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add loading TensorFlow/Caffe net from memory buffer

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add a corresponding test
This commit is contained in:
David Geldreich
2017-10-27 18:01:41 +02:00
parent 6e4f9433d0
commit f723cede2e
10 changed files with 219 additions and 45 deletions
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modules/dnn/test/test_caffe_importer.cpp
+35 -2
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@@ -55,6 +55,24 @@ static std::string _tf(TString filename)
return (getOpenCVExtraDir() + "/dnn/") + filename;
}
TEST(Test_Caffe, memory_read)
{
const string proto = findDataFile("dnn/bvlc_googlenet.prototxt", false);
const string model = findDataFile("dnn/bvlc_googlenet.caffemodel", false);
string dataProto;
ASSERT_TRUE(readFileInMemory(proto, dataProto));
string dataModel;
ASSERT_TRUE(readFileInMemory(model, dataModel));
Net net = readNetFromCaffe(dataProto.c_str(), dataProto.size());
ASSERT_FALSE(net.empty());
Net net2 = readNetFromCaffe(dataProto.c_str(), dataProto.size(),
dataModel.c_str(), dataModel.size());
ASSERT_FALSE(net2.empty());
}
TEST(Test_Caffe, read_gtsrb)
{
Net net = readNetFromCaffe(_tf("gtsrb.prototxt"));
@@ -67,13 +85,26 @@ TEST(Test_Caffe, read_googlenet)
ASSERT_FALSE(net.empty());
}
TEST(Reproducibility_AlexNet, Accuracy)
typedef testing::TestWithParam<tuple<bool> > Reproducibility_AlexNet;
TEST_P(Reproducibility_AlexNet, Accuracy)
{
bool readFromMemory = get<0>(GetParam());
Net net;
{
const string proto = findDataFile("dnn/bvlc_alexnet.prototxt", false);
const string model = findDataFile("dnn/bvlc_alexnet.caffemodel", false);
net = readNetFromCaffe(proto, model);
if (readFromMemory)
{
string dataProto;
ASSERT_TRUE(readFileInMemory(proto, dataProto));
string dataModel;
ASSERT_TRUE(readFileInMemory(model, dataModel));
net = readNetFromCaffe(dataProto.c_str(), dataProto.size(),
dataModel.c_str(), dataModel.size());
}
else
net = readNetFromCaffe(proto, model);
ASSERT_FALSE(net.empty());
}
@@ -86,6 +117,8 @@ TEST(Reproducibility_AlexNet, Accuracy)
normAssert(ref, out);
}
INSTANTIATE_TEST_CASE_P(Test_Caffe, Reproducibility_AlexNet, testing::Values(true, false));
#if !defined(_WIN32) || defined(_WIN64)
TEST(Reproducibility_FCN, Accuracy)
{