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755 lines
27 KiB
755 lines
27 KiB
/*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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// |
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//M*/ |
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#include <iostream> |
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#include <fstream> |
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#include <string> |
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#include "opencv2/opencv_modules.hpp" |
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#include "opencv2/highgui/highgui.hpp" |
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#include "opencv2/stitching/detail/autocalib.hpp" |
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#include "opencv2/stitching/detail/blenders.hpp" |
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#include "opencv2/stitching/detail/camera.hpp" |
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#include "opencv2/stitching/detail/exposure_compensate.hpp" |
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#include "opencv2/stitching/detail/matchers.hpp" |
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#include "opencv2/stitching/detail/motion_estimators.hpp" |
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#include "opencv2/stitching/detail/seam_finders.hpp" |
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#include "opencv2/stitching/detail/util.hpp" |
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#include "opencv2/stitching/detail/warpers.hpp" |
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#include "opencv2/stitching/warpers.hpp" |
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using namespace std; |
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using namespace cv; |
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using namespace cv::detail; |
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static 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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"stitching_detailed 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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" --features (surf|orb)\n" |
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" Type of features used for images matching. The default is surf.\n" |
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" --match_conf <float>\n" |
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" Confidence for feature matching step. The default is 0.65 for surf and 0.3 for orb.\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 (reproj|ray)\n" |
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" Bundle adjustment cost function. The default is ray.\n" |
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" --ba_refine_mask (mask)\n" |
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" Set refinement mask for bundle adjustment. It looks like 'x_xxx',\n" |
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" where 'x' means refine respective parameter and '_' means don't\n" |
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" refine one, and has the following format:\n" |
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" <fx><skew><ppx><aspect><ppy>. The default mask is 'xxxxx'. If bundle\n" |
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" adjustment doesn't support estimation of selected parameter then\n" |
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" the respective flag is ignored.\n" |
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" --wave_correct (no|horiz|vert)\n" |
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" Perform wave effect correction. The default is 'horiz'.\n" |
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" --save_graph <file_name>\n" |
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" Save matches graph represented in DOT language to <file_name> file.\n" |
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" Labels description: Nm is number of matches, Ni is number of inliers,\n" |
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" C is confidence.\n" |
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"\nCompositing Flags:\n" |
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" --warp (plane|cylindrical|spherical|fisheye|stereographic|compressedPlaneA2B1|compressedPlaneA1.5B1|compressedPlanePortraitA2B1|compressedPlanePortraitA1.5B1|paniniA2B1|paniniA1.5B1|paniniPortraitA2B1|paniniPortraitA1.5B1|mercator|transverseMercator)\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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float conf_thresh = 1.f; |
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string features_type = "surf"; |
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string ba_cost_func = "ray"; |
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string ba_refine_mask = "xxxxx"; |
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bool do_wave_correct = true; |
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WaveCorrectKind wave_correct = detail::WAVE_CORRECT_HORIZ; |
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bool save_graph = false; |
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std::string save_graph_to; |
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string warp_type = "spherical"; |
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int expos_comp_type = ExposureCompensator::GAIN_BLOCKS; |
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float match_conf = 0.3f; |
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string seam_find_type = "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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static 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]) == "--features") |
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{ |
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features_type = argv[i + 1]; |
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if (features_type == "orb") |
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match_conf = 0.3f; |
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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]) == "--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]) == "--ba") |
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{ |
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ba_cost_func = argv[i + 1]; |
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i++; |
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} |
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else if (string(argv[i]) == "--ba_refine_mask") |
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{ |
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ba_refine_mask = argv[i + 1]; |
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if (ba_refine_mask.size() != 5) |
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{ |
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cout << "Incorrect refinement mask length.\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]) == "--wave_correct") |
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{ |
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if (string(argv[i + 1]) == "no") |
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do_wave_correct = false; |
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else if (string(argv[i + 1]) == "horiz") |
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{ |
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do_wave_correct = true; |
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wave_correct = detail::WAVE_CORRECT_HORIZ; |
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} |
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else if (string(argv[i + 1]) == "vert") |
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{ |
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do_wave_correct = true; |
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wave_correct = detail::WAVE_CORRECT_VERT; |
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} |
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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]) == "--save_graph") |
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{ |
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save_graph = true; |
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save_graph_to = argv[i + 1]; |
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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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warp_type = string(argv[i + 1]); |
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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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string(argv[i + 1]) == "voronoi" || |
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string(argv[i + 1]) == "gc_color" || |
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string(argv[i + 1]) == "gc_colorgrad" || |
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string(argv[i + 1]) == "dp_color" || |
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string(argv[i + 1]) == "dp_colorgrad") |
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seam_find_type = argv[i + 1]; |
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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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Ptr<FeaturesFinder> finder; |
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if (features_type == "surf") |
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{ |
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#ifdef HAVE_OPENCV_GPU |
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if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0) |
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finder = new SurfFeaturesFinderGpu(); |
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else |
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#endif |
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finder = new SurfFeaturesFinder(); |
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} |
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else if (features_type == "orb") |
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{ |
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finder = new OrbFeaturesFinder(); |
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} |
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else |
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{ |
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cout << "Unknown 2D features type: '" << features_type << "'.\n"; |
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return -1; |
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} |
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Mat full_img, img; |
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vector<ImageFeatures> features(num_images); |
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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->collectGarbage(); |
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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.collectGarbage(); |
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LOGLN("Pairwise matching, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); |
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// Check if we should save matches graph |
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if (save_graph) |
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{ |
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LOGLN("Saving matches graph..."); |
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ofstream f(save_graph_to.c_str()); |
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f << matchesGraphAsString(img_names, pairwise_matches, conf_thresh); |
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} |
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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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HomographyBasedEstimator estimator; |
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vector<CameraParams> cameras; |
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estimator(features, pairwise_matches, cameras); |
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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 intrinsics #" << indices[i]+1 << ":\n" << cameras[i].K()); |
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} |
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Ptr<detail::BundleAdjusterBase> adjuster; |
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if (ba_cost_func == "reproj") adjuster = new detail::BundleAdjusterReproj(); |
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else if (ba_cost_func == "ray") adjuster = new detail::BundleAdjusterRay(); |
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else |
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{ |
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cout << "Unknown bundle adjustment cost function: '" << ba_cost_func << "'.\n"; |
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return -1; |
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} |
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adjuster->setConfThresh(conf_thresh); |
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Mat_<uchar> refine_mask = Mat::zeros(3, 3, CV_8U); |
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if (ba_refine_mask[0] == 'x') refine_mask(0,0) = 1; |
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if (ba_refine_mask[1] == 'x') refine_mask(0,1) = 1; |
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if (ba_refine_mask[2] == 'x') refine_mask(0,2) = 1; |
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if (ba_refine_mask[3] == 'x') refine_mask(1,1) = 1; |
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if (ba_refine_mask[4] == 'x') refine_mask(1,2) = 1; |
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adjuster->setRefinementMask(refine_mask); |
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(*adjuster)(features, pairwise_matches, cameras); |
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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 << ":\n" << cameras[i].K()); |
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focals.push_back(cameras[i].focal); |
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} |
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sort(focals.begin(), focals.end()); |
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float warped_image_scale; |
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if (focals.size() % 2 == 1) |
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warped_image_scale = static_cast<float>(focals[focals.size() / 2]); |
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else |
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warped_image_scale = static_cast<float>(focals[focals.size() / 2 - 1] + focals[focals.size() / 2]) * 0.5f; |
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if (do_wave_correct) |
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{ |
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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, wave_correct); |
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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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} |
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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<WarperCreator> warper_creator; |
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#ifdef HAVE_OPENCV_GPU |
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if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0) |
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{ |
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if (warp_type == "plane") warper_creator = new cv::PlaneWarperGpu(); |
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else if (warp_type == "cylindrical") warper_creator = new cv::CylindricalWarperGpu(); |
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else if (warp_type == "spherical") warper_creator = new cv::SphericalWarperGpu(); |
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} |
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else |
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#endif |
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{ |
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if (warp_type == "plane") warper_creator = new cv::PlaneWarper(); |
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else if (warp_type == "cylindrical") warper_creator = new cv::CylindricalWarper(); |
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else if (warp_type == "spherical") warper_creator = new cv::SphericalWarper(); |
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else if (warp_type == "fisheye") warper_creator = new cv::FisheyeWarper(); |
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else if (warp_type == "stereographic") warper_creator = new cv::StereographicWarper(); |
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else if (warp_type == "compressedPlaneA2B1") warper_creator = new cv::CompressedRectilinearWarper(2, 1); |
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else if (warp_type == "compressedPlaneA1.5B1") warper_creator = new cv::CompressedRectilinearWarper(1.5, 1); |
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else if (warp_type == "compressedPlanePortraitA2B1") warper_creator = new cv::CompressedRectilinearPortraitWarper(2, 1); |
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else if (warp_type == "compressedPlanePortraitA1.5B1") warper_creator = new cv::CompressedRectilinearPortraitWarper(1.5, 1); |
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else if (warp_type == "paniniA2B1") warper_creator = new cv::PaniniWarper(2, 1); |
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else if (warp_type == "paniniA1.5B1") warper_creator = new cv::PaniniWarper(1.5, 1); |
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else if (warp_type == "paniniPortraitA2B1") warper_creator = new cv::PaniniPortraitWarper(2, 1); |
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else if (warp_type == "paniniPortraitA1.5B1") warper_creator = new cv::PaniniPortraitWarper(1.5, 1); |
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else if (warp_type == "mercator") warper_creator = new cv::MercatorWarper(); |
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else if (warp_type == "transverseMercator") warper_creator = new cv::TransverseMercatorWarper(); |
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} |
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if (warper_creator.empty()) |
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{ |
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cout << "Can't create the following warper '" << warp_type << "'\n"; |
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return 1; |
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} |
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Ptr<RotationWarper> warper = warper_creator->create(static_cast<float>(warped_image_scale * seam_work_aspect)); |
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for (int i = 0; i < num_images; ++i) |
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{ |
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Mat_<float> K; |
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cameras[i].K().convertTo(K, CV_32F); |
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float swa = (float)seam_work_aspect; |
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K(0,0) *= swa; K(0,2) *= swa; |
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K(1,1) *= swa; K(1,2) *= swa; |
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corners[i] = warper->warp(images[i], K, cameras[i].R, INTER_LINEAR, BORDER_REFLECT, images_warped[i]); |
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sizes[i] = images_warped[i].size(); |
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warper->warp(masks[i], K, cameras[i].R, INTER_NEAREST, BORDER_CONSTANT, masks_warped[i]); |
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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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Ptr<ExposureCompensator> compensator = ExposureCompensator::createDefault(expos_comp_type); |
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compensator->feed(corners, images_warped, masks_warped); |
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Ptr<SeamFinder> seam_finder; |
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if (seam_find_type == "no") |
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seam_finder = new detail::NoSeamFinder(); |
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else if (seam_find_type == "voronoi") |
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seam_finder = new detail::VoronoiSeamFinder(); |
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else if (seam_find_type == "gc_color") |
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{ |
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#ifdef HAVE_OPENCV_GPU |
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if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0) |
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seam_finder = new detail::GraphCutSeamFinderGpu(GraphCutSeamFinderBase::COST_COLOR); |
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else |
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#endif |
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seam_finder = new detail::GraphCutSeamFinder(GraphCutSeamFinderBase::COST_COLOR); |
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} |
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else if (seam_find_type == "gc_colorgrad") |
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{ |
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#ifdef HAVE_OPENCV_GPU |
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if (try_gpu && gpu::getCudaEnabledDeviceCount() > 0) |
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seam_finder = new detail::GraphCutSeamFinderGpu(GraphCutSeamFinderBase::COST_COLOR_GRAD); |
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else |
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#endif |
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seam_finder = new detail::GraphCutSeamFinder(GraphCutSeamFinderBase::COST_COLOR_GRAD); |
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} |
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else if (seam_find_type == "dp_color") |
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seam_finder = new detail::DpSeamFinder(DpSeamFinder::COLOR); |
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else if (seam_find_type == "dp_colorgrad") |
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seam_finder = new detail::DpSeamFinder(DpSeamFinder::COLOR_GRAD); |
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if (seam_finder.empty()) |
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{ |
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cout << "Can't create the following seam finder '" << seam_find_type << "'\n"; |
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return 1; |
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} |
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seam_finder->find(images_warped_f, corners, masks_warped); |
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// Release unused memory |
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images.clear(); |
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images_warped.clear(); |
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images_warped_f.clear(); |
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masks.clear(); |
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LOGLN("Compositing..."); |
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t = getTickCount(); |
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Mat img_warped, img_warped_s; |
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Mat dilated_mask, seam_mask, mask, mask_warped; |
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Ptr<Blender> blender; |
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//double compose_seam_aspect = 1; |
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double compose_work_aspect = 1; |
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for (int img_idx = 0; img_idx < num_images; ++img_idx) |
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{ |
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LOGLN("Compositing image #" << indices[img_idx]+1); |
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// Read image and resize it if necessary |
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full_img = imread(img_names[img_idx]); |
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if (!is_compose_scale_set) |
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{ |
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if (compose_megapix > 0) |
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compose_scale = min(1.0, sqrt(compose_megapix * 1e6 / full_img.size().area())); |
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is_compose_scale_set = true; |
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// Compute relative scales |
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//compose_seam_aspect = compose_scale / seam_scale; |
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compose_work_aspect = compose_scale / work_scale; |
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// Update warped image scale |
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warped_image_scale *= static_cast<float>(compose_work_aspect); |
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warper = warper_creator->create(warped_image_scale); |
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// Update corners and sizes |
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for (int i = 0; i < num_images; ++i) |
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{ |
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// Update intrinsics |
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cameras[i].focal *= compose_work_aspect; |
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cameras[i].ppx *= compose_work_aspect; |
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cameras[i].ppy *= compose_work_aspect; |
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// Update corner and size |
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Size sz = full_img_sizes[i]; |
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if (std::abs(compose_scale - 1) > 1e-1) |
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{ |
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sz.width = cvRound(full_img_sizes[i].width * compose_scale); |
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sz.height = cvRound(full_img_sizes[i].height * compose_scale); |
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} |
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Mat K; |
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cameras[i].K().convertTo(K, CV_32F); |
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Rect roi = warper->warpRoi(sz, K, cameras[i].R); |
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corners[i] = roi.tl(); |
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sizes[i] = roi.size(); |
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} |
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} |
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if (abs(compose_scale - 1) > 1e-1) |
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resize(full_img, img, Size(), compose_scale, compose_scale); |
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else |
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img = full_img; |
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full_img.release(); |
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Size img_size = img.size(); |
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Mat K; |
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cameras[img_idx].K().convertTo(K, CV_32F); |
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// Warp the current image |
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warper->warp(img, K, cameras[img_idx].R, INTER_LINEAR, BORDER_REFLECT, img_warped); |
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// Warp the current image mask |
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mask.create(img_size, CV_8U); |
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mask.setTo(Scalar::all(255)); |
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warper->warp(mask, K, cameras[img_idx].R, INTER_NEAREST, BORDER_CONSTANT, mask_warped); |
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// Compensate exposure |
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compensator->apply(img_idx, corners[img_idx], img_warped, mask_warped); |
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img_warped.convertTo(img_warped_s, CV_16S); |
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img_warped.release(); |
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img.release(); |
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mask.release(); |
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dilate(masks_warped[img_idx], dilated_mask, Mat()); |
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resize(dilated_mask, seam_mask, mask_warped.size()); |
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mask_warped = seam_mask & mask_warped; |
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if (blender.empty()) |
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{ |
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blender = Blender::createDefault(blend_type, try_gpu); |
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Size dst_sz = resultRoi(corners, sizes).size(); |
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float blend_width = sqrt(static_cast<float>(dst_sz.area())) * blend_strength / 100.f; |
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if (blend_width < 1.f) |
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blender = Blender::createDefault(Blender::NO, try_gpu); |
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else if (blend_type == Blender::MULTI_BAND) |
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{ |
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MultiBandBlender* mb = dynamic_cast<MultiBandBlender*>(static_cast<Blender*>(blender)); |
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mb->setNumBands(static_cast<int>(ceil(log(blend_width)/log(2.)) - 1.)); |
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LOGLN("Multi-band blender, number of bands: " << mb->numBands()); |
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} |
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else if (blend_type == Blender::FEATHER) |
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{ |
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FeatherBlender* fb = dynamic_cast<FeatherBlender*>(static_cast<Blender*>(blender)); |
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fb->setSharpness(1.f/blend_width); |
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LOGLN("Feather blender, sharpness: " << fb->sharpness()); |
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} |
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blender->prepare(corners, sizes); |
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} |
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// Blend the current image |
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blender->feed(img_warped_s, mask_warped, corners[img_idx]); |
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} |
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Mat result, result_mask; |
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blender->blend(result, result_mask); |
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LOGLN("Compositing, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); |
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imwrite(result_name, result); |
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LOGLN("Finished, total time: " << ((getTickCount() - app_start_time) / getTickFrequency()) << " sec"); |
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return 0; |
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} |
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