public Result[] Detect(Tensor imageResults)
{
if (_graph == null)
{
throw new NullReferenceException("The multibox graph has not been initialized. Please call the Init function first.");
}
Tensor[] finalTensor = _session.Run(new Output[] { _graph["ResizeBilinear"] }, new Tensor[] { imageResults },
new Output[] { _graph["output_scores/Reshape"], _graph["output_locations/Reshape"] });
int labelCount = finalTensor[0].Dim[1];
Tensor[] topK = GetTopDetections(finalTensor[0], labelCount);
float[] encodedScores = topK[0].Flat <float>();
float[] encodedLocations = finalTensor[1].Flat <float>();
int[] indices = topK[1].Flat <int>();
float[] scores = DecodeScoresEncoding(encodedScores);
Result[] results = new Result[indices.Length];
float[][] locations = MultiboxGraph.DecodeLocationsEncoding(encodedLocations, _boxPriors);
for (int i = 0; i < indices.Length; i++)
{
results[i] = new Result();
results[i].Scores = scores[i];
results[i].DecodedLocations = locations[indices[i]];
}
return(results);
}
public Result[] Detect(Tensor imageResults)
{
Tensor[] finalTensor = _session.Run(new Output[] { _graph["ResizeBilinear"] }, new Tensor[] { imageResults },
new Output[] { _graph["output_scores/Reshape"], _graph["output_locations/Reshape"] });
int labelCount = finalTensor[0].Dim[1];
Tensor[] topK = GetTopDetections(finalTensor[0], labelCount);
float[] encodedScores = topK[0].Flat <float>();
float[] encodedLocations = finalTensor[1].Flat <float>();
int[] indices = topK[1].Flat <int>();
float[] scores = DecodeScoresEncoding(encodedScores);
Result[] results = new Result[indices.Length];
float[][] locations = MultiboxGraph.DecodeLocationsEncoding(encodedLocations, _boxPriors);
for (int i = 0; i < indices.Length; i++)
{
results[i] = new Result();
results[i].Scores = scores[i];
results[i].DecodedLocations = locations[indices[i]];
}
return(results);
}
public Result Detect(Tensor imageResults)
{
Session multiboxSession = new Session(this);
Tensor[] finalTensor = multiboxSession.Run(new Output[] { this["ResizeBilinear"] }, new Tensor[] { imageResults },
new Output[] { this["output_scores/Reshape"], this["output_locations/Reshape"] });
int labelCount = finalTensor[0].Dim[1];
Tensor[] topK = GetTopDetections(finalTensor, labelCount);
float[] encodedScores = topK[0].Flat <float>();
float[] encodedLocations = finalTensor[1].Flat <float>();
#if __ANDROID__
float[] boxPriors = ReadBoxPriors(System.IO.Path.Combine(Android.OS.Environment.ExternalStorageDirectory.AbsolutePath, Android.OS.Environment.DirectoryDownloads, _modelFiles[1]));
#else
float[] boxPriors = ReadBoxPriors(_modelFiles[1]);
#endif
Result result = new Result();
result.Scores = DecodeScoresEncoding(encodedScores);
result.Indices = topK[1].Flat <int>();
result.DecodedLocations = MultiboxGraph.DecodeLocationsEncoding(encodedLocations, boxPriors);
return(result);
}
public Result Detect(Tensor imageResults)
{
Tensor[] finalTensor = _session.Run(new Output[] { _graph["ResizeBilinear"] }, new Tensor[] { imageResults },
new Output[] { _graph["output_scores/Reshape"], _graph["output_locations/Reshape"] });
int labelCount = finalTensor[0].Dim[1];
Tensor[] topK = GetTopDetections(finalTensor, labelCount);
float[] encodedScores = topK[0].Flat <float>();
float[] encodedLocations = finalTensor[1].Flat <float>();
Result result = new Result();
result.Scores = DecodeScoresEncoding(encodedScores);
result.Indices = topK[1].Flat <int>();
result.DecodedLocations = MultiboxGraph.DecodeLocationsEncoding(encodedLocations, _boxPriors);
return(result);
}
public Result Detect(Tensor imageResults, SessionOptions sessionOptions = null)
{
Session multiboxSession = new Session(_graph, sessionOptions);
Tensor[] finalTensor = multiboxSession.Run(new Output[] { _graph["ResizeBilinear"] }, new Tensor[] { imageResults },
new Output[] { _graph["output_scores/Reshape"], _graph["output_locations/Reshape"] });
int labelCount = finalTensor[0].Dim[1];
Tensor[] topK = GetTopDetections(finalTensor, labelCount);
float[] encodedScores = topK[0].Flat <float>();
float[] encodedLocations = finalTensor[1].Flat <float>();
float[] boxPriors = ReadBoxPriors(_downloadManager.Files[1].LocalFile);
Result result = new Result();
result.Scores = DecodeScoresEncoding(encodedScores);
result.Indices = topK[1].Flat <int>();
result.DecodedLocations = MultiboxGraph.DecodeLocationsEncoding(encodedLocations, boxPriors);
return(result);
}
public Result Detect(Tensor imageResults)
{
Session multiboxSession = new Session(this);
Tensor[] finalTensor = multiboxSession.Run(new Output[] { this["ResizeBilinear"] }, new Tensor[] { imageResults },
new Output[] { this["output_scores/Reshape"], this["output_locations/Reshape"] });
int labelCount = finalTensor[0].Dim[1];
Tensor[] topK = GetTopDetections(finalTensor, labelCount);
float[] encodedScores = topK[0].Flat <float>();
float[] encodedLocations = finalTensor[1].Flat <float>();
float[] boxPriors = ReadBoxPriors(GetLocalFileName(_modelFiles[1]));
Result result = new Result();
result.Scores = DecodeScoresEncoding(encodedScores);
result.Indices = topK[1].Flat <int>();
result.DecodedLocations = MultiboxGraph.DecodeLocationsEncoding(encodedLocations, boxPriors);
return(result);
}
