private RecognizedTextPart RecognizeTextPart(OrderedBitmap page, IActorRef selfRef, DocumentToProcess document,
ICroppedArea croppedPart, FlattenedCroppedArea downscaleResult)
{
var recognitionResult = _handwrittenInputRecognizer.RecognizeFrom(downscaleResult).Result;
recognitionResult.AreaName = croppedPart.AreaUsedForCropping.AreaName;
selfRef.Tell(new DocumentPageTextAreaProcessingCompleted(document.Id, (int)page.Order,
croppedPart.AreaUsedForCropping.AreaName, recognitionResult));
return(recognitionResult as RecognizedTextPart);
}
public ProcessingResult <IRecognizedPart <string> > RecognizeFrom(FlattenedCroppedArea croppedArea)
{
var expectedData = croppedArea.AreaUsedForCropping.ExpectedData.AsFileStorageModel();
var modelBytes = _getRecognitionModelHandler.Handle(
new GetImageRecognitionModel
{
ExpectedData = expectedData
});
var model = Function.Load(modelBytes, _device);
try
{
var areaPartsPredictions = new List <OrderedRecognitionOutput>();
foreach (var flattenedBitmap in croppedArea.FlattenedBitmaps.OrderBy(fb => fb.Order))
{
if (flattenedBitmap.FlattenedBitmap == null)
{
areaPartsPredictions.Add(new OrderedRecognitionOutput(default(char), 1f, flattenedBitmap.Order));
continue;
}
Variable inputVar = model.Arguments[0];
NDShape inputShape = inputVar.Shape;
List <float> flattenedBitmapFeatures =
flattenedBitmap.FlattenedBitmap.Select(feat => (float)feat).ToList();
// Create input data map
var inputDataMap = new Dictionary <Variable, Value>();
var inputVal = Value.CreateBatch(inputShape, flattenedBitmapFeatures, _device);
inputDataMap.Add(inputVar, inputVal);
Variable outputVar = model.Output;
// Create output data map. Using null as Value to indicate using system allocated memory.
// Alternatively, create a Value object and add it to the data map.
var outputDataMap = new Dictionary <Variable, Value>();
outputDataMap.Add(outputVar, null);
// Start evaluation on the device
model.Evaluate(inputDataMap, outputDataMap, _device);
// Get evaluate result as dense output
var outputVal = outputDataMap[outputVar];
var outputData = outputVal.GetDenseData <float>(outputVar);
Dictionary <int, float> outputPred = new Dictionary <int, float>();
for (int i = 0; i < outputData[0].Count; i++)
{
outputPred.Add(i, outputData[0][i]);
}
var topPrediction = outputPred.GetTopRelativePrediction();
areaPartsPredictions.Add(new OrderedRecognitionOutput(
_labelMapConfiguration.GetCharFromLabel(croppedArea.AreaUsedForCropping.ExpectedData, topPrediction.EvaluationLabel),
topPrediction.RelativePercentageScore,
flattenedBitmap.Order));
}
return(ProcessingResult <IRecognizedPart <string> > .Success(
new RecognizedTextPart(croppedArea.AreaUsedForCropping.Id, areaPartsPredictions, croppedArea.DocumentId)));
}
catch (Exception ex)
{
//TODO: Return failure
throw ex;
}
}
