vision doorbell

#pragma warning (disable:4996)/* *************** license:************************** Oct. 3, right to use thi s code in any the want without warrenty, support or any guarentee of it working. Book:it would is nice if you cited It:learning Opencv:computer Vision with the OpenCV Library by Gary Bradski A nd Adrian kaehler Published by O ' Reilly Media, October 3, AVAILABLE at:http://www.amazon.com/learning- opencv-computer-

EMCV: OpenCV that can be run on the DSP EMCV Project Home: HTTP://SF.NET/PROJECTS/EMCVEMCV all called embedded computer Vision Library, is aComputer Vision Library running on the DM64X series DSP. EMCV provides a fully consistent function interface with OPENCV, and with EMCV, you can easily port your OPENCV algorithm to a DSP without even changing one line of code.At present EMCV has supported Iplimage, CV

http://blog.csdn.net/zhangyingchengqi/article/details/50969064First, machine learning1. Includes nearly 400 datasets of different sizes and types for classification, regression, clustering, and referral system tasks. The data set list is located at:http://archive.ics.uci.edu/ml/2. Kaggle datasets, Kagle data sets for various competitionsHttps://www.kaggle.com/competitions3.Second, computer vision"Machine learning meter/Computer

Security monitoring system won the National Computer software copyright registration Source: Huaqing Vision Research and Development Center January 7, 2016, by huaqing Foresight Research and development of "intelligent security monitoring System V1.0" won the National Computer software Copyright registration certificate. The system is widely used in embedded teaching and research platform, such as Yu Huaqing integrated Experiment box fs_wsn4412, emb

Today's end-user computing has come to a revolutionary era, with a common vision of how you can access your applications and data whenever and wherever you use it. Can desktop virtualization make us a step closer to this vision? I've been focusing on desktop virtualization since the end of 2008. There are also four or five desktop virtualization projects that are directly involved in the next few years.

A few days ago bought a micro-vision V411 acquisition card, initially want to use OPENCV to directly collect video stream, using the teacher's multi-camera acquisition program. Unfortunately, no image is collected, simply use the SDK provided by micro-vision to develop. SDK Scenario One: Mv_capturesingle Dcardnum = Mv_getdevicenumber () HWND Hwnd=getsafehwnd (); DWORD i; for (i=0;iThis line is

experience? Precisely because the concept of user experience is virtual, intangible, then the seoer are crazy to do? The answer, the seoer. Visible SEO1.0 and 2.0 times, a lot of seoer reduced to SEO migrant workers (of course, there are some more flexible brain people embarked on the Black Hat seo "no way"). And the SEO3.0 era is not just rely on a "crazy" can change the era of harvest, although the search engine in the user experience of the algorithm technology is not perfect, but this is a

The study of binocular vision has been a certain time, but always feel very vague, especially in the specific algorithm, so want to seriously study the calibration of the principle of matching and the implementation of the program, welcome to criticize correct, to start from the principle and then the program to achieve. From the definition, the camera calibration is essentially a process of determining the internal and external parameters of the cam

Machine Vision Learning Notes (8)--Bouguet stereo correction based on OPENCV In Machine Vision Learning notes (7)--based on OPENCV's binocular camera calibration, we have calculated the Matrix R and T, which describes the relationship of two {camera} coordinate systems, and the stereo correction is mainly the function of these two parameters. Binocular camera System is the main task is ranging, and paral

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

Title: Cover Vision [SQL Injection Vulnerability] Author: Kr4L BeNiM www.2cto.com KralBenimRocks [@] Gmail [.] Com : Http://unikscripts.com/yaxal_products.php? Display = product id = 66 Type: blind Injection ######################################## ############################ Defects: * SQL Injection * [#] Http://www.bkjia.com/content. php? Id = 1 + union + select + 1, 2, 3, 4, [sqli], 6, 7, 8, 9, 10, 11, 12, 13 [#] P0C: Http://w

composition.Let the observer take the velocity V and take an angle θ close to the wave source relative to the direction from the observer to the wave source (the time point is when the observer receives the light)Then the formula for the Doppler frequency shift with θ added isLing Then The following table lists the critical situations of Frequency Shift The light composition varies with the angle area. The color in the slice is the combination of the various colors that can be perceived in the

textureclassification algorithms (meastex ): The color Feret database (): Http://www.itl.nist.gov/iad/humanid/colorferet/home.html The extended m2vts database (xm2vtsdb ): Http://www.ee.surrey.ac.uk/Research/VSSP/xm2vtsdb/ The Feret database (): http://www.itl.nist.gov/iad/humanid/feret/ The japan ese female facial expression (Jaffe) database (Jaffe ): Http://www.mis.atr.co.jp /~ Mlyons/jaffe.html The m2vts database (m2vts ): Http://www.tele.ucl.ac.be/PROJECTS/M2VTS/m2fdb.html The psychological

performance of the edge extraction function. When the block_size is set to a larger value, such as block_size=21, 51, etc., it is two value The following is the extraction edgeImport cv2fn= "test3.jpg" Myimg=cv2.imread (FN) Img=cv2.cvtcolor (myimg,cv2. Color_bgr2gray) Newimg=cv2.adaptivethreshold (img,255,cv2. Adaptive_thresh_mean_c,cv2. thresh_binary,5,2) cv2.imshow (' Preview ', newimg) Cv2.waitkey () cv2.destroyallwindows () watermark/2/text/ahr0cdovl2jsb2cuy3nkbi5uzxqvbxloyxnwba==/fon

ReferencesMask R-CNNMask R-CNN DetailedOpen Source code: tensorflow version code link ; keras and TensorFlow version code link ; mxnet version code link First, MASK-RCNNMask R-CNN is an instance segmentation (Instance segmentation) algorithm, which can accomplish various tasks, such as target classification, target detection, semantic segmentation, case segmentation, human posture recognition, etc. by adding different branches, which is flexible and powerfu

and quickly perform work. (3) The shooting speed of Industrial cameras is much higher than that of general cameras. Industrial cameras can take 10 to several hundred images per second, while general cameras can only take 2-3 images, with too many differences. (4) Industrial cameras output raw data, which has a wide spectral range and is suitable for high-quality image processing algorithms, such as machine vision) application. However, the spectral r

Mathematical path-python computing practice (20)-machine vision-Laplace operator convolution filtering and Laplace operatorTwo-dimensional convolution calculation by Laplace operator, linear sharpening Filtering #-*-Coding: UTF-8-*-# linear sharpening filtering-Laplace operator for two-dimensional convolution calculation # code: myhaspl@myhaspl.comimport cv2import numpy as npfrom scipy import signalfn = "test6.jpg" myimg = cv2.imread (fn) img = cv2.cv

Mathematical path-python computing practice (7)-machine vision-Image Generation addition, zero mean Gaussian noise,-python mean The image produces zero-mean Gaussian noise and adds noise to the grayscale image. The noise is calculated by adding a gray value of each vertex to the noise value, the Box-Muller algorithm generates Gaussian noise. In computer simulation, it is often necessary to generate a value with a normal distribution. The most basic

Cvonline Http://homepages.inf.ed.ac.uk/rbf/CVonline/Imagedbase.htm#biomed Institute of Signal Processing Http://sipi.usc.edu/database? Volume = textures Some of the latest articles are good. Http://web.engr.oregonstate.edu /~ Sinisa/ Texture vistex Http://vismod.media.mit.edu/vismod/imagery/VisionTexture/distribution.html Http://www-cvr.ai.uiuc.edu/ponce_grp/data/ Berkeley Http://www.eecs.berkeley.edu/Research/Projects/CS/vision/gr