opencv object recognition

About Object DetectionEnvironment: OpenCV 2.4.11+vs2013Reference:Http://www.cnblogs.com/tornadomeet/archive/2012/06/02/2531705.htmlHttp://www.cnblogs.com/xinyuyuanm/archive/2013/04/29/3050750.html1#include string>2#include 3#include 4#include 5#include 6 7#include 8#include 9#include Ten#include One A using namespacestd; - using namespaceCV; - the #defineThreshold_diff 20 - intMain () - { -Mat Src1 = Imr

normalizes the pixel value of the image, and then uses the cvcvtcolor function in opencv to convert the image from the RGB space to the HSV space. 5. Set a random number Gsl_rng_env_setup (); // setup the enviorment of random number generator RNG = gsl_rng_alloc (gsl_rng_mt19937); // create a random number generator Gsl_rng_set (RNG, time (null); // initializes the random number generator. The author uses the GSL library to generate random numbers.

; - }Wuyi } theprintf"min Distance:%f", mindist); - Wu for(inti =0; i ) { - DoubleDist =matches[i].distance; About if(Dist 1.5*mindist,0.02)) { $ Goodmatches.push_back (Matches[i]); - } - } - ADrawmatches (IMG1, Keypoints_obj, Img2, Keypoints_scene, Goodmatches, Akazematchesimg, Scalar::all (-1), +Scalar::all (-1), vectorChar>(), drawmatchesflags::not_draw_single_points); theImshow ("Good match result", akazematchesimg); - $Waitkey (0); the ret

Original link: 50649811ImportCv2ImportNumPy as NP camera=Cv2. Videocapture (0) Firstframe=None whileTrue:ret,frame=Camera.read ()if notret: BreakGray=Cv2.cvtcolor (Frame,cv2. Color_bgr2gray) Gray=cv2. Gaussianblur (Gray, 21,21), 0)ifFirstframe isNone:firstframe=GrayContinueFramedelta=Cv2.absdiff (firstframe,gray) Thresh= Cv2.threshold (Framedelta, 255, Cv2. thresh_binary) [1] Thresh= Cv2.dilate (Thresh, None, iterations=2) #cnts= cv2.findcontours (Thresh.copy (), Cv2. Retr_external,cv2. Ch

considered an outlier. If srcpoints and dstpoints is measured in pixels, it usually makes sense to set this parameter SOMEWH Ere in the range of 1 to 10. mask –optional output mask set by a robust method ( Cv_ransac or cv_lmeds ). Note that the input mask values is ignored. The functions find and return the perspective transformation between the source and the destination planes: So, the back-projection error is minimized. If the parameter method is set t

Document directory 1) load the cascade classifier 2) read Video Streams 3) use this classifier for each frame 4) display the target The target detection method supported by opencv is the classifier training based on the Haar feature of the sample to obtain the cascade boosted classification ). Note: In addition to haar features, the new C ++ interface can also use the HSV features. First, we will introduce the relevant structure. featureevalua

In this paper, "PYTHON+OPENCV practice" A, color-based object tracking (I.) The functional enhancements were made as follows: (1) The addition of PTS emptying, that is, when the target is not detected, empty PTS, showing no longer traces of the image; (2) The direction of motion and the current coordinate can be judged by the addition of the movement directions. From collections import deque import NumPy a