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Open Source Computer Vision Library
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859 lines
30 KiB
859 lines
30 KiB
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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/core/utility.hpp> |
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#include "opencv2/imgcodecs.hpp" |
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#include "opencv2/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/timelapsers.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/warpers.hpp" |
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#include "opencv2/stitching/warpers.hpp" |
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|
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#define ENABLE_LOG 1 |
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#define LOG(msg) std::cout << msg |
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#define LOGLN(msg) std::cout << msg << std::endl |
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|
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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_cuda (yes|no)\n" |
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" Try to use CUDA. 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|sift)\n" |
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" Type of features used for images matching. The default is surf.\n" |
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" --matcher (homography|affine)\n" |
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" Matcher used for pairwise image matching.\n" |
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" --estimator (homography|affine)\n" |
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" Type of estimator used for transformation estimation.\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 (no|reproj|ray|affine)\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 (affine|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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" --timelapse (as_is|crop) \n" |
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" Output warped images separately as frames of a time lapse movie, with 'fixed_' prepended to input file names.\n" |
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" --rangewidth <int>\n" |
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" uses range_width to limit number of images to match with.\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_cuda = 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 matcher_type = "homography"; |
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string estimator_type = "homography"; |
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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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int timelapse_type = Timelapser::AS_IS; |
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float blend_strength = 5; |
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string result_name = "result.jpg"; |
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bool timelapse = false; |
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int range_width = -1; |
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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_cuda") |
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{ |
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if (string(argv[i + 1]) == "no") |
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try_cuda = false; |
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else if (string(argv[i + 1]) == "yes") |
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try_cuda = true; |
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else |
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{ |
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cout << "Bad --try_cuda 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]) == "--matcher") |
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{ |
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if (string(argv[i + 1]) == "homography" || string(argv[i + 1]) == "affine") |
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matcher_type = argv[i + 1]; |
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else |
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{ |
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cout << "Bad --matcher 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]) == "--estimator") |
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{ |
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if (string(argv[i + 1]) == "homography" || string(argv[i + 1]) == "affine") |
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estimator_type = argv[i + 1]; |
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else |
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{ |
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cout << "Bad --estimator 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]) == "--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]) == "--timelapse") |
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{ |
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timelapse = true; |
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if (string(argv[i + 1]) == "as_is") |
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timelapse_type = Timelapser::AS_IS; |
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else if (string(argv[i + 1]) == "crop") |
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timelapse_type = Timelapser::CROP; |
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else |
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{ |
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cout << "Bad timelapse 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]) == "--rangewidth") |
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{ |
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range_width = atoi(argv[i + 1]); |
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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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#if ENABLE_LOG |
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int64 app_start_time = getTickCount(); |
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#endif |
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#if 0 |
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cv::setBreakOnError(true); |
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#endif |
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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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#if ENABLE_LOG |
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int64 t = getTickCount(); |
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#endif |
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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_XFEATURES2D |
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if (try_cuda && cuda::getCudaEnabledDeviceCount() > 0) |
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finder = makePtr<SurfFeaturesFinderGpu>(); |
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else |
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#endif |
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finder = makePtr<SurfFeaturesFinder>(); |
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} |
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else if (features_type == "orb") |
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{ |
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finder = makePtr<OrbFeaturesFinder>(); |
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} |
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else if (features_type == "sift") { |
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finder = makePtr<SiftFeaturesFinder>(); |
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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(samples::findFile(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, INTER_LINEAR_EXACT); |
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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, INTER_LINEAR_EXACT); |
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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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#if ENABLE_LOG |
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t = getTickCount(); |
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#endif |
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vector<MatchesInfo> pairwise_matches; |
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Ptr<FeaturesMatcher> matcher; |
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if (matcher_type == "affine") |
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matcher = makePtr<AffineBestOf2NearestMatcher>(false, try_cuda, match_conf); |
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else if (range_width==-1) |
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matcher = makePtr<BestOf2NearestMatcher>(try_cuda, match_conf); |
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else |
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matcher = makePtr<BestOf2NearestRangeMatcher>(range_width, try_cuda, 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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|
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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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|
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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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Ptr<Estimator> estimator; |
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if (estimator_type == "affine") |
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estimator = makePtr<AffineBasedEstimator>(); |
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else |
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estimator = makePtr<HomographyBasedEstimator>(); |
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vector<CameraParams> cameras; |
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if (!(*estimator)(features, pairwise_matches, cameras)) |
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{ |
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cout << "Homography estimation failed.\n"; |
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return -1; |
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} |
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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 camera intrinsics #" << indices[i]+1 << ":\nK:\n" << cameras[i].K() << "\nR:\n" << cameras[i].R); |
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} |
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Ptr<detail::BundleAdjusterBase> adjuster; |
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if (ba_cost_func == "reproj") adjuster = makePtr<detail::BundleAdjusterReproj>(); |
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else if (ba_cost_func == "ray") adjuster = makePtr<detail::BundleAdjusterRay>(); |
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else if (ba_cost_func == "affine") adjuster = makePtr<detail::BundleAdjusterAffinePartial>(); |
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else if (ba_cost_func == "no") adjuster = makePtr<NoBundleAdjuster>(); |
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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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if (!(*adjuster)(features, pairwise_matches, cameras)) |
|
{ |
|
cout << "Camera parameters adjusting failed.\n"; |
|
return -1; |
|
} |
|
|
|
// Find median focal length |
|
|
|
vector<double> focals; |
|
for (size_t i = 0; i < cameras.size(); ++i) |
|
{ |
|
LOGLN("Camera #" << indices[i]+1 << ":\nK:\n" << cameras[i].K() << "\nR:\n" << cameras[i].R); |
|
focals.push_back(cameras[i].focal); |
|
} |
|
|
|
sort(focals.begin(), focals.end()); |
|
float warped_image_scale; |
|
if (focals.size() % 2 == 1) |
|
warped_image_scale = static_cast<float>(focals[focals.size() / 2]); |
|
else |
|
warped_image_scale = static_cast<float>(focals[focals.size() / 2 - 1] + focals[focals.size() / 2]) * 0.5f; |
|
|
|
if (do_wave_correct) |
|
{ |
|
vector<Mat> rmats; |
|
for (size_t i = 0; i < cameras.size(); ++i) |
|
rmats.push_back(cameras[i].R.clone()); |
|
waveCorrect(rmats, wave_correct); |
|
for (size_t i = 0; i < cameras.size(); ++i) |
|
cameras[i].R = rmats[i]; |
|
} |
|
|
|
LOGLN("Warping images (auxiliary)... "); |
|
#if ENABLE_LOG |
|
t = getTickCount(); |
|
#endif |
|
|
|
vector<Point> corners(num_images); |
|
vector<UMat> masks_warped(num_images); |
|
vector<UMat> images_warped(num_images); |
|
vector<Size> sizes(num_images); |
|
vector<UMat> masks(num_images); |
|
|
|
// Preapre images masks |
|
for (int i = 0; i < num_images; ++i) |
|
{ |
|
masks[i].create(images[i].size(), CV_8U); |
|
masks[i].setTo(Scalar::all(255)); |
|
} |
|
|
|
// Warp images and their masks |
|
|
|
Ptr<WarperCreator> warper_creator; |
|
#ifdef HAVE_OPENCV_CUDAWARPING |
|
if (try_cuda && cuda::getCudaEnabledDeviceCount() > 0) |
|
{ |
|
if (warp_type == "plane") |
|
warper_creator = makePtr<cv::PlaneWarperGpu>(); |
|
else if (warp_type == "cylindrical") |
|
warper_creator = makePtr<cv::CylindricalWarperGpu>(); |
|
else if (warp_type == "spherical") |
|
warper_creator = makePtr<cv::SphericalWarperGpu>(); |
|
} |
|
else |
|
#endif |
|
{ |
|
if (warp_type == "plane") |
|
warper_creator = makePtr<cv::PlaneWarper>(); |
|
else if (warp_type == "affine") |
|
warper_creator = makePtr<cv::AffineWarper>(); |
|
else if (warp_type == "cylindrical") |
|
warper_creator = makePtr<cv::CylindricalWarper>(); |
|
else if (warp_type == "spherical") |
|
warper_creator = makePtr<cv::SphericalWarper>(); |
|
else if (warp_type == "fisheye") |
|
warper_creator = makePtr<cv::FisheyeWarper>(); |
|
else if (warp_type == "stereographic") |
|
warper_creator = makePtr<cv::StereographicWarper>(); |
|
else if (warp_type == "compressedPlaneA2B1") |
|
warper_creator = makePtr<cv::CompressedRectilinearWarper>(2.0f, 1.0f); |
|
else if (warp_type == "compressedPlaneA1.5B1") |
|
warper_creator = makePtr<cv::CompressedRectilinearWarper>(1.5f, 1.0f); |
|
else if (warp_type == "compressedPlanePortraitA2B1") |
|
warper_creator = makePtr<cv::CompressedRectilinearPortraitWarper>(2.0f, 1.0f); |
|
else if (warp_type == "compressedPlanePortraitA1.5B1") |
|
warper_creator = makePtr<cv::CompressedRectilinearPortraitWarper>(1.5f, 1.0f); |
|
else if (warp_type == "paniniA2B1") |
|
warper_creator = makePtr<cv::PaniniWarper>(2.0f, 1.0f); |
|
else if (warp_type == "paniniA1.5B1") |
|
warper_creator = makePtr<cv::PaniniWarper>(1.5f, 1.0f); |
|
else if (warp_type == "paniniPortraitA2B1") |
|
warper_creator = makePtr<cv::PaniniPortraitWarper>(2.0f, 1.0f); |
|
else if (warp_type == "paniniPortraitA1.5B1") |
|
warper_creator = makePtr<cv::PaniniPortraitWarper>(1.5f, 1.0f); |
|
else if (warp_type == "mercator") |
|
warper_creator = makePtr<cv::MercatorWarper>(); |
|
else if (warp_type == "transverseMercator") |
|
warper_creator = makePtr<cv::TransverseMercatorWarper>(); |
|
} |
|
|
|
if (!warper_creator) |
|
{ |
|
cout << "Can't create the following warper '" << warp_type << "'\n"; |
|
return 1; |
|
} |
|
|
|
Ptr<RotationWarper> warper = warper_creator->create(static_cast<float>(warped_image_scale * seam_work_aspect)); |
|
|
|
for (int i = 0; i < num_images; ++i) |
|
{ |
|
Mat_<float> K; |
|
cameras[i].K().convertTo(K, CV_32F); |
|
float swa = (float)seam_work_aspect; |
|
K(0,0) *= swa; K(0,2) *= swa; |
|
K(1,1) *= swa; K(1,2) *= swa; |
|
|
|
corners[i] = warper->warp(images[i], K, cameras[i].R, INTER_LINEAR, BORDER_REFLECT, images_warped[i]); |
|
sizes[i] = images_warped[i].size(); |
|
|
|
warper->warp(masks[i], K, cameras[i].R, INTER_NEAREST, BORDER_CONSTANT, masks_warped[i]); |
|
} |
|
|
|
vector<UMat> images_warped_f(num_images); |
|
for (int i = 0; i < num_images; ++i) |
|
images_warped[i].convertTo(images_warped_f[i], CV_32F); |
|
|
|
LOGLN("Warping images, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); |
|
|
|
Ptr<ExposureCompensator> compensator = ExposureCompensator::createDefault(expos_comp_type); |
|
compensator->feed(corners, images_warped, masks_warped); |
|
|
|
Ptr<SeamFinder> seam_finder; |
|
if (seam_find_type == "no") |
|
seam_finder = makePtr<detail::NoSeamFinder>(); |
|
else if (seam_find_type == "voronoi") |
|
seam_finder = makePtr<detail::VoronoiSeamFinder>(); |
|
else if (seam_find_type == "gc_color") |
|
{ |
|
#ifdef HAVE_OPENCV_CUDALEGACY |
|
if (try_cuda && cuda::getCudaEnabledDeviceCount() > 0) |
|
seam_finder = makePtr<detail::GraphCutSeamFinderGpu>(GraphCutSeamFinderBase::COST_COLOR); |
|
else |
|
#endif |
|
seam_finder = makePtr<detail::GraphCutSeamFinder>(GraphCutSeamFinderBase::COST_COLOR); |
|
} |
|
else if (seam_find_type == "gc_colorgrad") |
|
{ |
|
#ifdef HAVE_OPENCV_CUDALEGACY |
|
if (try_cuda && cuda::getCudaEnabledDeviceCount() > 0) |
|
seam_finder = makePtr<detail::GraphCutSeamFinderGpu>(GraphCutSeamFinderBase::COST_COLOR_GRAD); |
|
else |
|
#endif |
|
seam_finder = makePtr<detail::GraphCutSeamFinder>(GraphCutSeamFinderBase::COST_COLOR_GRAD); |
|
} |
|
else if (seam_find_type == "dp_color") |
|
seam_finder = makePtr<detail::DpSeamFinder>(DpSeamFinder::COLOR); |
|
else if (seam_find_type == "dp_colorgrad") |
|
seam_finder = makePtr<detail::DpSeamFinder>(DpSeamFinder::COLOR_GRAD); |
|
if (!seam_finder) |
|
{ |
|
cout << "Can't create the following seam finder '" << seam_find_type << "'\n"; |
|
return 1; |
|
} |
|
|
|
seam_finder->find(images_warped_f, corners, masks_warped); |
|
|
|
// Release unused memory |
|
images.clear(); |
|
images_warped.clear(); |
|
images_warped_f.clear(); |
|
masks.clear(); |
|
|
|
LOGLN("Compositing..."); |
|
#if ENABLE_LOG |
|
t = getTickCount(); |
|
#endif |
|
|
|
Mat img_warped, img_warped_s; |
|
Mat dilated_mask, seam_mask, mask, mask_warped; |
|
Ptr<Blender> blender; |
|
Ptr<Timelapser> timelapser; |
|
//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(samples::findFile(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_creator->create(warped_image_scale); |
|
|
|
// Update corners and sizes |
|
for (int i = 0; i < num_images; ++i) |
|
{ |
|
// Update intrinsics |
|
cameras[i].focal *= compose_work_aspect; |
|
cameras[i].ppx *= compose_work_aspect; |
|
cameras[i].ppy *= compose_work_aspect; |
|
|
|
// Update corner and size |
|
Size sz = full_img_sizes[i]; |
|
if (std::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); |
|
} |
|
|
|
Mat K; |
|
cameras[i].K().convertTo(K, CV_32F); |
|
Rect roi = warper->warpRoi(sz, K, 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, INTER_LINEAR_EXACT); |
|
else |
|
img = full_img; |
|
full_img.release(); |
|
Size img_size = img.size(); |
|
|
|
Mat K; |
|
cameras[img_idx].K().convertTo(K, CV_32F); |
|
|
|
// Warp the current image |
|
warper->warp(img, K, cameras[img_idx].R, INTER_LINEAR, BORDER_REFLECT, img_warped); |
|
|
|
// Warp the current image mask |
|
mask.create(img_size, CV_8U); |
|
mask.setTo(Scalar::all(255)); |
|
warper->warp(mask, K, cameras[img_idx].R, INTER_NEAREST, BORDER_CONSTANT, mask_warped); |
|
|
|
// 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(), 0, 0, INTER_LINEAR_EXACT); |
|
mask_warped = seam_mask & mask_warped; |
|
|
|
if (!blender && !timelapse) |
|
{ |
|
blender = Blender::createDefault(blend_type, try_cuda); |
|
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_cuda); |
|
else if (blend_type == Blender::MULTI_BAND) |
|
{ |
|
MultiBandBlender* mb = dynamic_cast<MultiBandBlender*>(blender.get()); |
|
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*>(blender.get()); |
|
fb->setSharpness(1.f/blend_width); |
|
LOGLN("Feather blender, sharpness: " << fb->sharpness()); |
|
} |
|
blender->prepare(corners, sizes); |
|
} |
|
else if (!timelapser && timelapse) |
|
{ |
|
timelapser = Timelapser::createDefault(timelapse_type); |
|
timelapser->initialize(corners, sizes); |
|
} |
|
|
|
// Blend the current image |
|
if (timelapse) |
|
{ |
|
timelapser->process(img_warped_s, Mat::ones(img_warped_s.size(), CV_8UC1), corners[img_idx]); |
|
String fixedFileName; |
|
size_t pos_s = String(img_names[img_idx]).find_last_of("/\\"); |
|
if (pos_s == String::npos) |
|
{ |
|
fixedFileName = "fixed_" + img_names[img_idx]; |
|
} |
|
else |
|
{ |
|
fixedFileName = "fixed_" + String(img_names[img_idx]).substr(pos_s + 1, String(img_names[img_idx]).length() - pos_s); |
|
} |
|
imwrite(fixedFileName, timelapser->getDst()); |
|
} |
|
else |
|
{ |
|
blender->feed(img_warped_s, mask_warped, corners[img_idx]); |
|
} |
|
} |
|
|
|
if (!timelapse) |
|
{ |
|
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; |
|
}
|
|
|