new("RGB", (500, 500), (250, 250, 250))
with pytest.raises(ValueError):
dvclive.log_image("image.foo", img)