how is the PIXEL_MEAN and PIXEL_STD calculated?

[MapleLeafKiller]

First of all thank you for the great work.

In ret_benchmark/data/transforms/build.py, you have:
.......
normalize_transform = T.Normalize(mean=cfg.INPUT.PIXEL_MEAN,
std=cfg.INPUT.PIXEL_STD)
if is_train:
transform = T.Compose([
T.Resize(size=cfg.INPUT.ORIGIN_SIZE),
T.RandomResizedCrop(
scale=cfg.INPUT.CROP_SCALE,
size=cfg.INPUT.CROP_SIZE
),
T.RandomHorizontalFlip(p=cfg.INPUT.FLIP_PROB),
T.ToTensor(),
normalize_transform,
])
............

I wonder how is the PIXEL_MEAN and PIXEL_STD calculated? Are they calculated after Resize()、RandomResizedCrop(), RandomHorizontalFlip() and ToTensor()? Or they are calculated applying only ToTensor() (which converts a PIL image from [0, 255] to [0,1]) to all the pics in the dataset?

[bnu-wangxun]

PIXEL_MEAN and PIXEL_STD are fixed and given in the config file.