如何在Python中通过删除黑色像素(即[0,0,0])从图像的3D数组中获取2D数组 [英] How to get 2D array from 3D array of an image by removing black pixels, i.e. [0,0,0], in python

问题描述

我有一张面部皮肤的照片，周围有黑色像素.

I have a picture of the facial skin with black pixels around it.

图片是由像素(RGB)组成的3d阵列

The picture is an 3d array made up of pixels (RGB)

图片的数组=宽度*高度* RGB

picture's array = width * height * RGB

问题在于图片中有太多不属于皮肤的黑色像素.

The problem is that in the picture there are so many black pixels that do not belong to the skin.

黑色像素表示为零的数组.[0,0,0]

The black pixels represent as an array of zero. [0,0,0]

我想获取带有非黑色像素的2d数组，作为[[218,195,182].... [229,0，133] -仅包含面部肤色的像素

I want to get 2d array with non-black pixels as [[218,195,182]. ... [229,0, 133]] -with only the pixels of facial skin color

我尝试通过查找所有RGB等于0的所有像素来弹出黑色像素，仅类似于[0,0,0] :

I try to eject the black pixels by finding all the pixels whose all RGB is equal to 0 like [0,0,0] only:

        def eject_black_color(skin):
            list=[]
            #loop over pixels of skin-image
            for i in range(skin.shape[0]):
                for j in range(skin.shape[1]):
                    if(not (skin[i][j][0]==0 and skin[i][j][1]==0 and skin[i][j][2]==0)):
                        #add only non-black pixels to list
                        list.append(skin[i][j])
            return list

请注意，我不想从像[255,0,125] [0,0,255]之类的像素中提取零，因此numpy的非零方法不适合

如何以更高效，更快捷的方式编写它?

How to write it in a more efficient and fast way?

谢谢

推荐答案

假设您的图片位于 img 中.您可以使用以下代码:

Suppose your image is in img. You can use the code below:

import numpy as np

img=np.array([[[1,2,0],[24,5,67],[0,0,0],[8,4,5]],[[0,0,0],[24,5,67],[10,0,0],[8,4,5]]])
filter_zero=img[np.any(img!=0,axis=-1)]   #remove black pixels 
print(filter_zero)

输出(二维数组)为:

[[ 1  2  0]
 [24  5 67]
 [ 8  4  5]
 [24  5 67]
 [10  0  0]
 [ 8  4  5]]

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