adas-kitti-yolo11m

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This is a YOLO11 detector fine-tuned on the KITTI Object Detection Benchmark (training split, 7,481 frames) for an ADAS perception pipeline. See the full project: https://github.com/ishaannk/ADAS-Object-Detection-and-Collision-Avoidance

Classes

Car, Van, Truck, Pedestrian, Person_sitting, Cyclist, Tram, Misc — KITTI's own taxonomy, not remapped to COCO classes.

Training data

KITTI Object Detection Benchmark, training split only. Deterministic 85/15 train/val split (seed 42) over sorted frame ids — not the literature Chen et al. 3712/3769 split.

Metrics

See metrics.json in this repo for per-class mAP50 / mAP50-95 and KITTI-protocol-style easy/moderate/hard AP.

Intended use

Research and portfolio demonstration of a calibrated camera-LIDAR fusion + collision-risk pipeline. Not validated for deployment in a vehicle.

License

Base model (Ultralytics YOLO11) is AGPL-3.0. KITTI's terms restrict this dataset to non-commercial research use — these weights are not licensed for commercial/production use as-is.

Model Details

Model Description

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Uses

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Training Details

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Training Hyperparameters

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Evaluation

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Testing Data, Factors & Metrics

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Summary

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Environmental Impact

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