def test_accounts_for_aoi(self):
class_config = ClassConfig(names=['car', 'building', 'background'])
label_source_uri = data_file_path('evaluator/cc-label-filtered.json')
label_source_cfg = ChipClassificationLabelSourceConfig(
vector_source=GeoJSONVectorSourceConfig(
uri=label_source_uri, default_class_id=None))
label_store_uri = data_file_path('evaluator/cc-label-full.json')
label_store_cfg = ChipClassificationGeoJSONStoreConfig(
uri=label_store_uri)
raster_source_uri = data_file_path('evaluator/cc-label-img-blank.tif')
raster_source_cfg = RasterioSourceConfig(uris=[raster_source_uri])
aoi_uri = data_file_path('evaluator/cc-label-aoi.json')
s = SceneConfig(
id='test',
raster_source=raster_source_cfg,
label_source=label_source_cfg,
label_store=label_store_cfg,
aoi_uris=[aoi_uri])
with rv_config.get_tmp_dir() as tmp_dir:
scene = s.build(class_config, tmp_dir)
output_uri = os.path.join(tmp_dir, 'eval.json')
evaluator = ChipClassificationEvaluatorConfig(
output_uri=output_uri).build(class_config)
evaluator.process([scene], tmp_dir)
overall = file_to_json(output_uri)['overall']
for item in overall:
self.assertEqual(item['f1'], 1.0)
def hrefs_to_sceneconfig(
imagery: str,
labels: Optional[str],
name: str,
class_id_filter_dict: Dict[int, str],
extent_crop: Optional[CropOffsets] = None) -> SceneConfig:
transformers = [CastTransformerConfig(to_dtype='float16')]
image_source = RasterioSourceConfig(
channel_order=list(range(224)),
uris=[imagery],
allow_streaming=True,
transformers=transformers,
extent_crop=extent_crop,
)
label_vector_source = GeoJSONVectorSourceConfig(
uri=labels,
class_id_to_filter=class_id_filter_dict,
default_class_id=0xff)
label_raster_source = RasterizedSourceConfig(
vector_source=label_vector_source,
rasterizer_config=RasterizerConfig(background_class_id=0,
all_touched=True))
label_source = SemanticSegmentationLabelSourceConfig(
raster_source=label_raster_source)
return SceneConfig(id=name,
raster_source=image_source,
label_source=label_source)
def make_scene(scene_id, img_path, label_path):
raster_source = RasterioSourceConfig(channel_order=[0, 1, 2],
uris=[img_path])
label_source = ObjectDetectionLabelSourceConfig(
vector_source=GeoJSONVectorSourceConfig(uri=label_path,
default_class_id=None))
return SceneConfig(id=scene_id,
raster_source=raster_source,
label_source=label_source)
def make_scene(id, img_path, label_path):
raster_source = RasterioSourceConfig(channel_order=[0, 1, 2],
uris=[img_path])
label_source = SemanticSegmentationLabelSourceConfig(
rgb_class_config=class_config,
raster_source=RasterioSourceConfig(uris=[label_path]))
label_store = SemanticSegmentationLabelStoreConfig(
rgb=True,
vector_output=[
PolygonVectorOutputConfig(class_id=0),
BuildingVectorOutputConfig(class_id=1)
])
return SceneConfig(id=id,
raster_source=raster_source,
label_source=label_source,
label_store=label_store)
def make_scene(img_path, label_path):
id = basename(img_path)
label_source = ChipClassificationLabelSourceConfig(
vector_source=GeoJSONVectorSourceConfig(uri=label_path,
default_class_id=None,
ignore_crs_field=True),
ioa_thresh=0.5,
use_intersection_over_cell=False,
pick_min_class_id=True,
background_class_id=2,
infer_cells=True)
raster_source = RasterioSourceConfig(
channel_order=[0, 1, 2],
uris=[img_path],
transformers=[StatsTransformerConfig()])
return SceneConfig(id=id,
raster_source=raster_source,
label_source=label_source)