public async Task <ActionResult <Prediction> > GetClassify([FromBody] BasicRequest request)
{
if (string.IsNullOrWhiteSpace(request.Url))
{
return(BadRequest("url cannot be null or empty"));
}
var classification = await _formClassifierService.Classify(HttpUtility.HtmlDecode(request.Url));
if (classification != null && classification.Predictions != null && classification.Predictions.Any())
{
var first = classification.Predictions.OrderByDescending(o => o.Probability).First();
return(first);
}
return(null);
}
public ClassifiedImage PutImage(NewImage newImage)
{
ClassifiedImage classifiedImage = db.FindImage(newImage);
if (classifiedImage != null)
{
return(classifiedImage);
}
classifiedImage = classifier.Classify(newImage);
db.PutImage(classifiedImage);
return(classifiedImage);
}
public async Task <string> Post()
{
var stream = Request.Body;
var tmpFile = Path.GetTempFileName() + ".jpg";
using (var fs = new FileStream(tmpFile, FileMode.Create))
await stream.CopyToAsync(fs);
var tag = _imageProcessor.Classify(tmpFile);
System.IO.File.Delete(tmpFile);
return(tag);
}
public static double CalculateCorrectPercentage <T>(IEnumerable <ImageObservation <T> > validationSet,
IImageClassifier <ImageObservation <T>, IEnumerable <T> > classifier)
{
if (validationSet == null)
{
throw new ArgumentNullException(nameof(validationSet));
}
if (classifier == null)
{
throw new ArgumentNullException(nameof(classifier));
}
return(validationSet
.Select(obs => (classifier.Classify(obs.Pixels) == obs.Label) ? 1d : 0d)
.Average());
}
public async Task Classify(object image)
{
var probs = await _frameClassifier.Classify(image);
Probabilities = probs.ToList();
}