def test_convert_to_coco(self):
DatasetCatalog.register("test_dataset",
lambda: TestConvertCOCO.generate_data())
MetadataCatalog.get("test_dataset").set(thing_classes=["test_label"])
convert_to_coco_dict("test_dataset")
DatasetCatalog.pop("test_dataset")
MetadataCatalog.pop("test_dataset")
def write_coco_format_json(cfg, split):
timer = CodeTimer("writting to coco")
dataset_name, standard_format_json_file = get_dataset_name_and_json(cfg, split)
dataset_dicts = DatasetCatalog.get(dataset_name)
_,filtered_dicts = filter_dataset(dataset_dicts, required_fields=["bbox", "bbox_mode", "segmentation"])
register_dataset(cfg, split, getter= lambda: filtered_dicts, name=dataset_name+"_for_coco")
coco_dict = convert_to_coco_dict(dataset_name+"_for_coco")
json_format_file = standard_format_json_file.replace(".json", "_coco_format.json")
with open(json_format_file, "w") as f:
json.dump(coco_dict, f)
timer.done()
def test(self):
# Make a dummy dataset.
mask = make_mask()
DatasetCatalog.register("test_dataset",
lambda: make_dataset_dicts(mask))
MetadataCatalog.get("test_dataset").set(thing_classes=["test_label"])
# Dump to json.
json_dict = convert_to_coco_dict("test_dataset")
with tempfile.TemporaryDirectory() as tmpdir:
json_file_name = os.path.join(tmpdir, "test.json")
with open(json_file_name, "w") as f:
json.dump(json_dict, f)
# Load from json.
dicts = load_coco_json(json_file_name, "")
# Check the loaded mask matches the original.
anno = dicts[0]["annotations"][0]
loaded_mask = pycocotools.mask.decode(anno["segmentation"])
self.assertTrue(np.array_equal(loaded_mask, mask))