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tracking

tracking

Parse KITTI tracking labels with pykitti==0.3.1 and assess its incomplete tracking loader conservatively.

Independent GitHub snapshot · Automated classification · Original documentation governs

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name: tracking description: "Parse KITTI tracking labels with pykitti==0.3.1 and assess its incomplete tracking loader conservatively." disable-model-invocation: true metadata: disco-role: operating license: MIT

KITTI tracking labels

Use this sub-skill primarily for the two usable label utilities in pykitti==0.3.1: KittiTrackingLabels and to_array_list. They parse local KITTI tracking/detection records into per-frame arrays; they do not acquire a dataset and do not repair malformed data.

Route and boundary

  • Use KittiTrackingLabels(path_or_df, bbox_with_size=True, remove_dontcare=True, split_on_reappear=True) for a label/detection text file or a prepared pandas DataFrame.
  • Use to_array_list(df, length=None, by_id=True) for a frame-indexed DataFrame. Its index is the frame number, not a column.
  • Treat pykitti.tracking(base_path, sequence, **kwargs) as an incomplete, legacy sensor-loader skeleton, not as a verified tracking dataset loader. It has no initialized timestamps, prints a file count, and its frame sub-selection references missing cam0_files/cam1_files attributes. See API reference and troubleshooting.
  • Use raw-data for raw drives and odometry for odometry sequences. Read the shared root troubleshooting guide for installation and package-wide issues.

Minimal safe route

from pykitti.tracking import KittiTrackingLabels, to_array_list

labels = KittiTrackingLabels(
    "/data/kitti/tracking/training/label_02/0000.txt",
    remove_dontcare=True,
    split_on_reappear=True,
)
print(labels.ids, labels.index, len(labels))
boxes = labels.bbox                 # [frame, object, x1, y1, w, h] by default
classes = labels.cls                # [frame, object, 1] object arrays
visible = labels.presence            # [frame, normalized-id] bool array

The text schema, count rules, ID normalization, shape semantics, DataFrame contract, and current compatibility limits are in the bundled references. Run the deterministic fixture smoke before using a real file:

python scripts/labels_fixture_smoke.py --help
python scripts/labels_fixture_smoke.py

The normal package import reaches tracking.py, which imports cv2 eagerly; install a compatible OpenCV package when import pykitti or this module import fails with ModuleNotFoundError: cv2. The smoke script performs only local in-memory checks and has no network or GUI behavior.

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