import datasets # noqa # add pre-defined metadata
import sys
logger = setup_logger(name=__name__)
assert sys.argv[3] in DatasetCatalog.list()
meta = MetadataCatalog.get(sys.argv[3])
dicts = load_coco_json(sys.argv[1], sys.argv[2], sys.argv[3])
logger.info("Done loading {} samples.".format(len(dicts)))
dirname = "coco-data-vis"
os.makedirs(dirname, exist_ok=True)
for d in dicts:
img = np.array(Image.open(d["file_name"]))
visualizer = Visualizer(img, metadata=meta)
vis = visualizer.draw_dataset_dict(d)
fpath = os.path.join(dirname, os.path.basename(d["file_name"]))
vis.save(fpath)
class RotatedBoxes(Boxes):
"""
This structure stores a list of rotated boxes as a Nx5 torch.Tensor.
It supports some common methods about boxes
(`area`, `clip`, `nonempty`, etc),
and also behaves like a Tensor
(support indexing, `to(device)`, `.device`, and iteration over all boxes)
"""
def __init__(self, tensor: torch.Tensor):
"""
Args: