public T Score <T>(IScoringRequest request) where T : class
{
var requestGrpc = request.MakePredictRequest();
var result = _client.Predict(requestGrpc);
return(result.Outputs["output_alias"].Convert <T>());
}
public async Task <T> ScoreAsync <T>(IScoringRequest request) where T : class
{
var predictRequest = request.MakePredictRequest();
return(await RetryAsync(async() => {
var result = await _client.PredictAsync(predictRequest);
return result.Outputs["output_alias"].Convert <T>();
}));
}
public async Task <Dictionary <string, T> > PredictAsync <T>(IScoringRequest request, int retryCount = RetryCount) where T : class
{
var predictRequest = request.MakePredictRequest();
return(await RetryAsync(async() =>
{
var result = await _client.PredictAsync(predictRequest);
return result.Outputs.ToDictionary(
kvp => kvp.Key, kvp => kvp.Value.Convert <T>());
}, retryCount));
}
public List <ImageFeature> Process(ByteString image)
{
List <ImageFeature> result = new List <ImageFeature>();
try
{
IScoringRequest request = null;
float[] offsets = new float[] { 123, 117, 104 };
using (MemoryStream stream = new MemoryStream(image.ToByteArray()))
using (Bitmap bitmap = new Bitmap(stream))
{
int width = bitmap.Width;
int height = bitmap.Height;
float[] values = new float[3 * width * height];
int valuesIdx = 0;
for (int i = 0; i < height; i++)
{
for (int j = 0; j < width; j++)
{
var pixel = bitmap.GetPixel(j, i);
values[valuesIdx++] = pixel.B - offsets[0];
values[valuesIdx++] = pixel.G - offsets[1];
values[valuesIdx++] = pixel.R - offsets[2];
}
}
int[] shape = new int[] { 1, 300, 300, 3 };
Tuple <float[], int[]> tuple = new Tuple <float[], int[]>(values, shape);
Dictionary <string, Tuple <float[], int[]> > inputs = new Dictionary <string, Tuple <float[], int[]> >
{
{ "brainwave_ssd_vgg_1_Version_0.1_input_1:0", tuple }
};
request = new FloatRequest(inputs);
}
PredictResponse response = Predict(request.MakePredictRequest());
if (response != null)
{
result = FpgaPostProcess.PostProcess(response, selectThreshold: 0.5F, jaccardThreshold: 0.45F);
}
}
catch (Exception ex)
{
Console.WriteLine($"Failed during FPGA Pre- or Post- Process: {ex.Message}");
}
return(result);
}
public List <ImageFeature> Process(ByteString image)
{
List <ImageFeature> result = new List <ImageFeature>();
try
{
IScoringRequest request = null;
float[] values = new float[image.Length];
int idx = 0;
while (idx < image.Length)
{
values[idx] = image[idx] - rRefLevel;
idx++;
values[idx] = image[idx] - gRefLevel;
idx++;
values[idx] = image[idx] - bRefLevel;
idx++;
}
int[] shape = new int[] { 1, 300, 300, 3 };
Tuple <float[], int[]> tuple = new Tuple <float[], int[]>(values, shape);
Dictionary <string, Tuple <float[], int[]> > inputs = new Dictionary <string, Tuple <float[], int[]> >
{
{ "brainwave_ssd_vgg_1_Version_0.1_input_1:0", tuple }
};
request = new FloatRequest(inputs);
PredictResponse response = Predict(request.MakePredictRequest());
if (response != null)
{
result = FpgaPostProcess.PostProcess(response, selectThreshold: 0.5F, jaccardThreshold: 0.45F);
}
}
catch (Exception ex)
{
Console.WriteLine($"Failed during FPGA Pre- or Post- Process: {ex.Message}");
}
return(result);
}
public async Task <T> ScoreAsync <T>(IScoringRequest request, int retryCount = RetryCount, string output_name = "output_alias") where T : class
{
return((await this.PredictAsync <T>(request, retryCount))[output_name]);
}
public async Task <float[]> ScoreAsync(IScoringRequest request, int retryCount = RetryCount, string output_name = "output_alias")
{
return(await ScoreAsync <float[]>(request, retryCount, output_name));
}
public async Task <float[]> ScoreAsync(IScoringRequest request, int retryCount = RetryCount)
{
return(await ScoreAsync <float[]>(request, retryCount));
}
public async Task <float[]> ScoreAsync(IScoringRequest request)
{
return(await ScoreAsync <float[]>(request));
}
public float[] Score(IScoringRequest request)
{
return(Score <float[]>(request));
}
