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NeuralNetInferenceClient: Accept PixelMask

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This commit is contained in:
leonarski_f
2025-06-30 21:29:48 +02:00
parent dba2544c48
commit 92288c60d7
7 changed files with 110 additions and 37 deletions
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tests/NeuralNetResPredictorTest.cpp
+48 -4
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@@ -18,6 +18,8 @@ TEST_CASE("NeuralNetResPredictor_Prepare", "[LinearAlgebra][Coord]") {
v[1001 * experiment.GetXPixelsNum() + 1000] = 30;
v[1001 * experiment.GetXPixelsNum() + 1001] = INT16_MIN;
v[600 * experiment.GetXPixelsNum() + 600] = 121;
v[1050 * experiment.GetXPixelsNum() + 1050] = 52;
v[2000 * experiment.GetXPixelsNum() + 1500] = 160;
@@ -29,22 +31,64 @@ TEST_CASE("NeuralNetResPredictor_Prepare", "[LinearAlgebra][Coord]") {
REQUIRE(predictor.GetMaxPoolFactor(experiment) == 2);
auto br = predictor.Prepare(experiment, v.data(), Quarter::BottomRight);
PixelMask mask(experiment);
std::vector<uint32_t> mask_vec(experiment.GetPixelsNum());
mask.LoadUserMask(experiment, mask_vec);
auto br = predictor.Prepare(experiment, mask, v.data(), Quarter::BottomRight);
REQUIRE(br.size() == 512 * 512);
CHECK(br[0] == 10);
CHECK(br[25 * 512 + 25] == 7);
CHECK(br[500 * 512 + 250] == 12);
auto tl = predictor.Prepare(experiment, v.data(), Quarter::TopLeft);
auto tl = predictor.Prepare(experiment, mask, v.data(), Quarter::TopLeft);
REQUIRE(tl.size() == 512 * 512);
CHECK(tl[100 * 512 + 200] == 7);
CHECK(tl[200 * 512 + 200] == 11);
auto tr = predictor.Prepare(experiment, v.data(), Quarter::TopRight);
auto tr = predictor.Prepare(experiment, mask, v.data(), Quarter::TopRight);
REQUIRE(tr.size() == 512 * 512);
CHECK(tr[100 * 512 + 200] == 8);
auto bl = predictor.Prepare(experiment, v.data(), Quarter::BottomLeft);
auto bl = predictor.Prepare(experiment, mask, v.data(), Quarter::BottomLeft);
REQUIRE(bl.size() == 512 * 512);
CHECK(bl[100 * 512 + 200] == 6);
}
TEST_CASE("NeuralNetResPredictor_Prepare_PixelMask", "[LinearAlgebra][Coord]") {
DiffractionExperiment experiment(DetJF4M());
experiment.DetectorDistance_mm(75).IncidentEnergy_keV(12.4).BeamX_pxl(1000).BeamY_pxl(1000);
std::vector<int16_t> v(experiment.GetPixelsNum(),0);
v[1000 * experiment.GetXPixelsNum() + 1000] = 100;
v[1000 * experiment.GetXPixelsNum() + 1001] = 20;
v[1001 * experiment.GetXPixelsNum() + 1000] = 30;
v[1001 * experiment.GetXPixelsNum() + 1001] = INT16_MIN;
v[600 * experiment.GetXPixelsNum() + 600] = 121;
v[1050 * experiment.GetXPixelsNum() + 1050] = 52;
v[2000 * experiment.GetXPixelsNum() + 1500] = 160;
v[800 * experiment.GetXPixelsNum() + 600] = 49;
v[1200 * experiment.GetXPixelsNum() + 600] = 36;
v[800 * experiment.GetXPixelsNum() + 1400] = 64;
NeuralNetInferenceClient predictor;
REQUIRE(predictor.GetMaxPoolFactor(experiment) == 2);
PixelMask mask(experiment);
std::vector<uint32_t> mask_vec(experiment.GetPixelsNum());
mask_vec[600 * experiment.GetXPixelsNum() + 600] = 8;
mask.LoadUserMask(experiment, mask_vec);
auto tl = predictor.Prepare(experiment, mask, v.data(), Quarter::TopLeft);
REQUIRE(tl.size() == 512 * 512);
CHECK(tl[100 * 512 + 200] == 7);
CHECK(tl[200 * 512 + 200] == 0);
}