optimize memory usage

modules/gpu/src/icf.hpp

@@ -40,11 +40,13 @@
 //
 //M
 
-#include <opencv2/gpu/device/common.hpp>
 
 #ifndef __OPENCV_ICF_HPP__
 #define __OPENCV_ICF_HPP__
 
+#include <opencv2/gpu/device/common.hpp>
+#include <stdio.h>
+
 // #if defined __CUDACC__
 // # define __device __device__ __forceinline__
 // #else
@@ -92,20 +94,27 @@ struct __align__(8) Level //is actually 24 bytes
 
 struct __align__(8) Node
 {
-    // int feature;
     uchar4 rect;
-    float threshold;
+    // ushort channel;
+    uint threshold;
 
-    Node(const uchar4 c, const int t) : rect(c), threshold(t) {}
+    enum { THRESHOLD_MASK = 0x0FFFFFFF };
+
+    Node(const uchar4 r, const uint ch, const uint t) : rect(r), threshold(t + (ch << 28))
+    {
+        // printf("%d\n", t);
+        // printf("[%d %d %d %d] %d, %d\n",rect.x, rect.y, rect.z, rect.w, (int)(threshold >> 28),
+        //     (int)(0x0FFFFFFF & threshold));
+    }
 };
 
-struct __align__(8) Feature
-{
-    int channel;
-    uchar4 rect;
+// struct __align__(8) Feature
+// {
+//     int channel;
+//     uchar4 rect;
 
-    Feature(const int c, const uchar4 r) : channel(c), rect(r) {}
-};
+//     Feature(const int c, const uchar4 r) : channel(c), rect(r) {}
+// };
 }
 }}}
 // struct Cascade

modules/gpu/src/softcascade.cpp

@@ -60,19 +60,10 @@ namespace icf {
     void fillBins(cv::gpu::PtrStepSzb hogluv, const cv::gpu::PtrStepSzf& nangle,
         const int fw, const int fh, const int bins);
     void detect(const PtrStepSzb& levels, const PtrStepSzb& octaves, const PtrStepSzf& stages,
-        const PtrStepSzb& nodes, const PtrStepSzb& features,
-        PtrStepSz<uchar4> objects);
+        const PtrStepSzb& nodes, const PtrStepSzf& leaves, const PtrStepSzi& hogluv, PtrStepSz<uchar4> objects);
 }
 }}}
 
-// namespace {
-//     char *itoa(long i, char* s, int /*dummy_radix*/)
-//     {
-//         sprintf(s, "%ld", i);
-//         return s;
-//     }
-// }
-
 struct cv::gpu::SoftCascade::Filds
 {
 
@@ -97,7 +88,6 @@ struct cv::gpu::SoftCascade::Filds
     GpuMat stages;
     GpuMat nodes;
     GpuMat leaves;
-    GpuMat features;
     GpuMat levels;
 
     // preallocated buffer 640x480x10 for hogluv + 640x480 got gray
@@ -137,7 +127,7 @@ struct cv::gpu::SoftCascade::Filds
     bool fill(const FileNode &root, const float mins, const float maxs);
     void detect(cv::gpu::GpuMat objects, cudaStream_t stream) const
     {
-        device::icf::detect(levels, octaves, stages, nodes, features, objects);
+        device::icf::detect(levels, octaves, stages, nodes, leaves, hogluv, objects);
     }
 
 private:
@@ -216,10 +206,9 @@ inline bool cv::gpu::SoftCascade::Filds::fill(const FileNode &root, const float
         if (fn.empty()) return false;
 
     std::vector<Octave>  voctaves;
-    std::vector<float>        vstages;
+    std::vector<float>   vstages;
     std::vector<Node>    vnodes;
-    std::vector<float>        vleaves;
-    std::vector<Feature> vfeatures;
+    std::vector<float>   vleaves;
     scales.clear();
 
     FileNodeIterator it = fn.begin(), it_end = fn.end();
@@ -245,6 +234,8 @@ inline bool cv::gpu::SoftCascade::Filds::fill(const FileNode &root, const float
         FileNode ffs = fns[SC_FEATURES];
         if (ffs.empty()) return false;
 
+        FileNodeIterator ftrs = ffs.begin();
+
         fns = fns[SC_STAGES];
         if (fn.empty()) return false;
 
@@ -263,10 +254,21 @@ inline bool cv::gpu::SoftCascade::Filds::fill(const FileNode &root, const float
                 FileNodeIterator inIt = fns.begin(), inIt_end = fns.end();
                 for (; inIt != inIt_end;)
                 {
-                    int feature = (int)(*(inIt +=2)++) + feature_offset;
-                    float th = (float)(*(inIt++));
+                    // int feature = (int)(*(inIt +=2)) + feature_offset;
+                    inIt +=3;
+                    // extract feature, Todo:check it
+                    uint th = saturate_cast<uint>((float)(*(inIt++)));
+                    cv::FileNode ftn = (*ftrs)[SC_F_RECT];
+                    cv::FileNodeIterator r_it = ftn.begin();
                     uchar4 rect;
-                    vnodes.push_back(Node(rect, th));
+                    rect.x = saturate_cast<uchar>((int)*(r_it++));
+                    rect.y = saturate_cast<uchar>((int)*(r_it++));
+                    rect.z = saturate_cast<uchar>((int)*(r_it++));
+                    rect.w = saturate_cast<uchar>((int)*(r_it++));
+
+                    uint channel = saturate_cast<uint>((int)(*ftrs)[SC_F_CHANNEL]);
+                    vnodes.push_back(Node(rect, channel, th));
+                    ++ftrs;
                 }
 
                 fns = (*ftr)[SC_LEAF];
@@ -276,19 +278,6 @@ inline bool cv::gpu::SoftCascade::Filds::fill(const FileNode &root, const float
             }
         }
 
-        st = ffs.begin(), st_end = ffs.end();
-        for (; st != st_end; ++st )
-        {
-            cv::FileNode rn = (*st)[SC_F_RECT];
-            cv::FileNodeIterator r_it = rn.begin();
-            uchar4 rect;
-            rect.x = saturate_cast<uchar>((int)*(r_it++));
-            rect.y = saturate_cast<uchar>((int)*(r_it++));
-            rect.z = saturate_cast<uchar>((int)*(r_it++));
-            rect.w = saturate_cast<uchar>((int)*(r_it++));
-            vfeatures.push_back(Feature((int)(*st)[SC_F_CHANNEL], rect));
-        }
-
         feature_offset += octave.stages * 3;
         ++octIndex;
     }
@@ -306,9 +295,6 @@ inline bool cv::gpu::SoftCascade::Filds::fill(const FileNode &root, const float
     leaves.upload(cv::Mat(vleaves).reshape(1,1));
     CV_Assert(!leaves.empty());
 
-    features.upload(cv::Mat(1, vfeatures.size() * sizeof(Feature), CV_8UC1, (uchar*)&(vfeatures[0]) ));
-    CV_Assert(!features.empty());
-
     // compute levels
     calcLevels(voctaves, FRAME_WIDTH, FRAME_HEIGHT, TOTAL_SCALES);
     CV_Assert(!levels.empty());
@@ -425,7 +411,14 @@ bool cv::gpu::SoftCascade::load( const string& filename, const float minScale, c
     return true;
 }
 
-// #define USE_REFERENCE_VALUES
+#define USE_REFERENCE_VALUES
+namespace {
+    char *itoa(long i, char* s, int /*dummy_radix*/)
+    {
+        sprintf(s, "%ld", i);
+        return s;
+    }
+}
 void cv::gpu::SoftCascade::detectMultiScale(const GpuMat& colored, const GpuMat& /*rois*/,
                                 GpuMat& objects, const int /*rejectfactor*/, Stream s)
 {
@@ -438,17 +431,20 @@ void cv::gpu::SoftCascade::detectMultiScale(const GpuMat& colored, const GpuMat&
     Filds& flds = *filds;
 
 #if defined USE_REFERENCE_VALUES
-//     cudaMemset(flds.hogluv.data, 0, flds.hogluv.step * flds.hogluv.rows);
-//     cv::FileStorage imgs("/home/kellan/testInts.xml", cv::FileStorage::READ);
-//     char buff[33];
-
-//     for(int i = 0; i < Filds::HOG_LUV_BINS; ++i)
-//     {
-//         cv::Mat channel;
-//         imgs[std::string("channel") + itoa(i, buff, 10)] >> channel;
-//         GpuMat gchannel(flds.hogluv, cv::Rect(0, 121 * i, 161, 121));
-//         gchannel.upload(channel);
-//     }
+    cudaMemset(flds.hogluv.data, 0, flds.hogluv.step * flds.hogluv.rows);
+
+    cv::FileStorage imgs("/home/kellan/testInts.xml", cv::FileStorage::READ);
+    char buff[33];
+
+    for(int i = 0; i < Filds::HOG_LUV_BINS; ++i)
+    {
+        cv::Mat channel;
+        imgs[std::string("channel") + itoa(i, buff, 10)] >> channel;
+
+        // std::cout << "channel " << i << std::endl << channel << std::endl;
+        GpuMat gchannel(flds.hogluv, cv::Rect(0, 121 * i, 161, 121));
+        gchannel.upload(channel);
+    }
 #else
     GpuMat& plane = flds.plane;
     GpuMat& shrunk = flds.shrunk;