potok/opencv
1
0
Fork 0
mirror of https://github.com/opencv/opencv.git synced 2026-07-31 00:03:03 +04:00
Code Packages Releases Wiki Activity

Layers for OpenFace face recognition network

Browse Source
This commit is contained in:
Dmitry Kurtaev
2017-08-28 17:37:09 +03:00
parent 8a094a5f54
commit 7dc6b1d7d4
10 changed files with 328 additions and 34 deletions
Download Patch File Download Diff File Expand all files Collapse all files
modules/dnn/test/test_torch_importer.cpp
+45 -2
View File
@@ -56,11 +56,11 @@ using namespace cv::dnn;
template<typename TStr>
static std::string _tf(TStr filename, bool inTorchDir = true)
{
String path = getOpenCVExtraDir() + "/dnn/";
String path = "dnn/";
if (inTorchDir)
path += "torch/";
path += filename;
return path;
return findDataFile(path, false);
}
TEST(Torch_Importer, simple_read)
@@ -123,6 +123,7 @@ TEST(Torch_Importer, run_reshape)
runTorchNet("net_reshape");
runTorchNet("net_reshape_batch");
runTorchNet("net_reshape_single_sample");
runTorchNet("net_reshape_channels", "", false, true);
}
TEST(Torch_Importer, run_linear)
@@ -138,6 +139,7 @@ TEST(Torch_Importer, run_paralel)
TEST(Torch_Importer, run_concat)
{
runTorchNet("net_concat", "l5_torchMerge");
runTorchNet("net_depth_concat", "", false, true);
}
TEST(Torch_Importer, run_deconv)
@@ -172,6 +174,27 @@ TEST(Torch_Importer, net_logsoftmax)
runTorchNet("net_logsoftmax_spatial");
}
TEST(Torch_Importer, net_lp_pooling)
{
runTorchNet("net_lp_pooling_square", "", false, true);
runTorchNet("net_lp_pooling_power", "", false, true);
}
TEST(Torch_Importer, net_conv_gemm_lrn)
{
runTorchNet("net_conv_gemm_lrn", "", false, true);
}
TEST(Torch_Importer, net_inception_block)
{
runTorchNet("net_inception_block", "", false, true);
}
TEST(Torch_Importer, net_normalize)
{
runTorchNet("net_normalize", "", false, true);
}
TEST(Torch_Importer, ENet_accuracy)
{
Net net;
@@ -202,6 +225,26 @@ TEST(Torch_Importer, ENet_accuracy)
}
}
TEST(Torch_Importer, OpenFace_accuracy)
{
const string model = findDataFile("dnn/openface_nn4.small2.v1.t7", false);
Net net = readNetFromTorch(model);
Mat sample = imread(findDataFile("cv/shared/lena.png", false));
Mat sampleF32(sample.size(), CV_32FC3);
sample.convertTo(sampleF32, sampleF32.type());
sampleF32 /= 255;
resize(sampleF32, sampleF32, Size(96, 96), 0, 0, INTER_NEAREST);
Mat inputBlob = blobFromImage(sampleF32);
net.setInput(inputBlob);
Mat out = net.forward();
Mat outRef = readTorchBlob(_tf("net_openface_output.dat"), true);
normAssert(out, outRef);
}
}
#endif