def test_read_with_extent(self):
# Extent only includes the first box.
extent = Box.make_square(0, 0, 3)
config = ObjectDetectionLabelSourceConfig(
vector_source=GeoJSONVectorSourceConfig(
uri=self.file_path, default_class_id=None))
source = config.build(self.class_config, self.crs_transformer, extent,
self.tmp_dir.name)
labels = source.get_labels()
npboxes = np.array([[0., 0., 2., 2.]])
class_ids = np.array([0])
scores = np.array([0.9])
expected_labels = ObjectDetectionLabels(
npboxes, class_ids, scores=scores)
labels.assert_equal(expected_labels)
# Extent includes both boxes, but clips the second.
extent = Box.make_square(0, 0, 3.9)
config = ObjectDetectionLabelSourceConfig(
vector_source=GeoJSONVectorSourceConfig(
uri=self.file_path, default_class_id=None))
source = config.build(self.class_config, self.crs_transformer, extent,
self.tmp_dir.name)
labels = source.get_labels()
npboxes = np.array([[0., 0., 2., 2.], [2., 2., 3.9, 3.9]])
class_ids = np.array([0, 1])
scores = np.array([0.9, 0.9])
expected_labels = ObjectDetectionLabels(
npboxes, class_ids, scores=scores)
labels.assert_equal(expected_labels)
def get_vector_scene(self, class_id, use_aoi=False):
gt_uri = data_file_path('{}-gt-polygons.geojson'.format(class_id))
pred_uri = data_file_path('{}-pred-polygons.geojson'.format(class_id))
scene_id = str(class_id)
rs = MockRasterSource(channel_order=[0, 1, 3], num_channels=3)
rs.set_raster(np.zeros((10, 10, 3)))
crs_transformer = IdentityCRSTransformer()
extent = Box.make_square(0, 0, 360)
gt_rs = RasterizedSource(GeoJSONVectorSource(gt_uri, crs_transformer),
RasterizedSourceConfig.RasterizerOptions(2),
extent, crs_transformer)
gt_ls = SemanticSegmentationLabelSource(source=gt_rs)
pred_rs = RasterizedSource(
GeoJSONVectorSource(pred_uri, crs_transformer),
RasterizedSourceConfig.RasterizerOptions(2), extent,
crs_transformer)
pred_ls = SemanticSegmentationLabelSource(source=pred_rs)
pred_ls.vector_output = [{
'uri': pred_uri,
'denoise': 0,
'mode': 'polygons',
'class_id': class_id
}]
if use_aoi:
aoi_uri = data_file_path('{}-aoi.geojson'.format(class_id))
aoi_geojson = json.loads(file_to_str(aoi_uri))
aoi_polygons = [shape(aoi_geojson['features'][0]['geometry'])]
return Scene(scene_id, rs, gt_ls, pred_ls, aoi_polygons)
return Scene(scene_id, rs, gt_ls, pred_ls)
def setUp(self):
self.crs_transformer = IdentityCRSTransformer()
self.extent = Box.make_square(0, 0, 10)
self.tmp_dir = RVConfig.get_tmp_dir()
self.class_id = 2
self.background_class_id = 3
self.line_buffer = 1
self.uri = os.path.join(self.tmp_dir.name, 'temp.json')
def setUp(self):
self.crs_transformer = IdentityCRSTransformer()
self.extent = Box.make_square(0, 0, 10)
self.tmp_dir_obj = rv_config.get_tmp_dir()
self.tmp_dir = self.tmp_dir_obj.name
self.class_id = 0
self.background_class_id = 1
self.line_buffer = 1
self.class_config = ClassConfig(names=['a'])
self.uri = join(self.tmp_dir, 'tmp.json')
def test_get_chip_no_polygons(self):
geojson = {'type': 'FeatureCollection', 'features': []}
source = self.build_source(geojson)
with source.activate():
# Get chip that partially overlaps extent. Expect that chip has zeros
# outside of extent, and background_class_id otherwise.
self.assertEqual(source.get_extent(), self.extent)
chip = source.get_chip(Box.make_square(5, 5, 10))
self.assertEqual(chip.shape, (10, 10, 1))
expected_chip = np.full((10, 10, 1), self.background_class_id)
np.testing.assert_array_equal(chip, expected_chip)
def test_get_labels(self):
data = np.zeros((10, 10, 1), dtype=np.uint8)
data[7:, 7:, 0] = 1
null_class_id = 2
raster_source = MockRasterSource([0], 1)
raster_source.set_raster(data)
label_source = SemanticSegmentationLabelSource(raster_source,
null_class_id)
with label_source.activate():
window = Box.make_square(7, 7, 3)
labels = label_source.get_labels(window=window)
label_arr = labels.get_label_arr(window)
expected_label_arr = np.ones((3, 3))
np.testing.assert_array_equal(label_arr, expected_label_arr)
def test_get_labels_rgb(self):
data = np.zeros((10, 10, 3), dtype=np.uint8)
data[7:, 7:, :] = [1, 1, 1]
null_class_id = 2
raster_source = MockRasterSource([0, 1, 2], 3)
raster_source.set_raster(data)
rgb_class_config = ClassConfig(names=['a'], colors=['#010101'])
rgb_class_config.ensure_null_class()
label_source = SemanticSegmentationLabelSource(
raster_source, null_class_id, rgb_class_config=rgb_class_config)
with label_source.activate():
window = Box.make_square(7, 7, 3)
labels = label_source.get_labels(window=window)
label_arr = labels.get_label_arr(window)
expected_label_arr = np.zeros((3, 3))
np.testing.assert_array_equal(label_arr, expected_label_arr)
def set_return_vals(self, raster=None):
self.mock.get_extent.return_value = Box.make_square(0, 0, 2)
self.mock.get_dtype.return_value = np.uint8
self.mock.get_crs_transformer.return_value = IdentityCRSTransformer()
self.mock._get_chip.return_value = np.random.rand(1, 2, 2, 3)
if raster is not None:
self.mock.get_extent.return_value = Box(0, 0, raster.shape[0],
raster.shape[1])
self.mock.get_dtype.return_value = raster.dtype
def get_chip(window):
return raster[window.ymin:window.ymax,
window.xmin:window.xmax, :]
self.mock._get_chip.side_effect = get_chip
def setUp(self):
self.file_name = 'labels.json'
self.tmp_dir = rv_config.get_tmp_dir()
self.file_path = os.path.join(self.tmp_dir.name, self.file_name)
self.crs_transformer = DoubleCRSTransformer()
self.geojson = {
'type':
'FeatureCollection',
'features': [{
'type': 'Feature',
'geometry': {
'type':
'Polygon',
'coordinates': [[[0., 0.], [0., 1.], [1., 1.], [1., 0.],
[0., 0.]]]
},
'properties': {
'class_id': 0,
'score': 0.9
}
}, {
'type': 'Feature',
'geometry': {
'type':
'Polygon',
'coordinates': [[[1., 1.], [1., 2.], [2., 2.], [2., 1.],
[1., 1.]]]
},
'properties': {
'score': 0.9,
'class_id': 1
}
}]
}
self.extent = Box.make_square(0, 0, 10)
self.class_config = ClassConfig(names=['car', 'house'])
json_to_file(self.geojson, self.file_path)
def get_vector_scene(self, class_id, use_aoi=False):
gt_uri = data_file_path('{}-gt-polygons.geojson'.format(class_id))
pred_uri = data_file_path('{}-pred-polygons.geojson'.format(class_id))
scene_id = str(class_id)
rs = MockRasterSource(channel_order=[0, 1, 3], num_channels=3)
rs.set_raster(np.zeros((10, 10, 3)))
crs_transformer = IdentityCRSTransformer()
extent = Box.make_square(0, 0, 360)
config = RasterizedSourceConfig(
vector_source=GeoJSONVectorSourceConfig(uri=gt_uri,
default_class_id=0),
rasterizer_config=RasterizerConfig(background_class_id=1))
gt_rs = config.build(self.class_config, crs_transformer, extent)
gt_ls = SemanticSegmentationLabelSource(gt_rs, self.null_class_id)
config = RasterizedSourceConfig(
vector_source=GeoJSONVectorSourceConfig(uri=pred_uri,
default_class_id=0),
rasterizer_config=RasterizerConfig(background_class_id=1))
pred_rs = config.build(self.class_config, crs_transformer, extent)
pred_ls = SemanticSegmentationLabelSource(pred_rs, self.null_class_id)
pred_ls.vector_output = [
PolygonVectorOutputConfig(uri=pred_uri,
denoise=0,
class_id=class_id)
]
if use_aoi:
aoi_uri = data_file_path('{}-aoi.geojson'.format(class_id))
aoi_geojson = file_to_json(aoi_uri)
aoi_polygons = [shape(aoi_geojson['features'][0]['geometry'])]
return Scene(scene_id, rs, gt_ls, pred_ls, aoi_polygons)
return Scene(scene_id, rs, gt_ls, pred_ls)
def get_extent(self):
Box.make_square(0, 0, 2)
