615 lines
22 KiB
C++
615 lines
22 KiB
C++
/*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) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage 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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// 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 materials 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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// We follow to these papers:
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// 1) Construction of panoramic mosaics with global and local alignment.
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// Heung-Yeung Shum and Richard Szeliski. 2000.
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// 2) Eliminating Ghosting and Exposure Artifacts in Image Mosaics.
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// Matthew Uyttendaele, Ashley Eden and Richard Szeliski. 2001.
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// 3) Automatic Panoramic Image Stitching using Invariant Features.
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// Matthew Brown and David G. Lowe. 2007.
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#include "precomp.hpp"
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#include "util.hpp"
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#include "warpers.hpp"
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#include "blenders.hpp"
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#include "seam_finders.hpp"
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#include "motion_estimators.hpp"
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#include "exposure_compensate.hpp"
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using namespace std;
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using namespace cv;
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void printUsage()
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{
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cout <<
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"Rotation model images stitcher.\n\n"
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"opencv_stitching img1 img2 [...imgN] [flags]\n\n"
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"Flags:\n"
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" --preview\n"
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" Run stitching in the preview mode. Works faster than usual mode,\n"
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" but output image will have lower resolution.\n"
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" --try_gpu (yes|no)\n"
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" Try to use GPU. The default value is 'no'. All default values\n"
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" are for CPU mode.\n"
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"\nMotion Estimation Flags:\n"
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" --work_megapix <float>\n"
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" Resolution for image registration step. The default is 0.6 Mpx.\n"
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" --match_conf <float>\n"
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" Confidence for feature matching step. The default is 0.65.\n"
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" --conf_thresh <float>\n"
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" Threshold for two images are from the same panorama confidence.\n"
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" The default is 1.0.\n"
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" --ba (ray|focal_ray)\n"
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" Bundle adjustment cost function. The default is 'focal_ray'.\n"
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" --wave_correct (no|yes)\n"
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" Perform wave effect correction. The default is 'yes'.\n"
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"\nCompositing Flags:\n"
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" --warp (plane|cylindrical|spherical)\n"
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" Warp surface type. The default is 'spherical'.\n"
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" --seam_megapix <float>\n"
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" Resolution for seam estimation step. The default is 0.1 Mpx.\n"
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" --seam (no|voronoi|gc_color|gc_colorgrad)\n"
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" Seam estimation method. The default is 'gc_color'.\n"
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" --compose_megapix <float>\n"
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" Resolution for compositing step. Use -1 for original resolution.\n"
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" The default is -1.\n"
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" --expos_comp (no|gain|gain_blocks)\n"
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" Exposure compensation method. The default is 'gain_blocks'.\n"
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" --blend (no|feather|multiband)\n"
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" Blending method. The default is 'multiband'.\n"
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" --blend_strength <float>\n"
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" Blending strength from [0,100] range. The default is 5.\n"
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" --output <result_img>\n"
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" The default is 'result.jpg'.\n";
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}
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// Default command line args
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vector<string> img_names;
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bool preview = false;
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bool try_gpu = false;
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double work_megapix = 0.6;
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double seam_megapix = 0.1;
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double compose_megapix = -1;
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int ba_space = BundleAdjuster::FOCAL_RAY_SPACE;
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float conf_thresh = 1.f;
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bool wave_correct = true;
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int warp_type = Warper::SPHERICAL;
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int expos_comp_type = ExposureCompensator::GAIN_BLOCKS;
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float match_conf = 0.65f;
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int seam_find_type = SeamFinder::GC_COLOR;
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int blend_type = Blender::MULTI_BAND;
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float blend_strength = 5;
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string result_name = "result.jpg";
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int parseCmdArgs(int argc, char** argv)
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{
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if (argc == 1)
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{
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printUsage();
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return -1;
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}
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for (int i = 1; i < argc; ++i)
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{
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if (string(argv[i]) == "--help" || string(argv[i]) == "/?")
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{
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printUsage();
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return -1;
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}
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else if (string(argv[i]) == "--preview")
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{
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preview = true;
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}
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else if (string(argv[i]) == "--try_gpu")
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{
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if (string(argv[i + 1]) == "no")
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try_gpu = false;
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else if (string(argv[i + 1]) == "yes")
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try_gpu = true;
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else
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{
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cout << "Bad --try_gpu flag value\n";
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return -1;
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}
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i++;
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}
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else if (string(argv[i]) == "--work_megapix")
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{
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work_megapix = atof(argv[i + 1]);
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i++;
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}
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else if (string(argv[i]) == "--seam_megapix")
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{
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seam_megapix = atof(argv[i + 1]);
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i++;
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}
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else if (string(argv[i]) == "--compose_megapix")
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{
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compose_megapix = atof(argv[i + 1]);
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i++;
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}
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else if (string(argv[i]) == "--result")
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{
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result_name = argv[i + 1];
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i++;
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}
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else if (string(argv[i]) == "--match_conf")
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{
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match_conf = static_cast<float>(atof(argv[i + 1]));
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i++;
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}
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else if (string(argv[i]) == "--ba")
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{
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if (string(argv[i + 1]) == "ray")
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ba_space = BundleAdjuster::RAY_SPACE;
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else if (string(argv[i + 1]) == "focal_ray")
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ba_space = BundleAdjuster::FOCAL_RAY_SPACE;
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else
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{
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cout << "Bad bundle adjustment space\n";
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return -1;
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}
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i++;
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}
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else if (string(argv[i]) == "--conf_thresh")
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{
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conf_thresh = static_cast<float>(atof(argv[i + 1]));
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i++;
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}
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else if (string(argv[i]) == "--wave_correct")
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{
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if (string(argv[i + 1]) == "no")
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wave_correct = false;
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else if (string(argv[i + 1]) == "yes")
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wave_correct = true;
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else
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{
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cout << "Bad --wave_correct flag value\n";
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return -1;
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}
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i++;
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}
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else if (string(argv[i]) == "--warp")
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{
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if (string(argv[i + 1]) == "plane")
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warp_type = Warper::PLANE;
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else if (string(argv[i + 1]) == "cylindrical")
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warp_type = Warper::CYLINDRICAL;
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else if (string(argv[i + 1]) == "spherical")
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warp_type = Warper::SPHERICAL;
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else
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{
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cout << "Bad warping method\n";
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return -1;
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}
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i++;
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}
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else if (string(argv[i]) == "--expos_comp")
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{
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if (string(argv[i + 1]) == "no")
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expos_comp_type = ExposureCompensator::NO;
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else if (string(argv[i + 1]) == "gain")
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expos_comp_type = ExposureCompensator::GAIN;
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else if (string(argv[i + 1]) == "gain_blocks")
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expos_comp_type = ExposureCompensator::GAIN_BLOCKS;
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else
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{
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cout << "Bad exposure compensation method\n";
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return -1;
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}
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i++;
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}
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else if (string(argv[i]) == "--seam")
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{
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if (string(argv[i + 1]) == "no")
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seam_find_type = SeamFinder::NO;
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else if (string(argv[i + 1]) == "voronoi")
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seam_find_type = SeamFinder::VORONOI;
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else if (string(argv[i + 1]) == "gc_color")
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seam_find_type = SeamFinder::GC_COLOR;
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else if (string(argv[i + 1]) == "gc_colorgrad")
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seam_find_type = SeamFinder::GC_COLOR_GRAD;
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else
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{
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cout << "Bad seam finding method\n";
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return -1;
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}
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i++;
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}
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else if (string(argv[i]) == "--blend")
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{
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if (string(argv[i + 1]) == "no")
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blend_type = Blender::NO;
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else if (string(argv[i + 1]) == "feather")
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blend_type = Blender::FEATHER;
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else if (string(argv[i + 1]) == "multiband")
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blend_type = Blender::MULTI_BAND;
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else
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{
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cout << "Bad blending method\n";
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return -1;
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}
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i++;
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}
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else if (string(argv[i]) == "--blend_strength")
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{
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blend_strength = static_cast<float>(atof(argv[i + 1]));
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i++;
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}
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else if (string(argv[i]) == "--output")
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{
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result_name = argv[i + 1];
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i++;
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}
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else
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img_names.push_back(argv[i]);
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}
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if (preview)
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{
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compose_megapix = 0.6;
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}
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return 0;
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}
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int main(int argc, char* argv[])
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{
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int64 app_start_time = getTickCount();
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cv::setBreakOnError(true);
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int retval = parseCmdArgs(argc, argv);
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if (retval)
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return retval;
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// Check if have enough images
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int num_images = static_cast<int>(img_names.size());
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if (num_images < 2)
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{
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LOGLN("Need more images");
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return -1;
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}
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double work_scale = 1, seam_scale = 1, compose_scale = 1;
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bool is_work_scale_set = false, is_seam_scale_set = false, is_compose_scale_set = false;
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LOGLN("Finding features...");
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int64 t = getTickCount();
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vector<ImageFeatures> features(num_images);
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SurfFeaturesFinder finder(try_gpu);
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Mat full_img, img;
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vector<Mat> images(num_images);
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vector<Size> full_img_sizes(num_images);
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double seam_work_aspect = 1;
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for (int i = 0; i < num_images; ++i)
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{
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full_img = imread(img_names[i]);
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full_img_sizes[i] = full_img.size();
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if (full_img.empty())
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{
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LOGLN("Can't open image " << img_names[i]);
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return -1;
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}
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if (work_megapix < 0)
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{
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img = full_img;
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work_scale = 1;
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is_work_scale_set = true;
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}
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else
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{
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if (!is_work_scale_set)
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{
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work_scale = min(1.0, sqrt(work_megapix * 1e6 / full_img.size().area()));
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is_work_scale_set = true;
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}
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resize(full_img, img, Size(), work_scale, work_scale);
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}
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if (!is_seam_scale_set)
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{
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seam_scale = min(1.0, sqrt(seam_megapix * 1e6 / full_img.size().area()));
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seam_work_aspect = seam_scale / work_scale;
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is_seam_scale_set = true;
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}
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finder(img, features[i]);
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features[i].img_idx = i;
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LOGLN("Features in image #" << i+1 << ": " << features[i].keypoints.size());
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resize(full_img, img, Size(), seam_scale, seam_scale);
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images[i] = img.clone();
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}
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finder.releaseMemory();
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full_img.release();
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img.release();
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LOGLN("Finding features, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
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LOG("Pairwise matching");
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t = getTickCount();
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vector<MatchesInfo> pairwise_matches;
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BestOf2NearestMatcher matcher(try_gpu, match_conf);
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matcher(features, pairwise_matches);
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matcher.releaseMemory();
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LOGLN("Pairwise matching, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
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// Leave only images we are sure are from the same panorama
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vector<int> indices = leaveBiggestComponent(features, pairwise_matches, conf_thresh);
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vector<Mat> img_subset;
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vector<string> img_names_subset;
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vector<Size> full_img_sizes_subset;
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for (size_t i = 0; i < indices.size(); ++i)
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{
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img_names_subset.push_back(img_names[indices[i]]);
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img_subset.push_back(images[indices[i]]);
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full_img_sizes_subset.push_back(full_img_sizes[indices[i]]);
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}
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images = img_subset;
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img_names = img_names_subset;
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full_img_sizes = full_img_sizes_subset;
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// Check if we still have enough images
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num_images = static_cast<int>(img_names.size());
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if (num_images < 2)
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{
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LOGLN("Need more images");
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return -1;
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}
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LOGLN("Estimating rotations...");
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t = getTickCount();
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HomographyBasedEstimator estimator;
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vector<CameraParams> cameras;
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estimator(features, pairwise_matches, cameras);
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LOGLN("Estimating rotations, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
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for (size_t i = 0; i < cameras.size(); ++i)
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{
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Mat R;
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cameras[i].R.convertTo(R, CV_32F);
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cameras[i].R = R;
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LOGLN("Initial focal length #" << indices[i]+1 << ": " << cameras[i].focal);
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}
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LOG("Bundle adjustment");
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t = getTickCount();
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BundleAdjuster adjuster(ba_space, conf_thresh);
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adjuster(features, pairwise_matches, cameras);
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LOGLN("Bundle adjustment, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
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// Find median focal length
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vector<double> focals;
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for (size_t i = 0; i < cameras.size(); ++i)
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{
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LOGLN("Camera #" << indices[i]+1 << " focal length: " << cameras[i].focal);
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focals.push_back(cameras[i].focal);
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}
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nth_element(focals.begin(), focals.begin() + focals.size()/2, focals.end());
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float warped_image_scale = static_cast<float>(focals[focals.size() / 2]);
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if (wave_correct)
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{
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LOGLN("Wave correcting...");
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t = getTickCount();
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vector<Mat> rmats;
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for (size_t i = 0; i < cameras.size(); ++i)
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rmats.push_back(cameras[i].R);
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waveCorrect(rmats);
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for (size_t i = 0; i < cameras.size(); ++i)
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cameras[i].R = rmats[i];
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LOGLN("Wave correcting, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
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}
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LOGLN("Warping images (auxiliary)... ");
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t = getTickCount();
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vector<Point> corners(num_images);
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vector<Mat> masks_warped(num_images);
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vector<Mat> images_warped(num_images);
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vector<Size> sizes(num_images);
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vector<Mat> masks(num_images);
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// Preapre images masks
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for (int i = 0; i < num_images; ++i)
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{
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masks[i].create(images[i].size(), CV_8U);
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masks[i].setTo(Scalar::all(255));
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}
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// Warp images and their masks
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Ptr<Warper> warper = Warper::createByCameraFocal(static_cast<float>(warped_image_scale * seam_work_aspect),
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warp_type, try_gpu);
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for (int i = 0; i < num_images; ++i)
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{
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corners[i] = warper->warp(images[i], static_cast<float>(cameras[i].focal * seam_work_aspect),
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cameras[i].R, images_warped[i]);
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sizes[i] = images_warped[i].size();
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warper->warp(masks[i], static_cast<float>(cameras[i].focal * seam_work_aspect),
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cameras[i].R, masks_warped[i], INTER_NEAREST, BORDER_CONSTANT);
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}
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vector<Mat> images_warped_f(num_images);
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for (int i = 0; i < num_images; ++i)
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images_warped[i].convertTo(images_warped_f[i], CV_32F);
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LOGLN("Warping images, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
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LOGLN("Exposure compensation (feed)...");
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t = getTickCount();
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Ptr<ExposureCompensator> compensator = ExposureCompensator::createDefault(expos_comp_type);
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compensator->feed(corners, images_warped, masks_warped);
|
|
LOGLN("Exposure compensation (feed), time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
|
|
|
|
LOGLN("Finding seams...");
|
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t = getTickCount();
|
|
Ptr<SeamFinder> seam_finder = SeamFinder::createDefault(seam_find_type);
|
|
seam_finder->find(images_warped_f, corners, masks_warped);
|
|
LOGLN("Finding seams, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
|
|
|
|
// Release unused memory
|
|
images.clear();
|
|
images_warped.clear();
|
|
images_warped_f.clear();
|
|
masks.clear();
|
|
|
|
LOGLN("Compositing...");
|
|
t = getTickCount();
|
|
|
|
Mat img_warped, img_warped_s;
|
|
Mat dilated_mask, seam_mask, mask, mask_warped;
|
|
Ptr<Blender> blender;
|
|
double compose_seam_aspect = 1;
|
|
double compose_work_aspect = 1;
|
|
|
|
for (int img_idx = 0; img_idx < num_images; ++img_idx)
|
|
{
|
|
LOGLN("Compositing image #" << indices[img_idx]+1);
|
|
|
|
// Read image and resize it if necessary
|
|
full_img = imread(img_names[img_idx]);
|
|
if (!is_compose_scale_set)
|
|
{
|
|
if (compose_megapix > 0)
|
|
compose_scale = min(1.0, sqrt(compose_megapix * 1e6 / full_img.size().area()));
|
|
is_compose_scale_set = true;
|
|
|
|
// Compute relative scales
|
|
compose_seam_aspect = compose_scale / seam_scale;
|
|
compose_work_aspect = compose_scale / work_scale;
|
|
|
|
// Update warped image scale
|
|
warped_image_scale *= static_cast<float>(compose_work_aspect);
|
|
warper = Warper::createByCameraFocal(warped_image_scale, warp_type, try_gpu);
|
|
|
|
// Update corners and sizes
|
|
for (int i = 0; i < num_images; ++i)
|
|
{
|
|
// Update camera focal
|
|
cameras[i].focal *= compose_work_aspect;
|
|
|
|
// Update corner and size
|
|
Size sz = full_img_sizes[i];
|
|
if (abs(compose_scale - 1) > 1e-1)
|
|
{
|
|
sz.width = cvRound(full_img_sizes[i].width * compose_scale);
|
|
sz.height = cvRound(full_img_sizes[i].height * compose_scale);
|
|
}
|
|
Rect roi = warper->warpRoi(sz, static_cast<float>(cameras[i].focal), cameras[i].R);
|
|
corners[i] = roi.tl();
|
|
sizes[i] = roi.size();
|
|
}
|
|
}
|
|
if (abs(compose_scale - 1) > 1e-1)
|
|
resize(full_img, img, Size(), compose_scale, compose_scale);
|
|
else
|
|
img = full_img;
|
|
full_img.release();
|
|
Size img_size = img.size();
|
|
|
|
// Warp the current image
|
|
warper->warp(img, static_cast<float>(cameras[img_idx].focal), cameras[img_idx].R,
|
|
img_warped);
|
|
|
|
// Warp the current image mask
|
|
mask.create(img_size, CV_8U);
|
|
mask.setTo(Scalar::all(255));
|
|
warper->warp(mask, static_cast<float>(cameras[img_idx].focal), cameras[img_idx].R, mask_warped,
|
|
INTER_NEAREST, BORDER_CONSTANT);
|
|
|
|
// Compensate exposure
|
|
compensator->apply(img_idx, corners[img_idx], img_warped, mask_warped);
|
|
|
|
img_warped.convertTo(img_warped_s, CV_16S);
|
|
img_warped.release();
|
|
img.release();
|
|
mask.release();
|
|
|
|
dilate(masks_warped[img_idx], dilated_mask, Mat());
|
|
resize(dilated_mask, seam_mask, mask_warped.size());
|
|
mask_warped = seam_mask & mask_warped;
|
|
|
|
if (blender.empty())
|
|
{
|
|
blender = Blender::createDefault(blend_type, try_gpu);
|
|
Size dst_sz = resultRoi(corners, sizes).size();
|
|
float blend_width = sqrt(static_cast<float>(dst_sz.area())) * blend_strength / 100.f;
|
|
if (blend_width < 1.f)
|
|
blender = Blender::createDefault(Blender::NO, try_gpu);
|
|
else if (blend_type == Blender::MULTI_BAND)
|
|
{
|
|
MultiBandBlender* mb = dynamic_cast<MultiBandBlender*>(static_cast<Blender*>(blender));
|
|
mb->setNumBands(static_cast<int>(ceil(log(blend_width)/log(2.)) - 1.));
|
|
LOGLN("Multi-band blender, number of bands: " << mb->numBands());
|
|
}
|
|
else if (blend_type == Blender::FEATHER)
|
|
{
|
|
FeatherBlender* fb = dynamic_cast<FeatherBlender*>(static_cast<Blender*>(blender));
|
|
fb->setSharpness(1.f/blend_width);
|
|
LOGLN("Feather blender, number of bands: " << fb->sharpness());
|
|
}
|
|
blender->prepare(corners, sizes);
|
|
}
|
|
|
|
// Blend the current image
|
|
blender->feed(img_warped_s, mask_warped, corners[img_idx]);
|
|
}
|
|
|
|
Mat result, result_mask;
|
|
blender->blend(result, result_mask);
|
|
|
|
LOGLN("Compositing, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec");
|
|
|
|
imwrite(result_name, result);
|
|
|
|
LOGLN("Finished, total time: " << ((getTickCount() - app_start_time) / getTickFrequency()) << " sec");
|
|
return 0;
|
|
}
|
|
|
|
|