本文介绍了使用numpy将图像转换为灰度的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我有一个由矩阵 nxm 三元组(r,g,b)
并且我想使用自己的函数将其转换为灰度。
I have an image represented by a numpy.array
matrix nxm of triples (r,g,b)
and I want to convert it into grayscale, , using my own function.
我的尝试未能将矩阵 nxmx3 转换为单个矩阵值 nxm ,这意味着从数组 [r,g,b]
开始,我得到 [灰色,灰色,灰色]
,但我需要灰色
。
My attempts fail converting the matrix nxmx3 to a matrix of single values nxm, meaning that starting from an array [r,g,b]
I get [gray, gray, gray]
but I need gray
.
ie初始颜色通道: [150 246 98]
。
转换为灰色后: [134 134 134]
。
我需要什么: 134
i.e. Initial colour channel : [150 246 98]
. After converting to gray : [134 134 134]
. What I need : 134
我该如何实现?
我的代码:
def grayConversion(image):
height, width, channel = image.shape
for i in range(0, height):
for j in range(0, width):
blueComponent = image[i][j][0]
greenComponent = image[i][j][1]
redComponent = image[i][j][2]
grayValue = 0.07 * blueComponent + 0.72 * greenComponent + 0.21 * redComponent
image[i][j] = grayValue
cv2.imshow("GrayScale",image)
return image
推荐答案
以下是工作代码:
def grayConversion(image):
grayValue = 0.07 * image[:,:,2] + 0.72 * image[:,:,1] + 0.21 * image[:,:,0]
gray_img = grayValue.astype(np.uint8)
return gray_img
orig = cv2.imread(r'C:\Users\Jackson\Desktop\drum.png', 1)
g = grayConversion(orig)
cv2.imshow("Original", orig)
cv2.imshow("GrayScale", g)
cv2.waitKey(0)
cv2.destroyAllWindows()
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