形態(tài)學(xué)梯度調(diào)用

import cv2

import numpy as np

# 讀圖

# img = cv2.imread('./output2/2.jpg', 0)

# # 設(shè)置核

# kernel = np.ones((5, 5), np.uint8)

# # 形態(tài)學(xué)梯度調(diào)用

# gradient = cv2.morphologyEx(img, cv2.MORPH_GRADIENT, kernel)

#

# # 顯示效果

# cv2.imshow('src', img)

# cv2.imshow('result', gradient)

# cv2.waitKey()

img = cv2.imread('./output1/3.jpg', cv2.IMREAD_UNCHANGED)

# 設(shè)置核

kernel = np.ones((3, 3), np.uint8)

# 形態(tài)學(xué)梯度調(diào)用

erosion = cv2.erode(img, kernel)

# 顯示效果

cv2.imshow('src', img)

cv2.imshow('result', erosion)

cv2.waitKey()

開運算

不斷的開運算是沒有關(guān)系的

import cv2

import numpy as np

# 讀圖

img = cv2.imread('./output1/2.jpg', 0)

# 設(shè)置核

# kernel = np.ones((5, 5), np.uint8)

kernel = cv2.getStructuringElement(cv2.MORPH_RECT,(2,2))

# 開運算

opening = cv2.morphologyEx(img, cv2.MORPH_OPEN, kernel)

# 顯示效果

cv2.imshow('src', img)

cv2.imshow('result', opening)

cv2.waitKey()

# def open_demo(image):

# # print(image.shape)

# gray = cv.cvtColor(image,cv.COLOR_BGR2GRAY)

# ret , binary = cv.threshold(gray,0,255,cv.THRESH_BINARY|cv.THRESH_OTSU)

# # kernel = np.ones((5,5),np.uint16)

# kernel = cv.getStructuringElement(cv.MORPH_RECT,(5,5))

# dst = cv.morphologyEx(binary,cv.MORPH_OPEN,kernel)

# cv.imshow("open_demo",dst)

#

# img = cv.imread('./output2/2.jpg', 0)

# open_demo(img)

自實現(xiàn)開運算

主要是通過不同的系數(shù)來實現(xiàn)腐蝕和膨脹的結(jié)合

import cv2

from PIL import Image

import numpy as np

img = cv2.imread('./output1/0.jpg', cv2.IMREAD_UNCHANGED)

# 設(shè)置核

kernel = np.ones((2, 2), np.uint8)

# 形態(tài)學(xué)梯度調(diào)用

erosion = cv2.erode(img, kernel, iterations=2)

kernel = np.ones((2, 2), np.uint8)

dilate = cv2.dilate(erosion, kernel, iterations=1)

# 顯示效果

# v2.imshow('src', img)

# cv2.imshow('result', erosion)

# cv2.imshow('result1', dilate)

cv2.imwrite("./0x.jpg", dilate)

cv2.waitKey()

黑帽

import cv2

import numpy as np

#讀圖

img = cv2.imread('./output2/2.jpg',0)

#設(shè)置核

kernel = np.ones((5,5),np.uint8)

#黑帽調(diào)用

blackhat = cv2.morphologyEx(img, cv2.MORPH_BLACKHAT, kernel)

#顯示效果

cv2.imshow('src',img)

cv2.imshow('show',blackhat)

cv2.waitKey()

總結(jié)

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