Python+OpenCV image edge detection four implementation methods

import cv2 as cv
import numpy as np
import  as plt
# Setting up Chinese compatibility
[''] = ['sans-serif']
['-serif'] = ['SimHei']

D:\Anaconda\AZWZ\lib\site-packages\numpy\_distributor_init.py:30: UserWarning: loaded more than 1 DLL from .libs:
D:\Anaconda\AZWZ\lib\site-packages\numpy\.libs\libopenblas.-win_amd64.dll
D:\Anaconda\AZWZ\lib\site-packages\numpy\.libs\libopenblas.-win_amd64.dll
  ("loaded more than 1 DLL from .libs:\n%s" %

horse = ('img/',0)

(horse,cmap=)

(horse,cmap=)

# 1,0 represents the sobel operator in the x-direction.
x = (horse,cv.CV_16S,1,0)
# 0,1 represents the sobel operator in the y-direction.
y = (horse,cv.CV_16S,0,1)

# Format conversion
absx = (x)
absy = (y)

# Edge detection results
res = (absx,0.5,absy,0.5,0)

(figsize=(20,20))
(1,2,1)
m1 = (horse,cmap=)
("Original image.")
(1,2,2)
m2 = (res,cmap=)
("Sobel operator edge detection.")

Text(0.5, 1.0, 'Sobel operator edge detection')

# 1,0 represents the sobel operator in the x-direction.
x = (horse,cv.CV_16S,1,0,ksize=-1)
# 0,1 represents the sobel operator in the y-direction.
y = (horse,cv.CV_16S,0,1,ksize=-1)

# Format conversion
absx = (x)
absy = (y)

# Edge detection results
res = (absx,0.5,absy,0.5,0)

(figsize=(20,20))
(1,2,1)
m1 = (horse,cmap=)
("Original image.")
(1,2,2)
m2 = (res,cmap=)
("Schaar operator edge detection.")

Text(0.5, 1.0, 'Schaar operator edge detection')

res = (horse,cv.CV_16S)

res = (res)

(figsize=(20,20))
(1,2,1)
m1 = (horse,cmap=)
("Original image.")
(1,2,2)
m2 = (res,cmap=)
("Laplacian operator edge detection.")

Text(0.5, 1.0, 'Laplacian operator edge detection')

res = (horse,0,100)

# res = (res) Canny edge detection is a binary detection and does not require a format conversion step

(figsize=(20,20))
(1,2,1)
m1 = (horse,cmap=)
("Original image.")
(1,2,2)
m2 = (res,cmap=)
("Canny edge detection.")

Text(0.5, 1.0, 'Canny edge detection')