A common computer vision preprocessing step is to standardize the pixel intensities of each RGB (red, green, and blue) color channel independently. For every pixel in a given channel, the channel's mean value is subtracted and the result is divided by the channel's standard deviation. When fine-tuning a model pretrained on ImageNet, the standardization must use the source dataset's statistics rather than those of the target dataset. The canonical ImageNet channel means are $[0.485, 0.456, 0.406]$ and the corresponding standard deviations are $[0.229, 0.224, 0.225]$.