ReverendBayes/Co-DETR-Car-Damage-Detector

A deep learning–based computer vision training pipeline for car damage detection using a Co-DETR learner enhanced with CBAM Attention, Hybrid Loss, and Albumentations. Trains on Colab to identify and localize car body defects such as scratches, dents, and rust. Includes end-to-end model training and quantitative evaluation.

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Experimental

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MIT

Last pushed

Jun 03, 2025

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