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/*******************************************************
* Copyright (c) 2014, ArrayFire
* All rights reserved.
*
* This file is distributed under 3-clause BSD license.
* The complete license agreement can be obtained at:
* http://arrayfire.com/licenses/BSD-3-Clause
********************************************************/
#include <gtest/gtest.h>
#include <arrayfire.h>
#include <af/dim4.hpp>
#include <af/traits.hpp>
#include <af/compatible.h>
#include <string>
#include <vector>
#include <cmath>
#include <testHelpers.hpp>
#include <typeinfo>
using std::string;
using std::vector;
using std::abs;
using af::dim4;
typedef struct
{
float f[5];
} feat_t;
static bool feat_cmp(feat_t i, feat_t j)
{
for (int k = 0; k < 5; k++)
if (i.f[k] != j.f[k])
return (i.f[k] < j.f[k]);
return false;
}
static void array_to_feat(vector<feat_t>& feat, float *x, float *y, float *score, float *orientation, float *size, unsigned nfeat)
{
feat.resize(nfeat);
for (unsigned i = 0; i < feat.size(); i++) {
feat[i].f[0] = x[i];
feat[i].f[1] = y[i];
feat[i].f[2] = score[i];
feat[i].f[3] = orientation[i];
feat[i].f[4] = size[i];
}
}
template<typename T>
class FloatFAST : public ::testing::Test
{
public:
virtual void SetUp() {}
};
template<typename T>
class FixedFAST : public ::testing::Test
{
public:
virtual void SetUp() {}
};
typedef ::testing::Types<float, double> FloatTestTypes;
typedef ::testing::Types<int, unsigned, short, ushort> FixedTestTypes;
TYPED_TEST_CASE(FloatFAST, FloatTestTypes);
TYPED_TEST_CASE(FixedFAST, FixedTestTypes);
template<typename T>
void fastTest(string pTestFile, bool nonmax)
{
if (noDoubleTests<T>()) return;
if (noImageIOTests()) return;
vector<dim4> inDims;
vector<string> inFiles;
vector<vector<float> > gold;
readImageTests(pTestFile, inDims, inFiles, gold);
size_t testCount = inDims.size();
for (size_t testId=0; testId<testCount; ++testId) {
dim_t nElems = 0;
af_array inArray_f32 = 0;
af_array inArray = 0;
af_features out;
inFiles[testId].insert(0,string(TEST_DIR"/fast/"));
ASSERT_EQ(AF_SUCCESS, af_load_image(&inArray_f32, inFiles[testId].c_str(), false));
ASSERT_EQ(AF_SUCCESS, conv_image<T>(&inArray, inArray_f32));
ASSERT_EQ(AF_SUCCESS, af_fast(&out, inArray, 20.0f, 9, nonmax, 0.05f, 3));
dim_t n = 0;
af_array x, y, score, orientation, size;
ASSERT_EQ(AF_SUCCESS, af_get_features_num(&n, out));
ASSERT_EQ(AF_SUCCESS, af_get_features_xpos(&x, out));
ASSERT_EQ(AF_SUCCESS, af_get_features_ypos(&y, out));
ASSERT_EQ(AF_SUCCESS, af_get_features_score(&score, out));
ASSERT_EQ(AF_SUCCESS, af_get_features_orientation(&orientation, out));
ASSERT_EQ(AF_SUCCESS, af_get_features_size(&size, out));
ASSERT_EQ(AF_SUCCESS, af_get_elements(&nElems, x));
float * outX = new float[gold[0].size()];
float * outY = new float[gold[1].size()];
float * outScore = new float[gold[2].size()];
float * outOrientation = new float[gold[3].size()];
float * outSize = new float[gold[4].size()];
ASSERT_EQ(AF_SUCCESS, af_get_data_ptr((void*)outX, x));
ASSERT_EQ(AF_SUCCESS, af_get_data_ptr((void*)outY, y));
ASSERT_EQ(AF_SUCCESS, af_get_data_ptr((void*)outScore, score));
ASSERT_EQ(AF_SUCCESS, af_get_data_ptr((void*)outOrientation, orientation));
ASSERT_EQ(AF_SUCCESS, af_get_data_ptr((void*)outSize, size));
vector<feat_t> out_feat;
array_to_feat(out_feat, outX, outY, outScore, outOrientation, outSize, n);
vector<feat_t> gold_feat;
array_to_feat(gold_feat, &gold[0].front(), &gold[1].front(), &gold[2].front(), &gold[3].front(), &gold[4].front(), gold[0].size());
std::sort(out_feat.begin(), out_feat.end(), feat_cmp);
std::sort(gold_feat.begin(), gold_feat.end(), feat_cmp);
for (int elIter = 0; elIter < (int)nElems; elIter++) {
ASSERT_EQ(out_feat[elIter].f[0], gold_feat[elIter].f[0]) << "at: " << elIter << std::endl;
ASSERT_EQ(out_feat[elIter].f[1], gold_feat[elIter].f[1]) << "at: " << elIter << std::endl;
ASSERT_LE(fabs(out_feat[elIter].f[2] - gold_feat[elIter].f[2]), 1e-3) << "at: " << elIter << std::endl;
ASSERT_EQ(out_feat[elIter].f[3], gold_feat[elIter].f[3]) << "at: " << elIter << std::endl;
ASSERT_EQ(out_feat[elIter].f[4], gold_feat[elIter].f[4]) << "at: " << elIter << std::endl;
}
ASSERT_EQ(AF_SUCCESS, af_release_array(inArray));
ASSERT_EQ(AF_SUCCESS, af_release_array(inArray_f32));
ASSERT_EQ(AF_SUCCESS, af_release_array(x));
ASSERT_EQ(AF_SUCCESS, af_release_array(y));
ASSERT_EQ(AF_SUCCESS, af_release_array(score));
ASSERT_EQ(AF_SUCCESS, af_release_array(orientation));
ASSERT_EQ(AF_SUCCESS, af_release_array(size));
delete [] outX;
delete [] outY;
delete [] outScore;
delete [] outOrientation;
delete [] outSize;
}
}
#define FLOAT_FAST_INIT(desc, image, nonmax) \
TYPED_TEST(FloatFAST, desc) \
{ \
fastTest<TypeParam>(string(TEST_DIR"/fast/"#image"_float.test"), nonmax); \
}
#define FIXED_FAST_INIT(desc, image, nonmax) \
TYPED_TEST(FixedFAST, desc) \
{ \
fastTest<TypeParam>(string(TEST_DIR"/fast/"#image"_fixed.test"), nonmax); \
}
FLOAT_FAST_INIT(square, square, false);
FLOAT_FAST_INIT(square_nonmax, square_nonmax, true);
FIXED_FAST_INIT(square, square, false);
FIXED_FAST_INIT(square_nonmax, square_nonmax, true);
/////////////////////////////////// CPP ////////////////////////////////
TEST(FloatFAST, CPP)
{
if (noDoubleTests<float>()) return;
if (noImageIOTests()) return;
vector<dim4> inDims;
vector<string> inFiles;
vector<vector<float> > gold;
readImageTests(string(TEST_DIR"/fast/square_nonmax_float.test"), inDims, inFiles, gold);
inFiles[0].insert(0,string(TEST_DIR"/fast/"));
af::array in = af::loadImage(inFiles[0].c_str(), false);
af::features out = fast(in, 20.0f, 9, true, 0.05f, 3);
float * outX = new float[gold[0].size()];
float * outY = new float[gold[1].size()];
float * outScore = new float[gold[2].size()];
float * outOrientation = new float[gold[3].size()];
float * outSize = new float[gold[4].size()];
out.getX().host(outX);
out.getY().host(outY);
out.getScore().host(outScore);
out.getOrientation().host(outOrientation);
out.getSize().host(outSize);
vector<feat_t> out_feat;
array_to_feat(out_feat, outX, outY, outScore, outOrientation, outSize, out.getNumFeatures());
vector<feat_t> gold_feat;
array_to_feat(gold_feat, &gold[0].front(), &gold[1].front(), &gold[2].front(), &gold[3].front(), &gold[4].front(), gold[0].size());
std::sort(out_feat.begin(), out_feat.end(), feat_cmp);
std::sort(gold_feat.begin(), gold_feat.end(), feat_cmp);
for (unsigned elIter = 0; elIter < out.getNumFeatures(); elIter++) {
ASSERT_EQ(out_feat[elIter].f[0], gold_feat[elIter].f[0]) << "at: " << elIter << std::endl;
ASSERT_EQ(out_feat[elIter].f[1], gold_feat[elIter].f[1]) << "at: " << elIter << std::endl;
ASSERT_LE(fabs(out_feat[elIter].f[2] - gold_feat[elIter].f[2]), 1e-3) << "at: " << elIter << std::endl;
ASSERT_EQ(out_feat[elIter].f[3], gold_feat[elIter].f[3]) << "at: " << elIter << std::endl;
ASSERT_EQ(out_feat[elIter].f[4], gold_feat[elIter].f[4]) << "at: " << elIter << std::endl;
}
delete[] outX;
delete[] outY;
delete[] outScore;
delete[] outOrientation;
delete[] outSize;
}
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