KITTI-C2L-Dataset / code /tests /test_make_correction_animation.py
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Release KITTI-C2L v1.0.0: documented self-contained benchmark, loader and baselines
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from __future__ import annotations
import sys
from pathlib import Path
import pytest
pytest.importorskip("matplotlib")
pytest.importorskip("scipy")
sys.path.insert(0, str(Path(__file__).resolve().parent.parent / "scripts"))
from make_correction_animation import make_animation # noqa: E402
from PIL import Image # noqa: E402
from kitti_c2l.assets import generate_sequence_assets
from kitti_c2l.generate import generate_sequence_rows
from kitti_c2l.sequence_mapping import SequenceInfo
from kitti_c2l.stages import STAGES
from kitti_c2l.writer import write_assets, write_split
@pytest.fixture
def demo_data(fake_kitti_root: Path, tmp_path: Path) -> tuple[Path, Path]:
seq_info = SequenceInfo(sequence="04", date="2011_09_30", drive="0016", start=0, end=3, frame_count=4, split="train")
metadata_path = tmp_path / "train.parquet"
write_split(generate_sequence_rows(seq_info, fake_kitti_root, stages=STAGES), metadata_path)
assets_path = tmp_path / "frames_train.parquet"
write_assets(generate_sequence_assets(seq_info, fake_kitti_root), assets_path)
return metadata_path, assets_path
def test_make_animation_writes_a_multi_frame_gif(demo_data: tuple[Path, Path], tmp_path: Path):
metadata_path, assets_path = demo_data
output_path = make_animation(
metadata_path, assets_path, sequence="04", frame=1, stage=1,
output_path=tmp_path / "anim.gif", num_steps=4, hold_frames=1, fps=10,
)
assert output_path.exists()
with Image.open(output_path) as gif:
# PIL's GIF encoder dedups identical consecutive hold-frames, so the
# exact count isn't reliable -- just check it's a genuine animation.
assert gif.n_frames >= 2
assert gif.is_animated