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"""
@author: cuny
@file: MakeWhiter.py
@time: 2022/7/2 14:28
@description:
美白算法
"""
import os
import cv2
import math
import numpy as np
local_path = os.path.dirname(__file__)
class MakeWhiter(object):
class __LutWhite:
"""
美白的内部类
"""
def __init__(self, lut):
cube64rows = 8
cube64size = 64
cube256size = 256
cubeScale = int(cube256size / cube64size) # 4
reshapeLut = np.zeros((cube256size, cube256size, cube256size, 3))
for i in range(cube64size):
tmp = math.floor(i / cube64rows)
cx = int((i - tmp * cube64rows) * cube64size)
cy = int(tmp * cube64size)
cube64 = lut[cy:cy + cube64size, cx:cx + cube64size] # cube64 in lut(512*512 (512=8*64))
_rows, _cols, _ = cube64.shape
if _rows == 0 or _cols == 0:
continue
cube256 = cv2.resize(cube64, (cube256size, cube256size))
i = i * cubeScale
for k in range(cubeScale):
reshapeLut[i + k] = cube256
self.lut = reshapeLut
def imageInLut(self, src):
arr = src.copy()
bs = arr[:, :, 0]
gs = arr[:, :, 1]
rs = arr[:, :, 2]
arr[:, :] = self.lut[bs, gs, rs]
return arr
def __init__(self, lutImage: np.ndarray = None):
self.__lutWhiten = None
if lutImage is not None:
self.__lutWhiten = self.__LutWhite(lutImage)
def setLut(self, lutImage: np.ndarray):
self.__lutWhiten = self.__LutWhite(lutImage)
@staticmethod
def generate_identify_color_matrix(size: int = 512, channel: int = 3) -> np.ndarray:
"""
用于生成一张初始的查找表
Args:
size: 查找表尺寸，默认为512
channel: 查找表通道数，默认为3
Returns:
返回生成的查找表图像
"""
img = np.zeros((size, size, channel), dtype=np.uint8)
for by in range(size // 64):
for bx in range(size // 64):
for g in range(64):
for r in range(64):
x = r + bx * 64
y = g + by * 64
img[y][x][0] = int(r * 255.0 / 63.0 + 0.5)
img[y][x][1] = int(g * 255.0 / 63.0 + 0.5)
img[y][x][2] = int((bx + by * 8.0) * 255.0 / 63.0 + 0.5)
return cv2.cvtColor(img, cv2.COLOR_RGB2BGR).clip(0, 255).astype('uint8')
def run(self, src: np.ndarray, strength: int) -> np.ndarray:
"""
美白图像
Args:
src: 原图
strength: 美白强度，0 - 10
Returns:
美白后的图像
"""
dst = src.copy()
strength = min(10, int(strength)) / 10.
if strength <= 0:
return dst
self.setLut(cv2.imread(f"{local_path}/lut_image/3.png", -1))
_, _, c = src.shape
img = self.__lutWhiten.imageInLut(src[:, :, :3])
dst[:, :, :3] = cv2.addWeighted(src[:, :, :3], 1 - strength, img, strength, 0)
return dst
if __name__ == "__main__":
# makeLut = MakeWhiter()
# cv2.imwrite("lutOrigin.png", makeLut.generate_identify_color_matrix())
input_image = cv2.imread("test_image/7.jpg", -1)
lut_image = cv2.imread("lut_image/3.png")
makeWhiter = MakeWhiter(lut_image)
output_image = makeWhiter.run(input_image, 10)
cv2.imwrite("makeWhiterCompare.png", np.hstack((input_image, output_image)))
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