opencv+python 常见图像预处理

import os
import cv2
import numpy as np
import pandas as pd
from PIL import Image
import matplotlib.pylab as plt
"""图像预处理"""#缩放
#灰度化
#二值化-otsu,自定义，自适应
#均值滤波
#中值滤波
#自定义滤波
#高斯/双倍滤波
#开/闭运算
#图片展示class FigurePreprocessing:def __init__(self,img):self.img = img##缩放def resizefigure(self,reshape=(0,0)):new_img1 = cv2.resize(self.img, reshape, interpolation=cv2.INTER_AREA)self.img=new_img1return new_img1##灰度化def gray(self):grayImage = cv2.cvtColor(self.img, cv2.COLOR_BGR2GRAY)self.img = grayImagereturn grayImage##均值滤波def blur_img(self):#（1, 15）是垂直方向模糊，（15， 1）是水平方向模糊dst = cv2.blur(self.img, (1, 15))self.img = dstreturn dst##中值滤波def median_blur_img(self):dst = cv2.medianBlur(self.img, 5)self.img = dstreturn dst#自定义滤波def custom_blur_img(self):#36是防止数值溢出kernel = np.ones((6, 6), np.float32) / 36dst = cv2.filter2D(self.img, -1, kernel)self.img = dstreturn dst#高斯滤波def gauss_blur_img(self):img_gauss_blur = cv2.GaussianBlur(self.img, (3, 3), 0)self.img = img_gauss_blurreturn img_gauss_blur#双边滤波def bilateral_blur_img(self):img_bliteral_blur = cv2.bilateralFilter(self.img, 9, 20, 45)self.img = img_bliteral_blurreturn img_bliteral_blur#开/闭运算def open_close(self,open=True):kernel = np.ones((3, 3), dtype=np.uint8)if open:dst = cv2.morphologyEx(self.img, cv2.MORPH_OPEN, kernel)else:dst = cv2.morphologyEx(self.img, cv2.MORPH_CLOSE, kernel)self.img = dstreturn dst#otsu二值化def otsu_th(self):#ret2, th2 = cv2.threshold(self.img, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)# 先使用一个 5x5 的高斯核除去噪音，然后再使用 Otsu 二值化blur = cv2.GaussianBlur(self.img, (5, 5), 0)ret3, th3 = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)#print(ret2)self.img = th3return th3#自适应二值化def adap_th(self):adaptive_threshold_img = cv2.adaptiveThreshold(self.img, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 35, 3)self.img=adaptive_threshold_imgreturn adaptive_threshold_img#自定义二值化def self_th(self):ret, thresh1 = cv2.threshold(self.img, 180, 255, cv2.THRESH_BINARY)self.img=thresh1return thresh1##图片展示def show(self):cv2.imshow('new_img', self.img)cv2.waitKey(0)cv2.destroyAllWindows()if __name__ == '__main__':orc_img_path = "./data"img_paths = os.listdir(orc_img_path)for img_path in img_paths:print(img_path)img = cv2.imread(orc_img_path+"/" + img_path)print(img.shape)fp = FigurePreprocessing(img)fp.show()if img.shape[1]<200 :fp.resizefigure(reshape=(460,460))#fp.custom_blur_img()#fp.median_blur_img()# fp.gauss_blur_img()#fp.adap_th()#fp.gauss_blur_img()graimg = fp.gray()#fp.adap_th()#fp.self_th()#plt.hist(graimg.ravel(), 256, [0, 256])#plt.show()fp.open_close(open=True)fp.show()#break