From 8e1918e86eb5fc7a85960a37d2452883032d1230 Mon Sep 17 00:00:00 2001 From: Vadim Pisarevsky Date: Thu, 6 Mar 2014 18:04:04 +0400 Subject: [PATCH 1/6] added OpenCL-accelerated(?) FAST; for now the tests fail :( --- modules/features2d/src/fast.cpp | 79 ++ modules/features2d/src/opencl/fast.cl | 1229 +++++++++++++++++++++++++ 2 files changed, 1308 insertions(+) create mode 100644 modules/features2d/src/opencl/fast.cl diff --git a/modules/features2d/src/fast.cpp b/modules/features2d/src/fast.cpp index b3335a0672..d995ec3d70 100644 --- a/modules/features2d/src/fast.cpp +++ b/modules/features2d/src/fast.cpp @@ -43,6 +43,7 @@ The references are: #include "precomp.hpp" #include "fast_score.hpp" +#include "opencl_kernels.hpp" #if defined _MSC_VER # pragma warning( disable : 4127) @@ -249,8 +250,85 @@ void FAST_t(InputArray _img, std::vector& keypoints, int threshold, bo } } + +static bool ocl_FAST( InputArray _img, std::vector& keypoints, + int threshold, bool nonmax_suppression, int maxKeypoints ) +{ + UMat img = _img.getUMat(); + if( img.cols < 7 || img.rows < 7 ) + return false; + size_t globalsize[] = { img.cols-6, img.rows-6 }; + + ocl::Kernel fastKptKernel("FAST_findKeypoints", ocl::features2d::fast_oclsrc); + if (fastKptKernel.empty()) + return false; + + UMat kp1(1, maxKeypoints*2+1, CV_32S), score; + + UMat utemp(kp1, Rect(0,0,1,1)); + utemp.setTo(Scalar::all(0)); + + if( nonmax_suppression ) + { + score.create(img.size(), CV_8U); + score.setTo(Scalar::all(0)); + } + else + score = img; // initialize score with some non-empty value + + if( !fastKptKernel.args(ocl::KernelArg::ReadOnly(img), + ocl::KernelArg::WriteOnlyNoSize(score), + ocl::KernelArg::PtrReadWrite(kp1), + nonmax_suppression ? 1 : 0, + maxKeypoints, threshold).run(2, globalsize, 0, true)) + return false; + + Mat mcounter; + utemp.copyTo(mcounter); + int i, counter = mcounter.at(0); + + keypoints.clear(); + if( !nonmax_suppression ) + { + Mat m; + kp1(Rect(0, 0, counter*2+1, 1)).copyTo(m); + const Point* pt = (const Point*)(m.ptr() + 1); + for( i = 0; i < counter; i++ ) + keypoints.push_back(KeyPoint((float)pt[i].x, (float)pt[i].y, 7.f, -1, 1.f)); + } + else + { + UMat kp2(1, maxKeypoints*3+1, CV_32S); + utemp = kp2(Rect(0,0,1,1)); + utemp.setTo(Scalar::all(0)); + + ocl::Kernel fastNMSKernel("FAST_nonmaxSupression", ocl::features2d::fast_oclsrc); + if (fastNMSKernel.empty()) + return false; + + if( !fastNMSKernel.args(ocl::KernelArg::PtrReadOnly(kp1), + ocl::KernelArg::PtrReadWrite(kp2), + ocl::KernelArg::ReadOnlyNoSize(score), + counter, maxKeypoints).run(2, globalsize, 0, true)) + return false; + + Mat m; + kp2(Rect(0, 0, counter*3+1, 1)).copyTo(m); + const Point3i* pt = (const Point3i*)(m.ptr() + 1); + for( i = 0; i < counter; i++ ) + keypoints.push_back(KeyPoint((float)pt[i].x, (float)pt[i].y, 7.f, -1, (float)pt[i].z)); + } + + return true; +} + + void FAST(InputArray _img, std::vector& keypoints, int threshold, bool nonmax_suppression, int type) { + if( ocl::useOpenCL() && /*_img.isUMat() &&*/ type == FastFeatureDetector::TYPE_9_16 && + ocl_FAST(_img, keypoints, threshold, nonmax_suppression, 10000)) + return; + switch(type) { case FastFeatureDetector::TYPE_5_8: FAST_t<8>(_img, keypoints, threshold, nonmax_suppression); @@ -268,6 +346,7 @@ void FAST(InputArray _img, std::vector& keypoints, int threshold, bool } } + void FAST(InputArray _img, std::vector& keypoints, int threshold, bool nonmax_suppression) { FAST(_img, keypoints, threshold, nonmax_suppression, FastFeatureDetector::TYPE_9_16); diff --git a/modules/features2d/src/opencl/fast.cl b/modules/features2d/src/opencl/fast.cl new file mode 100644 index 0000000000..404580ec64 --- /dev/null +++ b/modules/features2d/src/opencl/fast.cl @@ -0,0 +1,1229 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2013, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +// Authors: +// * Peter Andreas Entschev, peter@entschev.com +// +//M*/ + +__constant uchar c_table[] = +{ + 0x80, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 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0x80, 0x00, 0x80, + 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, + 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, + 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, + 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, + 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, + 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, + 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, + 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, + 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, + 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, + 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, + 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0xc0, + 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, + 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, + 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, + 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, + 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, + 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, + 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, + 0x80, 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, + 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, + 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, + 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0xaa, 0xaa, 0xaa, + 0xaa, 0xaa, 0xaa, 0xaa, 0xaa, 0xaa, 0xaa, 0xaa, 0xaa, + 0xaa, 0xaa, 0xaa, 0xaa, 0xff, 0xff, 0xff, 0xff, 0xff, + 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, + 0xff, 0xff +}; + + +// 1 -> v > x + th +// 2 -> v < x - th +// 0 -> x - th <= v <= x + th +__inline int diffType(const int v, const int x, const int th) +{ + const int diff = x - v; + return (int)(diff < -th) + ((int)(diff > th) << 1); +} + +#ifdef USE_STANDARD_POPCOUNT +#define popCount popcount +#else +// For OpenCL 1.1 compatibility +__inline int popCount(int x) { + x = x - ((x >> 1) & 0x55555555); + x = (x & 0x33333333) + ((x >> 2) & 0x33333333); + x = (x + (x >> 4)) & 0x0F0F0F0F; + x = x + (x >> 8); + x = x + (x >> 16); + + return x & 0x0000003F; +} +#endif + +void calcMask( + const uint C[4], + const int v, + const int th, + int* mask1, + int* mask2) +{ + *mask1 = 0; + *mask2 = 0; + + int d1, d2; + + d1 = diffType(v, C[0] & 0xff, th); + d2 = diffType(v, C[2] & 0xff, th); + + if ((d1 | d2) == 0) + return; + + *mask1 |= (d1 & 1) << 0; + *mask2 |= ((d1 & 2) >> 1) << 0; + + *mask1 |= (d2 & 1) << 8; + *mask2 |= ((d2 & 2) >> 1) << 8; + + d1 = diffType(v, C[1] & 0xff, th); + d2 = diffType(v, C[3] & 0xff, th); + + if ((d1 | d2) == 0) + return; + + *mask1 |= (d1 & 1) << 4; + *mask2 |= ((d1 & 2) >> 1) << 4; + + *mask1 |= (d2 & 1) << 12; + *mask2 |= ((d2 & 2) >> 1) << 12; + + d1 = diffType(v, (C[0] >> (2 * 8)) & 0xff, th); + d2 = diffType(v, (C[2] >> (2 * 8)) & 0xff, th); + + if ((d1 | d2) == 0) + return; + + *mask1 |= (d1 & 1) << 2; + *mask2 |= ((d1 & 2) >> 1) << 2; + + *mask1 |= (d2 & 1) << 10; + *mask2 |= ((d2 & 2) >> 1) << 10; + + d1 = diffType(v, (C[1] >> (2 * 8)) & 0xff, th); + d2 = diffType(v, (C[3] >> (2 * 8)) & 0xff, th); + + if ((d1 | d2) == 0) + return; + + *mask1 |= (d1 & 1) << 6; + *mask2 |= ((d1 & 2) >> 1) << 6; + + *mask1 |= (d2 & 1) << 14; + *mask2 |= ((d2 & 2) >> 1) << 14; + + d1 = diffType(v, (C[0] >> (1 * 8)) & 0xff, th); + d2 = diffType(v, (C[2] >> (1 * 8)) & 0xff, th); + + /*if ((d1 | d2) == 0) + return;*/ + + *mask1 |= (d1 & 1) << 1; + *mask2 |= ((d1 & 2) >> 1) << 1; + + *mask1 |= (d2 & 1) << 9; + *mask2 |= ((d2 & 2) >> 1) << 9; + + d1 = diffType(v, (C[0] >> (3 * 8)) & 0xff, th); + d2 = diffType(v, (C[2] >> (3 * 8)) & 0xff, th); + + /*if ((d1 | d2) == 0) + return;*/ + + *mask1 |= (d1 & 1) << 3; + *mask2 |= ((d1 & 2) >> 1) << 3; + + *mask1 |= (d2 & 1) << 11; + *mask2 |= ((d2 & 2) >> 1) << 11; + + d1 = diffType(v, (C[1] >> (1 * 8)) & 0xff, th); + d2 = diffType(v, (C[3] >> (1 * 8)) & 0xff, th); + + /*if ((d1 | d2) == 0) + return;*/ + + *mask1 |= (d1 & 1) << 5; + *mask2 |= ((d1 & 2) >> 1) << 5; + + *mask1 |= (d2 & 1) << 13; + *mask2 |= ((d2 & 2) >> 1) << 13; + + d1 = diffType(v, (C[1] >> (3 * 8)) & 0xff, th); + d2 = diffType(v, (C[3] >> (3 * 8)) & 0xff, th); + + *mask1 |= (d1 & 1) << 7; + *mask2 |= ((d1 & 2) >> 1) << 7; + + *mask1 |= (d2 & 1) << 15; + *mask2 |= ((d2 & 2) >> 1) << 15; +} + +// 1 -> v > x + th +// 2 -> v < x - th +// 0 -> not a keypoint +__inline bool isKeyPoint(int mask1, int mask2) +{ + // TODO: Use OpenCL's popcount() function if OpenCL version >= 1.2 + return (popCount(mask1) > 8 && (c_table[(mask1 >> 3) - 63] & (1 << (mask1 & 7)))) || + (popCount(mask2) > 8 && (c_table[(mask2 >> 3) - 63] & (1 << (mask2 & 7)))); +} + +int cornerScore(const uint C[4], const int v, const int threshold) +{ + // binary search in [threshold + 1, 255] + + int min = threshold + 1; + int max = 255; + + while (min <= max) + { + const int mid = (min + max) >> 1; + + int mask1 = 0; + int mask2 = 0; + + calcMask(C, v, mid, &mask1, &mask2); + + int isKp = (int)isKeyPoint(mask1, mask2); + + min = isKp * (mid + 1) + (isKp ^ 1) * min; + max = (isKp ^ 1) * (mid - 1) + isKp * max; + } + + return min - 1; +} + +/////////////////////////////////////////////////////////////////////////// +// calcKeypoints + +__kernel +void FAST_findKeypoints( + __global const uchar * _img, int c_img_step, int c_img_offset, + int c_img_rows, int c_img_cols, + __global uchar * score, int score_step, int score_offset, + volatile __global int* kpLoc, int calcScore, int maxKeypoints, int threshold ) +{ + int j = get_global_id(0) + 3; + int i = get_global_id(1) + 3; + + if (i < c_img_rows - 3 && j < c_img_cols - 3) + { + __global const uchar* img = _img + c_img_offset; + int v; + uint C[4] = {0,0,0,0}; + + C[2] |= (uint)img[(i - 3) * c_img_step + j - 1] << 8; + C[2] |= (uint)img[(i - 3) * c_img_step + j]; + C[1] |= (uint)img[(i - 3) * c_img_step + j + 1] << (3 * 8); + + C[2] |= (uint)img[(i - 2) * c_img_step + j - 2] << (2 * 8); + C[1] |= (uint)img[(i - 2) * c_img_step + j + 2] << (2 * 8); + + C[2] |= (uint)img[(i - 1) * c_img_step + j - 3] << (3 * 8); + C[1] |= (uint)img[(i - 1) * c_img_step + j + 3] << 8; + + C[3] |= (uint)img[i * c_img_step + j - 3]; + v = (int) img[i * c_img_step + j]; + C[1] |= (uint)img[i * c_img_step + j + 3]; + + int d1 = diffType(v, C[1] & 0xff, threshold); + int d2 = diffType(v, C[3] & 0xff, threshold); + + if ((d1 | d2) == 0) + return; + + C[3] |= (uint)img[(i + 1) * c_img_step + j - 3] << 8; + C[0] |= (uint)img[(i + 1) * c_img_step + j + 3] << (3 * 8); + + C[3] |= (uint)img[(i + 2) * c_img_step + j - 2] << (2 * 8); + C[0] |= (uint)img[(i + 2) * c_img_step + j + 2] << (2 * 8); + + C[3] |= (uint)img[(i + 3) * c_img_step + j - 1] << (3 * 8); + C[0] |= (uint)img[(i + 3) * c_img_step + j]; + C[0] |= (uint)img[(i + 3) * c_img_step + j + 1] << 8; + + int mask1 = 0; + int mask2 = 0; + + calcMask(C, v, threshold, &mask1, &mask2); + + if (isKeyPoint(mask1, mask2)) + { + if (calcScore) score[i * score_step + j] = (uchar)cornerScore(C, v, threshold); + int idx = atomic_inc(kpLoc); + + if (idx < maxKeypoints) + { + kpLoc[1 + 2*idx] = j; + kpLoc[2 + 2*idx] = i; + } + } + } +} + +/////////////////////////////////////////////////////////////////////////// +// nonmaxSupression + +__kernel +void FAST_nonmaxSupression( + __global int* kpLocIn, volatile __global int* kpLocOut, + __global const uchar * _score, int c_score_step, int score_offset, + int counter, int maxKeypoints) +{ + const int idx = get_global_id(0); + + if (idx < counter) + { + __global const uchar* score = _score + score_offset; + int loc_x = kpLocIn[1 + 2*idx]; + int loc_y = kpLocIn[2 + 2*idx]; + + int s = score[loc_y * c_score_step + loc_x]; + + bool ismax = + s > score[(loc_y - 1) * c_score_step + loc_x - 1] && + s > score[(loc_y - 1) * c_score_step + loc_x ] && + s > score[(loc_y - 1) * c_score_step + loc_x + 1] && + + s > score[loc_y * c_score_step + loc_x - 1] && + s > score[loc_y * c_score_step + loc_x + 1] && + + s > score[(loc_y + 1) * c_score_step + loc_x - 1] && + s > score[(loc_y + 1) * c_score_step + loc_x ] && + s > score[(loc_y + 1) * c_score_step + loc_x + 1]; + + if (!ismax) + { + int new_idx = atomic_inc(kpLocOut); + if( new_idx < maxKeypoints ) + { + kpLocOut[1 + 3*new_idx] = loc_x; + kpLocOut[2 + 3*new_idx] = loc_y; + kpLocOut[3 + 3*new_idx] = s; + } + } + } +} From 06c138bd644f0c218fb899df90375849802616d2 Mon Sep 17 00:00:00 2001 From: Vadim Pisarevsky Date: Fri, 7 Mar 2014 18:18:10 +0400 Subject: [PATCH 2/6] make the correctness test pass --- modules/features2d/src/fast.cpp | 39 +- modules/features2d/src/opencl/fast.cl | 1289 +++---------------------- 2 files changed, 137 insertions(+), 1191 deletions(-) diff --git a/modules/features2d/src/fast.cpp b/modules/features2d/src/fast.cpp index d995ec3d70..7020727e07 100644 --- a/modules/features2d/src/fast.cpp +++ b/modules/features2d/src/fast.cpp @@ -250,6 +250,11 @@ void FAST_t(InputArray _img, std::vector& keypoints, int threshold, bo } } +template +struct cmp_pt +{ + bool operator ()(const pt& a, const pt& b) const { return a.y < b.y || (a.y == b.y && a.x < b.x); } +}; static bool ocl_FAST( InputArray _img, std::vector& keypoints, int threshold, bool nonmax_suppression, int maxKeypoints ) @@ -265,8 +270,8 @@ static bool ocl_FAST( InputArray _img, std::vector& keypoints, UMat kp1(1, maxKeypoints*2+1, CV_32S), score; - UMat utemp(kp1, Rect(0,0,1,1)); - utemp.setTo(Scalar::all(0)); + UMat ucounter1(kp1, Rect(0,0,1,1)); + ucounter1.setTo(Scalar::all(0)); if( nonmax_suppression ) { @@ -284,10 +289,15 @@ static bool ocl_FAST( InputArray _img, std::vector& keypoints, return false; Mat mcounter; - utemp.copyTo(mcounter); + ucounter1.copyTo(mcounter); int i, counter = mcounter.at(0); + counter = std::min(counter, maxKeypoints); keypoints.clear(); + + if( counter == 0 ) + return true; + if( !nonmax_suppression ) { Mat m; @@ -299,24 +309,29 @@ static bool ocl_FAST( InputArray _img, std::vector& keypoints, else { UMat kp2(1, maxKeypoints*3+1, CV_32S); - utemp = kp2(Rect(0,0,1,1)); - utemp.setTo(Scalar::all(0)); + UMat ucounter2 = kp2(Rect(0,0,1,1)); + ucounter2.setTo(Scalar::all(0)); ocl::Kernel fastNMSKernel("FAST_nonmaxSupression", ocl::features2d::fast_oclsrc); if (fastNMSKernel.empty()) return false; + size_t globalsize_nms[] = { counter }; if( !fastNMSKernel.args(ocl::KernelArg::PtrReadOnly(kp1), ocl::KernelArg::PtrReadWrite(kp2), ocl::KernelArg::ReadOnlyNoSize(score), - counter, maxKeypoints).run(2, globalsize, 0, true)) + counter, counter).run(1, globalsize_nms, 0, true)) return false; - Mat m; - kp2(Rect(0, 0, counter*3+1, 1)).copyTo(m); - const Point3i* pt = (const Point3i*)(m.ptr() + 1); - for( i = 0; i < counter; i++ ) - keypoints.push_back(KeyPoint((float)pt[i].x, (float)pt[i].y, 7.f, -1, (float)pt[i].z)); + Mat m2; + kp2(Rect(0, 0, counter*3+1, 1)).copyTo(m2); + Point3i* pt2 = (Point3i*)(m2.ptr() + 1); + int newcounter = std::min(m2.at(0), counter); + + std::sort(pt2, pt2 + newcounter, cmp_pt()); + + for( i = 0; i < newcounter; i++ ) + keypoints.push_back(KeyPoint((float)pt2[i].x, (float)pt2[i].y, 7.f, -1, (float)pt2[i].z)); } return true; @@ -325,7 +340,7 @@ static bool ocl_FAST( InputArray _img, std::vector& keypoints, void FAST(InputArray _img, std::vector& keypoints, int threshold, bool nonmax_suppression, int type) { - if( ocl::useOpenCL() && /*_img.isUMat() &&*/ type == FastFeatureDetector::TYPE_9_16 && + if( ocl::useOpenCL() && _img.isUMat() && type == FastFeatureDetector::TYPE_9_16 && ocl_FAST(_img, keypoints, threshold, nonmax_suppression, 10000)) return; diff --git a/modules/features2d/src/opencl/fast.cl b/modules/features2d/src/opencl/fast.cl index 404580ec64..3dd0d2e609 100644 --- a/modules/features2d/src/opencl/fast.cl +++ b/modules/features2d/src/opencl/fast.cl @@ -1,1185 +1,125 @@ -/*M/////////////////////////////////////////////////////////////////////////////////////// -// -// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. -// -// By downloading, copying, installing or using the software you agree to this license. -// If you do not agree to this license, do not download, install, -// copy or use the software. -// -// -// License Agreement -// For Open Source Computer Vision Library -// -// Copyright (C) 2013, OpenCV Foundation, all rights reserved. -// Third party copyrights are property of their respective owners. -// -// Redistribution and use in source and binary forms, with or without modification, -// are permitted provided that the following conditions are met: -// -// * Redistribution's of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// -// * Redistribution's in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// -// * The name of the copyright holders may not be used to endorse or promote products -// derived from this software without specific prior written permission. -// -// This software is provided by the copyright holders and contributors "as is" and -// any express or implied warranties, including, but not limited to, the implied -// warranties of merchantability and fitness for a particular purpose are disclaimed. -// In no event shall the Intel Corporation or contributors be liable for any direct, -// indirect, incidental, special, exemplary, or consequential damages -// (including, but not limited to, procurement of substitute goods or services; -// loss of use, data, or profits; or business interruption) however caused -// and on any theory of liability, whether in contract, strict liability, -// or tort (including negligence or otherwise) arising in any way out of -// the use of this software, even if advised of the possibility of such damage. -// -// Authors: -// * Peter Andreas Entschev, peter@entschev.com -// -//M*/ +// OpenCL port of the FAST corner detector. +// Copyright (C) 2014, Itseez Inc. See the license at http://opencv.org -__constant uchar c_table[] = +inline int cornerScore(__global const uchar* img, int step, int threshold) { - 0x80, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0xc0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x80, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 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0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, - 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0xaa, 0xaa, 0xaa, - 0xaa, 0xaa, 0xaa, 0xaa, 0xaa, 0xaa, 0xaa, 0xaa, 0xaa, - 0xaa, 0xaa, 0xaa, 0xaa, 0xff, 0xff, 0xff, 0xff, 0xff, - 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, - 0xff, 0xff -}; + int k, tofs, v = img[0], a0 = threshold, b0; + int d[16]; + #define LOAD2(idx, ofs) \ + tofs = ofs; d[idx] = (short)(v - img[tofs]); d[idx+8] = (short)(v - img[-tofs]) + LOAD2(0, 3); + LOAD2(1, -step+3); + LOAD2(2, -step*2+2); + LOAD2(3, -step*3+1); + LOAD2(4, -step*3); + LOAD2(5, -step*3-1); + LOAD2(6, -step*2-2); + LOAD2(7, -step-3); - -// 1 -> v > x + th -// 2 -> v < x - th -// 0 -> x - th <= v <= x + th -__inline int diffType(const int v, const int x, const int th) -{ - const int diff = x - v; - return (int)(diff < -th) + ((int)(diff > th) << 1); -} - -#ifdef USE_STANDARD_POPCOUNT -#define popCount popcount -#else -// For OpenCL 1.1 compatibility -__inline int popCount(int x) { - x = x - ((x >> 1) & 0x55555555); - x = (x & 0x33333333) + ((x >> 2) & 0x33333333); - x = (x + (x >> 4)) & 0x0F0F0F0F; - x = x + (x >> 8); - x = x + (x >> 16); - - return x & 0x0000003F; -} -#endif - -void calcMask( - const uint C[4], - const int v, - const int th, - int* mask1, - int* mask2) -{ - *mask1 = 0; - *mask2 = 0; - - int d1, d2; - - d1 = diffType(v, C[0] & 0xff, th); - d2 = diffType(v, C[2] & 0xff, th); - - if ((d1 | d2) == 0) - return; - - *mask1 |= (d1 & 1) << 0; - *mask2 |= ((d1 & 2) >> 1) << 0; - - *mask1 |= (d2 & 1) << 8; - *mask2 |= ((d2 & 2) >> 1) << 8; - - d1 = diffType(v, C[1] & 0xff, th); - d2 = diffType(v, C[3] & 0xff, th); - - if ((d1 | d2) == 0) - return; - - *mask1 |= (d1 & 1) << 4; - *mask2 |= ((d1 & 2) >> 1) << 4; - - *mask1 |= (d2 & 1) << 12; - *mask2 |= ((d2 & 2) >> 1) << 12; - - d1 = diffType(v, (C[0] >> (2 * 8)) & 0xff, th); - d2 = diffType(v, (C[2] >> (2 * 8)) & 0xff, th); - - if ((d1 | d2) == 0) - return; - - *mask1 |= (d1 & 1) << 2; - *mask2 |= ((d1 & 2) >> 1) << 2; - - *mask1 |= (d2 & 1) << 10; - *mask2 |= ((d2 & 2) >> 1) << 10; - - d1 = diffType(v, (C[1] >> (2 * 8)) & 0xff, th); - d2 = diffType(v, (C[3] >> (2 * 8)) & 0xff, th); - - if ((d1 | d2) == 0) - return; - - *mask1 |= (d1 & 1) << 6; - *mask2 |= ((d1 & 2) >> 1) << 6; - - *mask1 |= (d2 & 1) << 14; - *mask2 |= ((d2 & 2) >> 1) << 14; - - d1 = diffType(v, (C[0] >> (1 * 8)) & 0xff, th); - d2 = diffType(v, (C[2] >> (1 * 8)) & 0xff, th); - - /*if ((d1 | d2) == 0) - return;*/ - - *mask1 |= (d1 & 1) << 1; - *mask2 |= ((d1 & 2) >> 1) << 1; - - *mask1 |= (d2 & 1) << 9; - *mask2 |= ((d2 & 2) >> 1) << 9; - - d1 = diffType(v, (C[0] >> (3 * 8)) & 0xff, th); - d2 = diffType(v, (C[2] >> (3 * 8)) & 0xff, th); - - /*if ((d1 | d2) == 0) - return;*/ - - *mask1 |= (d1 & 1) << 3; - *mask2 |= ((d1 & 2) >> 1) << 3; - - *mask1 |= (d2 & 1) << 11; - *mask2 |= ((d2 & 2) >> 1) << 11; - - d1 = diffType(v, (C[1] >> (1 * 8)) & 0xff, th); - d2 = diffType(v, (C[3] >> (1 * 8)) & 0xff, th); - - /*if ((d1 | d2) == 0) - return;*/ - - *mask1 |= (d1 & 1) << 5; - *mask2 |= ((d1 & 2) >> 1) << 5; - - *mask1 |= (d2 & 1) << 13; - *mask2 |= ((d2 & 2) >> 1) << 13; - - d1 = diffType(v, (C[1] >> (3 * 8)) & 0xff, th); - d2 = diffType(v, (C[3] >> (3 * 8)) & 0xff, th); - - *mask1 |= (d1 & 1) << 7; - *mask2 |= ((d1 & 2) >> 1) << 7; - - *mask1 |= (d2 & 1) << 15; - *mask2 |= ((d2 & 2) >> 1) << 15; -} - -// 1 -> v > x + th -// 2 -> v < x - th -// 0 -> not a keypoint -__inline bool isKeyPoint(int mask1, int mask2) -{ - // TODO: Use OpenCL's popcount() function if OpenCL version >= 1.2 - return (popCount(mask1) > 8 && (c_table[(mask1 >> 3) - 63] & (1 << (mask1 & 7)))) || - (popCount(mask2) > 8 && (c_table[(mask2 >> 3) - 63] & (1 << (mask2 & 7)))); -} - -int cornerScore(const uint C[4], const int v, const int threshold) -{ - // binary search in [threshold + 1, 255] - - int min = threshold + 1; - int max = 255; - - while (min <= max) + #pragma unroll + for( k = 0; k < 16; k += 2 ) { - const int mid = (min + max) >> 1; - - int mask1 = 0; - int mask2 = 0; - - calcMask(C, v, mid, &mask1, &mask2); - - int isKp = (int)isKeyPoint(mask1, mask2); - - min = isKp * (mid + 1) + (isKp ^ 1) * min; - max = (isKp ^ 1) * (mid - 1) + isKp * max; + int a = min((int)d[(k+1)&15], (int)d[(k+2)&15]); + a = min(a, (int)d[(k+3)&15]); + a = min(a, (int)d[(k+4)&15]); + a = min(a, (int)d[(k+5)&15]); + a = min(a, (int)d[(k+6)&15]); + a = min(a, (int)d[(k+7)&15]); + a = min(a, (int)d[(k+8)&15]); + a0 = max(a0, min(a, (int)d[k&15])); + a0 = max(a0, min(a, (int)d[(k+9)&15])); } - return min - 1; -} + b0 = -a0; + #pragma unroll + for( k = 0; k < 16; k += 2 ) + { + int b = max((int)d[(k+1)&15], (int)d[(k+2)&15]); + b = max(b, (int)d[(k+3)&15]); + b = max(b, (int)d[(k+4)&15]); + b = max(b, (int)d[(k+5)&15]); + b = max(b, (int)d[(k+6)&15]); + b = max(b, (int)d[(k+7)&15]); + b = max(b, (int)d[(k+8)&15]); -/////////////////////////////////////////////////////////////////////////// -// calcKeypoints + b0 = min(b0, max(b, (int)d[k])); + b0 = min(b0, max(b, (int)d[(k+9)&15])); + } + + return -b0-1; +} __kernel void FAST_findKeypoints( - __global const uchar * _img, int c_img_step, int c_img_offset, - int c_img_rows, int c_img_cols, + __global const uchar * _img, int step, int img_offset, + int img_rows, int img_cols, __global uchar * score, int score_step, int score_offset, - volatile __global int* kpLoc, int calcScore, int maxKeypoints, int threshold ) + volatile __global int* kp_loc, int calc_score, + int max_keypoints, int threshold ) { int j = get_global_id(0) + 3; int i = get_global_id(1) + 3; - if (i < c_img_rows - 3 && j < c_img_cols - 3) + if (i < img_rows - 3 && j < img_cols - 3) { - __global const uchar* img = _img + c_img_offset; - int v; - uint C[4] = {0,0,0,0}; + __global const uchar* img = _img + mad24(i, step, j + img_offset); + int v = img[0], t0 = v - threshold, t1 = v + threshold; + int k, tofs, v0, v1; + int m0 = 0, m1 = 0; - C[2] |= (uint)img[(i - 3) * c_img_step + j - 1] << 8; - C[2] |= (uint)img[(i - 3) * c_img_step + j]; - C[1] |= (uint)img[(i - 3) * c_img_step + j + 1] << (3 * 8); + #define UPDATE_MASK(idx, ofs) \ + tofs = ofs; v0 = img[tofs]; v1 = img[-tofs]; \ + m0 |= ((v0 < t0) << idx) | ((v1 < t0) << (8 + idx)); \ + m1 |= ((v0 > t1) << idx) | ((v1 > t1) << (8 + idx)) - C[2] |= (uint)img[(i - 2) * c_img_step + j - 2] << (2 * 8); - C[1] |= (uint)img[(i - 2) * c_img_step + j + 2] << (2 * 8); - - C[2] |= (uint)img[(i - 1) * c_img_step + j - 3] << (3 * 8); - C[1] |= (uint)img[(i - 1) * c_img_step + j + 3] << 8; - - C[3] |= (uint)img[i * c_img_step + j - 3]; - v = (int) img[i * c_img_step + j]; - C[1] |= (uint)img[i * c_img_step + j + 3]; - - int d1 = diffType(v, C[1] & 0xff, threshold); - int d2 = diffType(v, C[3] & 0xff, threshold); - - if ((d1 | d2) == 0) + UPDATE_MASK(0, 3); + if( (m0 | m1) == 0 ) return; - C[3] |= (uint)img[(i + 1) * c_img_step + j - 3] << 8; - C[0] |= (uint)img[(i + 1) * c_img_step + j + 3] << (3 * 8); + UPDATE_MASK(2, -step*2+2); + UPDATE_MASK(4, -step*3); + UPDATE_MASK(6, -step*2-2); - C[3] |= (uint)img[(i + 2) * c_img_step + j - 2] << (2 * 8); - C[0] |= (uint)img[(i + 2) * c_img_step + j + 2] << (2 * 8); + #define EVEN_MASK (1+4+16+64) - C[3] |= (uint)img[(i + 3) * c_img_step + j - 1] << (3 * 8); - C[0] |= (uint)img[(i + 3) * c_img_step + j]; - C[0] |= (uint)img[(i + 3) * c_img_step + j + 1] << 8; + if( ((m0 | (m0 >> 8)) & EVEN_MASK) != EVEN_MASK && + ((m1 | (m1 >> 8)) & EVEN_MASK) != EVEN_MASK ) + return; - int mask1 = 0; - int mask2 = 0; + UPDATE_MASK(1, -step+3); + UPDATE_MASK(3, -step*3+1); + UPDATE_MASK(5, -step*3-1); + UPDATE_MASK(7, -step-3); + if( ((m0 | (m0 >> 8)) & 255) != 255 && + ((m1 | (m1 >> 8)) & 255) != 255 ) + return; - calcMask(C, v, threshold, &mask1, &mask2); + m0 |= m0 << 16; + m1 |= m1 << 16; + + #define CHECK0(i) ((m0 & (511 << i)) == (511 << i)) + #define CHECK1(i) ((m1 & (511 << i)) == (511 << i)) + + if( CHECK0(0) + CHECK0(1) + CHECK0(2) + CHECK0(3) + + CHECK0(4) + CHECK0(5) + CHECK0(6) + CHECK0(7) + + CHECK0(8) + CHECK0(9) + CHECK0(10) + CHECK0(11) + + CHECK0(12) + CHECK0(13) + CHECK0(14) + CHECK0(15) + + + CHECK1(0) + CHECK1(1) + CHECK1(2) + CHECK1(3) + + CHECK1(4) + CHECK1(5) + CHECK1(6) + CHECK1(7) + + CHECK1(8) + CHECK1(9) + CHECK1(10) + CHECK1(11) + + CHECK1(12) + CHECK1(13) + CHECK1(14) + CHECK1(15) == 0 ) + return; - if (isKeyPoint(mask1, mask2)) { - if (calcScore) score[i * score_step + j] = (uchar)cornerScore(C, v, threshold); - int idx = atomic_inc(kpLoc); - - if (idx < maxKeypoints) + int idx = atomic_inc(kp_loc); + if( idx < max_keypoints ) { - kpLoc[1 + 2*idx] = j; - kpLoc[2 + 2*idx] = i; + kp_loc[1 + 2*idx] = j; + kp_loc[2 + 2*idx] = i; } + if(calc_score) + score[mad24(i, score_step, score_offset+j)] = cornerScore(img, step, threshold); } } } @@ -1189,40 +129,31 @@ void FAST_findKeypoints( __kernel void FAST_nonmaxSupression( - __global int* kpLocIn, volatile __global int* kpLocOut, - __global const uchar * _score, int c_score_step, int score_offset, - int counter, int maxKeypoints) + __global const int* kp_in, volatile __global int* kp_out, + __global const uchar * _score, int step, int score_offset, + int counter, int max_keypoints) { const int idx = get_global_id(0); if (idx < counter) { - __global const uchar* score = _score + score_offset; - int loc_x = kpLocIn[1 + 2*idx]; - int loc_y = kpLocIn[2 + 2*idx]; + int x = kp_in[1 + 2*idx]; + int y = kp_in[2 + 2*idx]; - int s = score[loc_y * c_score_step + loc_x]; + __global const uchar* score = _score + mad24(y, step, x + score_offset); + int s = score[0]; - bool ismax = - s > score[(loc_y - 1) * c_score_step + loc_x - 1] && - s > score[(loc_y - 1) * c_score_step + loc_x ] && - s > score[(loc_y - 1) * c_score_step + loc_x + 1] && - - s > score[loc_y * c_score_step + loc_x - 1] && - s > score[loc_y * c_score_step + loc_x + 1] && - - s > score[(loc_y + 1) * c_score_step + loc_x - 1] && - s > score[(loc_y + 1) * c_score_step + loc_x ] && - s > score[(loc_y + 1) * c_score_step + loc_x + 1]; - - if (!ismax) + if( (s > (int)score[1]) + (s > (int)score[-1]) + + (s > (int)score[-step]) + (s > (int)score[step]) + + (s > (int)score[-step-1]) + (s > (int)score[-step+1]) + + (s > (int)score[step-1]) + (s > (int)score[step+1]) == 8 ) { - int new_idx = atomic_inc(kpLocOut); - if( new_idx < maxKeypoints ) + int new_idx = atomic_inc(kp_out); + if( new_idx < max_keypoints ) { - kpLocOut[1 + 3*new_idx] = loc_x; - kpLocOut[2 + 3*new_idx] = loc_y; - kpLocOut[3 + 3*new_idx] = s; + kp_out[1 + 3*new_idx] = x; + kp_out[2 + 3*new_idx] = y; + kp_out[3 + 3*new_idx] = s; } } } From efdfca7a112d118868f5ea0ac653182ccbde14d8 Mon Sep 17 00:00:00 2001 From: Vadim Pisarevsky Date: Fri, 7 Mar 2014 18:55:45 +0400 Subject: [PATCH 3/6] do not use the large "score" buffer; now without non-max suppression OpenCL FAST is pretty efficient --- modules/features2d/src/fast.cpp | 20 ++++++------------ modules/features2d/src/opencl/fast.cl | 30 ++++++++++++++------------- 2 files changed, 22 insertions(+), 28 deletions(-) diff --git a/modules/features2d/src/fast.cpp b/modules/features2d/src/fast.cpp index 7020727e07..004ebb3f8c 100644 --- a/modules/features2d/src/fast.cpp +++ b/modules/features2d/src/fast.cpp @@ -268,23 +268,13 @@ static bool ocl_FAST( InputArray _img, std::vector& keypoints, if (fastKptKernel.empty()) return false; - UMat kp1(1, maxKeypoints*2+1, CV_32S), score; + UMat kp1(1, maxKeypoints*2+1, CV_32S); UMat ucounter1(kp1, Rect(0,0,1,1)); ucounter1.setTo(Scalar::all(0)); - if( nonmax_suppression ) - { - score.create(img.size(), CV_8U); - score.setTo(Scalar::all(0)); - } - else - score = img; // initialize score with some non-empty value - if( !fastKptKernel.args(ocl::KernelArg::ReadOnly(img), - ocl::KernelArg::WriteOnlyNoSize(score), ocl::KernelArg::PtrReadWrite(kp1), - nonmax_suppression ? 1 : 0, maxKeypoints, threshold).run(2, globalsize, 0, true)) return false; @@ -319,7 +309,7 @@ static bool ocl_FAST( InputArray _img, std::vector& keypoints, size_t globalsize_nms[] = { counter }; if( !fastNMSKernel.args(ocl::KernelArg::PtrReadOnly(kp1), ocl::KernelArg::PtrReadWrite(kp2), - ocl::KernelArg::ReadOnlyNoSize(score), + ocl::KernelArg::ReadOnly(img), counter, counter).run(1, globalsize_nms, 0, true)) return false; @@ -340,9 +330,10 @@ static bool ocl_FAST( InputArray _img, std::vector& keypoints, void FAST(InputArray _img, std::vector& keypoints, int threshold, bool nonmax_suppression, int type) { - if( ocl::useOpenCL() && _img.isUMat() && type == FastFeatureDetector::TYPE_9_16 && + double t = (double)getTickCount(); + if( ocl::useOpenCL() && /*_img.isUMat() &&*/ type == FastFeatureDetector::TYPE_9_16 && ocl_FAST(_img, keypoints, threshold, nonmax_suppression, 10000)) - return; + ; switch(type) { case FastFeatureDetector::TYPE_5_8: @@ -359,6 +350,7 @@ void FAST(InputArray _img, std::vector& keypoints, int threshold, bool FAST_t<16>(_img, keypoints, threshold, nonmax_suppression); break; } + printf("time=%.2fms\n", ((double)getTickCount() - t)*1000./getTickFrequency()); } diff --git a/modules/features2d/src/opencl/fast.cl b/modules/features2d/src/opencl/fast.cl index 3dd0d2e609..84ca39ac7f 100644 --- a/modules/features2d/src/opencl/fast.cl +++ b/modules/features2d/src/opencl/fast.cl @@ -1,9 +1,9 @@ // OpenCL port of the FAST corner detector. // Copyright (C) 2014, Itseez Inc. See the license at http://opencv.org -inline int cornerScore(__global const uchar* img, int step, int threshold) +inline int cornerScore(__global const uchar* img, int step) { - int k, tofs, v = img[0], a0 = threshold, b0; + int k, tofs, v = img[0], a0 = 0, b0; int d[16]; #define LOAD2(idx, ofs) \ tofs = ofs; d[idx] = (short)(v - img[tofs]); d[idx+8] = (short)(v - img[-tofs]) @@ -53,8 +53,7 @@ __kernel void FAST_findKeypoints( __global const uchar * _img, int step, int img_offset, int img_rows, int img_cols, - __global uchar * score, int score_step, int score_offset, - volatile __global int* kp_loc, int calc_score, + volatile __global int* kp_loc, int max_keypoints, int threshold ) { int j = get_global_id(0) + 3; @@ -118,8 +117,6 @@ void FAST_findKeypoints( kp_loc[1 + 2*idx] = j; kp_loc[2 + 2*idx] = i; } - if(calc_score) - score[mad24(i, score_step, score_offset+j)] = cornerScore(img, step, threshold); } } } @@ -130,8 +127,8 @@ void FAST_findKeypoints( __kernel void FAST_nonmaxSupression( __global const int* kp_in, volatile __global int* kp_out, - __global const uchar * _score, int step, int score_offset, - int counter, int max_keypoints) + __global const uchar * _img, int step, int img_offset, + int rows, int cols, int counter, int max_keypoints) { const int idx = get_global_id(0); @@ -139,14 +136,19 @@ void FAST_nonmaxSupression( { int x = kp_in[1 + 2*idx]; int y = kp_in[2 + 2*idx]; + __global const uchar* img = _img + mad24(y, step, x + img_offset); - __global const uchar* score = _score + mad24(y, step, x + score_offset); - int s = score[0]; + int s = cornerScore(img, step); - if( (s > (int)score[1]) + (s > (int)score[-1]) + - (s > (int)score[-step]) + (s > (int)score[step]) + - (s > (int)score[-step-1]) + (s > (int)score[-step+1]) + - (s > (int)score[step-1]) + (s > (int)score[step+1]) == 8 ) + if( (x < 4 || s > cornerScore(img-1, step)) + + (y < 4 || s > cornerScore(img-step, step)) != 2 ) + return; + if( (x >= cols - 4 || s > cornerScore(img+1, step)) + + (y >= rows - 4 || s > cornerScore(img+step, step)) + + (x < 4 || y < 4 || s > cornerScore(img-step-1, step)) + + (x >= cols - 4 || y < 4 || s > cornerScore(img-step+1, step)) + + (x < 4 || y >= rows - 4 || s > cornerScore(img+step-1, step)) + + (x >= cols - 4 || y >= rows - 4 || s > cornerScore(img+step+1, step)) == 6) { int new_idx = atomic_inc(kp_out); if( new_idx < max_keypoints ) From 3e854fa6e5e790cdabf3d53d4ef5d10e799414bc Mon Sep 17 00:00:00 2001 From: Vadim Pisarevsky Date: Thu, 13 Mar 2014 22:56:53 +0400 Subject: [PATCH 4/6] finished OpenCL port of ORB --- modules/features2d/perf/perf_orb.cpp | 4 +- modules/features2d/src/fast.cpp | 18 +- modules/features2d/src/opencl/orb.cl | 254 +++++++++ modules/features2d/src/orb.cpp | 781 ++++++++++++++++----------- 4 files changed, 744 insertions(+), 313 deletions(-) create mode 100644 modules/features2d/src/opencl/orb.cl diff --git a/modules/features2d/perf/perf_orb.cpp b/modules/features2d/perf/perf_orb.cpp index 63de12e253..1c181c45ec 100644 --- a/modules/features2d/perf/perf_orb.cpp +++ b/modules/features2d/perf/perf_orb.cpp @@ -28,7 +28,7 @@ PERF_TEST_P(orb, detect, testing::Values(ORB_IMAGES)) TEST_CYCLE() detector(frame, mask, points); sort(points.begin(), points.end(), comparators::KeypointGreater()); - SANITY_CHECK_KEYPOINTS(points); + SANITY_CHECK_KEYPOINTS(points, 1e-5); } PERF_TEST_P(orb, extract, testing::Values(ORB_IMAGES)) @@ -72,6 +72,6 @@ PERF_TEST_P(orb, full, testing::Values(ORB_IMAGES)) TEST_CYCLE() detector(frame, mask, points, descriptors, false); perf::sort(points, descriptors); - SANITY_CHECK_KEYPOINTS(points); + SANITY_CHECK_KEYPOINTS(points, 1e-5); SANITY_CHECK(descriptors); } diff --git a/modules/features2d/src/fast.cpp b/modules/features2d/src/fast.cpp index 004ebb3f8c..beca7d6ec8 100644 --- a/modules/features2d/src/fast.cpp +++ b/modules/features2d/src/fast.cpp @@ -330,8 +330,7 @@ static bool ocl_FAST( InputArray _img, std::vector& keypoints, void FAST(InputArray _img, std::vector& keypoints, int threshold, bool nonmax_suppression, int type) { - double t = (double)getTickCount(); - if( ocl::useOpenCL() && /*_img.isUMat() &&*/ type == FastFeatureDetector::TYPE_9_16 && + if( ocl::useOpenCL() && _img.isUMat() && type == FastFeatureDetector::TYPE_9_16 && ocl_FAST(_img, keypoints, threshold, nonmax_suppression, 10000)) ; @@ -350,7 +349,6 @@ void FAST(InputArray _img, std::vector& keypoints, int threshold, bool FAST_t<16>(_img, keypoints, threshold, nonmax_suppression); break; } - printf("time=%.2fms\n", ((double)getTickCount() - t)*1000./getTickFrequency()); } @@ -371,10 +369,16 @@ FastFeatureDetector::FastFeatureDetector( int _threshold, bool _nonmaxSuppressio void FastFeatureDetector::detectImpl( InputArray _image, std::vector& keypoints, InputArray _mask ) const { - Mat image = _image.getMat(), mask = _mask.getMat(), grayImage = image; - if( image.type() != CV_8U ) - cvtColor( image, grayImage, COLOR_BGR2GRAY ); - FAST( grayImage, keypoints, threshold, nonmaxSuppression, type ); + Mat mask = _mask.getMat(), grayImage; + UMat ugrayImage; + _InputArray gray = _image; + if( _image.type() != CV_8U ) + { + _OutputArray ogray = _image.isUMat() ? _OutputArray(ugrayImage) : _OutputArray(grayImage); + cvtColor( _image, ogray, COLOR_BGR2GRAY ); + gray = ogray; + } + FAST( gray, keypoints, threshold, nonmaxSuppression, type ); KeyPointsFilter::runByPixelsMask( keypoints, mask ); } diff --git a/modules/features2d/src/opencl/orb.cl b/modules/features2d/src/opencl/orb.cl new file mode 100644 index 0000000000..ba5ec6f602 --- /dev/null +++ b/modules/features2d/src/opencl/orb.cl @@ -0,0 +1,254 @@ +// OpenCL port of the ORB feature detector and descriptor extractor +// Copyright (C) 2014, Itseez Inc. See the license at http://opencv.org +// +// The original code has been contributed by Peter Andreas Entschev, peter@entschev.com + +#define LAYERINFO_SIZE 1 +#define LAYERINFO_OFS 0 +#define KEYPOINT_SIZE 3 +#define ORIENTED_KEYPOINT_SIZE 4 +#define KEYPOINT_X 0 +#define KEYPOINT_Y 1 +#define KEYPOINT_Z 2 +#define KEYPOINT_ANGLE 3 + +///////////////////////////////////////////////////////////// + +#ifdef ORB_RESPONSES + +__kernel void +ORB_HarrisResponses(__global const uchar* imgbuf, int imgstep, int imgoffset0, + __global const int* layerinfo, __global const int* keypoints, + __global float* responses, int nkeypoints ) +{ + int idx = get_global_id(0); + if( idx < nkeypoints ) + { + __global const int* kpt = keypoints + idx*KEYPOINT_SIZE; + __global const int* layer = layerinfo + kpt[KEYPOINT_Z]*LAYERINFO_SIZE; + __global const uchar* img = imgbuf + imgoffset0 + layer[LAYERINFO_OFS] + + (kpt[KEYPOINT_Y] - blockSize/2)*imgstep + (kpt[KEYPOINT_X] - blockSize/2); + + int i, j; + int a = 0, b = 0, c = 0; + for( i = 0; i < blockSize; i++, img += imgstep-blockSize ) + { + for( j = 0; j < blockSize; j++, img++ ) + { + int Ix = (img[1] - img[-1])*2 + img[-imgstep+1] - img[-imgstep-1] + img[imgstep+1] - img[imgstep-1]; + int Iy = (img[imgstep] - img[-imgstep])*2 + img[imgstep-1] - img[-imgstep-1] + img[imgstep+1] - img[-imgstep+1]; + a += Ix*Ix; + b += Iy*Iy; + c += Ix*Iy; + } + } + responses[idx] = ((float)a * b - (float)c * c - HARRIS_K * (float)(a + b) * (a + b))*scale_sq_sq; + } +} + +#endif + +///////////////////////////////////////////////////////////// + +#ifdef ORB_ANGLES + +#define _DBL_EPSILON 2.2204460492503131e-16f +#define atan2_p1 (0.9997878412794807f*57.29577951308232f) +#define atan2_p3 (-0.3258083974640975f*57.29577951308232f) +#define atan2_p5 (0.1555786518463281f*57.29577951308232f) +#define atan2_p7 (-0.04432655554792128f*57.29577951308232f) + +inline float fastAtan2( float y, float x ) +{ + float ax = fabs(x), ay = fabs(y); + float a, c, c2; + if( ax >= ay ) + { + c = ay/(ax + _DBL_EPSILON); + c2 = c*c; + a = (((atan2_p7*c2 + atan2_p5)*c2 + atan2_p3)*c2 + atan2_p1)*c; + } + else + { + c = ax/(ay + _DBL_EPSILON); + c2 = c*c; + a = 90.f - (((atan2_p7*c2 + atan2_p5)*c2 + atan2_p3)*c2 + atan2_p1)*c; + } + if( x < 0 ) + a = 180.f - a; + if( y < 0 ) + a = 360.f - a; + return a; +} + + +__kernel void +ORB_ICAngle(__global const uchar* imgbuf, int imgstep, int imgoffset0, + __global const int* layerinfo, __global const int* keypoints, + __global float* responses, const __global int* u_max, + int nkeypoints, int half_k ) +{ + int idx = get_global_id(0); + if( idx < nkeypoints ) + { + __global const int* kpt = keypoints + idx*KEYPOINT_SIZE; + + __global const int* layer = layerinfo + kpt[KEYPOINT_Z]*LAYERINFO_SIZE; + __global const uchar* center = imgbuf + imgoffset0 + layer[LAYERINFO_OFS] + + kpt[KEYPOINT_Y]*imgstep + kpt[KEYPOINT_X]; + + int u, v, m_01 = 0, m_10 = 0; + + // Treat the center line differently, v=0 + for( u = -half_k; u <= half_k; u++ ) + m_10 += u * center[u]; + + // Go line by line in the circular patch + for( v = 1; v <= half_k; v++ ) + { + // Proceed over the two lines + int v_sum = 0; + int d = u_max[v]; + for( u = -d; u <= d; u++ ) + { + int val_plus = center[u + v*imgstep], val_minus = center[u - v*imgstep]; + v_sum += (val_plus - val_minus); + m_10 += u * (val_plus + val_minus); + } + m_01 += v * v_sum; + } + + // we do not use OpenCL's atan2 intrinsic, + // because we want to get _exactly_ the same results as the CPU version + responses[idx] = fastAtan2((float)m_01, (float)m_10); + } +} + +#endif + +///////////////////////////////////////////////////////////// + +#ifdef ORB_DESCRIPTORS + +__kernel void +ORB_computeDescriptor(__global const uchar* imgbuf, int imgstep, int imgoffset0, + __global const int* layerinfo, __global const int* keypoints, + __global uchar* _desc, const __global int* pattern, + int nkeypoints, int dsize ) +{ + int idx = get_global_id(0); + if( idx < nkeypoints ) + { + int i; + __global const int* kpt = keypoints + idx*ORIENTED_KEYPOINT_SIZE; + + __global const int* layer = layerinfo + kpt[KEYPOINT_Z]*LAYERINFO_SIZE; + __global const uchar* center = imgbuf + imgoffset0 + layer[LAYERINFO_OFS] + + kpt[KEYPOINT_Y]*imgstep + kpt[KEYPOINT_X]; + float angle = as_float(kpt[KEYPOINT_ANGLE]); + angle *= 0.01745329251994329547f; + + float sina = sin(angle); + float cosa = cos(angle); + + __global uchar* desc = _desc + idx*dsize; + + #define GET_VALUE(idx) \ + center[mad24(convert_int_rte(pattern[(idx)*2] * sina + pattern[(idx)*2+1] * cosa), imgstep, \ + convert_int_rte(pattern[(idx)*2] * cosa - pattern[(idx)*2+1] * sina))] + + for( i = 0; i < dsize; i++ ) + { + int val; + #if WTA_K == 2 + int t0, t1; + + t0 = GET_VALUE(0); t1 = GET_VALUE(1); + val = t0 < t1; + + t0 = GET_VALUE(2); t1 = GET_VALUE(3); + val |= (t0 < t1) << 1; + + t0 = GET_VALUE(4); t1 = GET_VALUE(5); + val |= (t0 < t1) << 2; + + t0 = GET_VALUE(6); t1 = GET_VALUE(7); + val |= (t0 < t1) << 3; + + t0 = GET_VALUE(8); t1 = GET_VALUE(9); + val |= (t0 < t1) << 4; + + t0 = GET_VALUE(10); t1 = GET_VALUE(11); + val |= (t0 < t1) << 5; + + t0 = GET_VALUE(12); t1 = GET_VALUE(13); + val |= (t0 < t1) << 6; + + t0 = GET_VALUE(14); t1 = GET_VALUE(15); + val |= (t0 < t1) << 7; + + pattern += 16*2; + + #elif WTA_K == 3 + int t0, t1, t2; + + t0 = GET_VALUE(0); t1 = GET_VALUE(1); t2 = GET_VALUE(2); + val = t2 > t1 ? (t2 > t0 ? 2 : 0) : (t1 > t0); + + t0 = GET_VALUE(3); t1 = GET_VALUE(4); t2 = GET_VALUE(5); + val |= (t2 > t1 ? (t2 > t0 ? 2 : 0) : (t1 > t0)) << 2; + + t0 = GET_VALUE(6); t1 = GET_VALUE(7); t2 = GET_VALUE(8); + val |= (t2 > t1 ? (t2 > t0 ? 2 : 0) : (t1 > t0)) << 4; + + t0 = GET_VALUE(9); t1 = GET_VALUE(10); t2 = GET_VALUE(11); + val |= (t2 > t1 ? (t2 > t0 ? 2 : 0) : (t1 > t0)) << 6; + + pattern += 12*2; + + #elif WTA_K == 4 + int t0, t1, t2, t3, k, val; + int a, b; + + t0 = GET_VALUE(0); t1 = GET_VALUE(1); + t2 = GET_VALUE(2); t3 = GET_VALUE(3); + a = 0, b = 2; + if( t1 > t0 ) t0 = t1, a = 1; + if( t3 > t2 ) t2 = t3, b = 3; + k = t0 > t2 ? a : b; + val = k; + + t0 = GET_VALUE(4); t1 = GET_VALUE(5); + t2 = GET_VALUE(6); t3 = GET_VALUE(7); + a = 0, b = 2; + if( t1 > t0 ) t0 = t1, a = 1; + if( t3 > t2 ) t2 = t3, b = 3; + k = t0 > t2 ? a : b; + val |= k << 2; + + t0 = GET_VALUE(8); t1 = GET_VALUE(9); + t2 = GET_VALUE(10); t3 = GET_VALUE(11); + a = 0, b = 2; + if( t1 > t0 ) t0 = t1, a = 1; + if( t3 > t2 ) t2 = t3, b = 3; + k = t0 > t2 ? a : b; + val |= k << 4; + + t0 = GET_VALUE(12); t1 = GET_VALUE(13); + t2 = GET_VALUE(14); t3 = GET_VALUE(15); + a = 0, b = 2; + if( t1 > t0 ) t0 = t1, a = 1; + if( t3 > t2 ) t2 = t3, b = 3; + k = t0 > t2 ? a : b; + val |= k << 6; + + pattern += 16*2; + #else + #error "unknown/undefined WTA_K value; should be 2, 3 or 4" + #endif + desc[i] = (uchar)val; + } + } +} + +#endif diff --git a/modules/features2d/src/orb.cpp b/modules/features2d/src/orb.cpp index b72a6dbcec..4fe9cbc237 100644 --- a/modules/features2d/src/orb.cpp +++ b/modules/features2d/src/orb.cpp @@ -35,6 +35,7 @@ /** Authors: Ethan Rublee, Vincent Rabaud, Gary Bradski */ #include "precomp.hpp" +#include "opencl_kernels.hpp" #include //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// @@ -43,14 +44,86 @@ namespace cv { const float HARRIS_K = 0.04f; -const int DESCRIPTOR_SIZE = 32; + +template inline void copyVectorToUMat(const std::vector<_Tp>& v, OutputArray um) +{ + if(v.empty()) + um.release(); + Mat(1, (int)(v.size()*sizeof(v[0])), CV_8U, (void*)&v[0]).copyTo(um); +} + +static bool +ocl_HarrisResponses(const UMat& imgbuf, + const UMat& layerinfo, + const UMat& keypoints, + UMat& responses, + int nkeypoints, int blockSize, float harris_k) +{ + size_t globalSize[] = {nkeypoints}; + + float scale = 1.f/((1 << 2) * blockSize * 255.f); + float scale_sq_sq = scale * scale * scale * scale; + + ocl::Kernel hr_ker("ORB_HarrisResponses", ocl::features2d::orb_oclsrc, + format("-D ORB_RESPONSES -D blockSize=%d -D scale_sq_sq=%.12ef -D HARRIS_K=%.12ff", blockSize, scale_sq_sq, harris_k)); + if( hr_ker.empty() ) + return false; + + return hr_ker.args(ocl::KernelArg::ReadOnlyNoSize(imgbuf), + ocl::KernelArg::PtrReadOnly(layerinfo), + ocl::KernelArg::PtrReadOnly(keypoints), + ocl::KernelArg::PtrWriteOnly(responses), + nkeypoints).run(1, globalSize, 0, true); +} + +static bool +ocl_ICAngles(const UMat& imgbuf, const UMat& layerinfo, + const UMat& keypoints, UMat& responses, + const UMat& umax, int nkeypoints, int half_k) +{ + size_t globalSize[] = {nkeypoints}; + + ocl::Kernel icangle_ker("ORB_ICAngle", ocl::features2d::orb_oclsrc, "-D ORB_ANGLES"); + if( icangle_ker.empty() ) + return false; + + return icangle_ker.args(ocl::KernelArg::ReadOnlyNoSize(imgbuf), + ocl::KernelArg::PtrReadOnly(layerinfo), + ocl::KernelArg::PtrReadOnly(keypoints), + ocl::KernelArg::PtrWriteOnly(responses), + ocl::KernelArg::PtrReadOnly(umax), + nkeypoints, half_k).run(1, globalSize, 0, true); +} + + +static bool +ocl_computeOrbDescriptors(const UMat& imgbuf, const UMat& layerInfo, + const UMat& keypoints, UMat& desc, const UMat& pattern, + int nkeypoints, int dsize, int WTA_K) +{ + size_t globalSize[] = {nkeypoints}; + + ocl::Kernel desc_ker("ORB_computeDescriptor", ocl::features2d::orb_oclsrc, + format("-D ORB_DESCRIPTORS -D WTA_K=%d", WTA_K)); + if( desc_ker.empty() ) + return false; + + return desc_ker.args(ocl::KernelArg::ReadOnlyNoSize(imgbuf), + ocl::KernelArg::PtrReadOnly(layerInfo), + ocl::KernelArg::PtrReadOnly(keypoints), + ocl::KernelArg::PtrWriteOnly(desc), + ocl::KernelArg::PtrReadOnly(pattern), + nkeypoints, dsize).run(1, globalSize, 0, true); +} + /** * Function that computes the Harris responses in a - * blockSize x blockSize patch at given points in an image + * blockSize x blockSize patch at given points in the image */ static void -HarrisResponses(const Mat& img, std::vector& pts, int blockSize, float harris_k) +HarrisResponses(const Mat& img, const std::vector& layerinfo, + std::vector& pts, int blockSize, float harris_k) { CV_Assert( img.type() == CV_8UC1 && blockSize*blockSize <= 2048 ); @@ -60,8 +133,7 @@ HarrisResponses(const Mat& img, std::vector& pts, int blockSize, float int step = (int)(img.step/img.elemSize1()); int r = blockSize/2; - float scale = (1 << 2) * blockSize * 255.0f; - scale = 1.0f / scale; + float scale = 1.f/((1 << 2) * blockSize * 255.f); float scale_sq_sq = scale * scale * scale * scale; AutoBuffer ofsbuf(blockSize*blockSize); @@ -72,10 +144,11 @@ HarrisResponses(const Mat& img, std::vector& pts, int blockSize, float for( ptidx = 0; ptidx < ptsize; ptidx++ ) { - int x0 = cvRound(pts[ptidx].pt.x - r); - int y0 = cvRound(pts[ptidx].pt.y - r); + int x0 = cvRound(pts[ptidx].pt.x); + int y0 = cvRound(pts[ptidx].pt.y); + int z = pts[ptidx].octave; - const uchar* ptr0 = ptr00 + y0*step + x0; + const uchar* ptr0 = ptr00 + (y0 - r + layerinfo[z].y)*step + x0 - r + layerinfo[z].x; int a = 0, b = 0, c = 0; for( int k = 0; k < blockSize*blockSize; k++ ) @@ -94,158 +167,175 @@ HarrisResponses(const Mat& img, std::vector& pts, int blockSize, float //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// -static float IC_Angle(const Mat& image, const int half_k, Point2f pt, - const std::vector & u_max) +static void ICAngles(const Mat& img, const std::vector& layerinfo, + std::vector& pts, const std::vector & u_max, int half_k) { - int m_01 = 0, m_10 = 0; + int step = (int)img.step1(); + size_t ptidx, ptsize = pts.size(); - const uchar* center = &image.at (cvRound(pt.y), cvRound(pt.x)); - - // Treat the center line differently, v=0 - for (int u = -half_k; u <= half_k; ++u) - m_10 += u * center[u]; - - // Go line by line in the circular patch - int step = (int)image.step1(); - for (int v = 1; v <= half_k; ++v) + for( ptidx = 0; ptidx < ptsize; ptidx++ ) { - // Proceed over the two lines - int v_sum = 0; - int d = u_max[v]; - for (int u = -d; u <= d; ++u) - { - int val_plus = center[u + v*step], val_minus = center[u - v*step]; - v_sum += (val_plus - val_minus); - m_10 += u * (val_plus + val_minus); - } - m_01 += v * v_sum; - } + const Rect& layer = layerinfo[pts[ptidx].octave]; + const uchar* center = &img.at(cvRound(pts[ptidx].pt.y) + layer.y, cvRound(pts[ptidx].pt.x) + layer.x); - return fastAtan2((float)m_01, (float)m_10); + int m_01 = 0, m_10 = 0; + + // Treat the center line differently, v=0 + for (int u = -half_k; u <= half_k; ++u) + m_10 += u * center[u]; + + // Go line by line in the circular patch + for (int v = 1; v <= half_k; ++v) + { + // Proceed over the two lines + int v_sum = 0; + int d = u_max[v]; + for (int u = -d; u <= d; ++u) + { + int val_plus = center[u + v*step], val_minus = center[u - v*step]; + v_sum += (val_plus - val_minus); + m_10 += u * (val_plus + val_minus); + } + m_01 += v * v_sum; + } + + pts[ptidx].angle = fastAtan2((float)m_01, (float)m_10); + } } //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// -static void computeOrbDescriptor(const KeyPoint& kpt, - const Mat& img, const Point* pattern, - uchar* desc, int dsize, int WTA_K) +static void +computeOrbDescriptors( const Mat& imagePyramid, const std::vector& layerInfo, + const std::vector& layerScale, std::vector& keypoints, + Mat& descriptors, const std::vector& _pattern, int dsize, int WTA_K ) { - float angle = kpt.angle; - //angle = cvFloor(angle/12)*12.f; - angle *= (float)(CV_PI/180.f); - float a = (float)cos(angle), b = (float)sin(angle); + int step = (int)imagePyramid.step; + int j, i, nkeypoints = (int)keypoints.size(); - const uchar* center = &img.at(cvRound(kpt.pt.y), cvRound(kpt.pt.x)); - int step = (int)img.step; + for( j = 0; j < nkeypoints; j++ ) + { + const KeyPoint& kpt = keypoints[j]; + const Rect& layer = layerInfo[kpt.octave]; + float scale = 1.f/layerScale[kpt.octave]; + float angle = kpt.angle; - float x, y; - int ix, iy; -#if 1 - #define GET_VALUE(idx) \ - (x = pattern[idx].x*a - pattern[idx].y*b, \ + angle *= (float)(CV_PI/180.f); + float a = (float)cos(angle), b = (float)sin(angle); + + const uchar* center = &imagePyramid.at(cvRound(kpt.pt.y*scale) + layer.y, + cvRound(kpt.pt.x*scale) + layer.x); + float x, y; + int ix, iy; + const Point* pattern = &_pattern[0]; + uchar* desc = descriptors.ptr(j); + + #if 1 + #define GET_VALUE(idx) \ + (x = pattern[idx].x*a - pattern[idx].y*b, \ + y = pattern[idx].x*b + pattern[idx].y*a, \ + ix = cvRound(x), \ + iy = cvRound(y), \ + *(center + iy*step + ix) ) + #else + #define GET_VALUE(idx) \ + (x = pattern[idx].x*a - pattern[idx].y*b, \ y = pattern[idx].x*b + pattern[idx].y*a, \ - ix = cvRound(x), \ - iy = cvRound(y), \ - *(center + iy*step + ix) ) -#else - #define GET_VALUE(idx) \ - (x = pattern[idx].x*a - pattern[idx].y*b, \ - y = pattern[idx].x*b + pattern[idx].y*a, \ - ix = cvFloor(x), iy = cvFloor(y), \ - x -= ix, y -= iy, \ - cvRound(center[iy*step + ix]*(1-x)*(1-y) + center[(iy+1)*step + ix]*(1-x)*y + \ - center[iy*step + ix+1]*x*(1-y) + center[(iy+1)*step + ix+1]*x*y)) -#endif + ix = cvFloor(x), iy = cvFloor(y), \ + x -= ix, y -= iy, \ + cvRound(center[iy*step + ix]*(1-x)*(1-y) + center[(iy+1)*step + ix]*(1-x)*y + \ + center[iy*step + ix+1]*x*(1-y) + center[(iy+1)*step + ix+1]*x*y)) + #endif - if( WTA_K == 2 ) - { - for (int i = 0; i < dsize; ++i, pattern += 16) + if( WTA_K == 2 ) { - int t0, t1, val; - t0 = GET_VALUE(0); t1 = GET_VALUE(1); - val = t0 < t1; - t0 = GET_VALUE(2); t1 = GET_VALUE(3); - val |= (t0 < t1) << 1; - t0 = GET_VALUE(4); t1 = GET_VALUE(5); - val |= (t0 < t1) << 2; - t0 = GET_VALUE(6); t1 = GET_VALUE(7); - val |= (t0 < t1) << 3; - t0 = GET_VALUE(8); t1 = GET_VALUE(9); - val |= (t0 < t1) << 4; - t0 = GET_VALUE(10); t1 = GET_VALUE(11); - val |= (t0 < t1) << 5; - t0 = GET_VALUE(12); t1 = GET_VALUE(13); - val |= (t0 < t1) << 6; - t0 = GET_VALUE(14); t1 = GET_VALUE(15); - val |= (t0 < t1) << 7; + for (i = 0; i < dsize; ++i, pattern += 16) + { + int t0, t1, val; + t0 = GET_VALUE(0); t1 = GET_VALUE(1); + val = t0 < t1; + t0 = GET_VALUE(2); t1 = GET_VALUE(3); + val |= (t0 < t1) << 1; + t0 = GET_VALUE(4); t1 = GET_VALUE(5); + val |= (t0 < t1) << 2; + t0 = GET_VALUE(6); t1 = GET_VALUE(7); + val |= (t0 < t1) << 3; + t0 = GET_VALUE(8); t1 = GET_VALUE(9); + val |= (t0 < t1) << 4; + t0 = GET_VALUE(10); t1 = GET_VALUE(11); + val |= (t0 < t1) << 5; + t0 = GET_VALUE(12); t1 = GET_VALUE(13); + val |= (t0 < t1) << 6; + t0 = GET_VALUE(14); t1 = GET_VALUE(15); + val |= (t0 < t1) << 7; - desc[i] = (uchar)val; + desc[i] = (uchar)val; + } } - } - else if( WTA_K == 3 ) - { - for (int i = 0; i < dsize; ++i, pattern += 12) + else if( WTA_K == 3 ) { - int t0, t1, t2, val; - t0 = GET_VALUE(0); t1 = GET_VALUE(1); t2 = GET_VALUE(2); - val = t2 > t1 ? (t2 > t0 ? 2 : 0) : (t1 > t0); + for (i = 0; i < dsize; ++i, pattern += 12) + { + int t0, t1, t2, val; + t0 = GET_VALUE(0); t1 = GET_VALUE(1); t2 = GET_VALUE(2); + val = t2 > t1 ? (t2 > t0 ? 2 : 0) : (t1 > t0); - t0 = GET_VALUE(3); t1 = GET_VALUE(4); t2 = GET_VALUE(5); - val |= (t2 > t1 ? (t2 > t0 ? 2 : 0) : (t1 > t0)) << 2; + t0 = GET_VALUE(3); t1 = GET_VALUE(4); t2 = GET_VALUE(5); + val |= (t2 > t1 ? (t2 > t0 ? 2 : 0) : (t1 > t0)) << 2; - t0 = GET_VALUE(6); t1 = GET_VALUE(7); t2 = GET_VALUE(8); - val |= (t2 > t1 ? (t2 > t0 ? 2 : 0) : (t1 > t0)) << 4; + t0 = GET_VALUE(6); t1 = GET_VALUE(7); t2 = GET_VALUE(8); + val |= (t2 > t1 ? (t2 > t0 ? 2 : 0) : (t1 > t0)) << 4; - t0 = GET_VALUE(9); t1 = GET_VALUE(10); t2 = GET_VALUE(11); - val |= (t2 > t1 ? (t2 > t0 ? 2 : 0) : (t1 > t0)) << 6; + t0 = GET_VALUE(9); t1 = GET_VALUE(10); t2 = GET_VALUE(11); + val |= (t2 > t1 ? (t2 > t0 ? 2 : 0) : (t1 > t0)) << 6; - desc[i] = (uchar)val; + desc[i] = (uchar)val; + } } - } - else if( WTA_K == 4 ) - { - for (int i = 0; i < dsize; ++i, pattern += 16) + else if( WTA_K == 4 ) { - int t0, t1, t2, t3, u, v, k, val; - t0 = GET_VALUE(0); t1 = GET_VALUE(1); - t2 = GET_VALUE(2); t3 = GET_VALUE(3); - u = 0, v = 2; - if( t1 > t0 ) t0 = t1, u = 1; - if( t3 > t2 ) t2 = t3, v = 3; - k = t0 > t2 ? u : v; - val = k; + for (i = 0; i < dsize; ++i, pattern += 16) + { + int t0, t1, t2, t3, u, v, k, val; + t0 = GET_VALUE(0); t1 = GET_VALUE(1); + t2 = GET_VALUE(2); t3 = GET_VALUE(3); + u = 0, v = 2; + if( t1 > t0 ) t0 = t1, u = 1; + if( t3 > t2 ) t2 = t3, v = 3; + k = t0 > t2 ? u : v; + val = k; - t0 = GET_VALUE(4); t1 = GET_VALUE(5); - t2 = GET_VALUE(6); t3 = GET_VALUE(7); - u = 0, v = 2; - if( t1 > t0 ) t0 = t1, u = 1; - if( t3 > t2 ) t2 = t3, v = 3; - k = t0 > t2 ? u : v; - val |= k << 2; + t0 = GET_VALUE(4); t1 = GET_VALUE(5); + t2 = GET_VALUE(6); t3 = GET_VALUE(7); + u = 0, v = 2; + if( t1 > t0 ) t0 = t1, u = 1; + if( t3 > t2 ) t2 = t3, v = 3; + k = t0 > t2 ? u : v; + val |= k << 2; - t0 = GET_VALUE(8); t1 = GET_VALUE(9); - t2 = GET_VALUE(10); t3 = GET_VALUE(11); - u = 0, v = 2; - if( t1 > t0 ) t0 = t1, u = 1; - if( t3 > t2 ) t2 = t3, v = 3; - k = t0 > t2 ? u : v; - val |= k << 4; + t0 = GET_VALUE(8); t1 = GET_VALUE(9); + t2 = GET_VALUE(10); t3 = GET_VALUE(11); + u = 0, v = 2; + if( t1 > t0 ) t0 = t1, u = 1; + if( t3 > t2 ) t2 = t3, v = 3; + k = t0 > t2 ? u : v; + val |= k << 4; - t0 = GET_VALUE(12); t1 = GET_VALUE(13); - t2 = GET_VALUE(14); t3 = GET_VALUE(15); - u = 0, v = 2; - if( t1 > t0 ) t0 = t1, u = 1; - if( t3 > t2 ) t2 = t3, v = 3; - k = t0 > t2 ? u : v; - val |= k << 6; + t0 = GET_VALUE(12); t1 = GET_VALUE(13); + t2 = GET_VALUE(14); t3 = GET_VALUE(15); + u = 0, v = 2; + if( t1 > t0 ) t0 = t1, u = 1; + if( t3 > t2 ) t2 = t3, v = 3; + k = t0 > t2 ? u : v; + val |= k << 6; - desc[i] = (uchar)val; + desc[i] = (uchar)val; + } } + else + CV_Error( Error::StsBadSize, "Wrong WTA_K. It can be only 2, 3 or 4." ); + #undef GET_VALUE } - else - CV_Error( Error::StsBadSize, "Wrong WTA_K. It can be only 2, 3 or 4." ); - - #undef GET_VALUE } @@ -591,21 +681,37 @@ void ORB::operator()(InputArray image, InputArray mask, std::vector& k } -/** Compute the ORB keypoint orientations - * @param image the image to compute the features and descriptors on - * @param integral_image the integral image of the iamge (can be empty, but the computation will be slower) - * @param scale the scale at which we compute the orientation - * @param keypoints the resulting keypoints - */ -static void computeOrientation(const Mat& image, std::vector& keypoints, - int halfPatchSize, const std::vector& umax) +static void uploadORBKeypoints(const std::vector& src, std::vector& buf, OutputArray dst) { - // Process each keypoint - for (std::vector::iterator keypoint = keypoints.begin(), - keypointEnd = keypoints.end(); keypoint != keypointEnd; ++keypoint) + size_t i, n = src.size(); + buf.resize(std::max(buf.size(), n)); + for( i = 0; i < n; i++ ) + buf[i] = Vec3i(cvRound(src[i].pt.x), cvRound(src[i].pt.y), src[i].octave); + copyVectorToUMat(buf, dst); +} + +typedef union if32_t +{ + int i; + float f; +} +if32_t; + +static void uploadORBKeypoints(const std::vector& src, + const std::vector& layerScale, + std::vector& buf, OutputArray dst) +{ + size_t i, n = src.size(); + buf.resize(std::max(buf.size(), n)); + for( i = 0; i < n; i++ ) { - keypoint->angle = IC_Angle(image, halfPatchSize, keypoint->pt, umax); + int z = src[i].octave; + float scale = 1.f/layerScale[z]; + if32_t angle; + angle.f = src[i].angle; + buf[i] = Vec4i(cvRound(src[i].pt.x*scale), cvRound(src[i].pt.y*scale), z, angle.i); } + copyVectorToUMat(buf, dst); } @@ -614,13 +720,18 @@ static void computeOrientation(const Mat& image, std::vector& keypoint * @param mask_pyramid the masks to apply at every level * @param keypoints the resulting keypoints, clustered per level */ -static void computeKeyPoints(const std::vector& imagePyramid, - const std::vector& maskPyramid, - std::vector >& allKeypoints, - int nfeatures, int firstLevel, double scaleFactor, - int edgeThreshold, int patchSize, int scoreType ) +static void computeKeyPoints(const Mat& imagePyramid, + const UMat& uimagePyramid, + const Mat& maskPyramid, + const std::vector& layerInfo, + const UMat& ulayerInfo, + const std::vector& layerScale, + std::vector& allKeypoints, + int nfeatures, double scaleFactor, + int edgeThreshold, int patchSize, int scoreType, + bool useOCL ) { - int nlevels = (int)imagePyramid.size(); + int i, nkeypoints, level, nlevels = (int)layerInfo.size(); std::vector nfeaturesPerLevel(nlevels); // fill the extractors and descriptors for the corresponding scales @@ -628,7 +739,7 @@ static void computeKeyPoints(const std::vector& imagePyramid, float ndesiredFeaturesPerScale = nfeatures*(1 - factor)/(1 - (float)std::pow((double)factor, (double)nlevels)); int sumFeatures = 0; - for( int level = 0; level < nlevels-1; level++ ) + for( level = 0; level < nlevels-1; level++ ) { nfeaturesPerLevel[level] = cvRound(ndesiredFeaturesPerScale); sumFeatures += nfeaturesPerLevel[level]; @@ -657,66 +768,116 @@ static void computeKeyPoints(const std::vector& imagePyramid, ++v0; } - allKeypoints.resize(nlevels); + allKeypoints.clear(); + std::vector keypoints; + std::vector counters(nlevels); + keypoints.reserve(nfeaturesPerLevel[0]*2); - for (int level = 0; level < nlevels; ++level) + for( level = 0; level < nlevels; level++ ) { int featuresNum = nfeaturesPerLevel[level]; - allKeypoints[level].reserve(featuresNum*2); - - std::vector & keypoints = allKeypoints[level]; + Mat img = imagePyramid(layerInfo[level]); + Mat mask = maskPyramid.empty() ? Mat() : maskPyramid(layerInfo[level]); // Detect FAST features, 20 is a good threshold FastFeatureDetector fd(20, true); - fd.detect(imagePyramid[level], keypoints, maskPyramid[level]); + fd.detect(img, keypoints, mask); // Remove keypoints very close to the border - KeyPointsFilter::runByImageBorder(keypoints, imagePyramid[level].size(), edgeThreshold); + KeyPointsFilter::runByImageBorder(keypoints, img.size(), edgeThreshold); - if( scoreType == ORB::HARRIS_SCORE ) + // Keep more points than necessary as FAST does not give amazing corners + KeyPointsFilter::retainBest(keypoints, scoreType == ORB::HARRIS_SCORE ? 2 * featuresNum : featuresNum); + + nkeypoints = (int)keypoints.size(); + counters[level] = nkeypoints; + + float sf = layerScale[level]; + for( i = 0; i < nkeypoints; i++ ) { - // Keep more points than necessary as FAST does not give amazing corners - KeyPointsFilter::retainBest(keypoints, 2 * featuresNum); - - // Compute the Harris cornerness (better scoring than FAST) - HarrisResponses(imagePyramid[level], keypoints, 7, HARRIS_K); + keypoints[i].octave = level; + keypoints[i].size = patchSize*sf; } - //cull to the final desired level, using the new Harris scores or the original FAST scores. - KeyPointsFilter::retainBest(keypoints, featuresNum); - - float sf = getScale(level, firstLevel, scaleFactor); - - // Set the level of the coordinates - for (std::vector::iterator keypoint = keypoints.begin(), - keypointEnd = keypoints.end(); keypoint != keypointEnd; ++keypoint) - { - keypoint->octave = level; - keypoint->size = patchSize*sf; - } - - computeOrientation(imagePyramid[level], keypoints, halfPatchSize, umax); + std::copy(keypoints.begin(), keypoints.end(), std::back_inserter(allKeypoints)); } -} + std::vector ukeypoints_buf; -/** Compute the ORB decriptors - * @param image the image to compute the features and descriptors on - * @param integral_image the integral image of the image (can be empty, but the computation will be slower) - * @param level the scale at which we compute the orientation - * @param keypoints the keypoints to use - * @param descriptors the resulting descriptors - */ -static void computeDescriptors(const Mat& image, std::vector& keypoints, Mat& descriptors, - const std::vector& pattern, int dsize, int WTA_K) -{ - //convert to grayscale if more than one color - CV_Assert(image.type() == CV_8UC1); - //create the descriptor mat, keypoints.size() rows, BYTES cols - descriptors = Mat::zeros((int)keypoints.size(), dsize, CV_8UC1); + nkeypoints = (int)allKeypoints.size(); + Mat responses; + UMat ukeypoints, uresponses(1, nkeypoints, CV_32F); - for (size_t i = 0; i < keypoints.size(); i++) - computeOrbDescriptor(keypoints[i], image, &pattern[0], descriptors.ptr((int)i), dsize, WTA_K); + // Select best features using the Harris cornerness (better scoring than FAST) + if( scoreType == ORB::HARRIS_SCORE ) + { + if( useOCL ) + { + uploadORBKeypoints(allKeypoints, ukeypoints_buf, ukeypoints); + useOCL = ocl_HarrisResponses( uimagePyramid, ulayerInfo, ukeypoints, + uresponses, nkeypoints, 7, HARRIS_K ); + if( useOCL ) + { + uresponses.copyTo(responses); + for( i = 0; i < nkeypoints; i++ ) + allKeypoints[i].response = responses.at(i); + } + } + + if( !useOCL ) + HarrisResponses(imagePyramid, layerInfo, allKeypoints, 7, HARRIS_K); + + std::vector newAllKeypoints; + newAllKeypoints.reserve(nfeaturesPerLevel[0]*nlevels); + + int offset = 0; + for( level = 0; level < nlevels; level++ ) + { + int featuresNum = nfeaturesPerLevel[level]; + nkeypoints = counters[level]; + keypoints.resize(nkeypoints); + std::copy(allKeypoints.begin() + offset, + allKeypoints.begin() + offset + nkeypoints, + keypoints.begin()); + offset += nkeypoints; + + //cull to the final desired level, using the new Harris scores. + KeyPointsFilter::retainBest(keypoints, featuresNum); + + std::copy(keypoints.begin(), keypoints.end(), std::back_inserter(newAllKeypoints)); + } + std::swap(allKeypoints, newAllKeypoints); + } + + nkeypoints = (int)allKeypoints.size(); + if( useOCL ) + { + UMat uumax; + if( useOCL ) + copyVectorToUMat(umax, uumax); + + uploadORBKeypoints(allKeypoints, ukeypoints_buf, ukeypoints); + useOCL = ocl_ICAngles(uimagePyramid, ulayerInfo, ukeypoints, uresponses, uumax, + nkeypoints, halfPatchSize); + + if( useOCL ) + { + uresponses.copyTo(responses); + for( i = 0; i < nkeypoints; i++ ) + allKeypoints[i].angle = responses.at(i); + } + } + + if( !useOCL ) + { + ICAngles(imagePyramid, layerInfo, allKeypoints, umax, halfPatchSize); + } + + for( i = 0; i < nkeypoints; i++ ) + { + float scale = layerScale[allKeypoints[i].octave]; + allKeypoints[i].pt *= scale; + } } @@ -728,8 +889,8 @@ static void computeDescriptors(const Mat& image, std::vector& keypoint * @param do_keypoints if true, the keypoints are computed, otherwise used as an input * @param do_descriptors if true, also computes the descriptors */ -void ORB::operator()( InputArray _image, InputArray _mask, std::vector& _keypoints, - OutputArray _descriptors, bool useProvidedKeypoints) const +void ORB::operator()( InputArray _image, InputArray _mask, std::vector& keypoints, + OutputArray _descriptors, bool useProvidedKeypoints ) const { CV_Assert(patchSize >= 2); @@ -744,11 +905,14 @@ void ORB::operator()( InputArray _image, InputArray _mask, std::vector int halfPatchSize = patchSize / 2; int border = std::max(edgeThreshold, std::max(halfPatchSize, HARRIS_BLOCK_SIZE/2))+1; + bool useOCL = ocl::useOpenCL(); + Mat image = _image.getMat(), mask = _mask.getMat(); if( image.type() != CV_8UC1 ) cvtColor(_image, image, COLOR_BGR2GRAY); - int levelsNum = this->nlevels; + int i, level, nLevels = this->nlevels, nkeypoints = (int)keypoints.size(); + bool sortedByLevel = true; if( !do_keypoints ) { @@ -761,129 +925,145 @@ void ORB::operator()( InputArray _image, InputArray _mask, std::vector // // In short, ultimately the descriptor should // ignore octave parameter and deal only with the keypoint size. - levelsNum = 0; - for( size_t i = 0; i < _keypoints.size(); i++ ) - levelsNum = std::max(levelsNum, std::max(_keypoints[i].octave, 0)); - levelsNum++; + nLevels = 0; + for( i = 0; i < nkeypoints; i++ ) + { + level = keypoints[i].octave; + CV_Assert(level >= 0); + if( i > 0 && level < keypoints[i-1].octave ) + sortedByLevel = false; + nLevels = std::max(nLevels, level); + } + nLevels++; } - // Pre-compute the scale pyramids - std::vector imagePyramid(levelsNum), maskPyramid(levelsNum); - for (int level = 0; level < levelsNum; ++level) + std::vector layerInfo(nLevels); + std::vector layerOfs(nLevels); + std::vector layerScale(nLevels); + Mat imagePyramid, maskPyramid; + UMat uimagePyramid, ulayerInfo; + + int level_dy = image.rows + border*2; + Point level_ofs(0,0); + Size bufSize((image.cols + border*2 + 15) & -16, 0); + + for( level = 0; level < nLevels; level++ ) { - float scale = 1/getScale(level, firstLevel, scaleFactor); - Size sz(cvRound(image.cols*scale), cvRound(image.rows*scale)); + float scale = getScale(level, firstLevel, scaleFactor); + layerScale[level] = scale; + Size sz(cvRound(image.cols/scale), cvRound(image.rows/scale)); Size wholeSize(sz.width + border*2, sz.height + border*2); - Mat temp(wholeSize, image.type()), masktemp; - imagePyramid[level] = temp(Rect(border, border, sz.width, sz.height)); + if( level_ofs.x + wholeSize.width > bufSize.width ) + { + level_ofs = Point(0, level_ofs.y + level_dy); + level_dy = wholeSize.height; + } + + Rect linfo(level_ofs.x + border, level_ofs.y + border, sz.width, sz.height); + layerInfo[level] = linfo; + layerOfs[level] = linfo.y*bufSize.width + linfo.x; + level_ofs.x += wholeSize.width; + } + bufSize.height = level_ofs.y + level_dy; + + imagePyramid.create(bufSize, CV_8U); + if( !mask.empty() ) + maskPyramid.create(bufSize, CV_8U); + + Mat prevImg = image, prevMask = mask; + + // Pre-compute the scale pyramids + for (level = 0; level < nLevels; ++level) + { + Rect linfo = layerInfo[level]; + Size sz(linfo.width, linfo.height); + Size wholeSize(sz.width + border*2, sz.height + border*2); + Rect wholeLinfo = Rect(linfo.x - border, linfo.y - border, wholeSize.width, wholeSize.height); + Mat extImg = imagePyramid(wholeLinfo), extMask; + Mat currImg = extImg(Rect(border, border, sz.width, sz.height)), currMask; if( !mask.empty() ) { - masktemp = Mat(wholeSize, mask.type()); - maskPyramid[level] = masktemp(Rect(border, border, sz.width, sz.height)); + extMask = maskPyramid(wholeLinfo); + currMask = extMask(Rect(border, border, sz.width, sz.height)); } // Compute the resized image if( level != firstLevel ) { - if( level < firstLevel ) + resize(prevImg, currImg, sz, 0, 0, INTER_LINEAR); + if( !mask.empty() ) { - resize(image, imagePyramid[level], sz, 0, 0, INTER_LINEAR); - if (!mask.empty()) - resize(mask, maskPyramid[level], sz, 0, 0, INTER_LINEAR); - } - else - { - resize(imagePyramid[level-1], imagePyramid[level], sz, 0, 0, INTER_LINEAR); - if (!mask.empty()) - { - resize(maskPyramid[level-1], maskPyramid[level], sz, 0, 0, INTER_LINEAR); - threshold(maskPyramid[level], maskPyramid[level], 254, 0, THRESH_TOZERO); - } + resize(prevMask, currMask, sz, 0, 0, INTER_LINEAR); + if( level > firstLevel ) + threshold(currMask, currMask, 254, 0, THRESH_TOZERO); } - copyMakeBorder(imagePyramid[level], temp, border, border, border, border, + copyMakeBorder(currImg, extImg, border, border, border, border, BORDER_REFLECT_101+BORDER_ISOLATED); if (!mask.empty()) - copyMakeBorder(maskPyramid[level], masktemp, border, border, border, border, + copyMakeBorder(currMask, extMask, border, border, border, border, BORDER_CONSTANT+BORDER_ISOLATED); } else { - copyMakeBorder(image, temp, border, border, border, border, + copyMakeBorder(image, extImg, border, border, border, border, BORDER_REFLECT_101); if( !mask.empty() ) - copyMakeBorder(mask, masktemp, border, border, border, border, + copyMakeBorder(mask, extMask, border, border, border, border, BORDER_CONSTANT+BORDER_ISOLATED); } + prevImg = currImg; + prevMask = currMask; } - // Pre-compute the keypoints (we keep the best over all scales, so this has to be done beforehand - std::vector < std::vector > allKeypoints; + if( useOCL ) + copyVectorToUMat(layerOfs, ulayerInfo); + if( do_keypoints ) { + if( useOCL ) + imagePyramid.copyTo(uimagePyramid); + // Get keypoints, those will be far enough from the border that no check will be required for the descriptor - computeKeyPoints(imagePyramid, maskPyramid, allKeypoints, - nfeatures, firstLevel, scaleFactor, - edgeThreshold, patchSize, scoreType); - - // make sure we have the right number of keypoints keypoints - /*std::vector temp; - - for (int level = 0; level < n_levels; ++level) - { - std::vector& keypoints = all_keypoints[level]; - temp.insert(temp.end(), keypoints.begin(), keypoints.end()); - keypoints.clear(); - } - - KeyPoint::retainBest(temp, n_features_); - - for (std::vector::iterator keypoint = temp.begin(), - keypoint_end = temp.end(); keypoint != keypoint_end; ++keypoint) - all_keypoints[keypoint->octave].push_back(*keypoint);*/ + computeKeyPoints(imagePyramid, uimagePyramid, maskPyramid, + layerInfo, ulayerInfo, layerScale, keypoints, + nfeatures, scaleFactor, edgeThreshold, patchSize, scoreType, useOCL); } else { - // Remove keypoints very close to the border - KeyPointsFilter::runByImageBorder(_keypoints, image.size(), edgeThreshold); + KeyPointsFilter::runByImageBorder(keypoints, image.size(), edgeThreshold); - // Cluster the input keypoints depending on the level they were computed at - allKeypoints.resize(levelsNum); - for (std::vector::iterator keypoint = _keypoints.begin(), - keypointEnd = _keypoints.end(); keypoint != keypointEnd; ++keypoint) - allKeypoints[keypoint->octave].push_back(*keypoint); - - // Make sure we rescale the coordinates - for (int level = 0; level < levelsNum; ++level) + if( !sortedByLevel ) { - if (level == firstLevel) - continue; - - std::vector & keypoints = allKeypoints[level]; - float scale = 1/getScale(level, firstLevel, scaleFactor); - for (std::vector::iterator keypoint = keypoints.begin(), - keypointEnd = keypoints.end(); keypoint != keypointEnd; ++keypoint) - keypoint->pt *= scale; + std::vector > allKeypoints(nLevels); + nkeypoints = (int)keypoints.size(); + for( i = 0; i < nkeypoints; i++ ) + { + level = keypoints[i].octave; + CV_Assert(0 <= level); + allKeypoints[level].push_back(keypoints[i]); + } + keypoints.clear(); + for( level = 0; level < nLevels; level++ ) + std::copy(allKeypoints[level].begin(), allKeypoints[level].end(), std::back_inserter(keypoints)); } } - Mat descriptors; - std::vector pattern; - if( do_descriptors ) { - int nkeypoints = 0; - for (int level = 0; level < levelsNum; ++level) - nkeypoints += (int)allKeypoints[level].size(); + int dsize = descriptorSize(); + + nkeypoints = (int)keypoints.size(); if( nkeypoints == 0 ) - _descriptors.release(); - else { - _descriptors.create(nkeypoints, descriptorSize(), CV_8U); - descriptors = _descriptors.getMat(); + _descriptors.release(); + return; } + _descriptors.create(nkeypoints, dsize, CV_8U); + std::vector pattern; + const int npoints = 512; Point patternbuf[npoints]; const Point* pattern0 = (const Point*)bit_pattern_31_; @@ -903,43 +1083,36 @@ void ORB::operator()( InputArray _image, InputArray _mask, std::vector int ntuples = descriptorSize()*4; initializeOrbPattern(pattern0, pattern, ntuples, WTA_K, npoints); } - } - _keypoints.clear(); - int offset = 0; - for (int level = 0; level < levelsNum; ++level) - { - // Get the features and compute their orientation - std::vector& keypoints = allKeypoints[level]; - int nkeypoints = (int)keypoints.size(); - - // Compute the descriptors - if (do_descriptors) + for( level = 0; level < nLevels; level++ ) { - Mat desc; - if (!descriptors.empty()) - { - desc = descriptors.rowRange(offset, offset + nkeypoints); - } - - offset += nkeypoints; // preprocess the resized image - Mat& workingMat = imagePyramid[level]; + Mat workingMat = imagePyramid(layerInfo[level]); + //boxFilter(working_mat, working_mat, working_mat.depth(), Size(5,5), Point(-1,-1), true, BORDER_REFLECT_101); GaussianBlur(workingMat, workingMat, Size(7, 7), 2, 2, BORDER_REFLECT_101); - computeDescriptors(workingMat, keypoints, desc, pattern, descriptorSize(), WTA_K); } - // Copy to the output data - if (level != firstLevel) + if( useOCL ) { - float scale = getScale(level, firstLevel, scaleFactor); - for (std::vector::iterator keypoint = keypoints.begin(), - keypointEnd = keypoints.end(); keypoint != keypointEnd; ++keypoint) - keypoint->pt *= scale; + imagePyramid.copyTo(uimagePyramid); + std::vector kptbuf; + UMat ukeypoints, upattern; + copyVectorToUMat(pattern, upattern); + uploadORBKeypoints(keypoints, layerScale, kptbuf, ukeypoints); + + UMat udescriptors = _descriptors.getUMat(); + useOCL = ocl_computeOrbDescriptors(uimagePyramid, ulayerInfo, + ukeypoints, udescriptors, upattern, + nkeypoints, dsize, WTA_K); + } + + if( !useOCL ) + { + Mat descriptors = _descriptors.getMat(); + computeOrbDescriptors(imagePyramid, layerInfo, layerScale, + keypoints, descriptors, pattern, dsize, WTA_K); } - // And add the keypoints to the output - _keypoints.insert(_keypoints.end(), keypoints.begin(), keypoints.end()); } } From 42e604abea2f1f36b321fa58937d2d2d46d2aabf Mon Sep 17 00:00:00 2001 From: Vadim Pisarevsky Date: Thu, 13 Mar 2014 23:17:28 +0400 Subject: [PATCH 5/6] fixed bug in FAST --- modules/features2d/src/fast.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/modules/features2d/src/fast.cpp b/modules/features2d/src/fast.cpp index beca7d6ec8..92059dc2d1 100644 --- a/modules/features2d/src/fast.cpp +++ b/modules/features2d/src/fast.cpp @@ -332,7 +332,7 @@ void FAST(InputArray _img, std::vector& keypoints, int threshold, bool { if( ocl::useOpenCL() && _img.isUMat() && type == FastFeatureDetector::TYPE_9_16 && ocl_FAST(_img, keypoints, threshold, nonmax_suppression, 10000)) - ; + return; switch(type) { case FastFeatureDetector::TYPE_5_8: From 4fafab37867b3e1834634d6c78671fececefffd5 Mon Sep 17 00:00:00 2001 From: Vadim Pisarevsky Date: Thu, 13 Mar 2014 23:18:41 +0400 Subject: [PATCH 6/6] fixed extra whitespace --- modules/features2d/src/fast.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/modules/features2d/src/fast.cpp b/modules/features2d/src/fast.cpp index 92059dc2d1..c01cbba698 100644 --- a/modules/features2d/src/fast.cpp +++ b/modules/features2d/src/fast.cpp @@ -323,7 +323,7 @@ static bool ocl_FAST( InputArray _img, std::vector& keypoints, for( i = 0; i < newcounter; i++ ) keypoints.push_back(KeyPoint((float)pt2[i].x, (float)pt2[i].y, 7.f, -1, (float)pt2[i].z)); } - + return true; }