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Rewrote googlenet tests

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This commit is contained in:
Aleksandr Rybnikov 2017-06-29 16:45:17 +03:00
parent 6ba22dea46
commit 7d1140340e
5 changed files with 52 additions and 18 deletions
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9
modules/dnn/src/dnn.cpp
View File

@ -694,6 +694,7 @@ struct Net::Impl
for (it = layers.begin(); it != layers.end(); it++)
{
if (it->second.id != 0) {
it->second.inputBlobs.clear();
it->second.outputBlobs.clear();
it->second.internals.clear();
}
@ -1106,10 +1107,12 @@ struct Net::Impl
bnormData->skipFlags[DNN_BACKEND_DEFAULT] = true;
ld.outputBlobs = layers[lpNext.lid].outputBlobs;
if( bnormData->consumers.size() == 1 )
{
nextData = &layers[bnormData->consumers[0].lid];
lpNext = LayerPin(bnormData->consumers[0].lid, 0);
}
}
}
Ptr<ScaleLayer> nextScaleLayer;
if( nextData )
@ -1124,7 +1127,10 @@ struct Net::Impl
scaleData->skipFlags[DNN_BACKEND_DEFAULT] = true;
ld.outputBlobs = layers[lpNext.lid].outputBlobs;
if( scaleData->consumers.size() == 1 )
{
nextData = &layers[scaleData->consumers[0].lid];
lpNext = LayerPin(scaleData->consumers[0].lid, 0);
}
}
}
@ -1132,7 +1138,8 @@ struct Net::Impl
if( nextData )
nextActivLayer = nextData->layerInstance.dynamicCast<ActivationLayer>();
if( !nextActivLayer.empty() && currLayer->setActivation(nextActivLayer) )
if( !nextActivLayer.empty() && pinsToKeep.count(lpNext) == 0
&& currLayer->setActivation(nextActivLayer) )
{
printf_(("\tfused with %s\n", nextActivLayer->name.c_str()));
nextData->skipFlags[DNN_BACKEND_DEFAULT] = true;

2
modules/dnn/src/layers/convolution_layer.cpp
View File

@ -198,6 +198,8 @@ public:
bool setActivation(const Ptr<ActivationLayer>& layer)
{
activ = layer;
if (activ.empty())
reluslope.clear();
return !activ.empty();
}

5
modules/dnn/test/imagenet_cls_test_alexnet.py
View File

@ -146,9 +146,8 @@ class DnnCaffeModel(Framework):
return 'DNN'
def get_output(self, input_blob):
self.net.setBlob(self.in_blob_name, input_blob)
self.net.forward()
return self.net.getBlob(self.out_blob_name)
self.net.setInput(input_blob, self.in_blob_name)
return self.net.forward(self.out_blob_name)
class ClsAccEvaluation:

50
modules/dnn/test/test_googlenet.cpp
View File

@ -56,16 +56,10 @@ static std::string _tf(TString filename)
return (getOpenCVExtraDir() + "/dnn/") + filename;
}
static void launchGoogleNetTest()
TEST(Reproducibility_GoogLeNet, Accuracy)
{
Net net;
{
const string proto = findDataFile("dnn/bvlc_googlenet.prototxt", false);
const string model = findDataFile("dnn/bvlc_googlenet.caffemodel", false);
Ptr<Importer> importer = createCaffeImporter(proto, model);
ASSERT_TRUE(importer != NULL);
importer->populateNet(net);
}
Net net = readNetFromCaffe(findDataFile("dnn/bvlc_googlenet.prototxt", false),
findDataFile("dnn/bvlc_googlenet.caffemodel", false));
std::vector<Mat> inpMats;
inpMats.push_back( imread(_tf("googlenet_0.png")) );
@ -77,6 +71,12 @@ static void launchGoogleNetTest()
Mat ref = blobFromNPY(_tf("googlenet_prob.npy"));
normAssert(out, ref);
}
TEST(IntermediateBlobs_GoogLeNet, Accuracy)
{
Net net = readNetFromCaffe(findDataFile("dnn/bvlc_googlenet.prototxt", false),
findDataFile("dnn/bvlc_googlenet.caffemodel", false));
std::vector<String> blobsNames;
blobsNames.push_back("conv1/7x7_s2");
@ -84,7 +84,7 @@ static void launchGoogleNetTest()
blobsNames.push_back("inception_4c/1x1");
blobsNames.push_back("inception_4c/relu_1x1");
std::vector<Mat> outs;
Mat in = blobFromImage(inpMats[0]);
Mat in = blobFromImage(imread(_tf("googlenet_0.png")));
net.setInput(in, "data");
net.forward(outs, blobsNames);
CV_Assert(outs.size() == blobsNames.size());
@ -95,13 +95,37 @@ static void launchGoogleNetTest()
std::replace( filename.begin(), filename.end(), '/', '#');
Mat ref = blobFromNPY(_tf("googlenet_" + filename + ".npy"));
//normAssert(outs[i], ref, "", 1E-4, 1E-2);
normAssert(outs[i], ref, "", 1E-4, 1E-2);
}
}
TEST(Reproducibility_GoogLeNet, Accuracy)
TEST(SeveralCalls_GoogLeNet, Accuracy)
{
launchGoogleNetTest();
Net net = readNetFromCaffe(findDataFile("dnn/bvlc_googlenet.prototxt", false),
findDataFile("dnn/bvlc_googlenet.caffemodel", false));
std::vector<Mat> inpMats;
inpMats.push_back( imread(_tf("googlenet_0.png")) );
inpMats.push_back( imread(_tf("googlenet_1.png")) );
ASSERT_TRUE(!inpMats[0].empty() && !inpMats[1].empty());
net.setInput(blobFromImages(inpMats), "data");
Mat out = net.forward();
Mat ref = blobFromNPY(_tf("googlenet_prob.npy"));
normAssert(out, ref);
std::vector<String> blobsNames;
blobsNames.push_back("conv1/7x7_s2");
std::vector<Mat> outs;
Mat in = blobFromImage(inpMats[0]);
net.setInput(in, "data");
net.forward(outs, blobsNames);
CV_Assert(outs.size() == blobsNames.size());
ref = blobFromNPY(_tf("googlenet_conv1#7x7_s2.npy"));
normAssert(outs[0], ref, "", 1E-4, 1E-2);
}
}

2
samples/dnn/torch_enet.cpp
View File

@ -85,7 +85,9 @@ int main(int argc, char **argv)
}
//! [Make forward pass]
tm.start();
Mat result = net.forward(oBlob);
tm.stop();
if (!resultFile.empty()) {
CV_Assert(result.isContinuous());