public static Result[] SearchSegmFree(NewImage QueryImage, ConcurrentDictionary <string, DocumentInfo> Dataset)
{
var myDSLPLibrary = new DoLF();
var myDSLPpoints = myDSLPLibrary.GetDSLPoints(QueryImage.Data, QueryImage.Width, QueryImage.Height, 3);
var queryVector = myDSLPLibrary.CreateNormalizedDescriptorForSegmFree(myDSLPpoints);
var results = new ConcurrentBag <Result>();
//Parallel.ForEach(Dataset.Keys, doc =>
foreach (var doc in Dataset.Keys)
{
var _results = myDSLPLibrary.DistanceSegmFree(queryVector, QueryImage.Width, QueryImage.Height, Dataset[doc].Descriptors);
foreach (var r in _results)
{
results.Add(new Result
{
X = (short)r.Block[0],
Y = (short)r.Block[1],
Width = (short)r.Block[2],
Height = (short)r.Block[3],
Similarity = r.Similarity,
Document = doc
});
}
}
return(results.OrderBy(x => x.Similarity).ToArray());
}
public static IEnumerable <int> Search(float[] QueryVector, int QueryWidth, int QueryHeight, float[] DocumentVector)
{
var myDSLPLibrary = new DoLF();
return(myDSLPLibrary.DistanceSegmFree(QueryVector, QueryWidth, QueryHeight, DocumentVector)
.OrderBy(d => d.Similarity)
.SelectMany(d => new int[] {
d.Block[0],
d.Block[1],
d.Block[2],
d.Block[3],
(int)Math.Round(10000 * d.Similarity)
}));
}