private void Test()
{
ClassificationNetwork network = ClassificationNetwork.FromFile(this.options.NetworkFileName);
List <ClassificationResult <string> > results = new List <ClassificationResult <string> >();
using (TestImageProvider <string> dataProvider = this.options.CreateTestImageProvider(network))
{
////Context model = Context.FromRegex(@"\d{1,5}", CultureInfo.InvariantCulture);
////int n = 0;
foreach (TestImage sample in dataProvider.Generate(network.AllowedClasses))
{
Interlocked.Increment(ref this.totalImages);
////sample.Image.Save("e:\\temp\\" + sample.Label + "_" + n.ToString(CultureInfo.InvariantCulture) + ".bmp");
////n++;
////if (n < 171) continue;
this.localTimeCounter.Restart();
Tensor x = ImageExtensions.FromImage(
sample.Image,
null,
Shape.BWHC,
network.InputShape.GetAxis(Axis.X),
network.InputShape.GetAxis(Axis.Y));
IList <IList <(string Answer, float Probability)> > answers = network.Execute(x).Answers;
////(IList<(string Answer, float Probability)> answers, _) = network.ExecuteSequence(x, model);
this.localTimeCounter.Stop();
long duration = this.localTimeCounter.ElapsedMilliseconds;
foreach (IList <(string answer, float probability)> answer in answers)
{
string text = answer.FirstOrDefault().answer;
float prob = answer.FirstOrDefault().probability;
results.Add(new ClassificationResult <string>(
sample.SourceId,
text,
string.Concat(sample.Labels),
prob,
prob >= 0.38f));
this.WriteLine(
null,
"({0})\tFile: {1} ... OK ({2} ms) {3} {4:F4}",
this.totalImages,
sample.SourceId.ToFileName(false),
duration,
text,
prob);
}
/*string answer = answers.Last().FirstOrDefault()?.Answer;
* int prob = (int)(((answers.Last().FirstOrDefault()?.Probability ?? 0.0f) * 100) + 0.5f);
*
* results.Add(new ClassificationResult<string>(
* sample.SourceId,
* answer,
* string.Concat(sample.Labels),
* prob,
* prob >= 0.38f));
*
* ////this.Write(".");
* this.Write(
* null,
* "({0})\tFile: {1} ... OK ({4} ms) {2} {3:F4}",
* this.totalImages,
* sample.SourceId.ToFileName(false),
* duration,
* answer,
* prob);*/
}
}
// write report
ClassificationReport <string> testReport = new ClassificationReport <string>(results);
using (StreamWriter outputFile = File.CreateText(this.options.OutputFileName))
{
ClassificationReportWriter <string> .WriteReport(outputFile, testReport, ClassificationReportMode.All);
}
}