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");
}
