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LBP features integrated in CascadeClassifier_GPU

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marina.kolpakova 2012-07-24 13:51:35 +04:00
parent 2dc93574e1
commit 1b7ad93dc9
5 changed files with 506 additions and 493 deletions
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54
modules/gpu/include/opencv2/gpu/gpu.hpp
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@ -1397,7 +1397,7 @@ public:
};
////////////////////////////////// CascadeClassifier_GPU //////////////////////////////////////////
// The cascade classifier class for object detection.
// The cascade classifier class for object detection: supports old haar and new lbp xlm formats and nvbin for haar cascades olny.
class CV_EXPORTS CascadeClassifier_GPU
{
public:
@ -1407,42 +1407,28 @@ public:
bool empty() const;
bool load(const std::string& filename);
void release();
/* returns number of detected objects */
int detectMultiScale(const GpuMat& image, GpuMat& objectsBuf, double scaleFactor=1.2, int minNeighbors=4, Size minSize=Size());
bool findLargestObject;
bool visualizeInPlace;
Size getClassifierSize() const;
private:
struct CascadeClassifierImpl;
CascadeClassifierImpl* impl;
};
// The cascade classifier class for object detection.
class CV_EXPORTS CascadeClassifier_GPU_LBP
{
public:
CascadeClassifier_GPU_LBP(cv::Size detectionFrameSize = cv::Size());
~CascadeClassifier_GPU_LBP();
bool empty() const;
bool load(const std::string& filename);
void release();
int detectMultiScale(const GpuMat& image, GpuMat& objectsBuf, double scaleFactor = 1.1, int minNeighbors = 4,
cv::Size maxObjectSize = cv::Size()/*, Size minSize = Size()*/);
Size getClassifierSize() const;
void release();
private:
/* returns number of detected objects */
int detectMultiScale(const GpuMat& image, GpuMat& objectsBuf, double scaleFactor = 1.2, int minNeighbors = 4, Size minSize = Size());
bool findLargestObject;
bool visualizeInPlace;
Size getClassifierSize() const;
private:
struct CascadeClassifierImpl;
CascadeClassifierImpl* impl;
};
////////////////////////////////// SURF //////////////////////////////////////////
struct HaarCascade;
struct LbpCascade;
friend class CascadeClassifier_GPU_LBP;
public:
int detectMultiScale(const GpuMat& image, GpuMat& objectsBuf, Size maxObjectSize, Size minSize = Size(), double scaleFactor = 1.1, int minNeighbors = 4);
};
////////////////////////////////// SURF //////////////////////////////////////////
class CV_EXPORTS SURF_GPU
{

2
modules/gpu/perf/perf_objdetect.cpp
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@ -70,7 +70,7 @@ GPU_PERF_TEST_1(LBPClassifier, cv::gpu::DeviceInfo)
cv::gpu::GpuMat img(img_host);
cv::gpu::GpuMat gpu_rects;
cv::gpu::CascadeClassifier_GPU_LBP cascade(img.size());
cv::gpu::CascadeClassifier_GPU cascade;
ASSERT_TRUE(cascade.load(perf::TestBase::getDataPath("gpu/lbpcascade/lbpcascade_frontalface.xml")));
cascade.detectMultiScale(img, gpu_rects);

924
modules/gpu/src/cascadeclassifier.cpp
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File diff suppressed because it is too large Load Diff

1
modules/gpu/src/cuda/lbp.cu
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@ -290,6 +290,7 @@ namespace cv { namespace gpu { namespace device
{
const int block = 128;
int grid = divUp(workAmount, block);
cudaFuncSetCacheConfig(lbp_cascade, cudaFuncCachePreferL1);
Cascade cascade((Stage*)mstages.ptr(), nstages, (ClNode*)mnodes.ptr(), mleaves.ptr(), msubsets.ptr(), (uchar4*)mfeatures.ptr(), subsetSize);
lbp_cascade<<<grid, block>>>(cascade, frameW, frameH, windowW, windowH, initialScale, factor, workAmount, integral.ptr(), integral.step / sizeof(int), objects, classified);
}

18
modules/gpu/test/test_objdetect.cpp
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@ -302,13 +302,13 @@ PARAM_TEST_CASE(LBP_Read_classifier, cv::gpu::DeviceInfo, int)
TEST_P(LBP_Read_classifier, Accuracy)
{
cv::gpu::CascadeClassifier_GPU_LBP 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)
@ -344,7 +344,7 @@ TEST_P(LBP_classify, Accuracy)
for (; it != rects.end(); ++it)
cv::rectangle(markedImage, *it, CV_RGB(0, 0, 255));
cv::gpu::CascadeClassifier_GPU_LBP gpuClassifier;
cv::gpu::CascadeClassifier_GPU gpuClassifier;
ASSERT_TRUE(gpuClassifier.load(classifierXmlPath));
cv::gpu::GpuMat gpu_rects;
@ -352,23 +352,23 @@ TEST_P(LBP_classify, Accuracy)
int count = gpuClassifier.detectMultiScale(tested, gpu_rects);
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;
#endif
std::cout << r.x << " " << r.y << " " << r.width << " " << r.height << std::endl;
cv::rectangle(markedImage, r , CV_RGB(255, 0, 0));
#endif
}
#if defined (LOG_CASCADE_STATISTIC)
cv::imshow("Res", markedImage); cv::waitKey();
cv::imshow("Res", markedImage); cv::waitKey();
#endif
}
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