feature_extractor_models/encoders/_preprocessing.py

import numpy as np


def preprocess_input(
    x, mean=None, std=None, input_space="RGB", input_range=None, **kwargs
):
    if input_space == "BGR":
        x = x[..., ::-1].copy()

    if input_range is not None:
        if x.max() > 1 and input_range[1] == 1:
            x = x / 255.0

    if mean is not None:
        mean = np.array(mean)
        x = x - mean

    if std is not None:
        std = np.array(std)
        x = x / std

    return x