public ActionResult StartLearning(LearningDTO simplepassword)
{
if (simplepassword.Password == "Flamingo007")
{
const string assetsRelativePath = @"assets";
string path = AITrainer.GetAbsolutePath(assetsRelativePath);
AITrainer.Train(Path.Combine(path, "images"));
return(new OkResult());
}
return(new UnauthorizedResult());
}
public ActionResult GetCategories()
{
const string assetsRelativePath = @"assets";
string path = AITrainer.GetAbsolutePath(assetsRelativePath);
Console.WriteLine(Directory.Exists(path));
Console.WriteLine(path);
var names = Directory.GetDirectories(Path.Combine(path, "images")).Select(dir => Path.GetFileName(dir));
dynamic obj = new ExpandoObject();
obj.categories = names;
return(new OkObjectResult(obj));
}
public bool testSimulation()
{
AI ai1 = new AI(0);
AI ai2 = new AI(0);
BotFightSim fightSim = new BotFightSim();
AI winnerAI = fightSim.getBestAI(ai1, ai2);
AITrainer aITrainer = new AITrainer();
aITrainer.train();
return(true);
}
public static PredictionDTO Recognize(string base64, string imagepath = null)
{
const string assetsRelativePath = @"assets";
var assetsPath = AITrainer.GetAbsolutePath(assetsRelativePath);
string imageForPrediction;
if (imagepath == null)
{
imageForPrediction = SaveTempImage(base64, assetsPath);
}
else
{
imageForPrediction = CopyTestImage(imagepath, assetsPath);
}
var imageClassifierModelZipFilePath = Path.Combine(assetsPath, "inputs", "model", "imageClassifier.zip");
try
{
var loadedModel = mlContext.Model.Load(imageClassifierModelZipFilePath, out var modelInputSchema);
var predictionEngine = mlContext.Model.CreatePredictionEngine <InMemoryImageData, ImagePrediction>(loadedModel);
var imagesToPredict = FileUtils.LoadInMemoryImagesFromDirectory(Path.Combine(assetsPath, "inputs", "toguess"), false);
var imageToPredict = imagesToPredict.Where(i =>
i.ImageFileName == Path.Combine(assetsPath, "inputs", "toguess", imageForPrediction) || i.ImageFileName == imageForPrediction).FirstOrDefault();
if (imageToPredict != null)
{
var prediction = predictionEngine.Predict(imageToPredict);
Console.WriteLine(prediction.PredictedLabel + "-----score---" + prediction.Score.Max());
if (prediction.Score.Max() * 100 > 69)
{
var maxindext = prediction.Score.ToList().IndexOf(prediction.Score.Max());
File.Delete(Path.Combine(assetsPath, "inputs", "toguess", imageForPrediction));
return(new PredictionDTO {
Label = prediction.PredictedLabel, Percentage = prediction.Score.Max() * 100
});
}
}
File.Delete(Path.Combine(assetsPath, "inputs", "toguess", imageForPrediction));
}
catch (Exception e)
{
}
return(null);
}
public ActionResult GuessImage(ImageDTO image)
{
if (image != null && !String.IsNullOrEmpty(image.Base64))
{
var result = AIRecognize.Recognize(image.Base64);
if (result != null)
{
const string assetsRelativePath = @"assets";
var assetsPath = AITrainer.GetAbsolutePath(assetsRelativePath);
List <AnimalDTO> res = JsonConvert.DeserializeObject <List <AnimalDTO> >(System.IO.File.ReadAllText(Path.Combine(assetsPath, "animals.json")));
return(new OkObjectResult(res.Where(r => r.Name == result.Label).FirstOrDefault()));
}
else
{
return(new NotFoundResult());
}
}
return(new BadRequestObjectResult("This request had no valid image send with it!"));
}
public ActionResult AddTrainingMaterial(List <ImageDTO> images)
{
if (images != null)
{
const string assetsRelativePath = @"assets";
string path = AITrainer.GetAbsolutePath(assetsRelativePath);
foreach (var image in images)
{
if (!Directory.Exists(Path.Combine(path, "images", image.Category)))
{
Directory.CreateDirectory(Path.Combine(path, "images", image.Category));
}
System.IO.File.WriteAllBytes(Path.Combine(path, "images", image.Category, Guid.NewGuid() + ".png"), Convert.FromBase64String(image.Base64));
}
return(new OkResult());
}
return(new BadRequestObjectResult("No Images Send"));
}
