public async Task PredictAll()
{
_applicationStatusManager.ChangeCurrentAppStatus(Enums.Status.Working, "");
try
{
Status = "starting ml model...";
//load config
var confDir = Path.Join(Environment.GetFolderPath(Environment.SpecialFolder.LocalApplicationData), "lacmus");
var configPath = Path.Join(confDir, "appConfig.json");
_appConfig = await AppConfig.Create(configPath);
var config = _appConfig.MlModelConfig;
using (var model = new MLModel(config))
{
await model.Init();
var count = 0;
var objectCount = 0;
Status = "processing...";
foreach (var photoViewModel in _photos.Items)
{
try
{
photoViewModel.Annotation.Objects = await model.Predict(photoViewModel);
photoViewModel.BoundBoxes = photoViewModel.GetBoundingBoxes();
if (photoViewModel.BoundBoxes.Any())
{
photoViewModel.Photo.Attribute = Attribute.WithObject;
photoViewModel.IsHasObject = true;
}
objectCount += photoViewModel.BoundBoxes.Count();
count++;
PredictProgress = (double)count / _photos.Items.Count() * 100;
PredictTextProgress = $"{Convert.ToInt32(PredictProgress)} %";
_applicationStatusManager.ChangeCurrentAppStatus(Enums.Status.Working, $"Working | {(int)((double) count / _photos.Items.Count() * 100)} %, [{count} of {_photos.Items.Count()}]");
Console.WriteLine($"\tProgress: {(double) count / _photos.Items.Count() * 100} %");
}
catch (Exception e)
{
Log.Error(e, $"Unable to process file {photoViewModel.Path}. Slipped.");
}
}
Status = "stopping ml model...";
await model.Stop();
PredictTextProgress = $"predict {_photos.Count} photos.";
Log.Information($"Successfully predict {_photos.Count} photos. Find {objectCount} objects.");
}
}
catch (Exception e)
{
Status = "error.";
Log.Error(e, "Unable to get prediction.");
}
_applicationStatusManager.ChangeCurrentAppStatus(Enums.Status.Ready, "");
}
