public void CalcInference(int idx)
{
Thread.Sleep(20000);
if (token.IsCancellationRequested)
{
return;
}
Console.WriteLine("After sleep");
string sample_name = files[idx];
NN_Inferencer inference_obj = new NN_Inferencer(model_path, sample_name);
float[] result = inference_obj.forward();
int res_class = 0;
float res_score = -10000;
double e = Math.E;
double sum_exp = 0;
for (int j = 0; j < result.Length; j++)
{
sum_exp += Math.Pow(e, result[j]);
if (result[j] > res_score)
{
res_score = result[j];
res_class = j;
}
}
double res_prob = Math.Pow(e, res_score) / sum_exp;
string res_string = sample_name + " class : " + res_class.ToString() + ", with prob : " + res_prob.ToString();
Console.WriteLine(res_string);
resultCollection.Add(res_string);
}
public void CalcInference(int idx)
{
if (token.IsCancellationRequested)
{
return;
}
string sample_name = files[idx];
NN_Inferencer inference_obj = new NN_Inferencer(model_path, sample_name);
float[] result = inference_obj.forward();
int res_class = 0;
float res_score = -10000;
double e = Math.E;
double sum_exp = 0;
for (int j = 0; j < result.Length; j++)
{
sum_exp += Math.Pow(e, result[j]);
if (result[j] > res_score)
{
res_score = result[j];
res_class = j;
}
}
float res_prob = (float)(Math.Pow(e, res_score) / sum_exp);
waitHandler.WaitOne();
{
all_results.results[res_class].Add(sample_name);
all_results.count[res_class].Count += 1;
if (!all_results.classes.Contains(res_class))
{
all_results.classes.Add(res_class);
}
string[] split_sample_name = sample_name.Split('\\');
string suffix = split_sample_name[split_sample_name.Length - 1];
images_with_classes img_obj = new images_with_classes(res_class, sample_name, res_prob, suffix);
all_results.images_with_classes.Add(img_obj);
using (UserContext db = new UserContext())
{
db.images_with_classes.Add(img_obj);
db.SaveChanges();
}
}
waitHandler.Set();
}
