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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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  • 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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  • 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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  • 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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  • 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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  • WPF WriteableBitmap

    - by Sam
    I'm using WriteableBitmap on an image of type Bgra32 to change the pixel value of certain pixels. I'm setting the value to 0x77CCCCCC. After calling WritePixels, the pixels I set to 0x77CCCCCC show up with a value of 0x77FFFFFF. Why does this happen? How do I make the pixels have the correct value?

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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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  • 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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  • 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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  • 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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  • 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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  • 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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  • imagejpeg memory exhaustion

    - by 0plus1
    I'm creating thumbnails cycling through a lot of images, when I find a large image I get: Fatal error: Allowed memory size of 33554432 bytes exhausted (tried to allocate 13056 bytes) Now I already know how to circumvent this with: ini_set('memory_limit', '-1'); What I want to know is why it exhaust the memory! Is there some debug tools that will show me exactly when memory is exhausting? And specifically that will show me if there are variables/arrays that are killing my memory? OR, are there better way to resize images other then: $thumb=imagecreatetruecolor($newwidth,$newheight); $source=imagecreatefromjpeg($imgfile); imagecopyresampled($thumb,$source,0,0,0,0,$newwidth,$newheight,$width,$height); imagejpeg($thumb,$destinationfile,85); ? Thank you very much!

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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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  • Using PHP script to fill in XML

    - by Yaaqov
    Hi - we are all familiar with "embedding" PHP scripts in HTML pages to do tasks like displaying form results, but how can that be done in a way that displays XML? For example, if I wrote: <? xml version='1.0' ?> <Responses> <?php $body = $_GET['Body']; $fromPh = $_GET['From']; echo echo "<Msg>Your number is: $fromPh, and you typed: $body.</Msg>" ?> </Response> I get a message that states "parse error, unexpected T_STRING on line 1". Any help or tutorials would be appreciated.

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  • Video match anlysis

    - by Mohammad
    Hi every body I am looking forward to find an algorithm to detect a pattern in a given video file. Actually I am going to index moments in a tennis match video at which service (first kick after a goal) is shot. PS1: sorry for broken English. PS2: I DO NOT know anything about tennis except that you need a ball to play!!

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  • MPIexec.exe Access denide

    - by shake
    I have installed microsoft compute cluster and MPI.net, now i have trouble to run program using mpiexec.exe on cluster. When i try to run it on console i get message: "Access Denied", and pop up: "mpiexec.exe is not valid win32 application". I tried google it, but found nothing. Pls help. :)

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  • deciding between subprocess, multiprocesser and thread in Python?

    - by user248237
    I'd like to parallelize my Python program so that it can make use of multiple processors on the machine that it runs on. My parallelization is very simple, in that all the parallel "threads" of the program are independent and write their output to separate files. I don't need the threads to exchange information but it is imperative that I know when the threads finish since some steps of my pipeline depend on their output. Portability is important, in that I'd like this to run on any Python version on Mac, Linux and Windows. Given these constraints, which is the most appropriate Python module for implementing this? I am tryign to decide between thread, subprocess and multiprocessing, which all seem to provide related functionality. Any thoughts on this? I'd like the simplest solution that's portable. Thanks.

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