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  • Running Awk command on a cluster

    - by alex
    How do you execute a Unix shell command (awk script, a pipe etc) on a cluster in parallel (step 1) and collect the results back to a central node (step 2) Hadoop seems to be a huge overkill with its 600k LOC and its performance is terrible (takes minutes just to initialize the job) i don't need shared memory, or - something like MPI/openMP as i dont need to synchronize or share anything, don't need a distributed VM or anything as complex Google's SawZall seems to work only with Google proprietary MapReduce API some distributed shell packages i found failed to compile, but there must be a simple way to run a data-centric batch job on a cluster, something as close as possible to native OS, may be using unix RPC calls i liked rsync simplicity but it seem to update remote notes sequentially, and you cant use it for executing scripts as afar as i know switching to Plan 9 or some other network oriented OS looks like another overkill i'm looking for a simple, distributed way to run awk scripts or similar - as close as possible to data with a minimal initialization overhead, in a nothing-shared, nothing-synchronized fashion Thanks Alex

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  • problem with Chrome form handling: input onfocus="this.select()"

    - by binaryorganic
    I'm using the following HTML code to autoselect some text in a form field when a user clicks on the field: input onfocus="this.select()" type="text" value="Search" This works fine in Firefox and Internet Explorer (the purpose being to use the default text to describe the field to the user, but highlight it so that on click they can just start typing), but I'm having trouble getting it to work in Chrome. When I click the form field in Chrome the text is highlighted for just a split second and then the cursor jumps to the end of the default text and the highlighting goes away. Any ideas on how to get this working in Chrome as well?

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  • How to isolate a single color in an image

    - by Janusz
    I'm using the python OpenCV bindings and at the moment I try to isolate a colorrange. That means I want to filter out everything that is not reddish. I tried to take only the red color channel but this includes the white spaces in the Image too. What is a good way to do that?

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  • How can I select the pixels from an image in opencv?

    - by ajith
    This is refined version of my previous question. Actually I want to do following operation... summation for all k|(i,j)?wk [(Ii-µk)*(Ij-µk)], where wk is a 3X3 window, µk is the mean of wk, Ii & Ij are the intensities of the image at i and j. I dont know how to select Ii & Ij separately from an image which is 2 dimensional[Iij]...or does the equation mean anything else?

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  • Regex for finding an unterminated string

    - by Austin Hyde
    I need to search for lines in a CSV file that end in an unterminated, double-quoted string. For example: 1,2,a,b,"dog","rabbit would match whereas 1,2,a,b,"dog","rabbit","cat bird" 1,2,a,b,"dog",rabbit would not. I have very limited experience with regular expressions, and the only thing I could think of is something like "[^"]*$ However, that matches the last quote to the end of the line. How would this be done?

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  • Django Template tag, generating template block tag

    - by Issy
    Hi Guys, Currently a bit stuck, wondering if anyone can assist. I am using django-adminfiles. Which is a near little application. I want to use it to insert images into posts/articles/pages for a site i am building. How django-adminfiles works is it inserts a placeholder i.e <<< ImageFile and this gets rendered using a django template. It also has the feature of inserting custom options i.e (Insert Medium Image) , i figured i would used this to automatically resize images and include it in the post (similar to how WP does it). Django-adminfiles makes use of sorl.thumbnail app to generate thumbnails. So i have tried testing generating thumbnails: The current template that is used to render the inserted image is: {% spaceless %} <img src="{{ upload.upload.url }}" width="{{ upload.width }}" height="{{ upload.height }}" class="{{ options.class }}" class="{{ options.size }}" alt="{% if options.alt %}{{ options.alt }}{% else %}{{ upload.title }}{% endif %}" /> {% endspaceless %} I tried modifying this to: {% load thumbnail %} {% spaceless %} <img src="{% thumbnail upload.upload.url 200x50 %}" width="{{ upload.width }}" height="{{ upload.height }}" class="{{ options.class }}" class="{{ options.size }}" alt="{% if options.alt %}{{ options.alt }}{% else %}{{ upload.title }}{% endif %}" /> {% endspaceless %} I get the error: Exception Value: Caught an exception while rendering: Source file: '/media/uploads/DSC_0014.jpg' does not exist. I figured the thumbnail needs the absolute path so tried putting that in the template, and that works. i.e this works: {% thumbnail '/Users/me/media/uploads/DSC_0014.jpg' 200x50 %} So basically i need to generate the absolute path to the file give the relative path (to web root). You could do this by passing the MEDIA_ROOT setting to the template, but the reason i want to do a template tag is to programmatically set the image size.

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  • C# - Data Clustering approach

    - by Brett
    Hi all, I am writing a program in C# in which I have a set of 200 points displayed on an image. However, the points tend to cluster in various regions, and I am looking to find a way to "cluster." In other words, maybe draw a circle/ellipse around the clustered points. Has anyone seen any way to do this? I have heard about K-means clustering, but I am not sure how to implement it in C#. Any favorite implementations out there? Cheers, Brett

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  • Spectral Reconstruction

    - by Hani
    I have a small system which consist of: Led Clusters, camera(RGB or grayscale) and an object to be detected. I am emitting a light from the LED clusters (ex: yellow). After emitting light on the object, I am capturing an image for the object from the camera. I want to get the spectral image of the object from the captured image. Please if any one knows the algorithm or a code for this purpose(grayscale or RGB camera), tell me. Thanks.....

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  • how to implement video and audio merger program ?

    - by egebilmuh
    Hi guys I want to make a program which takes video and audio and merges them. Video Type or audio type is not important for me. I just want to make so- called program. How can i make this ? does any library exist for this ? (I know there are many program about this topic but i want to learn how to implement such a program.) Help me please about this topic.

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  • RabbitMQ serializing messages from queue with multiple consumers

    - by Refefer
    Hi there, I'm having a problem where I have a queue set up in shared mode and multiple consumers bound to it. The issue is that it appears that rabbitmq is serializing the messages, that is, only one consumer at a time is able to run. I need this to be parallel, however, I can't seem to figure out how. Each consumer is running in its own process. There are plenty of messages in the queue. I'm using py-amqplib to interface with RabbitMQ. Any thoughts?

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  • Gradient Mapping in .NET

    - by Otaku
    Is there a way in .NET to perform the same technique Photoshop uses for Gradient Mapping (Image - Adjustments - Gradient Map [Gradient Editor])? Any ideas, links, code, etc. would be welcome.

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  • tfidf, am I understanding it right?

    - by alskndalsnd
    Hey everyone, I am interested in doing some document clustering, and right now I am considering using TF-IDF for this. If I am not wrong, TFIDF is particularly used for evaluating the relevance of a document given a query. If I do not have a particular query, how can I apply tfidf to clustering?

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  • rotating bitmaps. In code.

    - by Marco van de Voort
    Is there a faster way to rotate a large bitmap by 90 or 270 degrees than simply doing a nested loop with inverted coordinates? The bitmaps are 8bpp and typically 2048*2400*8bpp Currently I do this by simply copying with argument inversion, roughly (pseudo code: for x = 0 to 2048-1 for y = 0 to 2048-1 dest[x][y]=src[y][x]; (In reality I do it with pointers, for a bit more speed, but that is roughly the same magnitude) GDI is quite slow with large images, and GPU load/store times for textures (GF7 cards) are in the same magnitude as the current CPU time. Any tips, pointers? An in-place algorithm would even be better, but speed is more important than being in-place. Target is Delphi, but it is more an algorithmic question. SSE(2) vectorization no problem, it is a big enough problem for me to code it in assembler Duplicates How do you rotate a two dimensional array?. Follow up to Nils' answer Image 2048x2700 - 2700x2048 Compiler Turbo Explorer 2006 with optimization on. Windows: Power scheme set to "Always on". (important!!!!) Machine: Core2 6600 (2.4 GHz) time with old routine: 32ms (step 1) time with stepsize 8 : 12ms time with stepsize 16 : 10ms time with stepsize 32+ : 9ms Meanwhile I also tested on a Athlon 64 X2 (5200+ iirc), and the speed up there was slightly more than a factor four (80 to 19 ms). The speed up is well worth it, thanks. Maybe that during the summer months I'll torture myself with a SSE(2) version. However I already thought about how to tackle that, and I think I'll run out of SSE2 registers for an straight implementation: for n:=0 to 7 do begin load r0, <source+n*rowsize> shift byte from r0 into r1 shift byte from r0 into r2 .. shift byte from r0 into r8 end; store r1, <target> store r2, <target+1*<rowsize> .. store r8, <target+7*<rowsize> So 8x8 needs 9 registers, but 32-bits SSE only has 8. Anyway that is something for the summer months :-) Note that the pointer thing is something that I do out of instinct, but it could be there is actually something to it, if your dimensions are not hardcoded, the compiler can't turn the mul into a shift. While muls an sich are cheap nowadays, they also generate more register pressure afaik. The code (validated by subtracting result from the "naieve" rotate1 implementation): const stepsize = 32; procedure rotatealign(Source: tbw8image; Target:tbw8image); var stepsx,stepsy,restx,resty : Integer; RowPitchSource, RowPitchTarget : Integer; pSource, pTarget,ps1,ps2 : pchar; x,y,i,j: integer; rpstep : integer; begin RowPitchSource := source.RowPitch; // bytes to jump to next line. Can be negative (includes alignment) RowPitchTarget := target.RowPitch; rpstep:=RowPitchTarget*stepsize; stepsx:=source.ImageWidth div stepsize; stepsy:=source.ImageHeight div stepsize; // check if mod 16=0 here for both dimensions, if so -> SSE2. for y := 0 to stepsy - 1 do begin psource:=source.GetImagePointer(0,y*stepsize); // gets pointer to pixel x,y ptarget:=Target.GetImagePointer(target.imagewidth-(y+1)*stepsize,0); for x := 0 to stepsx - 1 do begin for i := 0 to stepsize - 1 do begin ps1:=@psource[rowpitchsource*i]; // ( 0,i) ps2:=@ptarget[stepsize-1-i]; // (maxx-i,0); for j := 0 to stepsize - 1 do begin ps2[0]:=ps1[j]; inc(ps2,RowPitchTarget); end; end; inc(psource,stepsize); inc(ptarget,rpstep); end; end; // 3 more areas to do, with dimensions // - stepsy*stepsize * restx // right most column of restx width // - stepsx*stepsize * resty // bottom row with resty height // - restx*resty // bottom-right rectangle. restx:=source.ImageWidth mod stepsize; // typically zero because width is // typically 1024 or 2048 resty:=source.Imageheight mod stepsize; if restx>0 then begin // one loop less, since we know this fits in one line of "blocks" psource:=source.GetImagePointer(source.ImageWidth-restx,0); // gets pointer to pixel x,y ptarget:=Target.GetImagePointer(Target.imagewidth-stepsize,Target.imageheight-restx); for y := 0 to stepsy - 1 do begin for i := 0 to stepsize - 1 do begin ps1:=@psource[rowpitchsource*i]; // ( 0,i) ps2:=@ptarget[stepsize-1-i]; // (maxx-i,0); for j := 0 to restx - 1 do begin ps2[0]:=ps1[j]; inc(ps2,RowPitchTarget); end; end; inc(psource,stepsize*RowPitchSource); dec(ptarget,stepsize); end; end; if resty>0 then begin // one loop less, since we know this fits in one line of "blocks" psource:=source.GetImagePointer(0,source.ImageHeight-resty); // gets pointer to pixel x,y ptarget:=Target.GetImagePointer(0,0); for x := 0 to stepsx - 1 do begin for i := 0 to resty- 1 do begin ps1:=@psource[rowpitchsource*i]; // ( 0,i) ps2:=@ptarget[resty-1-i]; // (maxx-i,0); for j := 0 to stepsize - 1 do begin ps2[0]:=ps1[j]; inc(ps2,RowPitchTarget); end; end; inc(psource,stepsize); inc(ptarget,rpstep); end; end; if (resty>0) and (restx>0) then begin // another loop less, since only one block psource:=source.GetImagePointer(source.ImageWidth-restx,source.ImageHeight-resty); // gets pointer to pixel x,y ptarget:=Target.GetImagePointer(0,target.ImageHeight-restx); for i := 0 to resty- 1 do begin ps1:=@psource[rowpitchsource*i]; // ( 0,i) ps2:=@ptarget[resty-1-i]; // (maxx-i,0); for j := 0 to restx - 1 do begin ps2[0]:=ps1[j]; inc(ps2,RowPitchTarget); end; end; end; end;

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  • C# .NET : Is using the .NET Image Conversion enough?

    - by contactmatt
    I've seen a lot of people try to code their own image conversion techniques. It often seems to be very complicated, and ends up using GDI+ funciton calls, and manipulating bits of the image. This has got me wondering if I am missing something in the simplicity of .NET's image conversion call when saving an image. Here's the code I have Bitmap tempBmp = new Bitmap("c:\temp\img.jpg"); Bitmap bmp = new Bitmap(tempBmp, 800, 600); bmp.Save(c:\temp\img.bmp, //extension depends on format ImageFormat.Bmp) //These are all the ImageFormats I allow conversion to within the program. Ignore the syntax for a second ;) ImageFormat.Gif) //or ImageFormat.Jpeg) //or ImageFormat.Png) //or ImageFormat.Tiff) //or ImageFormat.Wmf) //or ImageFormat.Bmp)//or ); This is all I'm doing in my image conversion. Just setting the location of where the image should be saved, and passing it an ImageFormat type. I've tested it the best I can, but I'm wondering if I am missing anything in this simple format conversion, or if this is suffice?

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  • Using MinHash to find similiarities between 2 images

    - by Sung Meister
    I am using MinHash algorithm to find similar images between images. I have run across this post, How can I recognize slightly modified images? which pointed me to MinHash algorithm. Being a bit mathematically challenged, I was using a C# implementation from this blog post, Set Similarity and Min Hash. But while trying to use the implementation, I have run into 2 problems. What value should I set universe value to? When passing image byte array to HashSet, it only contains distinct byte values; thus comparing values from 1 ~ 256. What is this universe in MinHash? And what can I do to improve the C# MinHash implementation? Since HashSet<byte> contains values upto 256, similarity value always come out to 1. Here is the source that uses the C# MinHash implementation from Set Similarity and Min Hash: class Program { static void Main(string[] args) { var imageSet1 = GetImageByte(@".\Images\01.JPG"); var imageSet2 = GetImageByte(@".\Images\02.TIF"); //var app = new MinHash(256); var app = new MinHash(Math.Min(imageSet1.Count, imageSet2.Count)); double imageSimilarity = app.Similarity(imageSet1, imageSet2); Console.WriteLine("similarity = {0}", imageSimilarity); } private static HashSet<byte> GetImageByte(string imagePath) { using (var fs = new FileStream(imagePath, FileMode.Open, FileAccess.Read)) using (var br = new BinaryReader(fs)) { //List<int> bytes = br.ReadBytes((int)fs.Length).Cast<int>().ToList(); var bytes = new List<byte>(br.ReadBytes((int) fs.Length).ToArray()); return new HashSet<byte>(bytes); } } }

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  • How to sort my paws?

    - by Ivo Flipse
    In my previous question I got an excellent answer that helped me detect where a paw hit a pressure plate, but now I'm struggling to link these results to their corresponding paws: I manually annotated the paws (RF=right front, RH= right hind, LF=left front, LH=left hind). As you can see there's clearly a pattern repeating pattern and it comes back in aknist every measurement. Here's a link to a presentation of 6 trials that were manually annotated. My initial thought was to use heuristics to do the sorting, like: There's a ~60-40% ratio in weight bearing between the front and hind paws; The hind paws are generally smaller in surface; The paws are (often) spatially divided in left and right. However, I’m a bit skeptical about my heuristics, as they would fail on me as soon as I encounter a variation I hadn’t thought off. They also won’t be able to cope with measurements from lame dogs, whom probably have rules of their own. Furthermore, the annotation suggested by Joe sometimes get's messed up and doesn't take into account what the paw actually looks like. Based on the answers I received on my question about peak detection within the paw, I’m hoping there are more advanced solutions to sort the paws. Especially because the pressure distribution and the progression thereof are different for each separate paw, almost like a fingerprint. I hope there's a method that can use this to cluster my paws, rather than just sorting them in order of occurrence. So I'm looking for a better way to sort the results with their corresponding paw. For anyone up to the challenge, I have pickled a dictionary with all the sliced arrays that contain the pressure data of each paw (bundled by measurement) and the slice that describes their location (location on the plate and in time). To clarfiy: walk_sliced_data is a dictionary that contains ['ser_3', 'ser_2', 'sel_1', 'sel_2', 'ser_1', 'sel_3'], which are the names of the measurements. Each measurement contains another dictionary, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] (example from 'sel_1') which represent the impacts that were extracted. Also note that 'false' impacts, such as where the paw is partially measured (in space or time) can be ignored. They are only useful because they can help recognizing a pattern, but won't be analyzed. And for anyone interested, I’m keeping a blog with all the updates regarding the project!

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  • libpng cannot read an image properly

    - by jonathanasdf
    Here is my function... I don't know why it's not working. The resulting image looks nothing like what the .png looks like. But there's no errors either. bool Bullet::read_png(std::string file_name, int pos) { png_structp png_ptr; png_infop info_ptr; FILE *fp; if ((fp = fopen(file_name.c_str(), "rb")) == NULL) { return false; } png_ptr = png_create_read_struct(PNG_LIBPNG_VER_STRING, NULL, NULL, NULL); if (png_ptr == NULL) { fclose(fp); return false; } info_ptr = png_create_info_struct(png_ptr); if (info_ptr == NULL) { fclose(fp); png_destroy_read_struct(&png_ptr, NULL, NULL); return false; } if (setjmp(png_jmpbuf(png_ptr))) { png_destroy_read_struct(&png_ptr, &info_ptr, NULL); fclose(fp); return false; } png_init_io(png_ptr, fp); png_read_png(png_ptr, info_ptr, PNG_TRANSFORM_STRIP_16 | PNG_TRANSFORM_SWAP_ALPHA | PNG_TRANSFORM_EXPAND, NULL); png_uint_32 width = png_get_image_width(png_ptr, info_ptr); png_uint_32 height = png_get_image_height(png_ptr, info_ptr); imageData[pos].width = width; imageData[pos].height = height; png_bytepp row_pointers; row_pointers = png_get_rows(png_ptr, info_ptr); imageData[pos].data = new unsigned int[width*height]; for (unsigned int i=0; i < height; ++i) { memcpy(&imageData[pos].data[i*width], &row_pointers[i], width*sizeof(unsigned int)); } png_destroy_read_struct(&png_ptr, &info_ptr, NULL); fclose(fp); for (unsigned int i=0; i < height; ++i) { for (unsigned int j=0; j < width; ++j) { unsigned int val = imageData[pos].data[i*width+j]; if (val != 0) { unsigned int a = ((val >> 24)); unsigned int r = (((val - (a << 24)) >> 16)); unsigned int g = (((val - (a << 24) - (r << 16)) >> 8)); unsigned int b = (((val - (a << 24) - (r << 16) - (g << 8)))); // for debugging std::string s(AS3_StringValue(AS3_Int(i*width+j))); s += " "; s += AS3_StringValue(AS3_Int(val)); s += " "; s += AS3_StringValue(AS3_Int(a)); s += " "; s += AS3_StringValue(AS3_Int(r)); s += " "; s += AS3_StringValue(AS3_Int(g)); s += " "; s += AS3_StringValue(AS3_Int(b)); AS3_Trace(AS3_String(s.c_str())); } } } return true; } ImageData is just a simple struct to keep x, y, width, and height, and imageData is an array of that struct. struct ImageData { int x; int y; int width; int height; unsigned int* data; }; Here is a side by side screenshot of the input and output graphics (something I made in a minute for testing), and this was after setting alpha to 255 in order to make it show up (because the alpha I was getting back was 1). Left side is original, right side is what happened after reading it through this function. Scaled up 400% for visibility. Here is a log of the traces: 0 16855328 1 1 49 32 1 16855424 1 1 49 128 2 16855456 1 1 49 160 3 16855488 1 1 49 192 4 16855520 1 1 49 224 5 16855552 1 1 50 0 6 16855584 1 1 50 32 7 16855616 1 1 50 64 8 16855424 1 1 49 128 9 16855456 1 1 49 160 10 16855488 1 1 49 192 11 16855520 1 1 49 224 12 16855552 1 1 50 0 13 16855584 1 1 50 32 14 16855616 1 1 50 64 15 16855648 1 1 50 96 16 16855456 1 1 49 160 17 16855488 1 1 49 192 18 16855520 1 1 49 224 19 16855552 1 1 50 0 20 16855584 1 1 50 32 21 16855616 1 1 50 64 22 16855648 1 1 50 96 23 16855680 1 1 50 128 24 16855488 1 1 49 192 25 16855520 1 1 49 224 26 16855552 1 1 50 0 27 16855584 1 1 50 32 28 16855616 1 1 50 64 29 16855648 1 1 50 96 30 16855680 1 1 50 128 31 16855712 1 1 50 160 32 16855520 1 1 49 224 33 16855552 1 1 50 0 34 16855584 1 1 50 32 35 16855616 1 1 50 64 36 16855648 1 1 50 96 37 16855680 1 1 50 128 38 16855712 1 1 50 160 39 16855744 1 1 50 192 40 16855552 1 1 50 0 41 16855584 1 1 50 32 42 16855616 1 1 50 64 43 16855648 1 1 50 96 44 16855680 1 1 50 128 45 16855712 1 1 50 160 46 16855744 1 1 50 192 47 16855776 1 1 50 224 48 16855584 1 1 50 32 49 16855616 1 1 50 64 50 16855648 1 1 50 96 51 16855680 1 1 50 128 52 16855712 1 1 50 160 53 16855744 1 1 50 192 54 16855776 1 1 50 224 55 16855808 1 1 51 0 56 16855616 1 1 50 64 57 16855648 1 1 50 96 58 16855680 1 1 50 128 59 16855712 1 1 50 160 60 16855744 1 1 50 192 61 16855776 1 1 50 224 62 16855808 1 1 51 0 63 16855840 1 1 51 32 64 16855648 1 1 50 96 65 16855680 1 1 50 128 66 16855712 1 1 50 160 67 16855744 1 1 50 192 68 16855776 1 1 50 224 69 16855808 1 1 51 0 70 16855840 1 1 51 32 71 16855872 1 1 51 64 72 16855680 1 1 50 128 73 16855712 1 1 50 160 74 16855744 1 1 50 192 75 16855776 1 1 50 224 76 16855808 1 1 51 0 77 16855840 1 1 51 32 78 16855872 1 1 51 64 79 16855904 1 1 51 96 80 16855712 1 1 50 160 81 16855744 1 1 50 192 82 16855776 1 1 50 224 83 16855808 1 1 51 0 84 16855840 1 1 51 32 85 16855872 1 1 51 64 86 16855904 1 1 51 96 87 16855936 1 1 51 128 88 16855744 1 1 50 192 89 16855776 1 1 50 224 90 16855808 1 1 51 0 91 16855840 1 1 51 32 92 16855872 1 1 51 64 93 16855904 1 1 51 96 94 16855936 1 1 51 128 95 16855968 1 1 51 160 96 16855776 1 1 50 224 97 16855808 1 1 51 0 98 16855840 1 1 51 32 99 16855872 1 1 51 64 100 16855904 1 1 51 96 101 16855936 1 1 51 128 102 16855968 1 1 51 160 103 16856000 1 1 51 192 104 16855808 1 1 51 0 105 16855840 1 1 51 32 106 16855872 1 1 51 64 107 16855904 1 1 51 96 108 16855936 1 1 51 128 109 16855968 1 1 51 160 110 16856000 1 1 51 192 111 16856032 1 1 51 224 112 16855840 1 1 51 32 113 16855872 1 1 51 64 114 16855904 1 1 51 96 115 16855936 1 1 51 128 116 16855968 1 1 51 160 117 16856000 1 1 51 192 118 16856032 1 1 51 224 119 16856064 1 1 52 0 120 16855872 1 1 51 64 121 16855904 1 1 51 96 122 16855936 1 1 51 128 123 16855968 1 1 51 160 124 16856000 1 1 51 192 125 16856032 1 1 51 224 126 16856064 1 1 52 0 127 16856096 1 1 52 32 128 16855904 1 1 51 96 129 16855936 1 1 51 128 130 16855968 1 1 51 160 131 16856000 1 1 51 192 132 16856032 1 1 51 224 133 16856064 1 1 52 0 134 16856096 1 1 52 32 135 16856128 1 1 52 64 136 16855936 1 1 51 128 137 16855968 1 1 51 160 138 16856000 1 1 51 192 139 16856032 1 1 51 224 140 16856064 1 1 52 0 141 16856096 1 1 52 32 142 16856128 1 1 52 64 143 16856160 1 1 52 96 144 16855968 1 1 51 160 145 16856000 1 1 51 192 146 16856032 1 1 51 224 147 16856064 1 1 52 0 148 16856096 1 1 52 32 149 16856128 1 1 52 64 150 16856160 1 1 52 96 151 16856192 1 1 52 128 152 16856000 1 1 51 192 153 16856032 1 1 51 224 154 16856064 1 1 52 0 155 16856096 1 1 52 32 156 16856128 1 1 52 64 157 16856160 1 1 52 96 158 16856192 1 1 52 128 159 16856224 1 1 52 160 160 16856032 1 1 51 224 161 16856064 1 1 52 0 162 16856096 1 1 52 32 163 16856128 1 1 52 64 164 16856160 1 1 52 96 165 16856192 1 1 52 128 166 16856224 1 1 52 160 167 16856256 1 1 52 192 168 16856064 1 1 52 0 169 16856096 1 1 52 32 170 16856128 1 1 52 64 171 16856160 1 1 52 96 172 16856192 1 1 52 128 173 16856224 1 1 52 160 174 16856256 1 1 52 192 175 16856288 1 1 52 224 176 16856096 1 1 52 32 177 16856128 1 1 52 64 178 16856160 1 1 52 96 179 16856192 1 1 52 128 180 16856224 1 1 52 160 181 16856256 1 1 52 192 182 16856288 1 1 52 224 183 16856320 1 1 53 0 184 16856128 1 1 52 64 185 16856160 1 1 52 96 186 16856192 1 1 52 128 187 16856224 1 1 52 160 188 16856256 1 1 52 192 189 16856288 1 1 52 224 190 16856320 1 1 53 0 192 16856160 1 1 52 96 193 16856192 1 1 52 128 194 16856224 1 1 52 160 195 16856256 1 1 52 192 196 16856288 1 1 52 224 197 16856320 1 1 53 0 200 16856192 1 1 52 128 201 16856224 1 1 52 160 202 16856256 1 1 52 192 203 16856288 1 1 52 224 204 16856320 1 1 53 0 208 16856224 1 1 52 160 209 16856256 1 1 52 192 210 16856288 1 1 52 224 211 16856320 1 1 53 0 216 16856256 1 1 52 192 217 16856288 1 1 52 224 218 16856320 1 1 53 0 224 16856288 1 1 52 224 225 16856320 1 1 53 0 232 16856320 1 1 53 0 Was stuck on this for a couple of days.

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  • HMM for perspective estimation in document image, can't understand the algorithm

    - by maximus
    Hello! Here is a paper, it is about estimating the perspective of binary image containing text and some noise or non text objects. PDF document The algorithm uses the Hidden Markov Model: actually two conditions T - text B - backgrouond (i.e. noise) It is hard to understand the algorithm itself. The question is that I've read about Hidden Markov Models and I know that it uses probabilities that must be known. But in this algorithm I can't understand, if they use HMM, how do they get those probabilities (probability of changing the state from S1 to another state for example S2)? I didn't find anything about training there also in that paper. So, if somebody understands it, please tell me. Also is it possible to use HMM without knowing the state change probabilities?

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  • mean image filter

    - by turmoil
    Starting to learn image filtering and stumped on a question found on website: Applying a 3×3 mean filter twice does not produce quite the same result as applying a 5×5 mean filter once. However, a 5×5 convolution kernel can be constructed which is equivalent. What does this kernel look like? Would appreciate help so that I can understand the subject better. Thanks.

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  • Preventing the opening of a form on a add button click

    - by Jonathan
    Hey guys, Did you guys know how to prevent the open of a Form when I click on a add button? Maybe using beforeShowForm? function(formid) { if(jQuery('#gridap').getGridParam('selrow')) { idgridap=jQuery('#gridap').getGridParam('selrow'); jQuery('#FK_numerocontrato_ap',formid).val(idgridap).attr('readonly','readonly'); } else { // I want to prevent the openning of the add form here and maybe show an alert using the "alertcap" } } CHECAROW; $grid->setNavEvent('add','beforeShowForm',$checarowid); BTW, there's a way to call the alertmod of jqgrid and add a custom message to it? tks!

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  • Retrieving saved checkboxes' name and values from database

    - by sermed
    I have a form with checkboxes, each one has a value. When the registered user select any checkbox the value is incremented (the summation) and then then registred user save his selection of checkbox if he satisfied with the result of summation into database all this work fine ...i want to enable the registred user to view his selection history by retriving and displaying the checkboxes he selected in a page with thier values ... How I can do that? I'm just able to save the selected checkboxes as choice 1, choice 2, for example .. I want to view the selected checkboxes that is saved in database as the appear in the page when the user first select them: for example if the registred user selects these 3 options LEAD DEEP KEEL (1825) FULLY BATTENED MAINSAIL (558) TEAK SIDE DECKS (2889) They will be saved as for example (choice1, choice2, choice3). But if he want to view selected checkboxes the appear exactly as first he selects them: LEAD DEEP KEEL (1825) FULLY BATTENED MAINSAIL (558) TEAK SIDE DECKS (2889) This is my user table: $query="CREATE TABLE User( user_id varchar(20), password varchar(40), user_type varchar(20), firstname varchar(30), lastname varchar(30), street varchar(50), city varchar(50), county varchar(50), post_code varchar(10), country varchar(50), gender varchar(6), dob varchar(15), tel_no varchar(50), vals varchar(50), email varchar(50))"; and the code to inser the options selected to database <?php include("databaseconnection.php"); $str = ''; foreach($_POST as $key => $val) if (strpos($key,'choice') !== false) $str .= $key.','; $query = "INSERT INTO User (vals) VALUES('$str')"; $result=mysql_query($query,$conn); if ($result) { (mysql_error(); } else { echo " done"; } ?> And this is my form: function checkTotal() { document.listForm.total.value = ''; var sum = 0; for (i=0;i <form name="listForm" method="post" action="insert_options.php" > <TABLE cellPadding=3 width=600 border=0> <TBODY> <TR> <TH align=left width="87%" bgColor=#b0b3b4><SPAN class=whiteText>Item</SPAN></TH> <TH align=right width="13%" bgColor=#b0b3b4><SPAN class=whiteText>Select</SPAN></TH></TR> <TR> <TD bgcolor="#9da8af"colSpan=2><SPAN class=normalText><B>General</B></SPAN></TD></TR> <TR> <TD bgcolor="#c4c8ca"><SPAN class=normalText >TEAK SIDE DECKS (2889)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="2889" type="checkbox" onchange="checkTotal()" /></TD></TR> <TR> <TD bgColor=#c4c8ca><SPAN class=normalText>LEAD DEEP KEEL (1825)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="1825" type="checkbox" onchange="checkTotal()"></TD></TR> <TR> <TD bgColor=#c4c8ca><SPAN class=normalText>FULLY BATTENED MAINSAIL (558)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="558" type="checkbox" onchange="checkTotal()"></TD></TR> <TR> <TD bgColor=#c4c8ca><SPAN class=normalText>HIGH TECH SAILS FOR CONVENTIONAL RIG (1979)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="1979" type="checkbox" onchange="checkTotal()"></TD></TR> <TR> <TD bgColor=#c4c8ca><SPAN class=normalText>IN MAST REEFING WITH HIGH TECH SAILS (2539)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="2539" type="checkbox" onchange="checkTotal()"></TD></TR> <TR> <TD bgColor=#c4c8ca><SPAN class=normalText>SPlNNAKER GEAR (POLE LINES DECK FITTINGS) (820)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="820" type="checkbox" onchange="checkTotal()"></TD></TR> <TR> <TD bgColor=#c4c8ca><SPAN class=normalText>SPINNAKER POLE VERTICAL STOWAGE SYSTEM (214)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="214" type="checkbox" onchange="checkTotal()"></TD></TR> <TR> <TD bgColor=#c4c8ca><SPAN class=normalText>GAS ROD KICKER (208)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="208" type="checkbox" onchange="checkTotal()"></TD></TR> <TR> <TD bgColor=#c4c8ca><SPAN class=normalText>SIDE RAIL OPENINGS (BOTH SIDES) (392)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="392" type="checkbox" onchange="checkTotal()"></TD></TR> <TR> <TD bgColor=#c4c8ca><SPAN class=normalText>SPRING CLEATS MIDSHIPS -ALUMIMIUM (148)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="148" type="checkbox" onchange="checkTotal()"></TD></TR> <TR> <TD bgColor=#c4c8ca><SPAN class=normalText>ELECTRIC ANCHOR WINDLASS (1189)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="1189" type="checkbox" onchange="checkTotal()"> </TD></TR> <TR> <TD bgColor=#c4c8ca><SPAN class=normalText>ANCHOR CHAIN GALVANISED (50m) (202)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="202" type="checkbox" onchange="checkTotal()"> </TD></TR> <TR> <TD bgColor=#c4c8ca><SPAN class=normalText>ANCHOR CHAIN GALVANISED (50m) (1141)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="1141" type="checkbox" onchange="checkTotal()"></TD></TR> <TR> <TD bgcolor="#9da8af"colSpan=2><SPAN class=normalText><B>NAVIGATION & ELECTRONICS</B></SPAN></TD></TR> <TR> <TD bgcolor="#c4c8ca"><SPAN class=normalText >WIND VANE (STAINLESS STEEL)(41)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="41" type="checkbox" onchange="checkTotal()" /></TD></TR> <TR> <TD bgColor=#c4c8ca><SPAN class=normalText>RAYMARINE ST6O LOG & DEPTH (SEPARATE UNITS)(226)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="226" type="checkbox" onchange="checkTotal()"></TD></TR> <TR> <TD bgcolor="#9da8af"colSpan=2><SPAN class=normalText><B>ENGINES & ELECTRICS</B></SPAN></TD></TR> <TR> <TD bgColor=#c4c8ca><SPAN class=normalText>SHORE SUPPLY (220V) WITH 3 OUTLETS (EXCLUDJNG SHORE CABLE) (327)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="327" type="checkbox" onchange="checkTotal()"></TD></TR> <TR> <TD bgColor=#c4c8ca><SPAN class=normalText>3rd BATTERY(14OA/H)(196)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="196" type="checkbox" onchange="checkTotal()"></TD></TR> <TD bgColor=#c4c8ca><SPAN class=normalText>24 AMP BATTERY CHARGER (475)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="475" type="checkbox" onchange="checkTotal()"></TD></TR> <TD bgColor=#c4c8ca><SPAN class=normalText>2 BLADED FOLDING PROPELLER (UPGRADE)(299)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="299" type="checkbox" onchange="checkTotal()"></TD></TR> <TR> <TD bgcolor="#9da8af"colSpan=2><SPAN class=normalText><B>BELOW DECKS/DOMESTIC</B></SPAN></TD></TR> <TD bgColor=#c4c8ca><SPAN class=normalText>WARM WATER (FROM ENGINE & 220V)(749)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="749" type="checkbox" onchange="checkTotal()"></TD></TR> <TD bgColor=#c4c8ca><SPAN class=normalText>SHOWER IN AFT HEADS WITH PUMPOUT(446)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="446" type="checkbox" onchange="checkTotal()"></TD></TR> <TD bgColor=#c4c8ca><SPAN class=normalText>DECK SUCTION DISPOSAL FOR HOLDINGTANK(166)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="166" type="checkbox" onchange="checkTotal()"></TD></TR> <TD bgColor=#c4c8ca><SPAN class=normalText>REFRIGERATED COOLBOX (12V)(666)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="666" type="checkbox" onchange="checkTotal()"></TD></TR> <TD bgColor=#c4c8ca><SPAN class=normalText>LFS SAFETY PACKAGE (COCKPIT HARNESS POINTS STAINLESS STEEL JACKSTAYS)(208)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="208" type="checkbox" onchange="checkTotal()"></TD></TR> <TD bgColor=#c4c8ca><SPAN class=normalText>UPHOLSTERY UPGRADE IN SALOON (SUEDETYPE)(701)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="701" type="checkbox" onchange="checkTotal()"></TD></TR> <TR> <TD bgcolor="#9da8af"colSpan=2><SPAN class=normalText><B>NAVIGATION ELECTRONICS & ELECTRICS</B></SPAN></TD></TR> <TD bgColor=#c4c8ca><SPAN class=normalText>VHF RADIO AERIAL CABLED TO NAVIGATION AREA(178)</SPAN></TD> <TD align=right bgColor=#c4c8ca><input name="choice" value="178" type="checkbox" onchange="checkTotal()"></TD></TR> </table>

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