Cleanup old TBB-related guards

modules/dpm/CMakeLists.txt

 set(the_description "Object Detection")
 
-#uncomment the following line to enable parallel computing
-#add_definitions(-DHAVE_TBB)
-
 ocv_define_module(dpm opencv_core opencv_imgproc opencv_objdetect OPTIONAL opencv_highgui WRAP python)
 
 ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4512) # disable warning on Win64

modules/dpm/samples/cascade_detect_camera.cpp

@@ -97,16 +97,6 @@ int main( int argc, char** argv )
         return -1;
     }
 
-#ifdef HAVE_TBB
-    cout << "Running with TBB" << endl;
-#else
-#ifdef _OPENMP
-    cout << "Running with OpenMP" << endl;
-#else
-    cout << "Running without OpenMP and without TBB" << endl;
-#endif
-#endif
-
     Mat frame;
     namedWindow("DPM Cascade Detection", 1);
     // the color of the rectangle

modules/dpm/samples/cascade_detect_sequence.cpp

@@ -113,16 +113,6 @@ int main( int argc, char** argv )
     if ( !readImageLists(image_list, imgFileList) )
         return -1;
 
-#ifdef HAVE_TBB
-    cout << "Running with TBB" << endl;
-#else
-#ifdef _OPENMP
-    cout << "Running with OpenMP" << endl;
-#else
-    cout << "Running without OpenMP and without TBB" << endl;
-#endif
-#endif
-
     cv::Ptr<DPMDetector> detector = \
     DPMDetector::create(vector<string>(1, model_path));
 

modules/dpm/src/dpm_cascade.cpp

@@ -220,36 +220,12 @@ void DPMCascade::computeRootPCAScores(vector< vector< Mat > > &rootScores)
     for (int comp = 0; comp < model.numComponents; comp++)
     {
         rootScores[comp].resize(nlevels);
-#ifdef HAVE_TBB // parallel computing
         ParalComputeRootPCAScores paralTask(pcaPyramid, model.rootPCAFilters[comp],
                 model.pcaDim, rootScores[comp]);
         parallel_for_(Range(interval, nlevels), paralTask);
-#else
-#ifdef _OPENMP
-#pragma omp parallel for
-#endif
-        for (int level = interval; level < nlevels; level++)
-        {
-            Mat feat = pcaPyramid[level];
-            Mat filter = model.rootPCAFilters[comp];
-
-            // compute size of output
-            int height = feat.rows - filter.rows + 1;
-            int width = (feat.cols - filter.cols) / model.pcaDim + 1;
-
-            if (height < 1 || width < 1)
-                CV_Error(CV_StsBadArg,
-                        "Invalid input, filter size should be smaller than feature size.");
-
-            Mat result = Mat::zeros(Size(width, height), CV_64F);
-            convolutionEngine.convolve(feat, filter, model.pcaDim, result);
-            rootScores[comp][level] = result;
-        }
-#endif
     }
 }
 
-#ifdef HAVE_TBB
 ParalComputeRootPCAScores::ParalComputeRootPCAScores(
         const vector< Mat > &pcaPyrad,
         const Mat &f,
@@ -279,7 +255,6 @@ void ParalComputeRootPCAScores::operator() (const Range &range) const
         scores[level] = result;
     }
 }
-#endif
 
 void DPMCascade::process( vector< vector<double> > &dets)
 {

modules/dpm/src/dpm_cascade.hpp

@@ -128,7 +128,6 @@ class DPMCascade
         std::vector< std::vector<double> > detect(Mat &image);
 };
 
-#ifdef HAVE_TBB
 /** @brief This class convolves root PCA feature pyramid
  * and root PCA filters in parallel using Intel Threading
  * Building Blocks (TBB)
@@ -151,7 +150,6 @@ class ParalComputeRootPCAScores : public ParallelLoopBody
         int pcaDim;
         std::vector< Mat > &scores;
 };
-#endif
 } // namespace dpm
 } // namespace cv
 

modules/dpm/src/dpm_feature.cpp

@@ -58,65 +58,11 @@ Feature::Feature (PyramidParameter p):params(p)
 
 void Feature::computeFeaturePyramid(const Mat &imageM, vector< Mat > &pyramid)
 {
-#ifdef HAVE_TBB
     ParalComputePyramid paralTask(imageM, pyramid, params);
     paralTask.initialize();
-    // perform parallel computing
     parallel_for_(Range(0, params.interval), paralTask);
-#else
-    CV_Assert(params.interval > 0);
-    // scale factor between two levels
-    params.sfactor = pow(2.0, 1.0/params.interval);
-    const Size_<double> imSize = imageM.size();
-    params.maxScale = 1 + (int)floor(log(min(imSize.width, imSize.height)/
-                (float)(params.binSize*5.0))/log(params.sfactor));
-
-    if (params.maxScale < params.interval)
-    {
-        CV_Error(CV_StsBadArg, "The image is too small to create a pyramid");
-        return;
-    }
-
-    pyramid.resize(params.maxScale + params.interval);
-    params.scales.resize(params.maxScale + params.interval);
-
-#ifdef _OPENMP
-#pragma omp parallel for
-#endif
-    for (int i = 0; i < params.interval; i++)
-    {
-        const double scale = (double)(1.0f/pow(params.sfactor, i));
-        Mat imScaled;
-        resize(imageM, imScaled, imSize * scale);
-        // First octave at twice the image resolution
-        computeHOG32D(imScaled, pyramid[i], params.binSize/2,
-                params.padx + 1, params.pady + 1);
-
-        params.scales[i] = 2*scale;
-
-        // Second octave at the original resolution
-        if (i + params.interval <= params.maxScale)
-            computeHOG32D(imScaled, pyramid[i+params.interval],
-                    params.binSize, params.padx + 1, params.pady + 1);
-
-        params.scales[i+params.interval] = scale;
-
-        // Remaining octaves
-        for ( int j = i + params.interval; j < params.maxScale; j += params.interval)
-        {
-            Mat imScaled2;
-            Size_<double> imScaledSize = imScaled.size();
-            resize(imScaled, imScaled2, imScaledSize*0.5);
-            imScaled = imScaled2;
-            computeHOG32D(imScaled2, pyramid[j+params.interval],
-                    params.binSize, params.padx + 1, params.pady + 1);
-            params.scales[j+params.interval] = params.scales[j]*0.5;
-        }
-    }
-#endif
 }
 
-#ifdef HAVE_TBB
 ParalComputePyramid::ParalComputePyramid(const Mat &inputImage, \
         vector< Mat > &outputPyramid,\
         PyramidParameter &p):
@@ -177,7 +123,6 @@ void ParalComputePyramid::operator() (const Range &range) const
         }
     }
 }
-#endif
 
 void Feature::computeHOG32D(const Mat &imageM, Mat &featM, const int sbin, const int pad_x, const int pad_y)
 {

modules/dpm/src/dpm_feature.hpp

@@ -137,7 +137,6 @@ class Feature
 
 };
 
-#ifdef HAVE_TBB
 /** @brief This class computes feature pyramid in parallel
  * using Intel Threading Building Blocks (TBB)
  */
@@ -165,7 +164,6 @@ class ParalComputePyramid : public ParallelLoopBody
         // pyramid parameters
         PyramidParameter &params;
 };
-#endif
 
 } // namespace dpm
 } // namespace cv