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  • Understanding The Convolution Matrix

    - by Ryan Naddy
    I am learning about the Convolution Matrix, and I understand how they work, but I don't understand how to know before hand what the output of a Matrix will look like. For example lets say I want to add a blur to an image, I could guess 10,000+ different combinations of numbers before I get the correct one. I do know though that this formula will give me a blur effect, but I have no idea why. float[] sharpen = new float[] { 1/9f, 1/9f, 1/9f, 1/9f, 1/9f, 1/9f, 1/9f, 1/9f, 1/9f }; Can anyone either explain to me how this works or point me to some article, that explains this? I would like to know before hand what a possible output of the matrix will be without guessing. Basically I would like to know why do we put that number in the filed, and why not some other number?

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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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  • Formatting a query to enumerate through 2 different datatables

    - by boiler1974
    I have 2 datatables sendTable and recvTable They both have identical column names and numbers of columns "NODE" "DSP Name" "BUS" "IDENT" "STATION" "REF1" "REF2" "REF3" "REF4" "REF5" "REF6" "REF7" "REF8" I need to compare these 2 tables and separate out the mismatches I only need to check Columns 3-11 and Ignore col 1 and 2 I tried at first removing the 2 columns and then loop thru row by row and return matches and mismatches but the problem with this approach is that I no longer have the "NODE" and "DSP Name" associated with the row when I finalize my results So I need help with a query Here is my attempt var samerecordQuery = from r1 in sendTable.AsEnumerable() where r1.Field<int>("BUS").Equals(from r2 in recvTable.AsEnumerable() where r2.Field<int>("BUS")) this obviously doesn't work so how do I format the query to say from r1 cols[3-11] equals r2 cols [3-11] and once I have this I can use the except to pull out the mismatches

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  • Per query relevance elevation for solr?

    - by plusplus
    I want to tune the relevance of solr search results on a per user basis - based on the number of times the user has clicked through a result before. Frequently hit items FOR THAT USER should rise to the top of their search results. Is there a way to provide custom boost/elevation for particular document ids on the query? I'm thinking in the order of ~100s of particular documents to elevate. The elevation should have no effect if the rest of the query doesn't find those documents. Alternatively, if this isn't possible, what is a sane way for setting up an alternative indexing approach that would make this possible? Could I add a field per user in the index to store their scores? I'm thinking in the order of 1000 users. The major drawback of that approach is the number of times a document would need to be reindexed (i.e. each time it was used by the user).

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  • How do I guarante node order for an Xpath 'OR' query

    - by Tom Carter
    I have a snippet of XML that looks like <body> Some text.... <nodeA>....</nodeA> more text <someOtherNode> <nodeA>.......</nodeA> </someOtherNode> <nodeB>.......</nodeB> etc..... </body> I'm selecting all nodeA and NodeB nodes inside <body> using an XPATH query similar to "//nodeA|//nodeB" As I understand it, .NET supports XPATH 1.0 which does not guarantee node order. How can I guarantee selected nodes are returned in document order in my OR query : that's to say : nodeA, nodeA, nodeB

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  • MongoDB query to return only embedded document

    - by Matt
    assume that i have a BlogPost model with zero-to-many embedded Comment documents. can i query for and have MongoDB return only Comment objects matching my query spec? eg, db.blog_posts.find({"comment.submitter": "some_name"}) returns only a list of comments. edit: an example: import pymongo connection = pymongo.Connection() db = connection['dvds'] db['dvds'].insert({'title': "The Hitchhikers Guide to the Galaxy", 'episodes': [{'title': "Episode 1", 'desc': "..."}, {'title': "Episode 2", 'desc': "..."}, {'title': "Episode 3", 'desc': "..."}, {'title': "Episode 4", 'desc': "..."}, {'title': "Episode 5", 'desc': "..."}, {'title': "Episode 6", 'desc': "..."}]}) episode = db['dvds'].find_one({'episodes.title': "Episode 1"}, fields=['episodes']) in this example, episode is: {u'_id': ObjectId('...'), u'episodes': [{u'desc': u'...', u'title': u'Episode 1'}, {u'desc': u'...', u'title': u'Episode 2'}, {u'desc': u'...', u'title': u'Episode 3'}, {u'desc': u'...', u'title': u'Episode 4'}, {u'desc': u'...', u'title': u'Episode 5'}, {u'desc': u'...', u'title': u'Episode 6'}]} but i just want: {u'desc': u'...', u'title': u'Episode 1'}

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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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  • What's the fastest way to strip and replace a document of high unicode characters using Python?

    - by Rhubarb
    I am looking to replace from a large document all high unicode characters, such as accented Es, left and right quotes, etc., with "normal" counterparts in the low range, such as a regular 'E', and straight quotes. I need to perform this on a very large document rather often. I see an example of this in what I think might be perl here: http://www.designmeme.com/mtplugins/lowdown.txt Is there a fast way of doing this in Python without using s.replace(...).replace(...).replace(...)...? I've tried this on just a few characters to replace and the document stripping became really slow.

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  • Whats wrong with my SQL query?

    - by William
    I'm trying to set up a query that shows the first post of each thread and is ordered by the date of the last post in each thread. I got the first part down with this query: SELECT * FROM ( SELECT Min( ID ) AS MinID FROM test_posts GROUP BY Thread )tmin JOIN test_posts ON test_posts.ID = tmin.MinID Now I need to figure out how to call the last post of each thread into a table, than use that table to order the first tables results. So far I got this, but it doesn't work. SELECT * FROM ( SELECT Min( ID ) AS MinID FROM test_posts GROUP BY Thread )tmin JOIN test_posts ON test_posts.ID = tmin.MinID ORDER BY (SELECT MAX( ID ) AS MaxID, Thread, MAX( Date ) FROM test_posts GROUP BY Thread )tmax tmax.Date

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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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  • How to scale JPEG image down so that text is clear as possible?

    - by Juha Syrjälä
    I have some JPEG images that I need scale down to about 80% of original size. Original image dimension are about 700px × 1000px. Images contain some computer generated text and possibly some graphics (similar to what you would find in corporate word documents). How to scale image so that the text is as legible as possible? Currently we are scaling the imaeg down using bicubic interpolation, but that makes the text blurry and foggy.

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  • "A generic error occurred in GDI+" error while showing uploaded images

    - by Prasad
    i am using the following code to show the image that has been saved in my database from my asp.net mvc(C#) application:. public ActionResult GetSiteHeaderLogo() { SiteHeader _siteHeader = new SiteHeader(); Image imgImage = null; long userId = Utility.GetUserIdFromSession(); if (userId > 0) { _siteHeader = this.siteBLL.GetSiteHeaderLogo(userId); if (_siteHeader.Logo != null && _siteHeader.Logo.Length > 0) { byte[] _imageBytes = _siteHeader.Logo; if (_imageBytes != null) { using (System.IO.MemoryStream imageStream = new System.IO.MemoryStream(_imageBytes)) { imgImage = Image.FromStream(imageStream); } } string sFileExtension = _siteHeader.FileName.Substring(_siteHeader.FileName.IndexOf('.') + 1, _siteHeader.FileName.Length - (_siteHeader.FileName.IndexOf('.') + 1)); Response.ContentType = Utility.GetContentTypeByExtension(sFileExtension.ToLower()); Response.Cache.SetCacheability(HttpCacheability.NoCache); Response.BufferOutput = false; if (imgImage != null) { ImageFormat _imageFormat = Utility.GetImageFormat(sFileExtension.ToLower()); imgImage.Save(Response.OutputStream, _imageFormat); imgImage.Dispose(); } } } return new EmptyResult(); } It works fine when i upload original image. But when i upload any downloaded images, it throws the following error: System.Runtime.InteropServices.ExternalException: A generic error occurred in GDI+. System.Runtime.InteropServices.ExternalException: A generic error occurred in GDI+. at System.Drawing.Image.Save(Stream stream, ImageCodecInfo encoder, EncoderParameters encoderParams) at System.Drawing.Image.Save(Stream stream, ImageFormat format) For. Ex: When i upload the original image, it shows as logo in my site and i downloaded that logo from the site and when i re-upload the same downloaded image, it throws the above error. It seems very weird to me and not able to find why its happening. Any ideas on this?

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  • lucene get matched terms in query

    - by iamrohitbanga
    what is the best way to find out which terms in a query matched against a given document returned as a hit in lucene? I have tried a weird method involving hit highlighting package in lucene contrib and also a method that searches for every word in the query against the top most document ("docId: xy AND description: each_word_in_query"). Do not get satisfactory results? hit highlighting does not report some of the words that matched for a document other than the first one. i am not sure if the second approach is the best alternative.

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  • Can anyone recommend a decent tool for optimising images other than photoshop

    - by toomanyairmiles
    Can anyone recommend a decent tool for optimising images other than adobe photoshop, the gimp etc? I'm looking to optimise images for the web preferably online and free. Basically I have a client who can't install additional software on their work PC but needs to optimise photographs and other images for their website and is presently uploading 1 or 2 Mb files. On a personal level I'm interested to see what other people are using...

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  • JJIL Android Java Problem

    - by Danny_E
    Hey Guys, Long time reader never posted until now. Im having some trouble with Android, im implementing a library called JJIL its an open source imaging library. My problem is this i need to run some analysis on an image and to do so i need to have it in jjil.core.image format and once those processes are complete i need to convert the changed image from jjil.core.image to java.awt.image. I cant seem to find a method of doing this does anyone have any ideas or have any experience with this? I would be grateful of any help. Danny

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  • How to read and save data from text file with variable number of columns in a Matrix in Matlab

    - by khan
    I have a text file with integer values. each row contains information about specific object. But unfortunately each row has different number of column. because of which when i try to use file_content = load('txtfile.txt'); it gives me error message that previous number of columns does not match. i also tried to use fgetl, fscanf, etc function but was unsuccessful. Can anybody give me a piece of code, or help me how to read a txt file and save in matrix in matlab. Three sample rows are given below. 1 1 1 1 1 95 17 54 111 92 17 54 111 92 17 54 111 92 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 58 109 96 15 58 109 96 15 58 109 96 15 58 109 96 15 58 109 96 15 58 109 96 15 58 109 96 15 58 109 96 15 58 109 96 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 54 109 92 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 58 109 96 15 58 109 96 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 58 109 96 15 56 109 94 15 56 109 94 15 58 109 96 15 58 109 96 15 56 109 94 15 58 109 96 15 58 109 96 15 58 109 96 15 58 109 96 17 58 111 96 15 58 109 96 15 58 109 96 15 58 109 96 15 58 109 96 15 58 109 96 15 58 109 96 15 58 109 96 15 58 109 96 15 58 109 96 15 58 109 96 15 58 109 96 15 56 109 94 15 58 109 96 15 58 109 96 15 58 109 96 15 58 109 96 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 1 1 1 2 96 185 13 56 107 94 13 56 107 94 13 56 107 94 13 56 107 94 13 56 107 94 13 56 107 94 13 56 107 94 13 56 107 94 13 56 107 94 13 56 107 94 15 56 109 94 13 56 107 94 13 56 107 94 13 56 107 94 13 56 107 94 13 56 107 94 13 56 107 94 13 56 107 94 13 56 107 94 13 56 107 94 13 56 107 94 13 56 107 94 13 56 107 94 13 56 107 94 13 54 107 92 13 56 107 94 13 56 107 94 13 56 107 94 13 56 107 94 13 56 107 94 13 56 107 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 54 109 92 15 54 109 92 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 1 1 1 3 186 245 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 56 109 94 15 58 109 96 15 58 109 96 15 58 109 96 15 58 109 96 13 58 107 96 13 56 107 94 13 56 107 94 13 58 107 96 13 58 107 96 13 58 107 96 13 58 107 96 13 58 107 96 13 56 107 94 13 58 107 96 13 58 107 96 13 58 107 96 13 58 107 96 13 58 107 96 13 58 107 96 13 58 107 96 13 58 107 96 13 58 107 96 13 58 107 96 13 58 107 96 13 60 107 98 13 58 107 96 13 58 107 96 15 58 109 96 13 58 107 96 As you can see the rows doesn't have equal number of columns. So how can i read and save it in a Matrix. Any help in this regards will be highly appreciated. Thanks

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