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/*
* Created on: Aug 14, 2015
* Author: Yida Wang
*/
#include "test_precomp.hpp"
using namespace cv;
using namespace cv::cnn_3dobj;
class CV_CNN_Feature_Test : public cvtest::BaseTest
{
public:
CV_CNN_Feature_Test();
protected:
void run(int);
};
CV_CNN_Feature_Test::CV_CNN_Feature_Test()
{
}
/**
* This test checks the following:
* Feature extraction by the triplet trained CNN model
*/
void CV_CNN_Feature_Test::run(int)
{
String caffemodel = String(ts->get_data_path()) + "3d_triplet_iter_30000.caffemodel";
String network_forIMG = cvtest::TS::ptr()->get_data_path() + "3d_triplet_testIMG.prototxt";
String mean_file = "no";
std::vector<String> ref_img;
String target_img = String(ts->get_data_path()) + "1_8.png";
String feature_blob = "feat";
String device = "CPU";
int dev_id = 0;
cv::Mat img_base = cv::imread(target_img, -1);
if (img_base.empty())
{
ts->printf(cvtest::TS::LOG, "could not read reference image %s\n", target_img.c_str(), "make sure the path of images are set properly.");
ts->set_failed_test_info(cvtest::TS::FAIL_MISSING_TEST_DATA);
return;
}
cv::cnn_3dobj::descriptorExtractor descriptor(device, dev_id);
if (strcmp(mean_file.c_str(), "no") == 0)
descriptor.loadNet(network_forIMG, caffemodel);
else
descriptor.loadNet(network_forIMG, caffemodel, mean_file);
cv::Mat feature_test;
descriptor.extract(img_base, feature_test, feature_blob);
Mat feature_reference = (Mat_<float>(1,16) << -134.03548, -203.48265, -105.96752, 55.343075, -211.36378, 487.85968, -182.15063, 62.229042, 297.19876, 206.07578, 291.74951, -19.906454, -464.09152, 135.79895, 420.43616, 2.2887282);
printf("Reference feature is computed by Caffe extract_features tool by \n To generate values for different images, use extract_features \n with the resetted image list in prototxt.");
float dist = norm(feature_test - feature_reference);
if (dist > 5) {
ts->printf(cvtest::TS::LOG, "Extracted featrue is not the same from the one extracted from Caffe.");
ts->set_failed_test_info(cvtest::TS::FAIL_MISSING_TEST_DATA);
return;
}
}
TEST(CNN_FEATURE, accuracy) { CV_CNN_Feature_Test test; test.safe_run(); }