feat(pointcloud): complete semantic annotation loop

shuishen

21 hours ago 8f75db57f3055b2a3575c86ee3e6acf1dd56ce47

 capabilities/05-3d-pointcloud/tests/test_apply_pointcloud_semantic_model.py

@@ -6,9 +6,10 @@
from pathlib import Path

import laspy
import numpy as np

sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
from apply_pointcloud_semantic_model import load_cloud  # noqa: E402
from apply_pointcloud_semantic_model import load_cloud, write_prediction_preview  # noqa: E402


class ApplyPointCloudSemanticModelTests(unittest.TestCase):
@@ -20,6 +21,22 @@
            with self.assertRaisesRegex(ValueError, "没有可读取的点"):
                load_cloud(source)

    def test_prediction_preview_retains_stable_classification_property(self) -> None:
        with tempfile.TemporaryDirectory() as directory:
            output = Path(directory) / "prediction.ply"
            write_prediction_preview(
                output,
                np.asarray([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], dtype=np.float32),
                np.asarray([5, 15], dtype=np.uint8),
                {5: {"color": [59, 163, 87]}, 15: {"color": [149, 89, 210]}},
            )

            header, records = output.read_bytes().split(b"end_header\n", maxsplit=1)
            self.assertIn(b"property uchar classification", header)
            self.assertEqual(len(records), 2 * 16)
            self.assertEqual(records[15], 5)
            self.assertEqual(records[31], 15)


if __name__ == "__main__":
    unittest.main()