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  • How does Content-Aware fill work?

    - by CiscoIPPhone
    The upcoming version of Photoshop a feature called Content-Aware fill. This feature will fill a selection of an image based on the surrounding image - to the point it can generate bushes and clouds while being seamless with the surrounding image. See http://www.youtube.com/watch?v=NH0aEp1oDOI for a preview of the Photoshop feature I'm talking about. My question is: How does this feature work algorithmically?

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  • How to display a thumb image or first frame from a MP4 file using Delphi 7

    - by Edelcom
    Hi, I need to display a thumbnail preview of a folder full of MP4 files. So, is there a Delphi 7 component which extract a thumbnail image from MP4 files (if MP4 does contain a thumbnail image), or is there a Delphi 7 component which can extract the 1st frame from a MP4 file ? I need to extract it so I can save it to a .jpg or .png file (to be used again later on). Any ideas, Thanks.

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  • what is problem in the following matlab codes

    - by raju
    img=imread('img27.jpg'); %function rectangle=rect_test(img) % edge detection [gx,gy]=gradient(img); gx=abs(gx); gy=abs(gy); g=gx+gy; g=abs(g); % make it 300x300 img=zeros(300); s=size(g); img(1:s(1),1:s(2))=g; figure; imagesc((img)); colormap(gray); title('Edge detection') % take the dct of the image IM=abs(dct2(img)); figure; imagesc((IM)); colormap(gray); title('DCT') % normalize m=max(max(IM)); IM2=IM./m*100; % get rid of the peak size_IM2=size(IM2); IM2(1:round(.05*size_IM2(1)),1:round(.05*size_IM2(2))) = 0; % threshold L=length( find(IM2>20)) ; if( L > 60 ) ret = 1; else ret = 0; end

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  • How to generate irregular ball shapes?

    - by tomato
    What kind of algorithms would generate random "goo balls" like those in World of Goo. (btw, if you haven't played it yet, highly recommended). I'm using Proccesing, but any generic algorithm would do. I guess it boils down to how to "randomly" make balls that are kind of round, but not perfectly round, and still looking realistic. Thanks in advance!

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  • MPI4Py Scatter sendbuf Argument Type?

    - by Noel
    I'm having trouble with the Scatter function in the MPI4Py Python module. My assumption is that I should be able to pass it a single list for the sendbuffer. However, I'm getting a consistent error message when I do that, or indeed add the other two arguments, recvbuf and root: File "code/step3.py", line 682, in subbox_grid i = mpi_communicator.Scatter(station_range, station_data) File "Comm.pyx", line 427, in mpi4py.MPI.Comm.Scatter (src/ mpi4py_MPI.c:44993) File "message.pxi", line 321, in mpi4py.MPI._p_msg_cco.for_scatter (src/mpi4py_MPI.c:14497) File "message.pxi", line 232, in mpi4py.MPI._p_msg_cco.for_cco_send (src/mpi4py_MPI.c:13630) File "message.pxi", line 36, in mpi4py.MPI.message_simple (src/ mpi4py_MPI.c:11904) ValueError: message: expecting 2 or 3 items Here is the relevant code snipped, starting a few lines above 682 mentioned above. for station in stations #snip--do some stuff with station station_data = [] station_range = range(1,len(station)) mpi_communicator = MPI.COMM_WORLD i = mpi_communicator.Scatter(station_range, nsm) #snip--do some stuff with station[i] nsm = combine(avg, wt, dnew, nf1, nl1, wti[i], wtm, station[i].id) station_data = mpi_communicator.Gather(station_range, nsm) I've tried a number of combinations initializing station_range, but I must not be understanding the Scatter argument types properly. Does a Python/MPI guru have a clarification this?

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  • Removing the transperancy from image while keeping the actual image

    - by KPL
    Hello people, I have three images,and , they are not square or rectangular in shape. They are just like face of anyone. So,basically, my images are in the size 196x196 or anything like that, but complete square or rectangle with the face in the middle and transperant background in the rest of the portion. Now, I want to remove the transperant background too and just keep the faces. Don't know if this is possible and mind you, this isn't a programming question.

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  • Django Photologue - use photo with original compression

    - by 123
    hi, I´m uploading photos with Django Photologue. Is it possible to leave the jpgs as the are? Even if I tell photosize to use Highest Quality compression the files end up having half as many kb as the originals. I must admit that the visable loss of quality is small but as i am a photographer i would like the images to apear exactly as i edited them (photoshop). I don´t need any of photosize´s cropping and effects tools. Can it be turned off completely? thanks for your answers.

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  • Scaling up an image

    - by codefail
    How do I fulfill the condition "returns the entire scaled up image" If I am coding this correctly, scaleColor handles individual colors, getRed handles the red, etc. I am multiplying this by the input, numTimes, which will create a new image that is scaled up it. This scaled up (increase size) is to be returned. This is what I have. Image Image::scaleUp(int numTimes) const { for (int x = 0; x < width; x++) { for (int y = 0; y < height; y++) { pixelData[x][y].scaleColor(pixelData[x][y].scaleRed(pixelData[x][y].getRed()*numTimes)); pixelData[x][y].scaleColor(pixelData[x][y].scaleGreen(pixelData[x][y].getGreen()*numTimes)); pixelData[x][y].scaleColor(pixelData[x][y].scaleBlue(pixelData[x][y].getBlue()*numTimes)); } } //return Image(); }

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  • looping through variable post vars and adding them to the database

    - by Neil Hickman
    I have been given the task of devising a custom forms manager that has a mysql backend. The problem I have now encountered after setting up all the front end, is how to process a form that is dynamic. For E.G Form one could contain 6 fields all with different name attributes in the input tag. Form two could contain 20 fields all with different name attributes in the input tag. How would i process the forms without using up oodles of resource.

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  • Scaling larger Image problem.

    - by krishna
    Hi, I m developing flex application, in which I want to Draw Image from User local hard-drive to the canvas of size 640x360. User can choose Image of bigger resolution & is scaled to Canvas size. But if user selected images of larger resolution like 3000x2000, the scaling take lot time & freezes the application until scale done. Is there any method to scale image faster or kind of threading can be done? I am using matrix to scale Image as below: var mat:Matrix = new Matrix(); var scalex:Number = canvasScreen.width/content.width; var scaley:Number = canvasScreen.height/content.height; mat.scale(scalex,scaley); canvasScreen.graphics.clear(); canvasScreen.graphics.beginBitmapFill(content.bitmapData,mat);

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  • simple process rollback question

    - by OckhamsRazor
    hi folks! while revising for an exam, i came across this simple question asking about rollbacks in processes. i understand how rollbacks occur, but i need some validation on my answer. The question: my confusion results from the fact that there is interprocess communication between the processes. does that change anything in terms of where to rollback? my answer would be R13, R23, R32 and R43. any help is greatly appreciated! thanks!

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  • What is the wrong of this converted code?

    - by Gum Slashy
    I'm developing shape identification project using javacv and I have found some opencv code to identify U shapes in particular image and I have try to convert it in to javacv but it doesn't provide same out put. Can you please help me to convert this opencv code into javacv? This is Opencv code import cv2 import numpy as np img = cv2.imread('sofud.jpg') gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) ret,thresh = cv2.threshold(gray,127,255,1) contours,hierarchy = cv2.findContours(thresh,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE) for cnt in contours: x,y,w,h = cv2.boundingRect(cnt) if 10 < w/float(h) or w/float(h) < 0.1: cv2.rectangle(img,(x,y),(x+w,y+h),(0,0,255),2) cv2.imshow('res',img) cv2.waitKey(0) cv2.destroyAllWindows() This is the expected output This is the code that I have converted import com.googlecode.javacpp.Loader; import com.googlecode.javacv.CanvasFrame; import static com.googlecode.javacpp.Loader.*; import static com.googlecode.javacv.cpp.opencv_core.*; import static com.googlecode.javacv.cpp.opencv_imgproc.*; import static com.googlecode.javacv.cpp.opencv_highgui.*; import java.io.File; import javax.swing.JFileChooser; public class TestBeam { public static void main(String[] args) { CvMemStorage storage=CvMemStorage.create(); CvSeq squares = new CvContour(); squares = cvCreateSeq(0, sizeof(CvContour.class), sizeof(CvSeq.class), storage); JFileChooser f=new JFileChooser(); int result=f.showOpenDialog(f);//show dialog box to choose files File myfile=null; String path=""; if(result==0){ myfile=f.getSelectedFile();//selected file taken to myfile path=myfile.getAbsolutePath();//get the path of the file } IplImage src = cvLoadImage(path);//hear path is actual path to image IplImage grayImage = IplImage.create(src.width(), src.height(), IPL_DEPTH_8U, 1); cvCvtColor(src, grayImage, CV_RGB2GRAY); cvThreshold(grayImage, grayImage, 127, 255, CV_THRESH_BINARY); CvSeq cvSeq=new CvSeq(); CvMemStorage memory=CvMemStorage.create(); cvFindContours(grayImage, memory, cvSeq, Loader.sizeof(CvContour.class), CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE); System.out.println(cvSeq.total()); for (int i = 0; i < cvSeq.total(); i++) { CvRect rect=cvBoundingRect(cvSeq, i); int x=rect.x(),y=rect.y(),h=rect.height(),w=rect.width(); if (10 < (w/h) || (w/h) < 0.1){ cvRectangle(src, cvPoint(x, y), cvPoint(x+w, y+h), CvScalar.RED, 1, CV_AA, 0); //cvSeqPush(squares, rect); } } CanvasFrame cnvs=new CanvasFrame("Beam"); cnvs.setDefaultCloseOperation(javax.swing.JFrame.EXIT_ON_CLOSE); cnvs.showImage(src); //cvShowImage("Final ", src); } } This is the out put that I got please can some one help me to solve this problem ?

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  • Embarrassingly parallel workflow creates too many output files

    - by Hooked
    On a Linux cluster I run many (N > 10^6) independent computations. Each computation takes only a few minutes and the output is a handful of lines. When N was small I was able to store each result in a separate file to be parsed later. With large N however, I find that I am wasting storage space (for the file creation) and simple commands like ls require extra care due to internal limits of bash: -bash: /bin/ls: Argument list too long. Each computation is required to run through a qsub scheduling algorithm so I am unable to create a master program which simply aggregates the output data to a single file. The simple solution of appending to a single fails when two programs finish at the same time and interleave their output. I have no admin access to the cluster, so installing a system-wide database is not an option. How can I collate the output data from embarrassingly parallel computation before it gets unmanageable?

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  • What is the best way to detect white color?

    - by dnul
    I'm trying to detect white objects in a video. The first step is to filter the image so that it leaves only white-color pixels. My first approach was using HSV color space and then checking for high level of VAL channel. Here is the code: //convert image to hsv cvCvtColor( src, hsv, CV_BGR2HSV ); cvCvtPixToPlane( hsv, h_plane, s_plane, v_plane, 0 ); for(int x=0;x<srcSize.width;x++){ for(int y=0;y<srcSize.height;y++){ uchar * hue=&((uchar*) (h_plane->imageData+h_plane->widthStep*y))[x]; uchar * sat=&((uchar*) (s_plane->imageData+s_plane->widthStep*y))[x]; uchar * val=&((uchar*) (v_plane->imageData+v_plane->widthStep*y))[x]; if((*val>170)) *hue=255; else *hue=0; } } leaving the result in the hue channel. Unfortunately, this approach is very sensitive to lighting. I'm sure there is a better way. Any suggestions?

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  • CUDA small kernel 2d convolution - how to do it

    - by paulAl
    I've been experimenting with CUDA kernels for days to perform a fast 2D convolution between a 500x500 image (but I could also vary the dimensions) and a very small 2D kernel (a laplacian 2d kernel, so it's a 3x3 kernel.. too small to take a huge advantage with all the cuda threads). I created a CPU classic implementation (two for loops, as easy as you would think) and then I started creating CUDA kernels. After a few disappointing attempts to perform a faster convolution I ended up with this code: http://www.evl.uic.edu/sjames/cs525/final.html (see the Shared Memory section), it basically lets a 16x16 threads block load all the convolution data he needs in the shared memory and then performs the convolution. Nothing, the CPU is still a lot faster. I didn't try the FFT approach because the CUDA SDK states that it is efficient with large kernel sizes. Whether or not you read everything I wrote, my question is: how can I perform a fast 2D convolution between a relatively large image and a very small kernel (3x3) with CUDA?

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  • C++ converting binary(P5) image to ascii(P2) image (.pgm)

    - by tubby
    I am writing a simple program to convert grayscale binary (P5) to grayscale ascii (P2) but am having trouble reading in the binary and converting it to int. #include <iostream> #include <fstream> #include <sstream> using namespace::std; int usage(char* arg) { // exit program cout << arg << ": Error" << endl; return -1; } int main(int argc, char* argv[]) { int rows, cols, size, greylevels; string filetype; // open stream in binary mode ifstream istr(argv[1], ios::in | ios::binary); if(istr.fail()) return usage(argv[1]); // parse header istr >> filetype >> rows >> cols >> greylevels; size = rows * cols; // check data cout << "filetype: " << filetype << endl; cout << "rows: " << rows << endl; cout << "cols: " << cols << endl; cout << "greylevels: " << greylevels << endl; cout << "size: " << size << endl; // parse data values int* data = new int[size]; int fail_tracker = 0; // find which pixel failing on for(int* ptr = data; ptr < data+size; ptr++) { char t_ch; // read in binary char istr.read(&t_ch, sizeof(char)); // convert to integer int t_data = static_cast<int>(t_ch); // check if legal pixel if(t_data < 0 || t_data > greylevels) { cout << "Failed on pixel: " << fail_tracker << endl; cout << "Pixel value: " << t_data << endl; return usage(argv[1]); } // if passes add value to data array *ptr = t_data; fail_tracker++; } // close the stream istr.close(); // write a new P2 binary ascii image ofstream ostr("greyscale_ascii_version.pgm"); // write header ostr << "P2 " << rows << cols << greylevels << endl; // write data int line_ctr = 0; for(int* ptr = data; ptr < data+size; ptr++) { // print pixel value ostr << *ptr << " "; // endl every ~20 pixels for some readability if(++line_ctr % 20 == 0) ostr << endl; } ostr.close(); // clean up delete [] data; return 0; } sample image - Pulled this from an old post. Removed the comment within the image file as I am not worried about this functionality now. When compiled with g++ I get output: $> ./a.out a.pgm filetype: P5 rows: 1024 cols: 768 greylevels: 255 size: 786432 Failed on pixel: 1 Pixel value: -110 a.pgm: Error The image is a little duck and there's no way the pixel value can be -110...where am I going wrong? Thanks.

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  • What is the best algorithm to locate a point in an image file?

    - by suugaku
    Hi all, I want to create a mark sheet recognizer. Here is the description: My system uses black and white color scheme. The mark sheet paper has a small black rectangle on each corner and an additional small black rectangle, to determine orientation, near one of the previous rectangles. The paper is scanned to yield an image (in bmp format for example). The first step is to locate these five references in image as eficient as possible. My rough idea is to trace row by row and from left to right for each row. It sounds very slow I think. Is there any better way to do that? Thank you in advance. regards, Suugaku

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