1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
|
/*
* 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 = cvtest::findDataFile("contrib/cnn_3dobj/3d_triplet_iter_30000.caffemodel");
String network_forIMG = cvtest::findDataFile("contrib/cnn_3dobj/3d_triplet_testIMG.prototxt");
String mean_file = "no";
std::vector<String> ref_img;
String target_img = cvtest::findDataFile("contrib/cnn_3dobj/4_78.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 (mean_file == "no")
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);
// Reference feature is computed by Caffe extract_features tool.
// To generate values for different images, use extract_features with the resetted image list in prototxt.
Mat feature_reference = (Mat_<float>(1,3) << -312.4805, 8.4768486, -224.98953);
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(); }
|
