Chiebot-Mirror
/
opencv
8
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

fixed unused warnings

Browse Source
pull/13/merge
marina.kolpakova 13 years ago
parent 66eb96d719
commit 9c13b84e35
7 changed files with 65 additions and 57 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 3
      modules/gpu/perf/perf_core.cpp
  2. 3
      modules/gpu/perf_cpu/perf_core.cpp
  3. 21
      modules/gpu/src/calib3d.cpp
  4. 8
      modules/gpu/src/cascadeclassifier.cpp
  5. 65
      modules/gpu/src/match_template.cpp
  6. 1
      modules/gpu/src/split_merge.cpp
  7. 21
      modules/gpu/test/test_objdetect.cpp

3
modules/gpu/perf/perf_core.cpp
Unescape View File

@ -1607,6 +1607,7 @@ GPU_PERF_TEST(Norm, cv::gpu::DeviceInfo, cv::Size, MatDepth, NormType)
{
dst = cv::gpu::norm(src, normType, buf);
}
(void)dst;
}
INSTANTIATE_TEST_CASE_P(Core, Norm, testing::Combine(
@ -1642,6 +1643,7 @@ GPU_PERF_TEST(NormDiff, cv::gpu::DeviceInfo, cv::Size, NormType)
{
dst = cv::gpu::norm(src1, src2, normType);
}
(void)dst;
}
INSTANTIATE_TEST_CASE_P(Core, NormDiff, testing::Combine(
@ -1829,6 +1831,7 @@ GPU_PERF_TEST(CountNonZero, cv::gpu::DeviceInfo, cv::Size, MatDepth)
{
dst = cv::gpu::countNonZero(src, buf);
}
(void)dst;
}
INSTANTIATE_TEST_CASE_P(Core, CountNonZero, testing::Combine(

3
modules/gpu/perf_cpu/perf_core.cpp
Unescape View File

@ -1229,6 +1229,7 @@ GPU_PERF_TEST(Norm, cv::gpu::DeviceInfo, cv::Size, MatDepth, NormType)
{
dst = cv::norm(src, normType);
}
(void)dst;
}
INSTANTIATE_TEST_CASE_P(Core, Norm, testing::Combine(
@ -1259,6 +1260,7 @@ GPU_PERF_TEST(NormDiff, cv::gpu::DeviceInfo, cv::Size, NormType)
{
dst = cv::norm(src1, src2, normType);
}
(void)dst;
}
INSTANTIATE_TEST_CASE_P(Core, NormDiff, testing::Combine(
@ -1338,6 +1340,7 @@ GPU_PERF_TEST(CountNonZero, cv::gpu::DeviceInfo, cv::Size, MatDepth)
{
dst = cv::countNonZero(src);
}
(void)dst;
}
INSTANTIATE_TEST_CASE_P(Core, CountNonZero, testing::Combine(

21
modules/gpu/src/calib3d.cpp
Unescape View File

@ -56,14 +56,14 @@ void cv::gpu::solvePnPRansac(const Mat&, const Mat&, const Mat&, const Mat&, Mat
#else
namespace cv { namespace gpu { namespace device
namespace cv { namespace gpu { namespace device
{
namespace transform_points
namespace transform_points
{
void call(const DevMem2D_<float3> src, const float* rot, const float* transl, DevMem2D_<float3> dst, cudaStream_t stream);
}
namespace project_points
namespace project_points
{
void call(const DevMem2D_<float3> src, const float* rot, const float* transl, const float* proj, DevMem2D_<float2> dst, cudaStream_t stream);
}
@ -154,11 +154,11 @@ namespace
class TransformHypothesesGenerator
{
public:
TransformHypothesesGenerator(const Mat& object_, const Mat& image_, const Mat& dist_coef_,
const Mat& camera_mat_, int num_points_, int subset_size_,
TransformHypothesesGenerator(const Mat& object_, const Mat& image_, const Mat& dist_coef_,
const Mat& camera_mat_, int num_points_, int subset_size_,
Mat rot_matrices_, Mat transl_vectors_)
: object(&object_), image(&image_), dist_coef(&dist_coef_), camera_mat(&camera_mat_),
num_points(num_points_), subset_size(subset_size_), rot_matrices(rot_matrices_),
: object(&object_), image(&image_), dist_coef(&dist_coef_), camera_mat(&camera_mat_),
num_points(num_points_), subset_size(subset_size_), rot_matrices(rot_matrices_),
transl_vectors(transl_vectors_) {}
void operator()(const BlockedRange& range) const
@ -211,9 +211,10 @@ namespace
void cv::gpu::solvePnPRansac(const Mat& object, const Mat& image, const Mat& camera_mat,
const Mat& dist_coef, Mat& rvec, Mat& tvec, bool use_extrinsic_guess,
int num_iters, float max_dist, int min_inlier_count,
int num_iters, float max_dist, int min_inlier_count,
vector<int>* inliers)
{
(void)min_inlier_count;
CV_Assert(object.rows == 1 && object.cols > 0 && object.type() == CV_32FC3);
CV_Assert(image.rows == 1 && image.cols > 0 && image.type() == CV_32FC2);
CV_Assert(object.cols == image.cols);
@ -236,7 +237,7 @@ void cv::gpu::solvePnPRansac(const Mat& object, const Mat& image, const Mat& cam
Mat transl_vectors(1, num_iters * 3, CV_32F);
// Generate set of hypotheses using small subsets of the input data
TransformHypothesesGenerator body(object, image_normalized, empty_dist_coef, eye_camera_mat,
TransformHypothesesGenerator body(object, image_normalized, empty_dist_coef, eye_camera_mat,
num_points, subset_size, rot_matrices, transl_vectors);
parallel_for(BlockedRange(0, num_iters), body);
@ -246,7 +247,7 @@ void cv::gpu::solvePnPRansac(const Mat& object, const Mat& image, const Mat& cam
GpuMat d_hypothesis_scores(1, num_iters, CV_32S);
solve_pnp_ransac::computeHypothesisScores(
num_iters, num_points, rot_matrices.ptr<float>(), transl_vectors.ptr<float3>(),
d_object.ptr<float3>(), d_image_normalized.ptr<float2>(), max_dist * max_dist,
d_object.ptr<float3>(), d_image_normalized.ptr<float2>(), max_dist * max_dist,
d_hypothesis_scores.ptr<int>());
// Find the best hypothesis index

8
modules/gpu/src/cascadeclassifier.cpp
Unescape View File

@ -143,7 +143,7 @@ public:
}
unsigned int process(const GpuMat& image, GpuMat& objectsBuf, float scaleFactor, int minNeighbors,
bool findLargestObject, bool visualizeInPlace, cv::Size minSize, cv::Size maxObjectSize)
bool findLargestObject, bool visualizeInPlace, cv::Size minSize, cv::Size /*maxObjectSize*/)
{
CV_Assert( scaleFactor > 1 && image.depth() == CV_8U);
@ -380,12 +380,12 @@ public:
LbpCascade(){}
virtual ~LbpCascade(){}
virtual unsigned int process(const GpuMat& image, GpuMat& objects, float scaleFactor, int groupThreshold, bool findLargestObject,
bool visualizeInPlace, cv::Size minObjectSize, cv::Size maxObjectSize)
virtual unsigned int process(const GpuMat& image, GpuMat& objects, float scaleFactor, int groupThreshold, bool /*findLargestObject*/,
bool /*visualizeInPlace*/, cv::Size minObjectSize, cv::Size maxObjectSize)
{
CV_Assert(scaleFactor > 1 && image.depth() == CV_8U);
const int defaultObjSearchNum = 100;
// const int defaultObjSearchNum = 100;
const float grouping_eps = 0.2f;
if( !objects.empty() && objects.depth() == CV_32S)

65
modules/gpu/src/match_template.cpp
Unescape View File

@ -52,9 +52,9 @@ void cv::gpu::matchTemplate(const GpuMat&, const GpuMat&, GpuMat&, int, Stream&)
#else
namespace cv { namespace gpu { namespace device
namespace cv { namespace gpu { namespace device
{
namespace match_template
namespace match_template
{
void matchTemplateNaive_CCORR_8U(const DevMem2Db image, const DevMem2Db templ, DevMem2Df result, int cn, cudaStream_t stream);
void matchTemplateNaive_CCORR_32F(const DevMem2Db image, const DevMem2Db templ, DevMem2Df result, int cn, cudaStream_t stream);
@ -71,47 +71,47 @@ namespace cv { namespace gpu { namespace device
void matchTemplatePrepared_CCOFF_8U(int w, int h, const DevMem2D_<unsigned int> image_sum, unsigned int templ_sum, DevMem2Df result, cudaStream_t stream);
void matchTemplatePrepared_CCOFF_8UC2(
int w, int h,
const DevMem2D_<unsigned int> image_sum_r,
const DevMem2D_<unsigned int> image_sum_g,
const DevMem2D_<unsigned int> image_sum_r,
const DevMem2D_<unsigned int> image_sum_g,
unsigned int templ_sum_r,
unsigned int templ_sum_g,
unsigned int templ_sum_g,
DevMem2Df result, cudaStream_t stream);
void matchTemplatePrepared_CCOFF_8UC3(
int w, int h,
const DevMem2D_<unsigned int> image_sum_r,
int w, int h,
const DevMem2D_<unsigned int> image_sum_r,
const DevMem2D_<unsigned int> image_sum_g,
const DevMem2D_<unsigned int> image_sum_b,
unsigned int templ_sum_r,
unsigned int templ_sum_g,
unsigned int templ_sum_b,
unsigned int templ_sum_r,
unsigned int templ_sum_g,
unsigned int templ_sum_b,
DevMem2Df result, cudaStream_t stream);
void matchTemplatePrepared_CCOFF_8UC4(
int w, int h,
const DevMem2D_<unsigned int> image_sum_r,
int w, int h,
const DevMem2D_<unsigned int> image_sum_r,
const DevMem2D_<unsigned int> image_sum_g,
const DevMem2D_<unsigned int> image_sum_b,
const DevMem2D_<unsigned int> image_sum_a,
unsigned int templ_sum_r,
unsigned int templ_sum_g,
unsigned int templ_sum_b,
unsigned int templ_sum_a,
unsigned int templ_sum_r,
unsigned int templ_sum_g,
unsigned int templ_sum_b,
unsigned int templ_sum_a,
DevMem2Df result, cudaStream_t stream);
void matchTemplatePrepared_CCOFF_NORMED_8U(
int w, int h, const DevMem2D_<unsigned int> image_sum,
int w, int h, const DevMem2D_<unsigned int> image_sum,
const DevMem2D_<unsigned long long> image_sqsum,
unsigned int templ_sum, unsigned long long templ_sqsum,
DevMem2Df result, cudaStream_t stream);
void matchTemplatePrepared_CCOFF_NORMED_8UC2(
int w, int h,
int w, int h,
const DevMem2D_<unsigned int> image_sum_r, const DevMem2D_<unsigned long long> image_sqsum_r,
const DevMem2D_<unsigned int> image_sum_g, const DevMem2D_<unsigned long long> image_sqsum_g,
unsigned int templ_sum_r, unsigned long long templ_sqsum_r,
unsigned int templ_sum_g, unsigned long long templ_sqsum_g,
DevMem2Df result, cudaStream_t stream);
void matchTemplatePrepared_CCOFF_NORMED_8UC3(
int w, int h,
int w, int h,
const DevMem2D_<unsigned int> image_sum_r, const DevMem2D_<unsigned long long> image_sqsum_r,
const DevMem2D_<unsigned int> image_sum_g, const DevMem2D_<unsigned long long> image_sqsum_g,
const DevMem2D_<unsigned int> image_sum_b, const DevMem2D_<unsigned long long> image_sqsum_b,
@ -120,7 +120,7 @@ namespace cv { namespace gpu { namespace device
unsigned int templ_sum_b, unsigned long long templ_sqsum_b,
DevMem2Df result, cudaStream_t stream);
void matchTemplatePrepared_CCOFF_NORMED_8UC4(
int w, int h,
int w, int h,
const DevMem2D_<unsigned int> image_sum_r, const DevMem2D_<unsigned long long> image_sqsum_r,
const DevMem2D_<unsigned int> image_sum_g, const DevMem2D_<unsigned long long> image_sqsum_g,
const DevMem2D_<unsigned int> image_sum_b, const DevMem2D_<unsigned long long> image_sqsum_b,
@ -131,7 +131,7 @@ namespace cv { namespace gpu { namespace device
unsigned int templ_sum_a, unsigned long long templ_sqsum_a,
DevMem2Df result, cudaStream_t stream);
void normalize_8U(int w, int h, const DevMem2D_<unsigned long long> image_sqsum,
void normalize_8U(int w, int h, const DevMem2D_<unsigned long long> image_sqsum,
unsigned long long templ_sqsum, DevMem2Df result, int cn, cudaStream_t stream);
void extractFirstChannel_32F(const DevMem2Db image, DevMem2Df result, int cn, cudaStream_t stream);
@ -140,17 +140,17 @@ namespace cv { namespace gpu { namespace device
using namespace ::cv::gpu::device::match_template;
namespace
namespace
{
// Evaluates optimal template's area threshold. If
// template's area is less than the threshold, we use naive match
// Evaluates optimal template's area threshold. If
// template's area is less than the threshold, we use naive match
// template version, otherwise FFT-based (if available)
int getTemplateThreshold(int method, int depth)
{
switch (method)
{
case CV_TM_CCORR:
case CV_TM_CCORR:
if (depth == CV_32F) return 250;
if (depth == CV_8U) return 300;
break;
@ -162,10 +162,10 @@ namespace
return 0;
}
void matchTemplate_CCORR_32F(
const GpuMat& image, const GpuMat& templ, GpuMat& result, MatchTemplateBuf &buf, Stream& stream)
{
{
result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
if (templ.size().area() < getTemplateThreshold(CV_TM_CCORR, CV_32F))
{
@ -223,10 +223,11 @@ namespace
normalize_8U(templ.cols, templ.rows, buf.image_sqsums[0], templ_sqsum, result, image.channels(), StreamAccessor::getStream(stream));
}
void matchTemplate_SQDIFF_32F(
const GpuMat& image, const GpuMat& templ, GpuMat& result, MatchTemplateBuf &buf, Stream& stream)
{
(void)buf;
result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
matchTemplateNaive_SQDIFF_32F(image, templ, result, image.channels(), StreamAccessor::getStream(stream));
}
@ -362,7 +363,7 @@ namespace
{
case 2:
matchTemplatePrepared_CCOFF_NORMED_8UC2(
templ.cols, templ.rows,
templ.cols, templ.rows,
buf.image_sums[0], buf.image_sqsums[0],
buf.image_sums[1], buf.image_sqsums[1],
(unsigned int)templ_sum[0], (unsigned long long)templ_sqsum[0],
@ -371,7 +372,7 @@ namespace
break;
case 3:
matchTemplatePrepared_CCOFF_NORMED_8UC3(
templ.cols, templ.rows,
templ.cols, templ.rows,
buf.image_sums[0], buf.image_sqsums[0],
buf.image_sums[1], buf.image_sqsums[1],
buf.image_sums[2], buf.image_sqsums[2],
@ -382,7 +383,7 @@ namespace
break;
case 4:
matchTemplatePrepared_CCOFF_NORMED_8UC4(
templ.cols, templ.rows,
templ.cols, templ.rows,
buf.image_sums[0], buf.image_sqsums[0],
buf.image_sums[1], buf.image_sqsums[1],
buf.image_sums[2], buf.image_sqsums[2],
@ -391,7 +392,7 @@ namespace
(unsigned int)templ_sum[1], (unsigned long long)templ_sqsum[1],
(unsigned int)templ_sum[2], (unsigned long long)templ_sqsum[2],
(unsigned int)templ_sum[3], (unsigned long long)templ_sqsum[3],
result, StreamAccessor::getStream(stream));
result, StreamAccessor::getStream(stream));
break;
default:
CV_Error(CV_StsBadArg, "matchTemplate: unsupported number of channels");

1
modules/gpu/src/split_merge.cpp
Unescape View File

@ -119,7 +119,6 @@ namespace
int depth = src.depth();
int num_channels = src.channels();
Size size = src.size();
if (depth == CV_64F)
{

21
modules/gpu/test/test_objdetect.cpp
Unescape View File

@ -302,13 +302,13 @@ PARAM_TEST_CASE(LBP_Read_classifier, cv::gpu::DeviceInfo, int)
TEST_P(LBP_Read_classifier, Accuracy)
{
cv::gpu::CascadeClassifier_GPU classifier;
cv::gpu::CascadeClassifier_GPU classifier;
std::string classifierXmlPath = std::string(cvtest::TS::ptr()->get_data_path()) + "lbpcascade/lbpcascade_frontalface.xml";
ASSERT_TRUE(classifier.load(classifierXmlPath));
}
INSTANTIATE_TEST_CASE_P(GPU_ObjDetect, LBP_Read_classifier,
testing::Combine(ALL_DEVICES, testing::Values<int>(0)));
INSTANTIATE_TEST_CASE_P(GPU_ObjDetect, LBP_Read_classifier,
testing::Combine(ALL_DEVICES, testing::Values<int>(0)));
PARAM_TEST_CASE(LBP_classify, cv::gpu::DeviceInfo, int)
@ -344,31 +344,32 @@ TEST_P(LBP_classify, Accuracy)
for (; it != rects.end(); ++it)
cv::rectangle(markedImage, *it, CV_RGB(0, 0, 255));
cv::gpu::CascadeClassifier_GPU gpuClassifier;
cv::gpu::CascadeClassifier_GPU gpuClassifier;
ASSERT_TRUE(gpuClassifier.load(classifierXmlPath));
cv::gpu::GpuMat gpu_rects;
cv::gpu::GpuMat tested(grey);
int count = gpuClassifier.detectMultiScale(tested, gpu_rects);
#if defined (LOG_CASCADE_STATISTIC)
cv::Mat downloaded(gpu_rects);
const cv::Rect* faces = downloaded.ptr<cv::Rect>();
const cv::Rect* faces = downloaded.ptr<cv::Rect>();
for (int i = 0; i < count; i++)
{
cv::Rect r = faces[i];
#if defined (LOG_CASCADE_STATISTIC)
std::cout << r.x << " " << r.y << " " << r.width << " " << r.height << std::endl;
std::cout << r.x << " " << r.y << " " << r.width << " " << r.height << std::endl;
cv::rectangle(markedImage, r , CV_RGB(255, 0, 0));
#endif
}
#endif
#if defined (LOG_CASCADE_STATISTIC)
cv::imshow("Res", markedImage); cv::waitKey();
cv::imshow("Res", markedImage); cv::waitKey();
#endif
(void)count;
}
INSTANTIATE_TEST_CASE_P(GPU_ObjDetect, LBP_classify,
testing::Combine(ALL_DEVICES, testing::Values<int>(0)));
testing::Combine(ALL_DEVICES, testing::Values<int>(0)));
} // namespace

Write Preview
Loading…
Cancel
Save