When the lighting changes, a detector trained under other conditions degrades. The textbook answer is to collect data, label it, retrain and redeploy. vcalib explores the cheap answer: keep the model frozen and fit, in minutes and without labels, a tiny filter that corrects the input.
The problem
RF-DETR is a state-of-the-art real-time detector and, like almost any vision model, it is sensitive to illumination: dawn vs. dusk, indoor vs. overcast, a new camera, a new site. When the input distribution drifts away from the training one, detection quality drops. Retraining or fine-tuning is expensive, needs labels and is impractical on edge devices.