clm1206的博客

#coding=utf-8 import cv2 import numpy as np '''双线性插值''' img = cv2.imread('timg.jpeg', cv2.CV_LOAD_IMAGE_GRAYSCALE) # load the gray image cv2.imwrite('img.jpg', img) h, w = img.shape[:2] # shrink to...

#coding=utf-8 import cv2 import numpy as np import matplotlib.pyplot as plt img=cv2.imread('timg.jpeg',cv2.CV_LOAD_IMAGE_GRAYSCALE) h,w=img.shape '''分段线性变换''' ''' img=np.array(img,dtype=np.uint8) fo...

#coding=utf-8 import cv2 import numpy as np img=cv2.imread('timg.jpeg',cv2.CV_LOAD_IMAGE_GRAYSCALE) #创建矩形结构单元 g=cv2.getStructuringElement(cv2.MORPH_RECT,(9,9)) #形态学处理,开运算 img_open=cv2.morphologyEx(img...

#coding=utf-8 import numpy as np import cv2 '''腐蚀操作''' img=cv2.imread('timg.jpeg',cv2.CV_LOAD_IMAGE_COLOR) #创建矩形结构单元 g=cv2.getStructuringElement(cv2.MORPH_RECT,(5,7)) #腐蚀图像，迭代次数采用默认1 img_erode=cv2.ero...

#coding=utf-8 import numpy as np import cv2 def img_polar_transform(input_img,center,r_range,theta_rangge=(0,360),r_step=0.5,theta_step=360.0/(180*8)): minr,maxr=r_range mintheta,maxtheta=thet...

#coding=utf-8 #极坐标变换就是（x,y）转换为（r,theta）,即（半径，角度） import math import cv2 import numpy as np x=[2,4] center=[4,0] r=math.sqrt(math.pow(x[0]-center[0],2)+math.pow(x[1]-center[1],2)) theta=math.atan2(x[1]...

对于可分离式卷积核可通过先进行x方向卷积再进行y方向卷积进行图像卷积计算 #coding=utf-8 import cv2 import numpy as np from scipy import signal def gauss_blur(img,sigma,H,W): gauss_kenrnel1=cv2.getGaussianKernel(W,sigma,cv2.CV_64F) ...

#coding=utf-8 '''openCV中最核心的的类是Mat，他是matrix的缩写代表矩阵，该类在头文件opencv2\core\core.hpp中，它含有很多基本矩阵运算，C++需引用 Python含有numpy，在Python中不需要使用Mat''' #openCV中图像存储方式为（h,w,channel）,顺序为BGR import cv2 import sys if __nam...

文章参考于张平编著《OpenCV算法精解-基于Python与C++》 #coding=utf-8 import cv2 import sys if __name__=='__main__': if len(sys.argv)>1: image=cv2.imread(sys.argv[1],cv2.CV_LOAD_IMAGE_UNCHANGED) else: ...

#coding=utf-8 '''对于投影变换需要有4组坐标值''' import cv2 import numpy as np img = cv2.imread('timg.jpeg', cv2.CV_LOAD_IMAGE_GRAYSCALE) h, w = img.shape[:2] src=np.array([[0,0],[w-1,0],[0,h-1],[w-1,h-1]],np.float...

#coding=utf-8 '''仿射变换包括平移、缩放、旋转，仿射矩阵包括6个未知数(平移(tx,ty),缩放（fx,fy）,旋转（sin a,cos a）)，利用方程法需要三组对应坐标才可求出来''' import cv2 import numpy as np a1=[2,3] a2=[3,8] a3=[4,7] a1_=[3,1] a2_=[6,0] a3_=[3,7] src=np.arr...