vision switcher

: flannbasedmatcher to optimize the training process and create an index tree for the descriptor, this operation will play a huge role in matching a large amount of data (for example, searching for matching images in a data set of hundreds of images ). Brute-force matcher does not operate in this process, but stores train descriptors in the memory.Sample Code #include Lab results References FLANN project HomepageFLANN manual PDFLearning opencv -- SURF (feature points) FLANNOpencv documentation

The turbo vision library is a Tui library and has many installation methods in windows. You can use cygwin, mingw + msys for compilation. For more information, see the installation documentation in DOC/install. Download the corresponding platform version. For Windows, download the corresponding BC ++ and mingw versions. For Linux or cygwin, download the corresponding version. In Windows, you can install it easily in cygwin: $./Configure $ make inst

Frontier: I used to write study notes on my blogs. In the future, I will post some projects/topics that I have worked on at the university and some projects/topics that I am working on, sharing ideas is also a summary of yourself. Skyseraph 3/24/2011 The following is what I am studying and the content of my graduation project. I am still working on it. I will first post some of the achievements I have made... Fabric DefectsPoint Detection Machine

Author: Li Zhimin, Shanghai Center lecturer of Huaqing vision embedded College. From the Linux kernel, a new driver management and registration mechanism is introduced: platform_device and platform_driver. Most device drivers in Linux can use this mechanism. The device is represented by platform_device, and the driver is registered by platform_driver. Compared with the traditional device driver mechanism (that is, registration through the driver_regis

criteria for the underlying meanShift());Termcriteria template class This class is used as the termination condition of the iteration algorithm. Its constructor requires three parameters:One is type, the second parameter is the maximum number of iterations, And the last parameter is a specific threshold. TermCriteria(int type, int maxCount, double epsilon); The types include cv_termcrit_iter, cv_termcrit_eps, cv_termcrit_iter + cv_termcrit_eps, which indicate that the iteration termination co

/*************************************** **************************************** **************************************** **************************************** * ************************** Translation: mastering next to the previous article: opencv with practical computer vision projects (Chapter 1) continue reading Reprinted! Please specify the source **************************************** **************************************** ***********

rewrite the above code -img = Cv2.imread ('Beauti.jpeg', Cv2. Imread_grayscale) - PrintImg.shape - #Img[0][0] = 0 in PrintImg.item (0,0) - Img.itemset ((0,0), 0) toCv2.imwrite ('Mypic-gray.png', IMG) + - #Remove the green channel theimg = Cv2.imread ('Beauti.jpeg') *img[:,:,1] =0 $Cv2.imwrite ('No_green.png', IMG)Panax Notoginseng PrintImg.shape,img.size,img.dtype - theimg = Cv2.imread ('Beauti.jpeg') + #To display a picture, you must enter two parameters ACv2.imshow ('My Image', IMG) the #Wi

://mmlab.ie.cuhk.edu.hk/projects/srcnn.htmlCode:http://mmlab.ie.cuhk.edu.hk/projects/srcnn.htmlpeople(1) Ross B. girshick-the Author of Rcnn, FAST-RCNNwebsite:http://www.cs.berkeley.edu/~rbg/#girshick2014rcnnGithub:https://github.com/rbgirshick(2) shaoqing ren-the Author of FASTER-RCNN, spp-netwebsite:http://home.ustc.edu.cn/~sqren/Github:https://github.com/shaoqingren(3) Georg nebehay-the Author of CMTWebsite:http://www.gnebehay.comGithub:https://github.com/gnebehay(4) Jianchao yang-the Author

Electronic AIDS is a conversion of the original image to a high degree of contrast of the picture, such as converting to black on white, red on the bottom, red, blue, yellow, yellow, blue bottom and so on.The main application scenario is to provide convenient reading for the elderly or those with special amblyopia. Domestic and foreign companies are specialized in such equipment, such as Nokia, Zoomax, Uemax and so on. The effect of Zoomax is particularly good, the color contrast is strong, the

()Mask =numpy.uint8 (Numpy.ones (gray.shape)) keypoints=S.detect (Gray, mask)#displaying images and feature pointsVis =Cv2.cvtcolor (Gray, Cv2. COLOR_GRAY2BGR) forKinchKeypoints[::10]: cv2.circle (Vis, (int (k.pt[0)), int (k.pt[1]), 2, (0, 255, 0), 1) cv2.circle (Vis, (int (k.pt[0)), int (k.pt[1])), int (k.size), (0, 255, 0), 2) Cv2.imshow ('Local descriptors', Vis) Cv2.waitkey () Cv2.imwrite ('c:/users/public/pictures/sample pictures/koala2.jpg', Vis)②duang~ jumping out of a picture like this

Interaction design and visual design of the importance of the industry has reached a consensus. Recently looked at the iphone version of Dolphin Browser design, just take the opportunity to state the relevant design principles. I would like to say that there are three main points: 1. Interaction design is limited by hard interaction (the underlying interaction properties of the hardware itself) and is designed to be extended on the basis of hard interaction. 2. The most important task of vis

that the human eye is not sensitive to the image due to insufficient illumination.　　McCann AlgorithmThis algorithm is intended to produce a better estimate of the uneven illumination, the extraction of the control information is no longer the weighted mode of the Gaussian convolution, but the intensity of a spiral is selected to be weighted, compared with the Gaussian weighting so that the greater range of illumination information can be obtained, and the specified number of iterations based on

fromMatplotlib Import Pyplot aspltimg=cv2.imread ("1.jpg") Gray=Cv2.cvtcolor (Img,cv2. Color_bgr2gray) #颜色转为灰度ret, Thresh=cv2.threshold (Gray,0,255, Cv2. thresh_binary_inv+Cv2. Thresh_otsu) #可为图像设一个阈值kernel=np.ones ((3,3), np.uint8) opening=cv2.morphologyex (Thresh,cv2. morph_open,kernel,iterations=2) #去除噪声sure_bg=cv2.dilate (opening,kernel,iterations=3) Dist_transform=cv2.distancetransform (Opening,cv2. DIST_L2,5) #可以通过distanceTransform来获取确定的前景区域. That is, this is the most likely foreground ar

pixels before storing them in DST. Bordertype –pixel extrapolation method (seeborderinterpolate () for details). The function applies a arbitrary linear filter to an image. In-place operation is supported. When the aperture was partially outside the image, the function interpolates outlier pixel values according to the Specifie d Border mode.#-*-Coding:utf-8-*- #卷积滤波 #code:[email protected]import cv2import numpy as npfn= "test2.jpg" Myimg=cv2.imread (FN) Img

triangular, diamond, circular stitching makes the page become flexible and diverse, ever-changing. But some design in order to pursue creativity and ignore the user's feelings, the page, although the vision is very good, but let the page did not do its duty, which led to the online after the effect is not good. All the above analysis is personal opinion, there is a wrong place also please understand I'm sure you'll want to a

region or any region that is created by the merge is added. Iii. Diversification StrategiesThe author gives two strategies for diversification: color space diversification, similar diversification. Color Space DiversityThe authors used different color methods in 8, mainly to consider scenes and lighting conditions. This strategy is mainly applied to the generation of the original region in the image segmentation algorithm in "1". The main color space used are: (1) RGB, (2) Grayscale I, (3

Try to use OPENCV to achieve stereoscopic vision also has a period of time, the main reference is learning OpenCV 11, 12 chapters and OpenCV forum some senior discussion. The process of bumps, took a lot of detours, and finally solved the biggest problem, the entire calibration, calibration, matching the process of debugging success. (although there are still some questions that have not been clarified yet) Write this article here, the first aspect is

Night Vision Effect Debugging Commissioning Requirements: Because of the use of the light is white LED lights, design requirements are in the night can also see the color of the picture, the reality of the scheme to achieve the picture is not ideal, the light is not bright enough, the image noise is large, because can not modify the hardware can only optimize the image as far as possible. hiisp_ae_attr_ex_s parameter Description: Enaemode the priori

access to the library Statement ************************************************************** *********Original work, from the "Deep Blue Blog" blog. Welcome reprint, please be sure to indicate the source when reproduced, otherwise hold the copyright legal responsibility.Please leave a message or email ([email protected]) to indicate the error.This reprint must be kept here: http://blog.csdn.net/huangyanlong/article/details/39677103Deep Blue Blog: Http://blog.csdn.net/huangyanlong***

inlierand then in the code, the author once again made a match, matchlocal, in my opinion and Findconsensus's purpose is the same, but also through the relative point of distance to determine whether the characteristics of the feature, and then do a match on these features, is selected in, Finally, the points of Inlier and the points of matchlocal are combined as the final feature points. the code for Matchlocal is as follows:void matcher::matchlocal (const vectorWell, because of the time relat