原题目给出是这个样子,
需要把图像像素值变换类似于卷积一样的。使原图像尺寸变小,只是计算步骤有点复杂。现在写的代码运行不了。
这是我写的代码和运行的结果。
import cv2
import numpy as np
image=cv2.imread("kate_gray.png")
for i in range(image.shape[0]):
if (image[i - 513] )or image[i - 513] <= image[i]:a = 0
else: a = 1
if (image[i - 512])or image[i - 512] <= image[i]:
b = 0
else:
b = 1
if image[i - 511] <= image[i]:
c = 0
else:
c = 1
if image[i - 1] <= image[i]:
d = 0
else:
d = 1
if image[i + 1] <= image[i]:
e = 0
else:
e = 1
if image[i + 511] <= image[i]:
f = 0
else:
f = 1
if image[i +512] <= image[i]:
g = 0
else:
g = 1
if image[i + 513] <= image[i]:
h = 0
else:
h = 1
else:a
threshold=np.array([[a,b,c],[d,0,e],[f,g,h]])
kernel=np.array([[1,2,4],[128,0,8],[64,32,16]])
result=np.dot(threshold,kernel)
print(array_sum(result))
for i in range(image.):import cv2
import numpy as np
image=cv2.imread("kate_gray.png")
for i in range(image.shape[0]):
if (image[i - 513] )or image[i - 513] <= image[i]:a = 0
else: a = 1
if (image[i - 512])or image[i - 512] <= image[i]:
b = 0
else:
b = 1
if image[i - 511] <= image[i]:
c = 0
else:
c = 1
if image[i - 1] <= image[i]:
d = 0
else:
d = 1
if image[i + 1] <= image[i]:
e = 0
else:
e = 1
if image[i + 511] <= image[i]:
f = 0
else:
f = 1
if image[i +512] <= image[i]:
g = 0
else:
g = 1
if image[i + 513] <= image[i]:
h = 0
else:
h = 1
else:a
threshold=np.array([[a,b,c],[d,0,e],[f,g,h]])
kernel=np.array([[1,2,4],[128,0,8],[64,32,16]])
result=np.dot(threshold,kernel)
print(array_sum(result))
for i in range(image.):import cv2
import numpy as np
image=cv2.imread("kate_gray.png")
for i in range(image.shape[0]):
if (image[i - 513] )or image[i - 513] <= image[i]:a = 0
else: a = 1
if (image[i - 512])or image[i - 512] <= image[i]:
b = 0
else:
b = 1
if image[i - 511] <= image[i]:
c = 0
else:
c = 1
if image[i - 1] <= image[i]:
d = 0
else:
d = 1
if image[i + 1] <= image[i]:
e = 0
else:
e = 1
if image[i + 511] <= image[i]:
f = 0
else:
f = 1
if image[i +512] <= image[i]:
g = 0
else:
g = 1
if image[i + 513] <= image[i]:
h = 0
else:
h = 1
else:a
threshold=np.array([[a,b,c],[d,0,e],[f,g,h]])
kernel=np.array([[1,2,4],[128,0,8],[64,32,16]])
result=np.dot(threshold,kernel)
print(array_sum(result))