private static void testBlending(string filePath1, string filePath2, string outputPath)
{
ImageBlender blender = new SimpleGrayscaleImageBlender();
List <ImageDescription> images = new List <ImageDescription>();
images.Add(ImageFileHandler.loadFromPath(filePath1));
images.Add(ImageFileHandler.loadFromPath(filePath2));
ImageDescription result = blender.blendImages(images);
ImageFileHandler.saveToPath(result, outputPath, ".png");
}
private static void testAlgorithmOnFile(string algorithmToTest, string filename)
{
Console.WriteLine("Started loading " + algorithmToTest);
EdgeDetectionAlgorithm edgeDetectionAlgorithm = EdgeDetectionAlgorithmUtil.loadAlgorithmFromCompressedFile(algorithmToTest);
Console.WriteLine("Loaded algorithm. Testing.");
ImageDescription inputImage = ImageFileHandler.loadFromPath(filename);
ImageDescription outputImage = edgeDetectionAlgorithm.test(inputImage);
ImageFileHandler.saveToPath(outputImage, "test", ".png");
Console.WriteLine("Saved");
}
private static void testFiltering(string filePath, string outputPath)
{
ImageDescription inputImage = ImageFileHandler.loadFromPath(filePath);
//ImageFilter filter = new CannyAppenderFilter();
//ImageFilter filter = new KirschAppenderFilter();
ImageFilter filter = new SobelAppenderFilter();
ImageDescription outputImage = filter.filter(inputImage);
GaussFilter gaussFilter = new GaussFilter(5, 1.4f, new HashSet <ColorChannelEnum> {
ColorChannelEnum.Red, ColorChannelEnum.Green, ColorChannelEnum.Blue
});
outputImage = gaussFilter.filter(outputImage);
ImageFileHandler.saveToPath(outputImage, outputPath, ".png");
//ImageDescription newOutputImage = new ImageDescription();
//newOutputImage.sizeX = outputImage.sizeX;
//newOutputImage.sizeY = outputImage.sizeY;
//newOutputImage.grayscale = true;
//newOutputImage.setColorChannel(ColorChannelEnum.Gray, outputImage.getColorChannel(ColorChannelEnum.Canny));
//ImageFileHandler.saveToPath(newOutputImage, "test2", ".png");
}
public void testNestedAlgorithm(ContextualMemoryNestedAlgorithm nestedAlgorithm)
{
DateTime testingStart = DateTime.Now;
List <String> fileList = benchmark.getTestFilesPathList();
int index = 1;
string outputDirectory = null;
foreach (string testFileName in fileList)
{
DateTime start = DateTime.Now;
outputDirectory = Path.GetDirectoryName(benchmark.getTestFileOutputPathWithoutExtension(testFileName));
if (!Directory.Exists(outputDirectory))
{
Directory.CreateDirectory(outputDirectory);
}
Console.WriteLine(index + "/" + fileList.Count + " Testing file: " + Path.GetFileName(testFileName));
ImageDescription inputImage = ImageFileHandler.loadFromPath(testFileName);
List <ContextualMemoryNestedAlgorithmLayer> layers = nestedAlgorithm.getLayers();
List <ImageDescription> computedImages = nestedAlgorithm.computeImageForLayers(inputImage, layers.Count);
for (int i = 0; i < layers.Count; i++)
{
if (layers[i].outputResults)
{
ImageFileHandler.saveToPath(computedImages[i], benchmark.getTestFileOutputPathWithoutExtension(testFileName) + "_layer" + i, outputFileExtension);
}
}
ImageDescription outputImage = nestedAlgorithm.getImageBlender().blendImages(computedImages);
ImageFileHandler.saveToPath(outputImage, benchmark.getTestFileOutputPathWithoutExtension(testFileName), outputFileExtension);
double timeElapsed = (DateTime.Now - start).TotalSeconds;
double timeElapsedSoFar = (DateTime.Now - testingStart).TotalSeconds;
double estimatedTime = (timeElapsedSoFar / index) * (fileList.Count - index);
Console.WriteLine(timeElapsed.ToString("0.00") + "s Time elapsed: "
+ timeElapsedSoFar.ToString("0.00") + "s ETA: " + estimatedTime.ToString("0.00") + "s");
index++;
}
double totalTimeElapsed = (DateTime.Now - testingStart).TotalSeconds;
Console.WriteLine("Testing took " + totalTimeElapsed.ToString("0.00") + " sec.");
if (testOnTrainingFiles)
{
Console.WriteLine("Testing on training files");
testingStart = DateTime.Now;
index = 0;
// we have the outputDirectory from test, else, relative to the exe
outputDirectory = Path.Combine(outputDirectory, trainingFilesTestOutput);
if (!Directory.Exists(outputDirectory))
{
Directory.CreateDirectory(outputDirectory);
}
fileList = new List <string>(benchmark.getTrainingFilesPathList());
foreach (string trainingFileName in fileList)
{
DateTime start = DateTime.Now;
string outputPath = Path.Combine(outputDirectory, Path.GetFileNameWithoutExtension(trainingFileName));
Console.WriteLine((index + 1) + "/" + fileList.Count + " Testing file: " + Path.GetFileName(trainingFileName));
ImageDescription inputImage = ImageFileHandler.loadFromPath(trainingFileName);
List <ContextualMemoryNestedAlgorithmLayer> layers = nestedAlgorithm.getLayers();
List <ImageDescription> computedImages = nestedAlgorithm.computeImageForLayers(inputImage, layers.Count);
for (int i = 0; i < layers.Count; i++)
{
if (layers[i].outputResults)
{
ImageFileHandler.saveToPath(computedImages[i], outputPath + "_layer" + i, outputFileExtension);
}
}
ImageDescription outputImage = nestedAlgorithm.getImageBlender().blendImages(computedImages);
ImageFileHandler.saveToPath(outputImage, outputPath, outputFileExtension);
index++;
double timeElapsed = (DateTime.Now - start).TotalSeconds;
Console.WriteLine(timeElapsed.ToString("0.00") + " seconds");
}
totalTimeElapsed = (DateTime.Now - testingStart).TotalSeconds;
Console.WriteLine("Testing on training files took " + totalTimeElapsed.ToString("0.00") + " sec.");
}
}
public void test(EdgeDetectionAlgorithm algorithm)
{
DateTime testingStart = DateTime.Now;
List <String> fileList = benchmark.getTestFilesPathList();
int index = 1;
string outputDirectory = null;
foreach (string testFileName in fileList)
{
DateTime start = DateTime.Now;
outputDirectory = Path.GetDirectoryName(benchmark.getTestFileOutputPathWithoutExtension(testFileName));
if (!Directory.Exists(outputDirectory))
{
Directory.CreateDirectory(outputDirectory);
}
Console.WriteLine(index + "/" + fileList.Count + " Testing file: " + Path.GetFileName(testFileName));
ImageDescription inputImage = ImageFileHandler.loadFromPath(testFileName);
ImageDescription outputImage = algorithm.test(inputImage);
ImageFileHandler.saveToPath(outputImage, benchmark.getTestFileOutputPathWithoutExtension(testFileName), outputFileExtension);
double timeElapsed = (DateTime.Now - start).TotalSeconds;
double timeElapsedSoFar = (DateTime.Now - testingStart).TotalSeconds;
double estimatedTime = (timeElapsedSoFar / index) * (fileList.Count - index);
Console.WriteLine(timeElapsed.ToString("0.00") + "s Time elapsed: "
+ timeElapsedSoFar.ToString("0.00") + "s ETA: " + estimatedTime.ToString("0.00") + "s");
index++;
}
double totalTimeElapsed = (DateTime.Now - testingStart).TotalSeconds;
Console.WriteLine("Testing took " + totalTimeElapsed.ToString("0.00") + " sec.");
if (testOnTrainingFiles)
{
Console.WriteLine("Testing on training files");
testingStart = DateTime.Now;
index = 0;
// we have the outputDirectory from test, else, relative to the exe
outputDirectory = Path.Combine(outputDirectory, trainingFilesTestOutput);
if (!Directory.Exists(outputDirectory))
{
Directory.CreateDirectory(outputDirectory);
}
fileList = new List <string>(benchmark.getTrainingFilesPathList());
foreach (string trainingFileName in fileList)
{
DateTime start = DateTime.Now;
string outputPath = Path.Combine(outputDirectory, Path.GetFileNameWithoutExtension(trainingFileName));
Console.WriteLine(index + "/" + fileList.Count + " Testing file: " + Path.GetFileName(trainingFileName));
ImageDescription inputImage = ImageFileHandler.loadFromPath(trainingFileName);
ImageDescription outputImage = algorithm.test(inputImage);
ImageFileHandler.saveToPath(outputImage, outputPath, outputFileExtension);
index++;
double timeElapsed = (DateTime.Now - start).TotalSeconds;
Console.WriteLine(timeElapsed.ToString("0.00") + " seconds");
}
totalTimeElapsed = (DateTime.Now - testingStart).TotalSeconds;
Console.WriteLine("Testing on training files took " + totalTimeElapsed.ToString("0.00") + " sec.");
}
}