opencv face detection

write in front of the articleThese days because the work needs to learn image detection, stupid I do not want to stare at OPENCV start to learn (; ′⌒ '), even the ability to check information is weak 〒▽〒Praise My best man ticket (*^▽^*) The man is not the image processing but love my stupid (the "contest")Let me give him the request (our store?? Omega??) Our store??? He put the game down and spent a day or

Hough Line transformation can only be the edge binary image.4. The specific principles of the Hough Line detection refer to:52944708Http://www.opencv.org.cn/opencvdoc/2.3.2/html/doc/tutorials/imgproc/imgtrans/hough_lines/hough_lines.htmlhttp://lib.csdn.net/article/opencv/24201The code is as follows:#Line Detection#using Hough linear transformation to do straight

", cv_window_autosize); -Imshow ("Input Image", SRC); - - Mat DST, Dst_gray; +Resize (Src,dst,size ( -, -));//Change Size - + Cvtcolor (dst,dst_gray,color_bgr2gray); A atHogdescriptor Detector (Size ( -, -), Size ( -, -), Size (8,8), Size (8,8),9); -vectorfloat> descriptors;//histogram vector -Vectorlocations; -Detector.compute (Dst_gray, Descriptors,size (0,0), Size (0,0), locations); -printf"Number of HOG descriptors:%d", Descriptors.size ()); - inWaitkey (0); - return 0; to}Pedestrian

I haven't made a summary for a while. I don't know what I'm busy with every day! Now it takes an hour to summarize the learning in the last few days. Edge detection technology is the first step in image analysis. It uses the extreme values of the first derivative of the image or the zero point information of the second derivative to extract the edge. To put it simply, it is the problem of gray-scale image changes. In some places, image changes are slo

PYTHON+OPENCV implementation of Gaussian smoothing filterPYTHON+OPENCV Realization of threshold segmentation(2016-5-10) to Opencv-python tutorials ' s documentation can be downloadedFunction:Create a slider bar to control the length threshold of the detection line, which is greater than the threshold value and is less

threshold value. This point is the corner point.To avoid calculating eigenvalues (time-consuming), use the following formula instead:The determinant of the Det matrix, traces of the trace matrix. It has been proved that the value of this equation is higher when two eigenvalues are high. The parameter k is generally set to 0.05~0.5.Harris Corner detection, can be improved by maximal value inhibition, that is, to ensure that the strength of the corner

*argv[]) { Charfilenamestring[ -]; Charwindownamestring[ -]; Charresultfilenamesring[ -]; Mat Srcimage,grayimage,blurimage,thresholdimage,gradientximage,gradientyimage,gradientimage,morphimage; for(intFileCount =1; FileCount 8; filecount++) {sprintf (filenamestring,"f:\\opencv\\ barcode Detection and identification \\barcode_0%d.jpg", FileCount); sprintf (windownamestring,"result 0%d", FileCount); sp

Original address: opencv for iOS Study Notes (4)-mark Detection 1 A simple tag is often a regular image consisting of a white block and a black block. Because we know these factors in advance, we can easily detect tags. First, we need to find the closed profile and then check our mark in the Rectangular profile. The following is the process for marking the monitoring pipeline: 1. Convert the input image

Previously, we used MATLAB to implement algorithms. Recently, we started to use opencv as a target tracking algorithm. We found that opencv is really powerful. It integrates many algorithms and encapsulates many functions, the method is similar to MATLAB, but it is more efficient than Matlab. The following describes the human body detection code using the hog alg

OpenCV Read the image sequence for hog pedestrian detection and saved as a video http://blog.csdn.net/masibuaa/article/details/160844672013-11-13 21:42 4273 People read comments (17) Collection Report Category: Computer Vision (OpenCV) Hog target detection (7) Copyright NOTICE: This article is the original article of

Traditional edge detection: OpenCV inside of the two functions, Cv2. Canny () and cv2.findcontours (): It looks like it's easy to come true, but the real picture is that it doesn't work in a complex background. The detection effect of the canny algorithm relies on several threshold parameters, and the selection of these threshold parameters is usually a human-s

Pure reading, please visit OPENCV using the Harris Algorithm for corner detectionSourceKqwopencvfeaturesdemoA corner point is an intersection of two edges or a point that has several significant edge orientations in a local neighborhood. Harris Corner Point Detection is one of the most common techniques in corner detection.The Harris corner detector uses a sliding window on the image to calculate the bright

small, ignore it PrintCv2.contourarea (c)ifCv2.contourarea (c) "Min_area"]: Continue #compute the bounding box for the contour, draw it on the frame, #and update the text #calculates the bounding box of the outline, drawing the box in the current frame(x, Y, W, h) =Cv2.boundingrect (c) Cv2.rectangle (frame, (x, y), (x+ W, y + h), (0, 255, 0), 2) Text="occupied" #Draw the text and timestamp on the frame #write text and timestamp on the current frameCv

Note that the axis of the OPENCV, the x-axis to the right, and the width corresponding to the Y axis downward, and the height of the corresponding; 1. MOG2 and KNN Mog:mixture of Gaussian Import cv2 cap = Cv2. Videocapture ('./data/video/768x576.avi ') knn_sub = CV2.CREATEBACKGROUNDSUBTRACTORKNN () mog2_sub = CV2.CREATEBACKGROUNDSUBTRACTORMOG2 () while True: ret, frame = Cap.read () if not ret: break Mog_ Sub_mask = mog2_sub.app

Use the opencv functions surffeaturedetector and detect to detect interest points; Use the opencv function drawkeypoints to draw the detection key points. /** * @file SURF_detector * @brief SURF keypoint detection + keypoint drawing with OpenCV functions * @author A. Huaman

=59244hilit=tbb_debug.dll#p59244 , follow the URL given in the forum, download a TBB package, unzip Tbb_debug.dll to D:\Program FILES\OPENCV\BUILD\COMMON\TBB\IA32\VC10 (this is my installation directory). Error 3.Haha, the end of the code more than a}, delete it is good.Error 4.The compilation has passed smoothly, and now a debugging will findVery simply, the routines are estimated to run main () with CMD, and the parameters are tapped into the comma

These days, we 've been stuck in the fast, surf, shift, brief, and ORB feature detection algorithms !!! All labs are in the previous blog. Opencv has already implemented them, so we will use opencv to test the effects of various methods, My original intention was match. The feature points detected by fast could not be extracted from descriptor !!! However, it is

Original address: opencv for iOS Study Notes (10)-mark detection Summary If you keep following our tutorial, you can run the program as follows: Even if we do not use a three-dimensional rendering engine for visualization, we have obtained all the necessary data. Let's sum up what we get: 1. One frame from the bgra format of the camera 2. Correctly used as the pivot projection matrix for Ar Scene Re

Opencv provides the pedestrain detection class. CV: definitions of parameters of the hogdescriptor class constructor: Cv_wrap hogdescriptor (): winsize (64,128), // detect window blocksize (16, 16), // block size blockstride (8, 8), // Slide Step cellsize (8, 8) of overlap block ), // cell size nbins (9), // Number of bin in the histogram derivaperture (1), // winsigma (-1 ), // perform Gaussian weighted

Detection code is as follows:#encoding: Utf-8##Sobel边缘检测#Import NumPy as Npimport cv2image = Cv2. Imread("H:\\img\\lena.jpg") image = Cv2. Cvtcolor(Image,cv2. COLOR_bgr2gray)#将图像转化为灰度图像Cv2. Imshow("Original", image) Cv2. Waitkey()#Sobel边缘检测Sobelx = Cv2. Sobel(Image,cv2. CV_64f,1,0)#x方向的梯度sobely = Cv2. Sobel(Image,cv2. CV_64f,0,1)#y方向的梯度SOBELX = NP. UINT8 (NP. Absolute(SOBELX))#x方向梯度的绝对值sobely = NP. UINT8 (NP. Absolute(sobely))#y方向梯度的绝对值sobelcombined