algzjh的博客

import numpy img=numpy.zeros((3,3),dtype=numpy.uint8) print(img)打印结果为：[[0 0 0] [0 0 0] [0 0 0]]import numpy,cv2 img=numpy.zeros((3,3),dtype=numpy.uint8) img=cv2.cvtColor(img,cv2.COLOR_GRAY2BGR) print

傅里叶变换import cv2 import numpy as np import matplotlib.pyplot as pltimg = cv2.imread('woman.tif',0)f = np.fft.fft2(img) # 快速傅里叶变换算法得到频率分布 fshift = np.fft.fftshift(f) # 默认结果中心点位置是在左上角，转移到中间位置 #取绝对值：将复数变

help===== Global Commands ===== \help (\?,\h) Print this help. \sql Switch to SQL processing mode. \js Switch to JavaScript processing mode. \py

NoteWhen the size of the kernel is 3, the Sobel kernel shown above may produce noticeable inaccuracies (after all, Sobel is only an approximation of the derivative). OpenCV addresses this inaccuracy fo

RGB ↔ GRAYRGB[A] to Gray:Y←0.299⋅R+0.587⋅G+0.114⋅BGray to RGB[A]:R←Y,G←Y,B←Y,A←max(ChannelRange)cvtColor(src, bwsrc, cv::COLOR_RGB2GRAY);

Measuring Performance with OpenCVimport cv2 import numpy as npimg1 = cv2.imread('messi5.jpg')e1 = cv2.getTickCount() for i in range(5,49,2): img1 = cv2.medianBlur(img1,i) e2 = cv2.getTickCount() t

Arithmetic Operation on Imagesimport cv2 import numpy as npx = np.uint8([250]) y = np.uint8([10])print(cv2.add(x,y)) # saturated operation print(x+y) # modulo operationImage Blendingimport cv2 import n

Making Borders for Images （Paddinig）import numpy as np import cv2 import matplotlib.pyplot as pltBLUE = [255,0,0]img1 = cv2.imread('lena_std.tif')replicate = cv2.copyMakeBorder(img1,10,10,10,10,cv2.BOR

Display and Write an imageimport numpy as np import cv2 from matplotlib import pyplot as pltimg = cv2.imread('img.tif', 0) cv2.imshow('image', img) k = cv2.waitKey(0) & 0xFF if k == 27: cv2.destroy

缩小图像（或称为下采样（subsampled）或降采样（downsampled））的主要目的有两个：1、使得图像符合显示区域的大小；2、生成对应图像的缩略图。放大图像（或称为上采样（upsampling）或图像插值（interpolating））的主要目的是放大原图像,从而可以显示在更高分辨率的显示设备上。对图像的缩放操作并不能带来更多关于该图像的信息, 因此图像的质量将不可避免地受到影响。然而，确

OTSU#include <stdio.h> #include <string> #include "opencv2/highgui/highgui.hpp" #include "opencv2/opencv.hpp" using namespace std; using namespace cv;// OTSU函数实现 int OTSU(cv::Mat srcImage) { int nC