Question

我试图在分离红色通道后对BGR图像进行阈值处理，但是我的代码总是返回“分段错误”。

import numpy as np
import cv2
def mostrarVentana (titulo, imagen):
  print('Mostrando imagen')
  cv2.imshow(titulo, imagen)
  k = cv2.waitKey(0)
  if k == 27:         # wait for ESC key to exit
     cv2.destroyAllWindows()

img = cv2.imread('RepoImagenes/640x480/P5.jpg', 1)  # loading image in BGR
redImg = img[:, :, 2]  # extracting red channel
rbin, threshImg = cv2.threshold(redImg, 58, 255, cv2.THRESH_BINARY)  # thresholding
mostrarVentana('Binary image', threshImg)

我已经阅读了有关如何使用threshold（）函数的文档，但我无法弄清楚出了什么问题。我只需要在红色通道上工作，我怎么能完成这个？

我正在使用python 3.4和opencv 3.1.0

Answer 1

首先，opencv提供了一个简单的API来分割n-channel图像，使用cv2.split()将返回图像中各种频道的列表。

您的mostrarVentana方法中还存在一个错误，您从未创建cv2.namedWindow()并且您直接引用cv2.imshow()，但不能简单地cv2.imshow()创建cv2.namedWindow()。

此外，您必须确保图像已正确加载，然后访问所需的频道，否则会导致奇怪的错误。具有一些场景处理的代码如下所示：

import numpy as np
import cv2
def mostrarVentana (titulo, imagen):
    print('Mostrando imagen')
    cv2.namedWindow(titulo, cv2.WINDOW_NORMAL)
    cv2.imshow(titulo,imagen)
    k = cv2.waitKey(0)
    if k == 27:         # wait for ESC key to exit
       cv2.destroyAllWindows()

img = cv2.imread('RepoImagenes/640x480/P5.jpg', 1)  # loading image in BGR
print img.shape #This should not print error response

if not img is None and len(img.shape) == 3 and img.shape[2] == 3:
    blue_img, green_img, red_img = cv2.split(img)  # extracting red channel
    rbin, threshImg = cv2.threshold(red_img, 58, 255, cv2.THRESH_BINARY)  # thresholding
    mostrarVentana('Binary image', threshImg)

else:
    if img is None:
        print ("Sorry the image path was not valid")
    else:
        print ("Sorry the Image was not loaded in BGR; 3-channel format")

python opencv阈值红色图像

1 个答案: