43 lines
1.7 KiB
C++
43 lines
1.7 KiB
C++
// Copyright (2019-2024) Paul Scherrer Institute
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#include <iostream>
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#include "NeuralNetResPredictor.h"
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#include "../writer/HDF5Objects.h"
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int main(int argc, char **argv) {
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DiffractionExperiment experiment(DetectorGeometry(8, 2, 8, 36));
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experiment.DetectorDistance_mm(75).PhotonEnergy_keV(12.4).BeamY_pxl(1136).BeamX_pxl(1090);
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experiment.NeuralNetModelPath(argv[1]);
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if (argc == 0)
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exit(EXIT_FAILURE);
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NeuralNetResPredictor predictor(experiment);
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HDF5ReadOnlyFile data("../../tests/test_data/compression_benchmark.h5");
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HDF5DataSet dataset(data, "/entry/data/data");
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HDF5DataSpace file_space(dataset);
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std::vector<int16_t> image_conv (file_space.GetDimensions()[1] * file_space.GetDimensions()[2]);
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std::vector<hsize_t> start = {4,0,0};
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std::vector<hsize_t> file_size = {1, file_space.GetDimensions()[1], file_space.GetDimensions()[2]};
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dataset.ReadVector(image_conv, start, file_size);
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std::cout << "Max pooling " << predictor.GetMaxPoolFactor() << std::endl;
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float x = 0;
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size_t niterations = 25;
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auto start_time = std::chrono::system_clock::now();
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for (int i = 0; i < niterations; i++)
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x += predictor.Inference(image_conv.data());
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auto end_time = std::chrono::system_clock::now();
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auto elapsed = std::chrono::duration_cast<std::chrono::microseconds>(end_time - start_time);
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int64_t frequency_Hz = (niterations * 1e6) / (double) (elapsed.count());
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std::cout << ((double) elapsed.count()) / (1e3 * niterations) << " ms" << std::endl;
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std::cout << frequency_Hz << " Hz" << std::endl;
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std::cout << "Resolution " << predictor.Inference(image_conv.data()) << std::endl;
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}
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