/// <inheritdoc />
/// <exception cref="ArgumentNullException">
/// <paramref name="sources"/> is <b>null</b>.
/// </exception>
public IList <Answer> Recognize(IList <ImageSource> sources, CancellationToken cancellationToken)
{
if (sources == null)
{
throw new ArgumentNullException(nameof(sources));
}
// create input tensor
Tensor x = ImageExtensions.FromImages(
sources,
source => source.Image,
"checkbox",
this.network.InputShape.Format,
this.network.InputShape.GetAxis(Axis.X),
this.network.InputShape.GetAxis(Axis.Y));
// recognize the image
IList <IList <(string Answer, float Probability)> > results = this.network.Execute(x).Answers;
// create the answers
List <Answer> answers = new List <Answer>(sources.Count);
for (int i = 0, ii = results.Count; i < ii; i++)
{
answers.Add(CheckboxReader.CreateAnswer(sources[i], results[i]));
}
return(answers);
}
/// <inheritdoc />
/// <exception cref="ArgumentNullException">
/// <paramref name="source"/> is <b>null</b>.
/// </exception>
public Answer Recognize(ImageSource source, CancellationToken cancellationToken)
{
if (source == null)
{
throw new ArgumentNullException(nameof(source));
}
// create input tensor
Tensor x = ImageExtensions.FromImage(
source.Image,
"checkbox",
this.network.InputShape.Format,
this.network.InputShape.GetAxis(Axis.X),
this.network.InputShape.GetAxis(Axis.Y));
// recognize the image
IList <(string Answer, float Probability)> result = this.network.Execute(x).Answers[0];
// create the answer
return(CheckboxReader.CreateAnswer(source, result));
}