mirror/opencv
1
0
Fork 0
mirror of https://github.com/opencv/opencv.git synced 2025-08-06 14:36:36 +08:00
Code Issues Actions Packages Projects Releases Wiki Activity

Fix change step

Browse Source
This commit is contained in:
Alexander Nesterov 2019-02-01 16:23:51 -01:00
parent f67b197d49
commit 9cbdb48d6d
2 changed files with 37 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

19
modules/dnn/src/layers/prior_box_layer.cpp
View File

@ -487,9 +487,7 @@ public:
if (_explicitSizes)
{
InferenceEngine::Builder::PriorBoxClusteredLayer ieLayer(name);
CV_Assert(_stepX == _stepY);
ieLayer.setStep(_stepX);
ieLayer.setSteps({_stepY, _stepX});
CV_CheckEQ(_offsetsX.size(), (size_t)1, ""); CV_CheckEQ(_offsetsY.size(), (size_t)1, ""); CV_CheckEQ(_offsetsX[0], _offsetsY[0], "");
ieLayer.setOffset(_offsetsX[0]);
@ -516,9 +514,6 @@ public:
if (_maxSize > 0)
ieLayer.setMaxSize(_maxSize);
CV_Assert(_stepX == _stepY);
ieLayer.setStep(_stepX);
CV_CheckEQ(_offsetsX.size(), (size_t)1, ""); CV_CheckEQ(_offsetsY.size(), (size_t)1, ""); CV_CheckEQ(_offsetsX[0], _offsetsY[0], "");
ieLayer.setOffset(_offsetsX[0]);
@ -526,6 +521,18 @@ public:
ieLayer.setFlip(false); // We already flipped aspect ratios.
InferenceEngine::Builder::Layer l = ieLayer;
if (_stepX == _stepY)
{
l.getParameters()["step"] = _stepX;
l.getParameters()["step_h"] = 0.0;
l.getParameters()["step_w"] = 0.0;
}
else
{
l.getParameters()["step"] = 0.0;
l.getParameters()["step_h"] = _stepY;
l.getParameters()["step_w"] = _stepX;
}
if (!_aspectRatios.empty())
{
l.getParameters()["aspect_ratio"] = _aspectRatios;

24
modules/dnn/test/test_backends.cpp
View File

@ -162,6 +162,18 @@ TEST_P(DNNTestNetwork, MobileNet_SSD_Caffe)
inp, "detection_out", "", diffScores);
}
TEST_P(DNNTestNetwork, MobileNet_SSD_Caffe_Different_Width_Height)
{
if (backend == DNN_BACKEND_HALIDE)
throw SkipTestException("");
Mat sample = imread(findDataFile("dnn/street.png", false));
Mat inp = blobFromImage(sample, 1.0f / 127.5, Size(300, 560), Scalar(127.5, 127.5, 127.5), false);
float diffScores = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.029 : 0.0;
float diffSquares = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.09 : 0.0;
processNet("dnn/MobileNetSSD_deploy.caffemodel", "dnn/MobileNetSSD_deploy.prototxt",
inp, "detection_out", "", diffScores, diffSquares);
}
TEST_P(DNNTestNetwork, MobileNet_SSD_v1_TensorFlow)
{
if (backend == DNN_BACKEND_HALIDE)
@ -174,6 +186,18 @@ TEST_P(DNNTestNetwork, MobileNet_SSD_v1_TensorFlow)
inp, "detection_out", "", l1, lInf);
}
TEST_P(DNNTestNetwork, MobileNet_SSD_v1_TensorFlow_Different_Width_Height)
{
if (backend == DNN_BACKEND_HALIDE)
throw SkipTestException("");
Mat sample = imread(findDataFile("dnn/street.png", false));
Mat inp = blobFromImage(sample, 1.0f, Size(300, 560), Scalar(), false);
float l1 = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.012 : 0.0;
float lInf = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 0.06 : 0.0;
processNet("dnn/ssd_mobilenet_v1_coco_2017_11_17.pb", "dnn/ssd_mobilenet_v1_coco_2017_11_17.pbtxt",
inp, "detection_out", "", l1, lInf);
}
TEST_P(DNNTestNetwork, MobileNet_SSD_v2_TensorFlow)
{
if (backend == DNN_BACKEND_HALIDE)