opencv 处理图像后RGB消失

我正在处理一个图像（2192 x 2921 x 3），将等于0的像素值替换为它以前的非零值。
代码完成时没有出现错误，但输出图像不再是RGB。
我的代码中有什么错误导致了这个吗？
函数“fill_zeros_with_last“来自StackOverflow。
代码如下：

import numpy as np
import cv2
from PIL import Image

def fill_zeros_with_last(arr):
    prev = np.arange(len(arr))
    prev[arr == 0] = 0
    prev = np.maximum.accumulate(prev)
    return arr[prev]

image = cv2.imread('path\to\image')
image_modified = [] # to store the processed image
for k in range(3):
    for j in range(2921):
        image1 = fill_zeros_with_last(image[:, j, k]) # replaces 0s with the previous nonzero value.
        image_modified.append(image1)

image_modified = np.reshape(image_modified, ((2192, 2921, 3))) # to reshape the image
image_modified = image_modified.astype('uint8') # convert to uint8
img1 = Image.fromarray(image_modified, 'RGB') # convert to RGB
img1.save('image_modified.png') # save image

下面是一个输入图像示例：

示例输出：

看起来您对存储OpenCV图像的NumPy数组的数据排序感到困惑。
OpenCV中图像的自然排序（在内存中）是“原始主要”，即b、g、r、b、g、r ......数据排序：

Row 0: BGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGR
Row 1: BGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGR
Row 3: BGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGRBGR

image数组的索引为：image[r, c, ch]（行、列、颜色通道）：
image_modified是已修改列的列表，列表中的每个元素应用一个颜色通道：

[                            
  All columns of blue channel of column  
  Applies image column 0: BBBBBBBBBBBBBBBBBBBBBBBBBBB,
  Applies image column 1: BBBBBBBBBBBBBBBBBBBBBBBBBBB,
  Applies image column 2: BBBBBBBBBBBBBBBBBBBBBBBBBBB,
  All columns of green channel of column  
  Applies image column 0: GGGGGGGGGGGGGGGGGGGGGGGGGGG,
  Applies image column 1: GGGGGGGGGGGGGGGGGGGGGGGGGGG,
  Applies image column 2: GGGGGGGGGGGGGGGGGGGGGGGGGGG,
  All columns of red channel of column
  Applies image column 0: RRRRRRRRRRRRRRRRRRRRRRRRRRR,
  Applies image column 1: RRRRRRRRRRRRRRRRRRRRRRRRRRR,
  Applies image column 2: RRRRRRRRRRRRRRRRRRRRRRRRRRR,
  ...
]

为了固定顺序，我们可以应用np.reshape，然后应用np.transpose：

按行按元素将形状调整为3列< cols >< rows >：

image_modified = np.reshape(image_modified, ((3, cols, rows)))

通过cols和3转置（置换）到rows：

image_modified = np.transpose(image_modified, (2, 1, 0))

代码示例：

import numpy as np
import cv2

def fill_zeros_with_last(arr):
    prev = np.arange(len(arr))
    prev[arr == 0] = 0
    prev = np.maximum.accumulate(prev)
    return arr[prev]

image = cv2.imread('test_image.jpg')
rows, cols = image.shape[0], image.shape[1]  # Get height and width of image

image_modified = [] # to store the processed image

for k in range(3):
    for j in range(cols):
        image1 = fill_zeros_with_last(image[:, j, k]) # replaces 0s with the previous nonzero value.
        image_modified.append(image1)

image_modified = np.reshape(image_modified, ((3, cols, rows))) # to reshape the image
image_modified = np.transpose(image_modified, (2, 1, 0))  # Fix the data ordering to match OpenCV convention

cv2.imwrite('image_modified.png', image_modified)  # Use cv2.imwrite instead of using PIL because the color ordering is different.

我们可以使用NumPy数组来存储image_modified，而不是使用列表，而不是打乱顺序：

import numpy as np
import cv2

def fill_zeros_with_last(arr):
    prev = np.arange(len(arr))
    prev[arr == 0] = 0
    prev = np.maximum.accumulate(prev)
    return arr[prev]

image = cv2.imread('test_image.jpg')

rows, cols = image.shape[0], image.shape[1]  # Get height and width of image

#image_modified = [] # to store the processed image
image_modified = np.zeros_like(image)  # Initialize image_modified to array of zeros with same size and type of image

for k in range(3):
    for j in range(cols):
        image1 = fill_zeros_with_last(image[:, j, k]) # replaces 0s with the previous nonzero value.
        image_modified[:, j, k] = image1  # Update the column
        #image_modified.append(image1)

cv2.imwrite('image_modified.png', image_modified)  # Use cv2.imwrite instead of using PIL because the color ordering is different.

输出量：

opencv 处理图像后RGB消失

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