GAN_player的博客

import cv2import numpy as npfrom matplotlib import pyplot as pltimg = cv2.imread('test2.jpg')kernel = np.ones((5,5),np.float32)/25dst = cv2.filter2D(img,-1,kernel)#blur = cv2.GaussianBlur(img,(5,5

import cv2import numpy as npfrom matplotlib import pyplot as pltimg = cv2.imread('thresh.png',0)# 中值滤波img = cv2.medianBlur(img,5)ret,th1 = cv2.threshold(img,127,255,cv2.THRESH_BINARY)#11 为 Block

原理部分： 具体代码见：

import cv2events=[i for i in dir(cv2) if 'EVENT'in i]print( events )#查看所有的鼠标事件''' CV_EVENT_MOUSEMOVE =0, //鼠标移动 CV_EVENT_LBUTTONDOWN =1, //按下左键 CV_EVENT_RBUTTONDOWN =2, //

import cv2import numpy as npfrom matplotlib import pyplot as plt'''扩充图像边界• src 输入图像• top, bottom, left, right 对应边界的像素数目。• borderType 要添加那种类型的边界,类型如下– cv2.BORDER_CONSTANT 添加有颜色的常数值边界,还需要下一个参数(v

#!/usr/bin/env python3# -*- coding: utf-8 -*-"""Created on Tue Oct 24 17:36:48 2017@author: fs"""import cv2events=[i for i in dir(cv2) if 'EVENT'in i]print( events )#查看所有的鼠标事件''' CV_EVENT_MOUS

实现opencv画直线/多边形/圆形/椭圆等操作import numpy as npimport cv2# Create a black imageimg=np.zeros((512,512,3), np.uint8)# Draw a diagonal blue line with thickness of 5 pxcv2.line(img,(0,0),(511,511),(255,0,0),

The result of matches = bf.match(des1,des2) line is a list of DMatch objects. This DMatch object has following attributes: DMatch.distance - Distance between descriptors. The lower, the better it is

使用 OpenCV 中的蛮力(Brute-Force)匹配和 FLANN 匹配。1：Brute-Force 匹配的基础蛮力匹配器是很简单的。首先在第一幅图像中选取一个关键点然后依次与第二幅图像的每个关键点进行(描述符)距离测试,最后返回距离最近的关键点。对于 BF 匹配器,我们首先要使用 cv2.BFMatcher() 创建一个 BF-Matcher 对象。它有两个可选参数。第一个是 norm

import cv2import numpy as npimg = cv2.imread('s2.jpg')gray= cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)descriptor = cv2.xfeatures2d.SIFT_create()kps = descriptor.detect(img,None)cv2.drawKeypoints(img,kps,

输入：左上角和右下角坐标 输出：留下的boxes的索引import numpy as npimport cv2import matplotlib.pyplot as pltimport randomdef py_cpu_nms(dets, thresh): """Pure Python NMS baseline.""" x1 = dets[:, 0] y1 = de

其中x1,y1;x2,y2分别表示两个矩形框的中心点def calcIOU(x1, y1, w1, h1, x2, y2, w2, h2): if((abs(x1 - x2) < ((w1 + w2)/ 2.0)) and (abs(y1-y2) < ((h1 + h2)/2.0))): left = max((x1 - (w1 / 2.0)), (x2 - (w2 / 2.

这些基础函数丢一段时间不用，就给忘记了。cv2.putText(I,'there 0 error(s):',(50,150),cv2.FONT_HERSHEY_COMPLEX,6,(0,0,255),25)各参数依次是：照片/添加的文字/左上角坐标/字体/字体大小/颜色/字体粗细