LBP features integrated in CascadeClassifier_GPU

modules/gpu/include/opencv2/gpu/gpu.hpp

@@ -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
 {

modules/gpu/perf/perf_objdetect.cpp

@@ -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);

modules/gpu/src/cuda/lbp.cu

@@ -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);
         }

modules/gpu/test/test_objdetect.cpp

@@ -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