/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009, Willow Garage Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other materials provided with the distribution. // // * The name of the copyright holders may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #include "precomp.hpp" #include "util.hpp" #include "warpers.hpp" #include "blenders.hpp" #include "seam_finders.hpp" #include "motion_estimators.hpp" using namespace std; using namespace cv; void printUsage() { cout << "Rotation model images stitcher.\n\n"; cout << "Usage: opencv_stitching img1 img2 [...imgN]\n" << "\t[--trygpu (yes|no)]\n" << "\t[--work_megapix ]\n" << "\t[--seam_megapix ]\n" << "\t[--compose_megapix ]\n" << "\t[--match_conf ]\n" << "\t[--ba (ray|focal_ray)]\n" << "\t[--conf_thresh ]\n" << "\t[--wavecorrect (no|yes)]\n" << "\t[--warp (plane|cylindrical|spherical)]\n" << "\t[--seam (no|voronoi|graphcut)]\n" << "\t[--blend (no|feather|multiband)]\n" << "\t[--numbands ]\n" << "\t[--output ]\n\n"; cout << "--match_conf\n" << "\tGood values are in [0.2, 0.8] range usually.\n\n"; cout << "HINT:\n" << "\tTry bigger values for --work_megapix if something is wrong.\n\n"; } // Default command line args vector img_names; bool trygpu = false; double work_megapix = 0.3; double seam_megapix = 0.1; double compose_megapix = 1; int ba_space = BundleAdjuster::FOCAL_RAY_SPACE; float conf_thresh = 1.f; bool wave_correct = true; int warp_type = Warper::SPHERICAL; bool user_match_conf = false; float match_conf = 0.6f; int seam_find_type = SeamFinder::GRAPH_CUT; int blend_type = Blender::MULTI_BAND; int numbands = 5; string result_name = "result.png"; int parseCmdArgs(int argc, char** argv) { if (argc == 1) { printUsage(); return -1; } for (int i = 1; i < argc; ++i) { if (string(argv[i]) == "--trygpu") { if (string(argv[i + 1]) == "no") trygpu = false; else if (string(argv[i + 1]) == "yes") trygpu = true; else { cout << "Bad --trygpu flag value\n"; return -1; } i++; } else if (string(argv[i]) == "--work_megapix") { work_megapix = atof(argv[i + 1]); i++; } else if (string(argv[i]) == "--seam_megapix") { seam_megapix = atof(argv[i + 1]); i++; } else if (string(argv[i]) == "--compose_megapix") { compose_megapix = atof(argv[i + 1]); i++; } else if (string(argv[i]) == "--result") { result_name = argv[i + 1]; i++; } else if (string(argv[i]) == "--match_conf") { user_match_conf = true; match_conf = static_cast(atof(argv[i + 1])); i++; } else if (string(argv[i]) == "--ba") { if (string(argv[i + 1]) == "ray") ba_space = BundleAdjuster::RAY_SPACE; else if (string(argv[i + 1]) == "focal_ray") ba_space = BundleAdjuster::FOCAL_RAY_SPACE; else { cout << "Bad bundle adjustment space\n"; return -1; } i++; } else if (string(argv[i]) == "--conf_thresh") { conf_thresh = static_cast(atof(argv[i + 1])); i++; } else if (string(argv[i]) == "--wavecorrect") { if (string(argv[i + 1]) == "no") wave_correct = false; else if (string(argv[i + 1]) == "yes") wave_correct = true; else { cout << "Bad --wavecorrect flag value\n"; return -1; } i++; } else if (string(argv[i]) == "--warp") { if (string(argv[i + 1]) == "plane") warp_type = Warper::PLANE; else if (string(argv[i + 1]) == "cylindrical") warp_type = Warper::CYLINDRICAL; else if (string(argv[i + 1]) == "spherical") warp_type = Warper::SPHERICAL; else { cout << "Bad warping method\n"; return -1; } i++; } else if (string(argv[i]) == "--seam") { if (string(argv[i + 1]) == "no") seam_find_type = SeamFinder::NO; else if (string(argv[i + 1]) == "voronoi") seam_find_type = SeamFinder::VORONOI; else if (string(argv[i + 1]) == "graphcut") seam_find_type = SeamFinder::GRAPH_CUT; else { cout << "Bad seam finding method\n"; return -1; } i++; } else if (string(argv[i]) == "--blend") { if (string(argv[i + 1]) == "no") blend_type = Blender::NO; else if (string(argv[i + 1]) == "feather") blend_type = Blender::FEATHER; else if (string(argv[i + 1]) == "multiband") blend_type = Blender::MULTI_BAND; else { cout << "Bad blending method\n"; return -1; } i++; } else if (string(argv[i]) == "--numbands") { numbands = atoi(argv[i + 1]); i++; } else if (string(argv[i]) == "--output") { result_name = argv[i + 1]; i++; } else img_names.push_back(argv[i]); } return 0; } int main(int argc, char* argv[]) { int64 app_start_time = getTickCount(); cv::setBreakOnError(true); int retval = parseCmdArgs(argc, argv); if (retval) return retval; // Check if have enough images int num_images = static_cast(img_names.size()); if (num_images < 2) { LOGLN("Need more images"); return -1; } double work_scale = 1, seam_scale = 1, compose_scale = 1; bool is_work_scale_set = false, is_seam_scale_set = false, is_compose_scale_set = false; LOGLN("Finding features..."); int64 t = getTickCount(); vector features(num_images); SurfFeaturesFinder finder(trygpu); Mat full_img, img; vector images(num_images); double seam_work_aspect = 1; for (int i = 0; i < num_images; ++i) { full_img = imread(img_names[i]); if (full_img.empty()) { LOGLN("Can't open image " << img_names[i]); return -1; } if (work_megapix < 0) { img = full_img; work_scale = 1; is_work_scale_set = true; } else { if (!is_work_scale_set) { work_scale = min(1.0, sqrt(work_megapix * 1e6 / full_img.size().area())); is_work_scale_set = true; } resize(full_img, img, Size(), work_scale, work_scale); } if (!is_seam_scale_set) { seam_scale = min(1.0, sqrt(seam_megapix * 1e6 / full_img.size().area())); seam_work_aspect = seam_scale / work_scale; is_seam_scale_set = true; } finder(img, features[i]); LOGLN("Features in image #" << i << ": " << features[i].keypoints.size()); resize(full_img, img, Size(), seam_scale, seam_scale); images[i] = img.clone(); } full_img.release(); img.release(); LOGLN("Finding features, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); LOGLN("Pairwise matching... "); t = getTickCount(); vector pairwise_matches; BestOf2NearestMatcher matcher(trygpu); if (user_match_conf) matcher = BestOf2NearestMatcher(trygpu, match_conf); matcher(features, pairwise_matches); LOGLN("Pairwise matching, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); // Leave only images we are sure are from the same panorama vector indices = leaveBiggestComponent(features, pairwise_matches, conf_thresh); vector img_subset; vector img_names_subset; for (size_t i = 0; i < indices.size(); ++i) img_names_subset.push_back(img_names[indices[i]]); img_names = img_names_subset; // Check if we still have enough images num_images = static_cast(img_names.size()); if (num_images < 2) { LOGLN("Need more images"); return -1; } LOGLN("Estimating rotations..."); t = getTickCount(); HomographyBasedEstimator estimator; vector cameras; estimator(features, pairwise_matches, cameras); LOGLN("Estimating rotations, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); for (size_t i = 0; i < cameras.size(); ++i) { Mat R; cameras[i].R.convertTo(R, CV_32F); cameras[i].R = R; LOGLN("Initial focal length #" << i << ": " << cameras[i].focal); } LOGLN("Bundle adjustment... "); t = getTickCount(); BundleAdjuster adjuster(ba_space, conf_thresh); adjuster(features, pairwise_matches, cameras); LOGLN("Bundle adjustment, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); if (wave_correct) { LOGLN("Wave correcting..."); t = getTickCount(); vector rmats; for (size_t i = 0; i < cameras.size(); ++i) rmats.push_back(cameras[i].R); waveCorrect(rmats); for (size_t i = 0; i < cameras.size(); ++i) cameras[i].R = rmats[i]; LOGLN("Wave correcting, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); } // Find median focal length vector focals; for (size_t i = 0; i < cameras.size(); ++i) { LOGLN("Camera #" << i << " focal length: " << cameras[i].focal); focals.push_back(cameras[i].focal); } nth_element(focals.begin(), focals.end(), focals.begin() + focals.size() / 2); float camera_focal = static_cast(focals[focals.size() / 2]); LOGLN("Warping images (auxiliary)... "); t = getTickCount(); vector corners(num_images); vector masks_warped(num_images); vector images_warped(num_images); vector sizes(num_images); vector 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 warper = Warper::createByCameraFocal(static_cast(camera_focal * seam_work_aspect), warp_type); for (int i = 0; i < num_images; ++i) { corners[i] = warper->warp(images[i], static_cast(cameras[i].focal * seam_work_aspect), cameras[i].R, images_warped[i]); sizes[i] = images_warped[i].size(); warper->warp(masks[i], static_cast(cameras[i].focal * seam_work_aspect), cameras[i].R, masks_warped[i], INTER_NEAREST, BORDER_CONSTANT); } // Convert to float for blending vector 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"); LOGLN("Finding seams..."); t = getTickCount(); // Find seams Ptr seam_finder = SeamFinder::createDefault(seam_find_type); seam_finder->find(images_warped_f, corners, masks_warped); LOGLN("Finding seams, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); // Release unused memory images.clear(); images_warped.clear(); images_warped_f.clear(); masks.clear(); LOGLN("Compositing..."); t = getTickCount(); Mat img_warped, img_warped_f; Mat dilated_mask, seam_mask, mask, mask_warped; Ptr blender; double compose_seam_aspect = 1; double compose_work_aspect = 1; for (int img_idx = 0; img_idx < num_images; ++img_idx) { LOGLN("Compositing image #" << img_idx); // Read image and resize it if necessary full_img = imread(img_names[img_idx]); if (!is_compose_scale_set) { if (compose_megapix > 0) compose_scale = min(1.0, sqrt(compose_megapix * 1e6 / full_img.size().area())); is_compose_scale_set = true; compose_seam_aspect = compose_scale / seam_scale; compose_work_aspect = compose_scale / work_scale; camera_focal *= static_cast(compose_work_aspect); warper = Warper::createByCameraFocal(camera_focal, warp_type); } if (abs(compose_scale - 1) > 1e-1) resize(full_img, img, Size(), compose_scale, compose_scale); else img = full_img; full_img.release(); // Update cameras paramters cameras[img_idx].focal *= compose_work_aspect; // Warp the current image warper->warp(img, static_cast(cameras[img_idx].focal), cameras[img_idx].R, img_warped); img_warped.convertTo(img_warped_f, CV_32F); img_warped.release(); // Warp current image mask mask.create(img.size(), CV_8U); mask.setTo(Scalar::all(255)); warper->warp(mask, static_cast(cameras[img_idx].focal), cameras[img_idx].R, mask_warped, INTER_NEAREST, BORDER_CONSTANT); mask.release(); dilate(masks_warped[img_idx], dilated_mask, Mat()); resize(dilated_mask, seam_mask, mask_warped.size()); mask_warped = seam_mask & mask_warped; if (static_cast(blender) == 0) { blender = Blender::createDefault(blend_type); if (blend_type == Blender::MULTI_BAND) { MultiBandBlender* mb = dynamic_cast(static_cast(blender)); mb->setNumBands(numbands); } // Determine the final image size Rect dst_roi = resultRoi(corners, sizes); for (int i = 0; i < num_images; ++i) { corners[i] = dst_roi.tl() + (corners[i] - dst_roi.tl()) * compose_seam_aspect; sizes[i] = Size(static_cast((sizes[i].width + 1) * compose_seam_aspect), static_cast((sizes[i].height + 1) * compose_seam_aspect)); } blender->prepare(corners, sizes); } // Blend the current image blender->feed(img_warped_f, mask_warped, corners[img_idx]); } Mat result, result_mask; blender->blend(result, result_mask); LOGLN("Compositing, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); imwrite(result_name, result); LOGLN("Finished, total time: " << ((getTickCount() - app_start_time) / getTickFrequency()) << " sec"); return 0; }