# Copyright (c) Open-MMLab. All rights reserved.
import cv2
import numpy as np
[docs]def imnormalize(img, mean, std, to_rgb=True):
"""Normalize an image with mean and std.
Args:
img (ndarray): Image to be normalized.
mean (ndarray): The mean to be used for normalize.
std (ndarray): The std to be used for normalize.
to_rgb (bool): Whether to convert to rgb.
Returns:
ndarray: The normalized image.
"""
img = np.float32(img) if img.dtype != np.float32 else img.copy()
return imnormalize_(img, mean, std, to_rgb)
[docs]def imnormalize_(img, mean, std, to_rgb=True):
"""Inplace normalize an image with mean and std.
Args:
img (ndarray): Image to be normalized.
mean (ndarray): The mean to be used for normalize.
std (ndarray): The std to be used for normalize.
to_rgb (bool): Whether to convert to rgb.
Returns:
ndarray: The normalized image.
"""
# cv2 inplace normalization does not accept uint8
assert img.dtype != np.uint8
mean = np.float64(mean.reshape(1, -1))
stdinv = 1 / np.float64(std.reshape(1, -1))
if to_rgb:
cv2.cvtColor(img, cv2.COLOR_BGR2RGB, img) # inplace
cv2.subtract(img, mean, img) # inplace
cv2.multiply(img, stdinv, img) # inplace
return img
def imdenormalize(img, mean, std, to_bgr=True):
assert img.dtype != np.uint8
mean = mean.reshape(1, -1).astype(np.float64)
std = std.reshape(1, -1).astype(np.float64)
img = cv2.multiply(img, std) # make a copy
cv2.add(img, mean, img) # inplace
if to_bgr:
cv2.cvtColor(img, cv2.COLOR_RGB2BGR, img) # inplace
return img