Question

我正在尝试从图像中提取棋盘。它有很多其他不需要的内容，我想删除。所以我创造了一个具有所有斜坡的面具。然后bitwise_and使用原始灰度图像。我是一个新手，我发现OpenCV非常有趣，但我坚持这个问题。请帮忙！

import cv2
import numpy as np
from PIL import Image


kernel = np.ones((5,5),np.uint8)
img = cv2.imread('test1.jpg',0)
img = cv2.morphologyEx(img, cv2.MORPH_CLOSE, kernel)

ret,thresh1 = cv2.threshold(img,60,255,cv2.THRESH_BINARY)
edges = cv2.Canny(thresh1,100,200)

cv2.imwrite("canny.jpg", edges)
minL = 10000
maxL = 8
lines = cv2.HoughLinesP(edges,1,np.pi/180, 85)#, minL, maxL)


mask_l = np.zeros(img.shape[:2])
mask_r = np.zeros(img.shape[:2])
mask_t = np.zeros(img.shape[:2])
mask_b = np.zeros(img.shape[:2])


width, height = lines.shape[:2]

im_x, im_y = img.shape


for x1,y1,x2,y2 in lines[0]:
   cv2.line(edges,(x1,y1),(x2,y2),(255,255,255),2)
   if (x2-x1) == 0:
      continue
   else:
     m = (y2 - y1)/(x2 - x1)
     if(m > 0):
        for im_count in range(im_x):
            yp = round(m * (im_count - x1)) + y1
            if yp >= 1 and yp <= im_y:
                for temp1 in range(int(im_count),int(im_x)):
                    mask_r[int(yp)][int(temp1)] = 1
                for temp2 in range(int(im_count)):
                    mask_l[int(yp)][int(temp2)] = 1
    else:
        for im_count in range(im_x):
            yp = round(m * (im_count - x1)) + y1
            if yp >= 1 and yp <= im_y:
                for temp1 in range(int(yp), int(im_y)):
                    mask_b[int(im_count)][int(temp1)] = 1
                for temp2 in range(int(yp)):
                    mask_t[int(im_count)][int(temp2)] = 1

cv2.imwrite('new.jpg', edges)


temp_mask1 = cv2.bitwise_and(mask_l, mask_r, mask=None)
temp_mask2 = cv2.bitwise_and(mask_t, mask_b, mask=None)
final_mask = cv2.bitwise_and(temp_mask1, temp_mask2)




 final_mask = cv2.morphologyEx((final_mask * 1.0).astype(np.float32), cv2.MORPH_CLOSE, kernel=None)

cv2.imshow('final',final_mask)
cv2.waitKey(0)


cv2.destroyAllWindows()

x,y = img.shape
print x
print y
ret, orig_mask = cv2.threshold(final_mask, 10, 255, cv2.THRESH_BINARY)
a,b = final_mask.shape
print a
print b


imeg = cv2.imread('test1.jpg',cv2.CV_LOAD_IMAGE_GRAYSCALE)

ret, orig_mask1 = cv2.threshold(imeg, 10, 255, cv2.THRESH_BINARY)
(thresh, im_bw) = cv2.threshold(imeg, 128, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)
images1 = cv2.bitwise_and(img,img, mask=orig_mask)
cv2.imwrite("123.jpg",images1)

这是我得到的错误：

OpenCV Error: Assertion failed ((mask.type() == CV_8UC1 || mask.type() == CV_8SC1)) in binary_op, file /build/buildd/opencv-2.3.1/modules/core/src/arithm.cpp, line 1033

掩模和图像的尺寸相同。但我仍然得到这个错误！

Answer 1

mask需要由有符号或无符号的8位整数组成。这就是CV_8SC1和CV_8C1的含义。

尝试为签名版本创建掩码np.zeros(shape, dtype=np.uint8)或np.int8。

同时检查分配给掩码的计算是否属于正确的8位范围：0-255。

当我尝试使用bitwise_and带有掩码的图像时，python中的OpenCV错误

1 个答案: