public void FilterElement() { IPipe pipeNull = new PipeNull(); //Creamos una tag de Image Dictionary <string, Attribute> attributeList = new Dictionary <string, Attribute>(); Attribute attribute = new Attribute("Name", "image1"); Attribute attribute2 = new Attribute("PositionY", "100"); Attribute attribute3 = new Attribute("PositionX", "100"); Attribute attribute4 = new Attribute("Length", "100"); Attribute attribute5 = new Attribute("Width", "100"); Attribute attribute6 = new Attribute("ImagePath", "Oceano.jpg"); attributeList.Add(attribute.Key, attribute); attributeList.Add(attribute2.Key, attribute2); attributeList.Add(attribute3.Key, attribute3); attributeList.Add(attribute4.Key, attribute4); attributeList.Add(attribute5.Key, attribute5); attributeList.Add(attribute6.Key, attribute6); Tag tag = new Tag("Image", attributeList); //Creamos un filterImage IFilterConditional filterImage = new FilterImage(); IPipe pipe0 = new PipeConditional(filterImage, pipeNull, pipeNull); //Testeamos que el resultado de la pipe sea el correcto. Assert.True(pipe0.Send(tag) is VisitorImage); }
static void Main(string[] args) { PictureProvider p = new PictureProvider(); IPicture pic = p.GetPicture("matrix.png"); FilterGreyscale filterGreyscale = new FilterGreyscale(); FilterNegative filterNegative = new FilterNegative(); FilterPostTwitter filterPostTwitter = new FilterPostTwitter(); PipeNull pipeNull = new PipeNull(); PipeConditional pipeSerialConditional = new PipeConditional(filterPostTwitter, filterNegative, pipeNull); pic = pipeSerialConditional.Send(pic); Persist(pic, "imagenFiltrada.jpg"); }
public void FilterScreen() { IPipe pipeNull = new PipeNull(); //Creamos una tag de Screen falsa Dictionary <string, Attribute> attributeList = new Dictionary <string, Attribute>(); Attribute attribute = new Attribute("Name", "screen1"); attributeList.Add(attribute.Key, attribute); Tag tag = new Tag("Screen", attributeList); //Creamos un filterScreen IFilterConditional filterScreen = new FilterScreen(); IPipe pipe0 = new PipeConditional(filterScreen, pipeNull, pipeNull); //Nos fijamos que devuelva el Visitor correcto Assert.True(pipe0.Send(tag) is VisitorScreen); }
public void FilterLevelTest() { IPipe pipeNull = new PipeNull(); //Creamos una tag falsa de Level Dictionary <string, Attribute> attributeList = new Dictionary <string, Attribute>(); Attribute attribute = new Attribute("Name", "level1"); attributeList.Add(attribute.Key, attribute); Tag tag = new Tag("Level", attributeList); //Creamos un filter Level IFilterConditional filterLevel = new FilterLevel(); IPipe pipe0 = new PipeConditional(filterLevel, pipeNull, pipeNull); //Nos fijamos que el resultado de la pipe sea un VisitorLevel Assert.True(pipe0.Send(tag) is VisitorLevel); }
static void Main(string[] args) { PictureProvider pictureProvider = new PictureProvider(); IPicture picOrig = pictureProvider.GetPicture("jac.jpg"); FilterNegative negative = new FilterNegative(); //https://twitter.com/POOUCU?lang=en&lang=en FilterTwitterPublish twitterPublish = new FilterTwitterPublish(); FilterCognitive faceRecog = new FilterCognitive(); IConvolutionMatrix matrix = new BlurConvolutionMatrix(); FilterConvolution blurConvo = new FilterConvolution(matrix); PipeNull pipeEnd = new PipeNull(); //PipeSerial pipe32 = new PipeSerial(negative,pipeEnd); PipeSerial pipe22 = new PipeSerial(negative, pipeEnd); PipeSerial pipe21 = new PipeSerial(twitterPublish, pipeEnd); PipeConditional pipe1 = new PipeConditional(faceRecog, pipe21, pipe22); pictureProvider.SavePicture(pipe1.Send(picOrig), "jacFiltrado.jpg"); }
static void Main(string[] args) { PictureProvider imgProvider = new PictureProvider(); IPicture pictureProv = imgProvider.GetPicture("Vikings.jpg"); IConvolution matrix = new BlurConvolutionMatriz(); FilterConvolution blurFilter = new FilterConvolution(matrix); FilterNegative negativeFilter = new FilterNegative(); FilterTwitter twitterFilter = new FilterTwitter(); FilterCognitive faceRecognition = new FilterCognitive(); PipeNull pipeEnd = new PipeNull(); PipeSerial pipeTwitter = new PipeSerial(twitterFilter, pipeEnd); PipeSerial pipeBlur = new PipeSerial(blurFilter, pipeEnd); PipeSerial pipeNegative = new PipeSerial(negativeFilter, pipeEnd); PipeConditional pipeFace = new PipeConditional(faceRecognition, pipeTwitter, pipeNegative); imgProvider.SavePicture(pipeFace.Send(pictureProv), "Vikings.jpg"); }