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  • How do people prove the correctness of Computer Vision methods?

    - by solvingPuzzles
    I'd like to pose a few abstract questions about computer vision research. I haven't quite been able to answer these questions by searching the web and reading papers. How does someone know whether a computer vision algorithm is correct? How do we define "correct" in the context of computer vision? Do formal proofs play a role in understanding the correctness of computer vision algorithms? A bit of background: I'm about to start my PhD in Computer Science. I enjoy designing fast parallel algorithms and proving the correctness of these algorithms. I've also used OpenCV from some class projects, though I don't have much formal training in computer vision. I've been approached by a potential thesis advisor who works on designing faster and more scalable algorithms for computer vision (e.g. fast image segmentation). I'm trying to understand the common practices in solving computer vision problems.

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  • Extracting Information from Images

    - by Khorkrak
    What are some fast and somewhat reliable ways to extract information about images? I've been tinkering with openCV and this seems so far to be the best route plus it has Python bindings. So to be more specific I'd like to determine what I can about what's in an image. So for example the haar face detection and full body detection classifiers are great - now I can tell that most likely there are faces and / or people in the image as well as about how many. okay - what else - how about whether there are any buildings and if so what do they seem to be - huts, office buildings etc? Is there sky visible, grass, trees and so forth. From what I've read about training classifiers to detect objects, it seems like a rather laborious process 10,000 or so wrong images and 5,000 or so correct samples to train a classifier. I'm hoping that there are some decent ones around already instead of having to do this all myself for a bunch of different objects - or is there some other way to go about this sort of thing?

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  • Images to video - converting to IplImage makes video blue

    - by user891908
    I want to create a video from images using opencv. The strange problem is that if i will write image (bmp) to disk and then load (cv.LoadImage) it it renders fine, but when i try to load image from StringIO and convert it to IplImage, it turns video to blue. Heres the code: import StringIO output = StringIO.StringIO() FOREGROUND = (0, 0, 0) TEXT = 'MY TEXT' font_path = 'arial.ttf' font = ImageFont.truetype(font_path, 18, encoding='unic') text = TEXT.decode('utf-8') (width, height) = font.getsize(text) # Create with background with place for text w,h=(600,600) contentimage=Image.open('0.jpg') background=Image.open('background.bmp') x, y = contentimage.size # put content onto background background.paste(contentimage,(((w-x)/2),0)) draw = ImageDraw.Draw(background) draw.text((0,0), text, font=font, fill=FOREGROUND) pi = background pi.save(output, "bmp") #pi.show() #shows image in full color output.seek(0) pi= Image.open(output) print pi, pi.format, "%dx%d" % pi.size, pi.mode cv_im = cv.CreateImageHeader(pi.size, cv.IPL_DEPTH_8U, 3) cv.SetData(cv_im, pi.tostring()) print pi.size, cv.GetSize(cv_im) w = cv.CreateVideoWriter("2.avi", cv.CV_FOURCC('M','J','P','G'), 1,(cv.GetSize(cv_im)[0],cv.GetSize(cv_im)[1]), is_color=1) for i in range(1,5): cv.WriteFrame(w, cv_im) del w

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  • O'Reilly book clarification on 2d linear system

    - by Eric
    The Oreilly book "Learning openCV" states at page 356 : Quote Before we get totally lost, let’s consider a particular realistic situation of taking measurements on a car driving in a parking lot. We might imagine that the state of the car could be summarized by two position variables, x and y, and two velocities, vx and vy. These four variables would be the elements of the state vector xk. Th is suggests that the correct form for F is: x = [ x; y; vx; vy; ]k F = [ 1, 0, dt, 0; 0, 1, 0, dt; 0, 0, 1, 0; 0, 0, 0, 1; ] It seems natural to put 'dt' just there in the F matrix but I just don't get why. What if I have a n states system, how would I spray some "dt" in the F matrix?

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  • How to detect circles accurately

    - by user1767798
    Is there any way to accurately detect circles in opencv? I was using hough transform which give me good result but most of the time, shadow of the object and surrounding,light etc gives bad results, so am looking for options other than hough circles, accurate detection is very important for my project. My basic approach so far is to find some spheres in the image taken in realtime. I am using houghcircle to find the spheres and base later calculations on the radius I am getting from that. If the background is plain and nothing the sphere detect without problem, however if I am taking that image in my room where the background will have other objects it's often difficult to detect. So am looking for some other approach.

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  • Track Pedestrians

    - by 2vision2
    I am using OpenCV sample code “peopledetect.cpp” to detect and track pedestrians. The code uses HoG for feature extraction and SVM for classification. Please find the reference paper used here. The camera is mounted on the wall at a height of 10 feet and 45 degree down. There is no restriction on the pedestrian movement within the frame. I want to track the detected pedestrians’ movement within the frame. The issue I am facing is pedestrians are detected only in the middle region of the frame as most of the features are not visible as soon as the pedestrian enters the frame region. I want to track each person’s movement in the entire frame region. How to do it? Is tracking required? Can anyone give any reference to blogs/codes?

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  • Approximate photo of a simple drawing using lines

    - by user3704596
    As an input I have a photo of a simple symbol, e.g.: https://www.dropbox.com/s/nrmsvfd0le0bkke/symbol.jpg I would like to detect the straight lines in it, like points of start and ends of the lines. In this case, assuming the top left of the symbol is (0,0), the lines would be defined like this: start end (coordinates of beginning and end of a line) 1. (0,0); (0,10) (vertical line) 2. (0,10); (15, 15) 3. (15,15); (0, 20) 4. (0,20); (0,30) How can I do it (pereferably using OpenCV)? I though about Hough lines, but they seem to be good for perfect thin straight lines, which is not the case in a drawing. I'll probably work on binarized image, too.

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  • How to make this jpeg compression faster

    - by Richard Knop
    I am using OpenCV to compress binary images from a camera: vector<int> p; p.push_back(CV_IMWRITE_JPEG_QUALITY); p.push_back(75); // JPG quality vector<unsigned char> jpegBuf; cv::imencode(".jpg", fIplImageHeader, jpegBuf, p); The code above compresses a binary RGB image stored in fIplImageHeader to a JPEG image. For a 640*480 image it takes about 0.25 seconds to execute the five lines above. Is there any way I could make it faster? I really need to repeat the compression more than 4 times a second.

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  • Working with image pixels

    - by Mario
    Hey Guys, I'm trying to do a project here, which I want to implement the following: I have a rotation matrix and translation matrix are estimated, now I have an image in a certain location and I want to multiply all the image pixel by the rotation matrix and add the results to the translation matrix..... My issue is how to work with the pixels? I mean how to extract the pixel from the image in order to do the operation that I mentioned above? it's ok to give me the suggestion in either opencv or c++ *I need to know how to do this operation new_p(x,y) = old(x,y)* rotation_matrix + translation_matrix. I'm defining the image like that IplImage(), 3 channel image. For now I need to do the geometrical transformation* Thank you.

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  • What causes Python "Interpreter not Initialized" error?

    - by ?????
    I'm now on my third full day this week of trying to get OpenCV to work with Python. (I have been trying on and off for the past 6 months). I get this error Python 2.7.1 (r271:86882M, Nov 30 2010, 10:35:34) [GCC 4.2.1 (Apple Inc. build 5664)] on darwin Type "help", "copyright", "credits" or "license" for more information. dlopen("/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/lib-dynload/readline.so", 2); import readline # dynamically loaded from /Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/lib-dynload/readline.so >>> import cv dlopen("./cv.so", 2); Fatal Python error: Interpreter not initialized (version mismatch?) and then it crashes (core dumps). python -v gives nothing after the dlopen. Any ideas from anyone who actually knows about this error?

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  • Detecting crosses in an image

    - by MrOrdinaire
    I am working on a program to detect the tips of a probing device and analyze the color change during probing. The input/output mechanisms are more or less in place. What I need now is the actual meat of the thing: detecting the tips. In the images below, the tips are at the center of the crosses. I thought of applying BFS to the images after some threshold'ing but was then stuck and didn't know how to proceed. I then turned to OpenCV after reading that it offers feature detection in images. However, I am overwhelmed by the vast amount of concepts and techniques utilized here and again, clueless about how to proceed. Am I looking at it the right way? Can you give me some pointers? Image extracted from short video Binary version with threshold set at 95

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  • cvRetrieveFrame crahses

    - by pooh_bear
    I'm trying to write a simple openCV code that create a capture and retrieves the first frame from it. **CvCapture *m_pCapfile = cvCreateFileCapture(m_aviFileName.c_str()); if (m_pCapfile) m_frames = cvRound(cvGetCaptureProperty(m_pCapfile, CV_CAP_PROP_FRAME_COUNT)); cvSetCaptureProperty(m_pCapfile, CV_CAP_PROP_POS_FRAMES, 0); int ret = cvGrabFrame( m_pCapfile); IplImage *cap = cvRetrieveFrame( m_pCapfile);** In m_frames is have 153, which is the correct number of frames as far as I know. cvGrabFrame returns 1 to ret however cvRetrieveFrame crashes. I tries using cvCaptureFromFile and cvCaptureFromAVI instead of cvCreateFileCapture In both cases cvRetrieveFrame method crashes. Any ideas? Thanks

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  • Fast, very lightweight algorithm for camera motion detection?

    - by Ertebolle
    I'm working on an augmented reality app for iPhone that involves a very processor-intensive object recognition algorithm (pushing the CPU at 100% it can get through maybe 5 frames per second), and in an effort to both save battery power and make the whole thing less "jittery" I'm trying to come up with a way to only run that object recognizer when the user is actually moving the camera around. My first thought was to simply use the iPhone's accelerometers / gyroscope, but in testing I found that very often people would move the iPhone at a consistent enough attitude and velocity that there wouldn't be any way to tell that it was still in motion. So that left the option of analyzing the actual video feed and detecting movement in that. I got OpenCV working and tried running their pyramidal Lucas-Kanade optical flow algorithm, which works well but seems to be almost as processor-intensive as my object recognizer - I can get it to an acceptable framerate if I lower the depth levels / downsample the image / track fewer points, but then accuracy suffers and it starts to miss some large movements and trigger on small hand-shaking-y ones. So my question is, is there another optical flow algorithm that's faster than Lucas-Kanade if I just want to detect the overall magnitude of camera movement? I don't need to track individual objects, I don't even need to know which direction the camera is moving, all I really need is a way to feed something two frames of video and have it tell me how far apart they are.

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  • View results of affine transform

    - by stckjp
    I am trying to find out the reason why when I apply affine transformations on an image in OpenCV, the result of it is not visible in the preview window, but the entire window is black.How can I find workaround for this problem so that I can always view my transformed image (the result of the affine transform) in the window no matter the applied transformation? Update: I think that this happens because all the transformations are calculated with respect to the origin of the coordinate system (top left corner of the image). While for rotation I can specify the center of the rotation, and I am able to view the result, when I perform scaling I am not able to control where the transformed image goes. Is it possible to somehow move the coordinate system to make the image fit in the window? Update2: I have an image which contains only ROI at some position in it (the rest of the image is black), and I need to apply a set of affine transforms on it. To make things simpler and to see the effect of each individual transform, I applied each transform one by one. What I noticed is that, whenever I move (translate) the image such that the center of the ROI is in the center of the coordinate system (top left corner of the view window), all the affine transforms perform correctly without moving. However, by translating the center of ROI at the center of the coordinate system, the upper and the left part of the ROI remain cut out of the current view window. If I move ROI's central point to another point in the view window (for example the window center), an affine transform of type: A=[a 0 0; 0 b 0] (A is 2x3 matrix, parameter of the warpAffine function) moves the image (ROI), outside of the view window (which doesn't happen if the ROI's center is in the top-left corner). How can I modify the affine transform so the image doesn't move out of its place (behaves the same way as when the ROI center is in the center of the coordinate system)?

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  • Choosing a VS project type (C++)

    - by typoknig
    Hi all, I do not use C++ much (I try to stick to the easier stuff like Java and VB.NET), but the lately I have not had a choice. When I am picking a project type in VS for some C++ source I download, what project type should I pick? I had just been sticking with Win32 Console Applications, but I just downloaded some code (below) that will not work right even when it compiles with out errors. I have tried to use a CLR Console Application and an empty project too, and have changed many variables along the way, but I cannot get this code to work. I noticed that this code does not have "int main()" at its beginning, does that have something to do with it? Anyways, here is the code, got it from here: /* Demo of modified Lucas-Kanade optical flow algorithm. See the printf below */ #ifdef _CH_ #pragma package <opencv> #endif #ifndef _EiC #include "cv.h" #include "highgui.h" #include <stdio.h> #include <ctype.h> #endif #include <windows.h> #define FULL_IMAGE_AS_OUTPUT_FILE #define cvMirror cvFlip //IplImage *image = 0, *grey = 0, *prev_grey = 0, *pyramid = 0, *prev_pyramid = 0, *swap_temp; IplImage **buf = 0; IplImage *image1 = 0; IplImage *imageCopy=0; IplImage *image = 0; int win_size = 10; const int MAX_COUNT = 500; CvPoint2D32f* points[2] = {0,0}, *swap_points; char* status = 0; //int count = 0; //int need_to_init = 0; //int night_mode = 0; int flags = 0; //int add_remove_pt = 0; bool bLButtonDown = false; //bool bstopLoop = false; CvPoint pt, pt1,pt2; //IplImage* img1; FILE* FileDest; char* strImageDir = "E:\\Projects\\TSCreator\\Images"; char* strItemName = "b"; int imageCount=0; int bFirstFace = 1; // flag for first face int mode = 1; // Mode 1 - Haar Traing Sample Creation, 2 - HMM sample creation, Mode = 3 - Both Harr and HMM. //int startImgeNo = 1; bool isEqualRation = false; //Weidth to height ratio is equal //Selected Image data IplImage *selectedImage = 0; int selectedX = 0, selectedY = 0, currentImageNo = 0, selectedWidth = 0, selectedHeight= 0; CvRect selectedROI; void saveFroHarrTraining(IplImage *src, int x, int y, int width, int height, int imageCount); void saveForHMMTraining(IplImage *src, CvRect roi,int imageCount); // Code for draw ROI Cropping Image void on_mouse( int event, int x, int y, int flags, void* param ) { char f[200]; CvRect reg; if( !image ) return; if( event == CV_EVENT_LBUTTONDOWN ) { bLButtonDown = true; pt1.x = x; pt1.y = y; } else if ( event == CV_EVENT_MOUSEMOVE ) //Draw the selected area rectangle { pt2.x = x; pt2.y = y; if(bLButtonDown) { if( !image1 ) { /* allocate all the buffers */ image1 = cvCreateImage( cvGetSize(image), 8, 3 ); image1->origin = image->origin; points[0] = (CvPoint2D32f*)cvAlloc(MAX_COUNT*sizeof(points[0][0])); points[1] = (CvPoint2D32f*)cvAlloc(MAX_COUNT*sizeof(points[0][0])); status = (char*)cvAlloc(MAX_COUNT); flags = 0; } cvCopy( image, image1, 0 ); //Equal Weight-Height Ratio if(isEqualRation) { pt2.y = pt1.y + (pt2.x-pt1.x); } //Max Height and Width is the image width and height if(pt2.x>image->width) { pt2.x = image->width; } if(pt2.y>image->height) { pt2.y = image->height; } CvPoint InnerPt1 = pt1; CvPoint InnerPt2 = pt2; if ( InnerPt1.x > InnerPt2.x) { int tempX = InnerPt1.x; InnerPt1.x = InnerPt2.x; InnerPt2.x = tempX; } if ( pt2.y < InnerPt1.y ) { int tempY = InnerPt1.y; InnerPt1.y = InnerPt2.y; InnerPt2.y = tempY; } InnerPt1.y = image->height - InnerPt1.y; InnerPt2.y = image->height - InnerPt2.y; CvFont font; double hScale=1.0; double vScale=1.0; int lineWidth=1; cvInitFont(&font,CV_FONT_HERSHEY_SIMPLEX|CV_FONT_ITALIC, hScale,vScale,0,lineWidth); char size [200]; reg.x = pt1.x; reg.y = image->height - pt2.y; reg.height = abs (pt2.y - pt1.y); reg.width = InnerPt2.x -InnerPt1.x; //print width and heght of the selected reagion sprintf(size, "(%dx%d)",reg.width, reg.height); cvPutText (image1,size,cvPoint(10,10), &font, cvScalar(255,255,0)); cvRectangle(image1, InnerPt1, InnerPt2, CV_RGB(255,0,0), 1); //Mark Selected Reagion selectedImage = image; selectedX = pt1.x; selectedY = pt1.y; selectedWidth = reg.width; selectedHeight = reg.height; selectedROI = reg; //Show the modified image cvShowImage("HMM-Harr Positive Image Creator",image1); } } else if ( event == CV_EVENT_LBUTTONUP ) { bLButtonDown = false; // pt2.x = x; // pt2.y = y; // // if ( pt1.x > pt2.x) // { // int tempX = pt1.x; // pt1.x = pt2.x; // pt2.x = tempX; // } // // if ( pt2.y < pt1.y ) // { // int tempY = pt1.y; // pt1.y = pt2.y; // pt2.y = tempY; // // } // //reg.x = pt1.x; //reg.y = image->height - pt2.y; // //reg.height = abs (pt2.y - pt1.y); ////reg.width = reg.height/3; //reg.width = pt2.x -pt1.x; ////reg.height = (2 * reg.width)/3; #ifdef FULL_IMAGE_AS_OUTPUT_FILE CvRect FullImageRect; FullImageRect.x = 0; FullImageRect.y = 0; FullImageRect.width = image->width; FullImageRect.height = image->height; IplImage *regionFullImage =0; regionFullImage = cvCreateImage(cvSize (FullImageRect.width, FullImageRect.height), image->depth, image->nChannels); image->roi = NULL; //cvSetImageROI (image, FullImageRect); //cvCopy (image, regionFullImage, 0); #else IplImage *region =0; region = cvCreateImage(cvSize (reg.width, reg.height), image1->depth, image1->nChannels); image->roi = NULL; cvSetImageROI (image1, reg); cvCopy (image1, region, 0); #endif //cvNamedWindow("Result", CV_WINDOW_AUTOSIZE); //selectedImage = image; //selectedX = pt1.x; //selectedY = pt1.y; //selectedWidth = reg.width; //selectedHeight = reg.height; ////currentImageNo = startImgeNo; //selectedROI = reg; /*if(mode == 1) { saveFroHarrTraining(image,pt1.x,pt1.y,reg.width,reg.height,startImgeNo); } else if(mode == 2) { saveForHMMTraining(image,reg,startImgeNo); } else if(mode ==3) { saveFroHarrTraining(image,pt1.x,pt1.y,reg.width,reg.height,startImgeNo); saveForHMMTraining(image,reg,startImgeNo); } else { printf("Invalid mode."); } startImgeNo++;*/ } } /* Save popsitive samples for Harr Training. Also add an entry to the PositiveSample.txt with the location of the item of interest. */ void saveFroHarrTraining(IplImage *src, int x, int y, int width, int height, int imageCount) { char f[255] ; sprintf(f,"%s\\%s\\harr_%s%d%d.jpg",strImageDir,strItemName,strItemName,imageCount/10, imageCount%10); cvNamedWindow("Harr", CV_WINDOW_AUTOSIZE); cvShowImage("Harr", src); cvSaveImage(f, src); printf("output%d%d \t ", imageCount/10, imageCount%10); printf("width %d \t", width); printf("height %d \t", height); printf("x1 %d \t", x); printf("y1 %d \t\n", y); char f1[255]; sprintf(f1,"%s\\PositiveSample.txt",strImageDir); FileDest = fopen(f1, "a"); fprintf(FileDest, "%s\\harr_%s%d.jpg 1 %d %d %d %d \n",strItemName,strItemName, imageCount, x, y, width, height); fclose(FileDest); } /* Create Sample Images for HMM recognition algorythm trai ning. */ void saveForHMMTraining(IplImage *src, CvRect roi,int imageCount) { char f[255] ; printf("x=%d, y=%d, w= %d, h= %d\n",roi.x,roi.y,roi.width,roi.height); //Create the file name sprintf(f,"%s\\%s\\hmm_%s%d.pgm",strImageDir,strItemName,strItemName, imageCount); //Create storage for grayscale image IplImage* gray = cvCreateImage(cvSize(roi.width,roi.height), 8, 1); //Create storage for croped reagon IplImage* regionFullImage = cvCreateImage(cvSize(roi.width,roi.height),8,3); //Croped marked region cvSetImageROI(src,roi); cvCopy(src,regionFullImage); cvResetImageROI(src); //Flip croped image - otherwise it will saved upside down cvConvertImage(regionFullImage, regionFullImage, CV_CVTIMG_FLIP); //Convert croped image to gray scale cvCvtColor(regionFullImage,gray, CV_BGR2GRAY); //Show final grayscale image cvNamedWindow("HMM", CV_WINDOW_AUTOSIZE); cvShowImage("HMM", gray); //Save final grayscale image cvSaveImage(f, gray); } int maina( int argc, char** argv ) { CvCapture* capture = 0; //if( argc == 1 || (argc == 2 && strlen(argv[1]) == 1 && isdigit(argv[1][0]))) // capture = cvCaptureFromCAM( argc == 2 ? argv[1][0] - '0' : 0 ); //else if( argc == 2 ) // capture = cvCaptureFromAVI( argv[1] ); char* video; if(argc ==7) { mode = atoi(argv[1]); strImageDir = argv[2]; strItemName = argv[3]; video = argv[4]; currentImageNo = atoi(argv[5]); int a = atoi(argv[6]); if(a==1) { isEqualRation = true; } else { isEqualRation = false; } } else { printf("\nUsage: TSCreator.exe <Mode> <Sample Image Save Path> <Sample Image Save Directory> <Video File Location> <Start Image No> <Is Equal Ratio>\n"); printf("Mode = 1 - Haar Traing Sample Creation. \nMode = 2 - HMM sample creation.\nMode = 3 - Both Harr and HMM\n"); printf("Is Equal Ratio = 0 or 1. 1 - Equal weidth and height, 0 - custom."); printf("Note: You have to create the image save directory in correct path first.\n"); printf("Eg: TSCreator.exe 1 E:\Projects\TSCreator\Images A 11.avi 1 1\n\n"); return 0; } capture = cvCaptureFromAVI(video); if( !capture ) { fprintf(stderr,"Could not initialize capturing...\n"); return -1; } cvNamedWindow("HMM-Harr Positive Image Creator", CV_WINDOW_AUTOSIZE); cvSetMouseCallback("HMM-Harr Positive Image Creator", on_mouse, 0); //cvShowImage("Test", image1); for(;;) { IplImage* frame = 0; int i, k, c; frame = cvQueryFrame( capture ); if( !frame ) break; if( !image ) { /* allocate all the buffers */ image = cvCreateImage( cvGetSize(frame), 8, 3 ); image->origin = frame->origin; //grey = cvCreateImage( cvGetSize(frame), 8, 1 ); //prev_grey = cvCreateImage( cvGetSize(frame), 8, 1 ); //pyramid = cvCreateImage( cvGetSize(frame), 8, 1 ); // prev_pyramid = cvCreateImage( cvGetSize(frame), 8, 1 ); points[0] = (CvPoint2D32f*)cvAlloc(MAX_COUNT*sizeof(points[0][0])); points[1] = (CvPoint2D32f*)cvAlloc(MAX_COUNT*sizeof(points[0][0])); status = (char*)cvAlloc(MAX_COUNT); flags = 0; } cvCopy( frame, image, 0 ); // cvCvtColor( image, grey, CV_BGR2GRAY ); cvShowImage("HMM-Harr Positive Image Creator", image); cvSetMouseCallback("HMM-Harr Positive Image Creator", on_mouse, 0); c = cvWaitKey(0); if((char)c == 's') { //Save selected reagion as training data if(selectedImage) { printf("Selected Reagion Saved\n"); if(mode == 1) { saveFroHarrTraining(selectedImage,selectedX,selectedY,selectedWidth,selectedHeight,currentImageNo); } else if(mode == 2) { saveForHMMTraining(selectedImage,selectedROI,currentImageNo); } else if(mode ==3) { saveFroHarrTraining(selectedImage,selectedX,selectedY,selectedWidth,selectedHeight,currentImageNo); saveForHMMTraining(selectedImage,selectedROI,currentImageNo); } else { printf("Invalid mode."); } currentImageNo++; } } } cvReleaseCapture( &capture ); //cvDestroyWindow("HMM-Harr Positive Image Creator"); cvDestroyAllWindows(); return 0; } #ifdef _EiC main(1,"lkdemo.c"); #endif If I put... #include "stdafx.h" int _tmain(int argc, _TCHAR* argv[]) { return 0; } ... before the previous code (and link it to the correct OpenCV .lib files) it compiles without errors, but does nothing at the command line. How do I make it work?

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  • How to solve QPixmap::fromImage memory leak?

    - by dodoent
    Hello everyone! I have a problem with Qt. Here is a part of code that troubles me: void FullScreenImage::QImageIplImageCvt(IplImage *input) { help=cvCreateImage(cvGetSize(input), input->depth, input->nChannels); cvCvtColor(input, help, CV_BGR2RGB); QImage tmp((uchar *)help->imageData, help->width, help->height, help->widthStep, QImage::Format_RGB888); this->setPixmap(QPixmap::fromImage(tmp).scaled(this->size(), Qt::IgnoreAspectRatio, Qt::SmoothTransformation)); cvReleaseImage(&help); } void FullScreenImage::hideOnScreen() { this->hide(); this->clear(); } void FullScreenImage::showOnScreen(IplImage *slika, int delay) { QImageIplImageCvt(slika); this->showFullScreen(); if(delay>0) QTimer::singleShot(delay*1000, this, SLOT(hideOnScreen())); } So, the method showOnScreen uses private method QImageIplImageCvt to create QImage from IplImage (which is used by the openCV), which is then used to create QPixmap in order to show the image in full screen. FullScreenImage class inherits QLabel. After some delay, the fullscreen picture should be hidden, so I use QTimer to trigger an event after some delay. The event handler is the hideOnScreen method which hides the label and should clear the memory. The problem is the following: Whenever I call QPixmap::fromImage, it allocates the memory for the pixmap data and copies the data from QImage memory buffer to the QPixmap memory buffer. After the label is hidden, the QPixmap data still remains allocated, and even worse, after the new QPixmap::fromImage call the new chunk of memory is allocated for the new picture, and the old data is not freed from memory. This causes a memory leak (cca 10 MB per method call with my testing pictures). How can I solve that leak? I've even tried to create a private QPixmap variable, store pixmap created by the QPixmap::fromImage to it, and then tried to call its destructor in hideOnScreen method, but it didn't help. Is there a non-static way to create QPixmap from QImage? Or even better, is there a way to create QPixmap directly from IplImage* ? Thank you in advance for your answers.

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  • Using fft2 with reshaping for an RGB filter

    - by Mahmoud Aladdin
    I want to apply a filter on an image, for example, blurring filter [[1/9.0, 1/9.0, 1/9.0], [1/9.0, 1/9.0, 1/9.0], [1/9.0, 1/9.0, 1/9.0]]. Also, I'd like to use the approach that convolution in Spatial domain is equivalent to multiplication in Frequency domain. So, my algorithm will be like. Load Image. Create Filter. convert both Filter & Image to Frequency domains. multiply both. reconvert the output to Spatial Domain and that should be the required output. The following is the basic code I use, the image is loaded and displayed as cv.cvmat object. Image is a class of my creation, it has a member image which is an object of scipy.matrix and toFrequencyDomain(size = None) uses spf.fftshift(spf.fft2(self.image, size)) where spf is scipy.fftpack and dotMultiply(img) uses scipy.multiply(self.image, image) f = Image.fromMatrix([[1/9.0, 1/9.0, 1/9.0], [1/9.0, 1/9.0, 1/9.0], [1/9.0, 1/9.0, 1/9.0]]) lena = Image.fromFile("Test/images/lena.jpg") print lena.image.shape lenaf = lena.toFrequencyDomain(lena.image.shape) ff = f.toFrequencyDomain(lena.image.shape) lenafm = lenaf.dotMultiplyImage(ff) lenaff = lenafm.toTimeDomain() lena.display() lenaff.display() So, the previous code works pretty well, if I told OpenCV to load the image via GRAY_SCALE. However, if I let the image to be loaded in color ... lena.image.shape will be (512, 512, 3) .. so, it gives me an error when using scipy.fttpack.ftt2 saying "When given, Shape and Axes should be of same length". What I tried next was converted my filter to 3-D .. as [[[1/9.0, 1/9.0, 1/9.0], [1/9.0, 1/9.0, 1/9.0], [1/9.0, 1/9.0, 1/9.0]], [[1/9.0, 1/9.0, 1/9.0], [1/9.0, 1/9.0, 1/9.0], [1/9.0, 1/9.0, 1/9.0]], [[1/9.0, 1/9.0, 1/9.0], [1/9.0, 1/9.0, 1/9.0], [1/9.0, 1/9.0, 1/9.0]]] And, not knowing what the axes argument do, I added it with random numbers as (-2, -1, -1), (-1, -1, -2), .. etc. until it gave me the correct filter output shape for the dotMultiply to work. But, of course it wasn't the correct value. Things were totally worse. My final trial, was using fft2 function on each of the components 2-D matrices, and then re-making the 3-D one, using the following code. # Spiltting the 3-D matrix to three 2-D matrices. for i, row in enumerate(self.image): r.append(list()) g.append(list()) b.append(list()) for pixel in row: r[i].append(pixel[0]) g[i].append(pixel[1]) b[i].append(pixel[2]) rfft = spf.fftshift(spf.fft2(r, size)) gfft = spf.fftshift(spf.fft2(g, size)) bfft = spf.fftshift(spf.fft2(b, size)) newImage.image = sp.asarray([[[rfft[i][j], gfft[i][j], bfft[i][j]] for j in xrange(len(rfft[i]))] for i in xrange(len(rfft))] ) return newImage Any help on what I made wrong, or how can I achieve that for both GreyScale and Coloured pictures.

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  • Calculating rotation and translation matrices between two odometry positions for monocular linear triangulation

    - by user1298891
    Recently I've been trying to implement a system to identify and triangulate the 3D position of an object in a robotic system. The general outline of the process goes as follows: Identify the object using SURF matching, from a set of "training" images to the actual live feed from the camera Move/rotate the robot a certain amount Identify the object using SURF again in this new view Now I have: a set of corresponding 2D points (same object from the two different views), two odometry locations (position + orientation), and camera intrinsics (focal length, principal point, etc.) since it's been calibrated beforehand, so I should be able to create the 2 projection matrices and triangulate using a basic linear triangulation method as in Hartley & Zissermann's book Multiple View Geometry, pg. 312. Solve the AX = 0 equation for each of the corresponding 2D points, then take the average In practice, the triangulation only works when there's almost no change in rotation; if the robot even rotates a slight bit while moving (due to e.g. wheel slippage) then the estimate is way off. This also applies for simulation. Since I can only post two hyperlinks, here's a link to a page with images from the simulation (on the map, the red square is simulated robot position and orientation, and the yellow square is estimated position of the object using linear triangulation.) So you can see that the estimate is thrown way off even by a little rotation, as in Position 2 on that page (that was 15 degrees; if I rotate it any more then the estimate is completely off the map), even in a simulated environment where a perfect calibration matrix is known. In a real environment when I actually move around with the robot, it's worse. There aren't any problems with obtaining point correspondences, nor with actually solving the AX = 0 equation once I compute the A matrix, so I figure it probably has to do with how I'm setting up the two camera projection matrices, specifically how I'm calculating the translation and rotation matrices from the position/orientation info I have relative to the world frame. How I'm doing that right now is: Rotation matrix is composed by creating a 1x3 matrix [0, (change in orientation angle), 0] and then converting that to a 3x3 one using OpenCV's Rodrigues function Translation matrix is composed by rotating the two points (start angle) degrees and then subtracting the final position from the initial position, in order to get the robot's straight and lateral movement relative to its starting orientation Which results in the first projection matrix being K [I | 0] and the second being K [R | T], with R and T calculated as described above. Is there anything I'm doing really wrong here? Or could it possibly be some other problem? Any help would be greatly appreciated.

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  • Little more help with writing a o buffer with libjpeg

    - by Richard Knop
    So I have managed to find another question discussing how to use the libjpeg to compress an image to jpeg. I have found this code which is supposed to work: Compressing IplImage to JPEG using libjpeg in OpenCV Here's the code (it compiles ok): /* This a custom destination manager for jpeglib that enables the use of memory to memory compression. See IJG documentation for details. */ typedef struct { struct jpeg_destination_mgr pub; /* base class */ JOCTET* buffer; /* buffer start address */ int bufsize; /* size of buffer */ size_t datasize; /* final size of compressed data */ int* outsize; /* user pointer to datasize */ int errcount; /* counts up write errors due to buffer overruns */ } memory_destination_mgr; typedef memory_destination_mgr* mem_dest_ptr; /* ------------------------------------------------------------- */ /* MEMORY DESTINATION INTERFACE METHODS */ /* ------------------------------------------------------------- */ /* This function is called by the library before any data gets written */ METHODDEF(void) init_destination (j_compress_ptr cinfo) { mem_dest_ptr dest = (mem_dest_ptr)cinfo->dest; dest->pub.next_output_byte = dest->buffer; /* set destination buffer */ dest->pub.free_in_buffer = dest->bufsize; /* input buffer size */ dest->datasize = 0; /* reset output size */ dest->errcount = 0; /* reset error count */ } /* This function is called by the library if the buffer fills up I just reset destination pointer and buffer size here. Note that this behavior, while preventing seg faults will lead to invalid output streams as data is over- written. */ METHODDEF(boolean) empty_output_buffer (j_compress_ptr cinfo) { mem_dest_ptr dest = (mem_dest_ptr)cinfo->dest; dest->pub.next_output_byte = dest->buffer; dest->pub.free_in_buffer = dest->bufsize; ++dest->errcount; /* need to increase error count */ return TRUE; } /* Usually the library wants to flush output here. I will calculate output buffer size here. Note that results become incorrect, once empty_output_buffer was called. This situation is notified by errcount. */ METHODDEF(void) term_destination (j_compress_ptr cinfo) { mem_dest_ptr dest = (mem_dest_ptr)cinfo->dest; dest->datasize = dest->bufsize - dest->pub.free_in_buffer; if (dest->outsize) *dest->outsize += (int)dest->datasize; } /* Override the default destination manager initialization provided by jpeglib. Since we want to use memory-to-memory compression, we need to use our own destination manager. */ GLOBAL(void) jpeg_memory_dest (j_compress_ptr cinfo, JOCTET* buffer, int bufsize, int* outsize) { mem_dest_ptr dest; /* first call for this instance - need to setup */ if (cinfo->dest == 0) { cinfo->dest = (struct jpeg_destination_mgr *) (*cinfo->mem->alloc_small) ((j_common_ptr) cinfo, JPOOL_PERMANENT, sizeof (memory_destination_mgr)); } dest = (mem_dest_ptr) cinfo->dest; dest->bufsize = bufsize; dest->buffer = buffer; dest->outsize = outsize; /* set method callbacks */ dest->pub.init_destination = init_destination; dest->pub.empty_output_buffer = empty_output_buffer; dest->pub.term_destination = term_destination; } /* ------------------------------------------------------------- */ /* MEMORY SOURCE INTERFACE METHODS */ /* ------------------------------------------------------------- */ /* Called before data is read */ METHODDEF(void) init_source (j_decompress_ptr dinfo) { /* nothing to do here, really. I mean. I'm not lazy or something, but... we're actually through here. */ } /* Called if the decoder wants some bytes that we cannot provide... */ METHODDEF(boolean) fill_input_buffer (j_decompress_ptr dinfo) { /* we can't do anything about this. This might happen if the provided buffer is either invalid with regards to its content or just a to small bufsize has been given. */ /* fail. */ return FALSE; } /* From IJG docs: "it's not clear that being smart is worth much trouble" So I save myself some trouble by ignoring this bit. */ METHODDEF(void) skip_input_data (j_decompress_ptr dinfo, INT32 num_bytes) { /* There might be more data to skip than available in buffer. This clearly is an error, so screw this mess. */ if ((size_t)num_bytes > dinfo->src->bytes_in_buffer) { dinfo->src->next_input_byte = 0; /* no buffer byte */ dinfo->src->bytes_in_buffer = 0; /* no input left */ } else { dinfo->src->next_input_byte += num_bytes; dinfo->src->bytes_in_buffer -= num_bytes; } } /* Finished with decompression */ METHODDEF(void) term_source (j_decompress_ptr dinfo) { /* Again. Absolute laziness. Nothing to do here. Boring. */ } GLOBAL(void) jpeg_memory_src (j_decompress_ptr dinfo, unsigned char* buffer, size_t size) { struct jpeg_source_mgr* src; /* first call for this instance - need to setup */ if (dinfo->src == 0) { dinfo->src = (struct jpeg_source_mgr *) (*dinfo->mem->alloc_small) ((j_common_ptr) dinfo, JPOOL_PERMANENT, sizeof (struct jpeg_source_mgr)); } src = dinfo->src; src->next_input_byte = buffer; src->bytes_in_buffer = size; src->init_source = init_source; src->fill_input_buffer = fill_input_buffer; src->skip_input_data = skip_input_data; src->term_source = term_source; /* IJG recommend to use their function - as I don't know **** about how to do better, I follow this recommendation */ src->resync_to_restart = jpeg_resync_to_restart; } All I need to do is replace the jpeg_stdio_dest in my program with this code: int numBytes = 0; //size of jpeg after compression char * storage = new char[150000]; //storage buffer JOCTET *jpgbuff = (JOCTET*)storage; //JOCTET pointer to buffer jpeg_memory_dest(&cinfo,jpgbuff,150000,&numBytes); So I need some help to incorporate the above four lines into this function which now works but writes to a file instead of a memory: int write_jpeg_file( char *filename ) { struct jpeg_compress_struct cinfo; struct jpeg_error_mgr jerr; /* this is a pointer to one row of image data */ JSAMPROW row_pointer[1]; FILE *outfile = fopen( filename, "wb" ); if ( !outfile ) { printf("Error opening output jpeg file %s\n!", filename ); return -1; } cinfo.err = jpeg_std_error( &jerr ); jpeg_create_compress(&cinfo); jpeg_stdio_dest(&cinfo, outfile); /* Setting the parameters of the output file here */ cinfo.image_width = width; cinfo.image_height = height; cinfo.input_components = bytes_per_pixel; cinfo.in_color_space = color_space; /* default compression parameters, we shouldn't be worried about these */ jpeg_set_defaults( &cinfo ); /* Now do the compression .. */ jpeg_start_compress( &cinfo, TRUE ); /* like reading a file, this time write one row at a time */ while( cinfo.next_scanline < cinfo.image_height ) { row_pointer[0] = &raw_image[ cinfo.next_scanline * cinfo.image_width * cinfo.input_components]; jpeg_write_scanlines( &cinfo, row_pointer, 1 ); } /* similar to read file, clean up after we're done compressing */ jpeg_finish_compress( &cinfo ); jpeg_destroy_compress( &cinfo ); fclose( outfile ); /* success code is 1! */ return 1; } Anybody could help me out a bit with it? I've tried meddling with it but I am not sure how to do it. I I just replace this line: jpeg_stdio_dest(&cinfo, outfile); It's not going to work. There is more stuff that needs to be changed a bit in that function and I am being a little lost from all those pointers and memory management.

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  • Warping Images using cvWarpPerspective Results in Some Parts of the images out of the viewable area

    - by Birkan Cilingir
    Hi, I am trying to stich two images together. In order to do so I extracted sift features and find matches on the two images using this C implementation. http://web.engr.oregonstate.edu/~hess/index.html After that I found the homography matrix using the matched points. http://www.ics.forth.gr/~lourakis/homest/ But if I use this Homography Matrix in "cvWarpPerspective" function, some of the parts of the image goes out of the viewable area (negative corrdinates). To solve this I tried to calculate the bounding box first by piping the four corners of the image through Homography matrix. And move the initial image then warp it. But this caused the warping result to change. Is there any way for warping an image and keeping it in the viewable area? I would appreciate any help. Thanks in advance...

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  • Converting cv::Mat to IplImage*

    - by amr
    The documentation on this seems incredibly spotty. I've basically got an empty array of IplImage*s (IplImage** imageArray) and I'm calling a function to import an array of cv::Mats - I want to convert my cv::Mat into an IplImage* so I can copy it into the array. Currently I'm trying this: while(loop over cv::Mat array) { IplImage* xyz = &(IplImage(array[i])); cvCopy(iplimagearray[i], xyz); } Which generates a segfault. Also trying: while(loop over cv::Mat array) { IplImage* xyz; xyz = &array[i]; cvCopy(iplimagearray[i], xyz); } Which gives me a compile time error of: error: cannot convert ‘cv::Mat*’ to ‘IplImage*’ in assignment Stuck as to how I can go further and would appreciate some advice :)

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  • BGR Color Space

    - by updateraj
    I understand RGB --- value (0-255)Red,(0-255)Green,(0-255)Blue to form a color. What is exactly BGR color space ? How is it different from RGB color space ?

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  • Computing orientation of a square and displaying an object with the same orientation

    - by Robin
    Hi, I wrote an application which detects a square within an image. To give you a good understanding of how such an image containing such a square, in this case a marker, could look like: What I get, after the detection, are the coordinates of the four corners of my marker. Now I don't know how to display an object on my marker. The object should have the same rotation/angle/direction as the marker. Are there any papers on how to achieve that, any algorithms that I can use that proofed to be pretty solid/working? It doesn't need to be a working solution, it could be a simple description on how to achieve that or something similar. If you point me at a library or something, it should work under linux, windows is not needed but would be great in case I need to port the application at some point. I already looked at the ARToolkit but they you camera parameter files and more complex matrices while I only got the four corner points and a single image instead of a whole video / camera stream.

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  • what is the reason of Invalid Address specified to RtlFreeHeap

    - by carl
    the develop environment is vs2008, the language is c++, when I release the problem,at beginning it run with out problem but after several minutes it stop and show error like that : HEAP[guessModel.exe]: Invalid Address specified to RtlFreeHeap( 003E0000, 7D7C737B ). who can tell me the reason of the error. thank you very much.

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