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Merge branch 4.x

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This commit is contained in:
Alexander Smorkalov
2026-05-25 16:29:45 +03:00
parent c2594b41bf e0d604378f
commit d8263a9899
54 changed files with 523 additions and 414 deletions
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modules/dnn/test/test_int8_layers.cpp
+6 -8
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@@ -979,7 +979,7 @@ TEST_P(Test_Int8_nets, MobileNet_v1_SSD)
Mat blob = blobFromImage(inp, 1.0, Size(300, 300), Scalar(), true, false);
Mat ref = blobFromNPY(_tf("tensorflow/ssd_mobilenet_v1_coco_2017_11_17.detection_out.npy"));
float confThreshold = 0.5, scoreDiff = 0.034, iouDiff = 0.13;
float confThreshold = 0.5, scoreDiff = 0.034, iouDiff = 0.14;
testDetectionNet(net, blob, ref, confThreshold, scoreDiff, iouDiff);
}
@@ -997,7 +997,7 @@ TEST_P(Test_Int8_nets, MobileNet_v1_SSD_PPN)
Mat blob = blobFromImage(inp, 1.0, Size(300, 300), Scalar(), true, false);
Mat ref = blobFromNPY(_tf("tensorflow/ssd_mobilenet_v1_ppn_coco.detection_out.npy"));
float confThreshold = 0.51, scoreDiff = 0.05, iouDiff = 0.06;
float confThreshold = 0.51, scoreDiff = 0.05, iouDiff = 0.07;
testDetectionNet(net, blob, ref, confThreshold, scoreDiff, iouDiff);
}
@@ -1259,7 +1259,7 @@ TEST_P(Test_Int8_nets, YOLOv3)
std::string model_file = "yolov3.onnx";
double scoreDiff = 0.08, iouDiff = 0.21, confThreshold = 0.25;
double scoreDiff = 0.08, iouDiff = 0.21, confThreshold = 0.28;
{
SCOPED_TRACE("batch size 1");
testYOLOModel(model_file, ref.rowRange(0, N0), scoreDiff, iouDiff, confThreshold);
@@ -1285,7 +1285,7 @@ TEST_P(Test_Int8_nets, YOLOv4)
applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL);
const int N0 = 3;
const int N1 = 7;
const int N1 = 5;
static const float ref_[/* (N0 + N1) * 7 */] = {
0, 16, 0.992194f, 0.172375f, 0.402458f, 0.403918f, 0.932801f,
0, 1, 0.988326f, 0.166708f, 0.228236f, 0.737208f, 0.735803f,
@@ -1296,8 +1296,6 @@ TEST_P(Test_Int8_nets, YOLOv4)
1, 2, 0.98233f, 0.452007f, 0.462217f, 0.495612f, 0.521687f,
1, 9, 0.919195f, 0.374642f, 0.316524f, 0.398126f, 0.393714f,
1, 9, 0.856303f, 0.666842f, 0.372215f, 0.685539f, 0.44141f,
1, 9, 0.313516f, 0.656791f, 0.374734f, 0.671959f, 0.438371f,
1, 9, 0.256625f, 0.940232f, 0.326931f, 0.967586f, 0.374002f,
};
Mat ref(N0 + N1, 7, CV_32FC1, (void*)ref_);
@@ -1305,13 +1303,13 @@ TEST_P(Test_Int8_nets, YOLOv4)
double scoreDiff = 0.15, iouDiff = 0.2;
{
SCOPED_TRACE("batch size 1");
testYOLOModel(model_file, ref.rowRange(0, N0), scoreDiff, iouDiff);
testYOLOModel(model_file, ref.rowRange(0, N0), scoreDiff, iouDiff, 0.5);
}
{
SCOPED_TRACE("batch size 2");
testYOLOModel(model_file, ref, scoreDiff, iouDiff);
testYOLOModel(model_file, ref, scoreDiff, iouDiff, 0.5);
}
}