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#include "test_precomp.hpp"
#include "npy_blob.hpp"

namespace cvtest
{

using namespace cv;
using namespace cv::dnn;

template<typename TString>
static std::string _tf(TString filename)
{
    return (getOpenCVExtraDir() + "/dnn/") + filename;
}

TEST(Test_Caffe, read_gtsrb)
{
    Net net;
    {
        Ptr<Importer> importer = createCaffeImporter(_tf("gtsrb.prototxt"), "");
        ASSERT_TRUE(importer != NULL);
        importer->populateNet(net);
    }
}

TEST(Test_Caffe, read_googlenet)
{
    Net net;
    {
        Ptr<Importer> importer = createCaffeImporter(_tf("bvlc_googlenet.prototxt"), "");
        ASSERT_TRUE(importer != NULL);
        importer->populateNet(net);
    }
}

#if defined(ENABLE_CAFFE_MODEL_TESTS)

#if defined(ENABLE_CAFFE_ALEXNET_TEST) //AlexNet is disabled now

TEST(Reproducibility_AlexNet, Accuracy)
{
    Net net;
    {
        Ptr<Importer> importer = createCaffeImporter(_tf("bvlc_alexnet.prototxt"), _tf("bvlc_alexnet.caffemodel"));
        ASSERT_TRUE(importer != NULL);
        importer->populateNet(net);
    }

    Mat sample = imread(_tf("grace_hopper_227.png"));
    ASSERT_TRUE(!sample.empty());
    cv::cvtColor(sample, sample, cv::COLOR_BGR2RGB);

    Size inputSize(227, 227);

    if (sample.size() != inputSize)
        resize(sample, sample, inputSize);

    net.setBlob(".data", dnn::Blob::fromImages(sample));
    net.forward();

    Blob out = net.getBlob("prob");
    Blob ref = blobFromNPY(_tf("caffe_alexnet_prob.npy"));
    normAssert(ref, out);
}

#endif

#if defined(ENABLE_CAFFE_FCN_TEST)

TEST(Reproducibility_FCN, Accuracy)
{
    Net net;
    {
        Ptr<Importer> importer = createCaffeImporter(_tf("fcn8s-heavy-pascal.prototxt"), _tf("fcn8s-heavy-pascal.caffemodel"));
        ASSERT_TRUE(importer != NULL);
        importer->populateNet(net);
    }

    Mat sample = imread(_tf("street.png"));
    ASSERT_TRUE(!sample.empty());

    Size inputSize(500, 500);
    if (sample.size() != inputSize)
        resize(sample, sample, inputSize);

    cv::cvtColor(sample, sample, cv::COLOR_BGR2RGB);

    net.setBlob(".data", dnn::Blob::fromImages(sample));
    net.forward();

    Blob out = net.getBlob("score");

    Blob ref = blobFromNPY(_tf("caffe_fcn8s_prob.npy"));
    normAssert(ref, out);
}

#endif

#endif

}