public void DeleteEarliestIteration(bool isClothing)
{
if (isClothing)
{
var iterations = ClothingTrainingApi.GetIterations(ClothingModelProjectID);
Iteration iterationToDelete = iterations[iterations.Count - 1];
if (iterations.Count == 10)
{
ClothingTrainingApi.DeleteIteration(ClothingModelProjectID, iterationToDelete.Id);
}
}
else
{
var iterations = ClassifierTrainingApi.GetIterations(ClassifierModelProjectID);
Iteration iterationToDelete = iterations[iterations.Count - 1];
if (iterations.Count == 10)
{
ClassifierTrainingApi.DeleteIteration(ClassifierModelProjectID, iterationToDelete.Id);
}
}
}
protected void CreateNewTag(string newTag)
{
var tags = ClassifierTrainingApi.GetTags(ClassifierModelProjectID);
bool tagExists = false;
Tag bookTag = null;
foreach (Tag tag in tags)
{
if (tag.Name.Equals(newTag))
{
tagExists = true;
bookTag = tag;
break;
}
}
if (!tagExists)
{
// Save image in tag folder
// Check number of images in folder
// If > 5, proceed with creating tag and training
bookTag = ClassifierTrainingApi.CreateTag(ClassifierModelProjectID, newTag);
}
}
public void TrainClassifierModel(string imagePath, string imageTag)
{
// Since apparently we can only have 10 iterations max
DeleteEarliestIteration(false);
var tags = ClassifierTrainingApi.GetTags(ClassifierModelProjectID);
Tag trainTag = null;
foreach (Tag tag in tags)
{
if (tag.Name.Equals(imageTag))
{
trainTag = tag;
break;
}
}
using (var stream = File.Open(imagePath, FileMode.Open))
{
ClassifierTrainingApi.CreateImagesFromData(ClassifierModelProjectID, stream, new List <string>()
{
trainTag.Id.ToString()
});
}
var iteration = ClassifierTrainingApi.TrainProject(ClassifierModelProjectID);
while (iteration.Status == "Training")
{
Thread.Sleep(1000);
iteration = ClassifierTrainingApi.GetIteration(ClassifierModelProjectID, iteration.Id);
}
iteration.IsDefault = true;
ClassifierTrainingApi.UpdateIteration(ClassifierModelProjectID, iteration.Id, iteration);
File.Delete(imagePath);
}
