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revise ocl samples, add tvl1 sample
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yao
+79
-126
@@ -1,48 +1,3 @@
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
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// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// @Authors
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// Peng Xiao, pengxiao@multicorewareinc.com
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other oclMaterials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors as is and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include <iostream>
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#include <stdio.h>
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#include "opencv2/core/core.hpp"
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@@ -61,27 +16,20 @@ const float GOOD_PORTION = 0.15f;
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namespace
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{
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void help();
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void help()
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{
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std::cout << "\nThis program demonstrates using SURF_OCL features detector and descriptor extractor" << std::endl;
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std::cout << "\nUsage:\n\tsurf_matcher --left <image1> --right <image2> [-c]" << std::endl;
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std::cout << "\nExample:\n\tsurf_matcher --left box.png --right box_in_scene.png" << std::endl;
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}
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int64 work_begin = 0;
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int64 work_end = 0;
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void workBegin()
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{
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void workBegin()
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{
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work_begin = getTickCount();
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}
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void workEnd()
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{
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work_end = getTickCount() - work_begin;
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}
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double getTime(){
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double getTime()
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{
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return work_end /((double)cvGetTickFrequency() * 1000.);
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}
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@@ -114,17 +62,17 @@ struct SURFMatcher
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Mat drawGoodMatches(
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const Mat& cpu_img1,
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const Mat& cpu_img2,
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const vector<KeyPoint>& keypoints1,
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const vector<KeyPoint>& keypoints2,
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const vector<KeyPoint>& keypoints1,
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const vector<KeyPoint>& keypoints2,
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vector<DMatch>& matches,
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vector<Point2f>& scene_corners_
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)
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)
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{
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//-- Sort matches and preserve top 10% matches
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//-- Sort matches and preserve top 10% matches
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std::sort(matches.begin(), matches.end());
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std::vector< DMatch > good_matches;
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double minDist = matches.front().distance,
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maxDist = matches.back().distance;
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maxDist = matches.back().distance;
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const int ptsPairs = std::min(GOOD_PTS_MAX, (int)(matches.size() * GOOD_PORTION));
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for( int i = 0; i < ptsPairs; i++ )
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@@ -139,8 +87,8 @@ Mat drawGoodMatches(
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// drawing the results
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Mat img_matches;
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drawMatches( cpu_img1, keypoints1, cpu_img2, keypoints2,
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good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
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vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
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good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
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vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
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//-- Localize the object
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std::vector<Point2f> obj;
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@@ -154,28 +102,30 @@ Mat drawGoodMatches(
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}
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//-- Get the corners from the image_1 ( the object to be "detected" )
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std::vector<Point2f> obj_corners(4);
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obj_corners[0] = cvPoint(0,0); obj_corners[1] = cvPoint( cpu_img1.cols, 0 );
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obj_corners[2] = cvPoint( cpu_img1.cols, cpu_img1.rows ); obj_corners[3] = cvPoint( 0, cpu_img1.rows );
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obj_corners[0] = cvPoint(0,0);
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obj_corners[1] = cvPoint( cpu_img1.cols, 0 );
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obj_corners[2] = cvPoint( cpu_img1.cols, cpu_img1.rows );
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obj_corners[3] = cvPoint( 0, cpu_img1.rows );
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std::vector<Point2f> scene_corners(4);
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Mat H = findHomography( obj, scene, CV_RANSAC );
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perspectiveTransform( obj_corners, scene_corners, H);
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scene_corners_ = scene_corners;
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//-- Draw lines between the corners (the mapped object in the scene - image_2 )
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line( img_matches,
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scene_corners[0] + Point2f( (float)cpu_img1.cols, 0), scene_corners[1] + Point2f( (float)cpu_img1.cols, 0),
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Scalar( 0, 255, 0), 2, CV_AA );
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line( img_matches,
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scene_corners[1] + Point2f( (float)cpu_img1.cols, 0), scene_corners[2] + Point2f( (float)cpu_img1.cols, 0),
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Scalar( 0, 255, 0), 2, CV_AA );
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line( img_matches,
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scene_corners[2] + Point2f( (float)cpu_img1.cols, 0), scene_corners[3] + Point2f( (float)cpu_img1.cols, 0),
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Scalar( 0, 255, 0), 2, CV_AA );
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line( img_matches,
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scene_corners[3] + Point2f( (float)cpu_img1.cols, 0), scene_corners[0] + Point2f( (float)cpu_img1.cols, 0),
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Scalar( 0, 255, 0), 2, CV_AA );
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line( img_matches,
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scene_corners[0] + Point2f( (float)cpu_img1.cols, 0), scene_corners[1] + Point2f( (float)cpu_img1.cols, 0),
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Scalar( 0, 255, 0), 2, CV_AA );
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line( img_matches,
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scene_corners[1] + Point2f( (float)cpu_img1.cols, 0), scene_corners[2] + Point2f( (float)cpu_img1.cols, 0),
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Scalar( 0, 255, 0), 2, CV_AA );
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line( img_matches,
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scene_corners[2] + Point2f( (float)cpu_img1.cols, 0), scene_corners[3] + Point2f( (float)cpu_img1.cols, 0),
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Scalar( 0, 255, 0), 2, CV_AA );
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line( img_matches,
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scene_corners[3] + Point2f( (float)cpu_img1.cols, 0), scene_corners[0] + Point2f( (float)cpu_img1.cols, 0),
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Scalar( 0, 255, 0), 2, CV_AA );
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return img_matches;
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}
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@@ -185,6 +135,21 @@ Mat drawGoodMatches(
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// use cpu findHomography interface to calculate the transformation matrix
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int main(int argc, char* argv[])
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{
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const char* keys =
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"{ h | help | false | print help message }"
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"{ l | left | | specify left image }"
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"{ r | right | | specify right image }"
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"{ o | output | SURF_output.jpg | specify output save path (only works in CPU or GPU only mode) }"
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"{ c | use_cpu | false | use CPU algorithms }"
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"{ a | use_all | false | use both CPU and GPU algorithms}";
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CommandLineParser cmd(argc, argv, keys);
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if (cmd.get<bool>("help"))
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{
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std::cout << "Avaible options:" << std::endl;
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cmd.printParams();
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return 0;
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}
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vector<cv::ocl::Info> info;
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if(cv::ocl::getDevice(info) == 0)
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{
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@@ -195,54 +160,38 @@ int main(int argc, char* argv[])
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Mat cpu_img1, cpu_img2, cpu_img1_grey, cpu_img2_grey;
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oclMat img1, img2;
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bool useCPU = false;
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bool useCPU = cmd.get<bool>("c");
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bool useGPU = false;
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bool useALL = false;
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bool useALL = cmd.get<bool>("a");
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for (int i = 1; i < argc; ++i)
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string outpath = cmd.get<std::string>("o");
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cpu_img1 = imread(cmd.get<std::string>("l"));
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CV_Assert(!cpu_img1.empty());
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cvtColor(cpu_img1, cpu_img1_grey, CV_BGR2GRAY);
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img1 = cpu_img1_grey;
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cpu_img2 = imread(cmd.get<std::string>("r"));
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CV_Assert(!cpu_img2.empty());
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cvtColor(cpu_img2, cpu_img2_grey, CV_BGR2GRAY);
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img2 = cpu_img2_grey;
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if(useALL)
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{
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if (string(argv[i]) == "--left")
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{
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cpu_img1 = imread(argv[++i]);
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CV_Assert(!cpu_img1.empty());
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cvtColor(cpu_img1, cpu_img1_grey, CV_BGR2GRAY);
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img1 = cpu_img1_grey;
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}
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else if (string(argv[i]) == "--right")
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{
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cpu_img2 = imread(argv[++i]);
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CV_Assert(!cpu_img2.empty());
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cvtColor(cpu_img2, cpu_img2_grey, CV_BGR2GRAY);
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img2 = cpu_img2_grey;
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}
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else if (string(argv[i]) == "-c")
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{
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useCPU = true;
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useGPU = false;
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useALL = false;
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}else if(string(argv[i]) == "-g")
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{
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useGPU = true;
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useCPU = false;
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useALL = false;
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}else if(string(argv[i]) == "-a")
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{
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useALL = true;
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useCPU = false;
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useGPU = false;
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}
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else if (string(argv[i]) == "--help")
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{
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help();
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return -1;
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}
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useCPU = false;
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useGPU = false;
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}
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else if(useCPU==false && useALL==false)
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{
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useGPU = true;
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}
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if(!useCPU)
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{
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std::cout
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<< "Device name:"
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<< info[0].DeviceName[0]
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<< std::endl;
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<< "Device name:"
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<< info[0].DeviceName[0]
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<< std::endl;
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}
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double surf_time = 0.;
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@@ -262,12 +211,12 @@ int main(int argc, char* argv[])
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//instantiate detectors/matchers
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SURFDetector<SURF> cpp_surf;
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SURFDetector<SURF_OCL> ocl_surf;
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SURFMatcher<BFMatcher> cpp_matcher;
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SURFMatcher<BFMatcher_OCL> ocl_matcher;
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//-- start of timing section
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if (useCPU)
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if (useCPU)
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{
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for (int i = 0; i <= LOOP_NUM; i++)
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{
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@@ -298,7 +247,8 @@ int main(int argc, char* argv[])
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surf_time = getTime();
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std::cout << "SURF run time: " << surf_time / LOOP_NUM << " ms" << std::endl<<"\n";
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}else
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}
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else
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{
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//cpu runs
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for (int i = 0; i <= LOOP_NUM; i++)
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@@ -353,14 +303,14 @@ int main(int argc, char* argv[])
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for(size_t i = 0; i < cpu_corner.size(); i++)
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{
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if((std::abs(cpu_corner[i].x - gpu_corner[i].x) > 10)
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||(std::abs(cpu_corner[i].y - gpu_corner[i].y) > 10))
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||(std::abs(cpu_corner[i].y - gpu_corner[i].y) > 10))
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{
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std::cout<<"Failed\n";
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result = false;
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break;
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}
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result = true;
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}
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}
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if(result)
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std::cout<<"Passed\n";
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}
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@@ -371,12 +321,15 @@ int main(int argc, char* argv[])
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{
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namedWindow("cpu surf matches", 0);
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imshow("cpu surf matches", img_matches);
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imwrite(outpath, img_matches);
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}
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else if(useGPU)
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{
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namedWindow("ocl surf matches", 0);
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imshow("ocl surf matches", img_matches);
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}else
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imwrite(outpath, img_matches);
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}
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else
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{
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namedWindow("cpu surf matches", 0);
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imshow("cpu surf matches", img_matches);
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