我遇到了一个令人沮丧的问题，我试图将边缘过滤器应用于图像以进行类分配。当我运行代码时，我收到错误"0"；ValueError Traceback(最近一次通话(
在12 sobel_horiz=sobel_vert.T13--->14 d_horiz=卷积2d(平均值，sobel_horiz，边界="symm"，模式="me"，填充值=0(15 d_vert=卷积2d(平均值，sobel_vert，模式="me"，边界="symm"，填充值=0(16edgel=np.sqrt(np.square(d_horiz(+np.squart(d_vert((
/卷积2d中的usr/local/lib/python3.7/dist-packages/scipy/signal/signaltools.py(in1，in2，模式，边界，填充值(16941695，如果不是in1.ndim==in2.ndim==2：->1696引发ValueError("已解析的2d输入必须都是2-D数组"(16971698 if _inputs_swap_needed(mode，in1.shape，in2.shape(:
ValueError：卷积2d输入必须都是2-D阵列"；
我知道我传递给卷积二维的数组实际上是二维数组，但卷积二维似乎没有注册，有什么方法可以解决这个问题吗？这是代码：
import numpy as np
import cv2
import math
import random
from matplotlib import pyplot as plt
from scipy.signal import convolve2d
#mount drive
from google.colab import drive
drive.mount('/content/drive')
#from google.colab.patches import cv2_imshow
def in_circle(x,y, center_x, center_y, radius):
distance = math.sqrt(math.pow(x-center_x,2)+math.pow(y-center_y,2))
return (distance < radius)
def in_disk(x,y,center_x,center_y,inner_radius,outer_radius):
return not in_circle(x,y,center_x,center_y,inner_radius) and in_circle(x,y,center_x,center_y,outer_radius)
img = cv2.imread('/content/mydata/circles.jpg')
# apply average filter
average_kernel = np.array(
[[0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01],
[0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01],
[0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01],
[0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01],
[0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01],
[0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01],
[0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01],
[0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01],
[0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01],
[0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01,0.01]]
)
average = cv2.filter2D(img,-1,average_kernel)
#cv2.imshow('first_average',average)
plt.figure()
plt.title('first AVR')
plt.imshow(average,cmap='gray', vmin=0, vmax=255)
# apply edge filter
l_kern2 = np.array([
[-1.0, -1.0, -1.0]
,[-1.0, 8.0, -1.0]
,[-1.0, -1.0, -1.0]
])
sobel_vert = np.array([
[-1.0, 0.0, 1.0]
,[-2.0, 0.0, 2.0]
,[-1.0, 0.0, 1.0]
])
sobel_horiz = sobel_vert.T
d_horiz = convolve2d(average, sobel_horiz, boundary = 'symm', mode='same', fillvalue=0)
d_vert = convolve2d(average, sobel_vert, mode='same', boundary = 'symm', fillvalue=0)
edgel=np.sqrt(np.square(d_horiz) + np.square(d_vert))
#edgel = cv2.filter2D(average, -1, l_kern2)
#edgel = convolve2d(average, l_kern2, mode='same', boundary = 'symm', fillvalue=0)
#edgel= np.absolute(edgel)
edgel *= 255.0 / np.max(edgel)
plt.figure()
plt.title('Edge')
plt.imshow(edgel,cmap='gray', vmin=0, vmax=255)
相关代码位于#applyedgefilter注释下方。非常感谢。
我发现我在哪里搞砸了，我需要添加一个0作为该段参数的一部分：
img = cv2.imread('/content/mydata/circles.jpg',0)