def test_from_dict():
mock_dict_complete = {"strength": "strong"}
sharpen_mock_dict_complete = RasterSharpener.from_dict(mock_dict_complete)
assert sharpen_mock_dict_complete.strength == "strong"
mock_dict_empty = {}
sharpen_mock_dict_complete = RasterSharpener.from_dict(mock_dict_empty)
assert sharpen_mock_dict_complete.strength == "medium"
def test_run(tmp_raster_fixture):
"""
Checks the raster processing for multiple images.
"""
_, out_path = tmp_raster_fixture
# Set params via env vars and load them
os.environ["UP42_TASK_PARAMETERS"] = """
{
"strength": "light"
}
"""
RasterSharpener().run()
assert out_path.exists()
def test_raster_sharpening_expected_pixel_values(tmp_raster_fixture, strength,
expected_mean):
in_path, out_path = tmp_raster_fixture
params_dict = {"strength": strength}
RasterSharpener().from_dict(params_dict).sharpen_raster(in_path, out_path)
assert out_path.exists()
with rio.open(str(out_path), "r") as src:
band_count = src.meta["count"]
assert band_count == 4
img_array = np.stack(list(src.read(range(1, band_count + 1))))
assert img_array.shape == (4, 256, 256)
assert img_array.mean() == expected_mean
def test_alpha_band_ignored(tmp_raster_fixture, test_array_fixture):
"""
Checks if alpha band has changed.
"""
in_path, out_path = tmp_raster_fixture
params_dict = {"strength": "medium"}
img_array = test_array_fixture
RasterSharpener().from_dict(params_dict).sharpen_raster(in_path, out_path)
assert out_path.exists()
with rio.open(str(out_path), "r") as src:
band_count = src.meta["count"]
assert band_count == 4
sharpened = src.read()
assert np.array_equal(img_array[-1], sharpened[-1])
def test_process_data_path(tmp_raster_fixture):
"""
Checks the raster processing for multiple images.
"""
in_path, _ = tmp_raster_fixture
img_file_list = [in_path]
feature_list: List[Feature] = []
for img_path in img_file_list:
bbox = [2.5, 1.0, 4.0, 5.0]
geom = box(*bbox)
in_properties = {
"up42.data_path": str(Path(*img_path.parts[-2:])),
"acquisitionDate": "2018-10-16T10:39:43.431Z",
}
feature_list.append(
Feature(geometry=geom, bbox=bbox, properties=in_properties))
input_fc = FeatureCollection(feature_list)
output_fc = RasterSharpener().process(input_fc)
# Check that all features are derived
assert len(output_fc["features"]) == 1
for feature in output_fc.features:
# Check that file paths in metadata are relative
feature_file = feature["properties"]["up42.data_path"]
assert feature["properties"]["up42.data_path"]
assert Path(feature_file).root == ""
# Check that metadata is propagated
assert feature["properties"][
"acquisitionDate"] == "2018-10-16T10:39:43.431Z"
# Check that feature outputs exist
feature_path = Path("/tmp/output").joinpath(feature_file)
assert feature_path.is_file()
# Cleanup
feature_path.unlink()
def test_sharpen_raster(tmp_raster_fixture):
in_path, out_path = tmp_raster_fixture
RasterSharpener().sharpen_raster(in_path, out_path)
assert out_path.exists()
def test_sharpen_array(test_array_fixture):
sharpened = RasterSharpener().sharpen_array(test_array_fixture)
assert sharpened.shape == (4, 256, 256)