racing-gears / AGENTS.md
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v2: add new sources, extraction pipeline, better train/val split
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Agent Context: Racing Gear Digits Dataset

Domain knowledge

  • A lap in circuit racing takes ~1.5–2.5 minutes depending on track length. During a single lap the driver uses every gear at least once (except reverse/neutral).
  • So any ~2 minute window of onboard footage guarantees examples of all forward gears (typically 1–6 or 1–7 depending on car).
  • Gear changes are not uniform — the car spends much more time in mid-range gears (2, 3, 4) than in 1st or top gear. Low gears appear briefly during braking zones; top gear only on long straights.
  • The gear indicator is part of the telemetry overlay baked into the video. Its position, font, size, and background vary per video source. Each source needs its own crop coordinates.
  • Gears 0, 8, 9 don't occur in normal racing — 0 is neutral (rare), 8+ don't exist on these cars. We include them via MNIST for classifier completeness.

Video sources

Each video source has different crop coordinates for the gear digit:

Video Resolution Gear crop (x, y, w, h) Gears Notes
Sebring Q Tobi Lap 6 1920×1080 (1440, 780, 90, 105) 1–6 White digit on dark semi-transparent overlay
Paul Ricard Alpine LMPh 832×464 (685, 320, 55, 55) 1–7 White digit on dark circle

Working with the data

  • Use uv run for all Python scripts (dependencies managed via pyproject.toml)
  • Extraction scripts live in scripts/, reference examples live in examples/
  • The dataset parquet files are in data/ and tracked with Git LFS
  • Source column values: racing (real crops), racing_aug (augmented), mnist (handwritten)