python - 如何通过调整 RGB 值来编写自定义灰度滤镜？

Question

我正在尝试创建一个灰度滤镜，允许您调整图像中所有像素的 RGB 百分比，例如(红色=20%、绿色=70%、蓝色=10%)。我宁愿这样做是基本级别，所以转换量最少，只需使用公式来允许这种情况发生。
我会假设代码看起来很像这样:

import numpy as np
import cv2
img=cv2.imread(filepath)
imgBlue=img[:,:,0]
imgGreen=[:,:,1]
imgRed=[:,:,2]
blueCon=imgBlue*.1
greenCon=imgGreen*.7
redCon=imgRed*.2
greyscaledImg=img[:,:,:]
greyscaledImg[:,:,0]=blueCon
greyscaledImg[:,:,1]=greenCon
greyscaledImg[:,:,2]=redCon
cv2.imwrite(filepath,greyscaledImg)

Answer 1

这可能是使用 OpenCV 的轨迹栏的一个很好的例子，见 this example .
但是，我认为灰度过滤器的提议概念不会那样工作，因为你只是线性缩放整个图像的 RGB 值。要获得灰色调，您需要单独处理图像中的所有像素。
不过，这是您在上面示例中构建的概念:

import cv2

# Setup maximum factors for each channel
r_max = 100
g_max = 100
b_max = 100

# Window title
title_window = 'Custom gray scale'


# Event for R trackbar change
def on_r_trackbar(val):
    dst[:, :, 2] = val / r_max * src[:, :, 2]
    cv2.imshow(title_window, dst)


# Event for G trackbar change
def on_g_trackbar(val):
    dst[:, :, 1] = val / g_max * src[:, :, 1]
    cv2.imshow(title_window, dst)


# Event for B trackbar change
def on_b_trackbar(val):
    dst[:, :, 0] = val / b_max * src[:, :, 0]
    cv2.imshow(title_window, dst)


# Read some input image
src = cv2.imread('path/to/your/image.png')
dst = src.copy()

# Setup window and create trackbars for each channel
cv2.namedWindow(title_window)
cv2.createTrackbar('R', title_window, 100, r_max, on_r_trackbar)
cv2.createTrackbar('G', title_window, 100, g_max, on_g_trackbar)
cv2.createTrackbar('B', title_window, 100, b_max, on_b_trackbar)

# Show something, and wait until user presses some key
cv2.imshow(title_window, dst)
cv2.waitKey()

这就是窗口最初的样子:

并且，设置你的值(value)观，给出:

因此，为了获得一些灰色的外观，我会坚持使用 HSV color space ，并简单地修改饱和 channel :

import cv2

# Setup maximum factor for the saturation
s_max = 100

# Window title
title_window = 'Custom gray scale'


# Event for S (saturation) trackbar change
def on_s_trackbar(val):
    dst[:, :, 1] = val / s_max * hsv[:, :, 1]
    cv2.imshow(title_window, cv2.cvtColor(dst, cv2.COLOR_HSV2BGR))


# Read some input image, and convert to HSV color space
src = cv2.imread('path/to/your/image.png')
hsv = cv2.cvtColor(src, cv2.COLOR_BGR2HSV)
dst = hsv.copy()

# Setup window and create trackbar for the S (saturation) channel
cv2.namedWindow(title_window)
cv2.createTrackbar('S', title_window, 100, s_max, on_s_trackbar)

# Show something, and wait until user presses some key
cv2.imshow(title_window, cv2.cvtColor(dst, cv2.COLOR_HSV2BGR))
cv2.waitKey()

同样，在初始窗口中，只剩下一个用于饱和的轨迹栏:

并且，饱和度的一些调整给出:

----------------------------------------
System information
----------------------------------------
Platform:    Windows-10-10.0.16299-SP0
Python:      3.8.5
OpenCV:      4.4.0
----------------------------------------