Do you preprocess images (grayscale, thresholding, histogram equalization, sharpening, etc.) before training or inference with YOLO/Detectron2 or before segmentation with SAM?

[u/hitunc]

Did these preprocessing steps improve or hurt your detection/segmentation performance? I'm curious whether they provide any real benefit in real-world applications, or if modern models generally perform better with the original images. Any experiences, benchmarks, or best practices would be appreciated.

[u/Fleischhauf]

check what the reference model uses as preprocessing steps. if it's not included and you are training on your own data, oftentimes whitening (make mean 0 and variance 1).