python圖片由RGB空間轉(zhuǎn)成LAB空間的實(shí)現(xiàn)方式

更新時(shí)間：2023年10月12日 14:56:11 作者：Fly~~

這篇文章主要介紹了python圖片由RGB空間轉(zhuǎn)成LAB空間的實(shí)現(xiàn)方式,具有很好的參考價(jià)值,希望對(duì)大家有所幫助,如有錯(cuò)誤或未考慮完全的地方,望不吝賜教

python圖片由RGB空間轉(zhuǎn)成LAB空間

RGB轉(zhuǎn)Lab顏色空間

RGB顏色空間不能直接轉(zhuǎn)換為L(zhǎng)ab顏色空間，需要借助XYZ顏色空間，把RGB顏色空間轉(zhuǎn)換到XYZ顏色空間，之后再把XYZ顏色空間轉(zhuǎn)換到Lab顏色空間。

RGB與XYZ顏色空間有如下關(guān)系：

其中m如下：

XYZ到LAB的轉(zhuǎn)換公式如下

X_(1,) Y_(1,) Z_(1,)分別是X,Y,X線性歸一化之后的值，其中f(x)如下：

python實(shí)現(xiàn)

import numpy as np
import cv2
# region 輔助函數(shù)
# RGB2XYZ空間的系數(shù)矩陣
M = np.array([[0.412453, 0.357580, 0.180423],
              [0.212671, 0.715160, 0.072169],
              [0.019334, 0.119193, 0.950227]])
# im_channel取值范圍：[0,1]
def f(im_channel):
    return np.power(im_channel, 1 / 3) if im_channel > 0.008856 else 7.787 * im_channel + 0.137931
def anti_f(im_channel):
    return np.power(im_channel, 3) if im_channel > 0.206893 else (im_channel - 0.137931) / 7.787
# endregion
# region RGB 轉(zhuǎn) Lab
# 像素值RGB轉(zhuǎn)XYZ空間，pixel格式:(B,G,R)
# 返回XYZ空間下的值
def __rgb2xyz__(pixel):
    b, g, r = pixel[0], pixel[1], pixel[2]
    rgb = np.array([r, g, b])
    # rgb = rgb / 255.0
    # RGB = np.array([gamma(c) for c in rgb])
    XYZ = np.dot(M, rgb.T)
    XYZ = XYZ / 255.0
    return (XYZ[0] / 0.95047, XYZ[1] / 1.0, XYZ[2] / 1.08883)
def __xyz2lab__(xyz):
    """
    XYZ空間轉(zhuǎn)Lab空間
    :param xyz: 像素xyz空間下的值
    :return: 返回Lab空間下的值
    """
    F_XYZ = [f(x) for x in xyz]
    L = 116 * F_XYZ[1] - 16 if xyz[1] > 0.008856 else 903.3 * xyz[1]
    a = 500 * (F_XYZ[0] - F_XYZ[1])
    b = 200 * (F_XYZ[1] - F_XYZ[2])
    return (L, a, b)
def RGB2Lab(pixel):
    """
    RGB空間轉(zhuǎn)Lab空間
    :param pixel: RGB空間像素值，格式：[G,B,R]
    :return: 返回Lab空間下的值
    """
    xyz = __rgb2xyz__(pixel)
    Lab = __xyz2lab__(xyz)
    return Lab
if __name__ == '__main__':
    img = cv2.imread(r'2020_94470.jpg')
    w = img.shape[0]
    h = img.shape[1]
    img_new = np.zeros((w, h, 3))
    lab = np.zeros((w, h, 3))
    for i in range(w):
        for j in range(h):
            Lab = RGB2Lab(img[i, j])
            lab[i, j] = (Lab[0], Lab[1], Lab[2])
        cv2.imwrite(r'00000122_1.jpg', lab)

比較顏色相似度，RGB空間轉(zhuǎn)Lab空間

import numpy as np
from colormath.color_objects import LabColor, sRGBColor
from colormath.color_conversions import convert_color
from colormath.color_diff import delta_e_cie2000
np.set_printoptions(np.inf)
class Color(object):
    def __init__(self, color_file = 'color_list.txt'):
        self.color_name_en = []
        self.color_name_zh = []
        self.color_HEX = []
        self.color_RGB = []
        self.color_Lab = []
        self.readColorFile(color_file)
    def readColorFile(self, color_file):
        with open(color_file, 'r', encoding='utf-8') as f:
            colors = f.readlines()
        for color in colors:
            lc = color.split('\t')
            self.color_name_en.append(lc[0].strip())
            self.color_name_zh.append(lc[1].strip())
            self.color_HEX.append(lc[2].strip())
            rgb = lc[3].strip().split(',')
            rgb = [int(v) for v in rgb]
            self.color_RGB.append(rgb)
        self.rgbToLab()
    def rgbToLab(self):
        for rgb in self.color_RGB:
            srgb = sRGBColor(*rgb)
            lab = convert_color(srgb, LabColor)
            self.color_Lab.append(lab)
    def getMinCIE2000Distance(self, rgb):
        srgb = sRGBColor(*rgb)
        tlab = convert_color(srgb, LabColor)
        min_index = -1
        min_delta_e = np.inf
        for idx, lab in enumerate(self.color_Lab):
            delta_e = delta_e_cie2000(tlab, lab)
            if delta_e < min_delta_e:
                min_delta_e = delta_e
                min_index = idx
        return min_delta_e, min_index
    def calculateRGBDistance(self, rgb=(0,0,0)):
        array_rgb = np.array(self.color_RGB)
        print(array_rgb)
        print(array_rgb.shape)
        temp1_rgb = (rgb - array_rgb) / 255
        temp2_rgb = temp1_rgb[:,0]*temp1_rgb[:,0] + temp1_rgb[:,1]*temp1_rgb[:,1] + temp1_rgb[:,2]*temp1_rgb[:,2]
    def __getitem__(self, index):
        info = f"英文代碼 : {self.color_name_en[index]}\n"
        info += f"形象顏色 : {self.color_name_zh[index]}\n"
        info += f"HEX格式 : {self.color_HEX[index]}\n"
        info += f"RGB格式 : {self.color_RGB[index]}\n"
        info += f"Lab格式 : {self.color_Lab[index]}\n\n"
        return info
    def __len__(self):
        assert len(self.color_name_en) == len(self.color_name_zh)
        assert len(self.color_name_en) == len(self.color_HEX)
        assert len(self.color_name_en) == len(self.color_RGB)
        return len(self.color_name_en)
if __name__ == '__main__':
    c = Color()
    rgb = (123, 145, 111)
    delta_e, index = c.getMinCIE2000Distance(rgb)
    print(delta_e, index)
    print(c[index])