/*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*/ // We follow to methods described in these two papers: // 1) Construction of panoramic mosaics with global and local alignment. // Heung-Yeung Shum and Richard Szeliski. 2000. // 2) Eliminating Ghosting and Exposure Artifacts in Image Mosaics. // Matthew Uyttendaele, Ashley Eden and Richard Szeliski. 2001. // 3) Automatic Panoramic Image Stitching using Invariant Features. // Matthew Brown and David G. Lowe. 2007. #include "precomp.hpp" #include "util.hpp" #include "warpers.hpp" #include "blenders.hpp" #include "seam_finders.hpp" #include "motion_estimators.hpp" #include "exposure_compensate.hpp" using namespace std; using namespace cv; void printUsage() { cout << "Rotation model images stitcher.\n\n" "opencv_stitching img1 img2 [...imgN] [flags]\n\n" "Flags:\n" " --preview\n" " Run stitching in the preview mode. Works faster than usual mode,\n" " but output image will have lower resolution.\n" " --try_gpu (yes|no)\n" " Try to use GPU. The default value is 'no'. All default values\n" " are for CPU mode.\n" "\nMotion Estimation:\n" " --work_megapix <float>\n" " Resolution for image registration step. The default is 0.6 Mpx.\n" " --match_conf <float>\n" " Confidence for feature matching step. The default is 0.7.\n" " --conf_thresh <float>\n" " Threshold for two images are from the same panorama confidence.\n" " The default is 1.0.\n" " --ba (ray|focal_ray)\n" " Bundle adjustment cost function. The default is 'focal_ray'.\n" " --wave_correct (no|yes)\n" " Perform wave effect correction. The default is 'yes'.\n" "\nCompositing:\n" " --warp (plane|cylindrical|spherical)\n" " Warp surface type. The default is 'spherical'.\n" " --seam_megapix <float>\n" " Resolution for seam estimation step. The default is 0.1 Mpx.\n" " --seam (no|voronoi|gc_color|gc_colorgrad)\n" " Seam estimation method. The default is 'gc_color'.\n" " --compose_megapix <float>\n" " Resolution for compositing step. Use -1 for original resolution.\n" " The default is -1.\n" " --expos_comp (no|gain|gain_blocks)\n" " Exposure compensation method. The default is 'gain_blocks'.\n" " --blend (no|feather|multiband)\n" " Blending method. The default is 'multiband'.\n" " --blend_strength <float>\n" " Blending strength from [0,100] range. The default is 5.\n" " --output <result_img>\n" " The default is 'result.png'.\n"; } // Default command line args vector<string> img_names; bool preview = false; bool try_gpu = false; double work_megapix = 0.6; 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; int expos_comp_type = ExposureCompensator::GAIN_BLOCKS; float match_conf = 0.65f; int seam_find_type = SeamFinder::GC_COLOR; int blend_type = Blender::MULTI_BAND; float blend_strength = 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]) == "--help" || string(argv[i]) == "/?") { printUsage(); return -1; } else if (string(argv[i]) == "--preview") { preview = true; } else if (string(argv[i]) == "--try_gpu") { if (string(argv[i + 1]) == "no") try_gpu = false; else if (string(argv[i + 1]) == "yes") try_gpu = true; else { cout << "Bad --try_gpu 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") { match_conf = static_cast<float>(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<float>(atof(argv[i + 1])); i++; } else if (string(argv[i]) == "--wave_correct") { if (string(argv[i + 1]) == "no") wave_correct = false; else if (string(argv[i + 1]) == "yes") wave_correct = true; else { cout << "Bad --wave_correct 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]) == "--expos_comp") { if (string(argv[i + 1]) == "no") expos_comp_type = ExposureCompensator::NO; else if (string(argv[i + 1]) == "gain") expos_comp_type = ExposureCompensator::GAIN; else if (string(argv[i + 1]) == "gain_blocks") expos_comp_type = ExposureCompensator::GAIN_BLOCKS; else { cout << "Bad exposure compensation 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]) == "gc_color") seam_find_type = SeamFinder::GC_COLOR; else if (string(argv[i + 1]) == "gc_colorgrad") seam_find_type = SeamFinder::GC_COLOR_GRAD; 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]) == "--blend_strength") { blend_strength = static_cast<float>(atof(argv[i + 1])); i++; } else if (string(argv[i]) == "--output") { result_name = argv[i + 1]; i++; } else img_names.push_back(argv[i]); } if (preview) { compose_megapix = 0.6; } 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<int>(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<ImageFeatures> features(num_images); SurfFeaturesFinder finder(try_gpu); Mat full_img, img; vector<Mat> 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]); features[i].img_idx = i; LOGLN("Features in image #" << i+1 << ": " << 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"); LOG("Pairwise matching"); t = getTickCount(); vector<MatchesInfo> pairwise_matches; BestOf2NearestMatcher matcher(try_gpu, 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<int> indices = leaveBiggestComponent(features, pairwise_matches, conf_thresh); vector<Mat> img_subset; vector<string> img_names_subset; for (size_t i = 0; i < indices.size(); ++i) { img_names_subset.push_back(img_names[indices[i]]); img_subset.push_back(images[indices[i]]); } images = img_subset; img_names = img_names_subset; // Check if we still have enough images num_images = static_cast<int>(img_names.size()); if (num_images < 2) { LOGLN("Need more images"); return -1; } LOGLN("Estimating rotations..."); t = getTickCount(); HomographyBasedEstimator estimator; vector<CameraParams> 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 #" << indices[i]+1 << ": " << cameras[i].focal); } LOG("Bundle adjustment"); t = getTickCount(); BundleAdjuster adjuster(ba_space, conf_thresh); adjuster(features, pairwise_matches, cameras); LOGLN("Bundle adjustment, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); // Find median focal length vector<double> focals; for (size_t i = 0; i < cameras.size(); ++i) { LOGLN("Camera #" << indices[i]+1 << " focal length: " << cameras[i].focal); focals.push_back(cameras[i].focal); } nth_element(focals.begin(), focals.begin() + focals.size()/2, focals.end()); float warped_image_scale = static_cast<float>(focals[focals.size() / 2]); if (wave_correct) { LOGLN("Wave correcting..."); t = getTickCount(); vector<Mat> 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"); } LOGLN("Warping images (auxiliary)... "); t = getTickCount(); vector<Point> corners(num_images); vector<Mat> masks_warped(num_images); vector<Mat> images_warped(num_images); vector<Size> sizes(num_images); vector<Mat> 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 = Warper::createByCameraFocal(static_cast<float>(warped_image_scale * seam_work_aspect), warp_type); for (int i = 0; i < num_images; ++i) { corners[i] = warper->warp(images[i], static_cast<float>(cameras[i].focal * seam_work_aspect), cameras[i].R, images_warped[i]); sizes[i] = images_warped[i].size(); warper->warp(masks[i], static_cast<float>(cameras[i].focal * seam_work_aspect), cameras[i].R, masks_warped[i], INTER_NEAREST, BORDER_CONSTANT); } vector<Mat> 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("Exposure compensation (feed)..."); t = getTickCount(); Ptr<ExposureCompensator> compensator = ExposureCompensator::createDefault(expos_comp_type); compensator->feed(corners, images_warped, masks_warped); LOGLN("Exposure compensation (feed), time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); LOGLN("Finding seams..."); t = getTickCount(); Ptr<SeamFinder> seam_finder = SeamFinder::createDefault(seam_find_type); seam_finder->find(images_warped_f, corners, masks_warped); LOGLN("Finding seams, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); // Release unused memory images.clear(); images_warped.clear(); images_warped_f.clear(); masks.clear(); LOGLN("Compositing..."); t = getTickCount(); Mat img_warped, img_warped_s; Mat dilated_mask, seam_mask, mask, mask_warped; Ptr<Blender> blender; double compose_seam_aspect = 1; double compose_work_aspect = 1; for (int img_idx = 0; img_idx < num_images; ++img_idx) { LOGLN("Compositing image #" << indices[img_idx]+1); // Read image and resize it if necessary full_img = imread(img_names[img_idx]); if (!is_compose_scale_set) { if (compose_megapix > 0) compose_scale = min(1.0, sqrt(compose_megapix * 1e6 / full_img.size().area())); is_compose_scale_set = true; // Compute relative scales compose_seam_aspect = compose_scale / seam_scale; compose_work_aspect = compose_scale / work_scale; // Update warped image scale warped_image_scale *= static_cast<float>(compose_work_aspect); warper = Warper::createByCameraFocal(warped_image_scale, warp_type); // Update corners and sizes Rect dst_roi = resultRoi(corners, sizes); for (int i = 0; i < num_images; ++i) { // Update camera focal cameras[i].focal *= compose_work_aspect; // Update corner and size corners[i] = dst_roi.tl() + (corners[i] - dst_roi.tl()) * compose_seam_aspect; sizes[i] = Size(static_cast<int>((sizes[i].width + 1) * compose_seam_aspect), static_cast<int>((sizes[i].height + 1) * compose_seam_aspect)); } } if (abs(compose_scale - 1) > 1e-1) resize(full_img, img, Size(), compose_scale, compose_scale); else img = full_img; full_img.release(); Size img_size = img.size(); // Warp the current image warper->warp(img, static_cast<float>(cameras[img_idx].focal), cameras[img_idx].R, img_warped); // Warp the current image mask mask.create(img_size, CV_8U); mask.setTo(Scalar::all(255)); warper->warp(mask, static_cast<float>(cameras[img_idx].focal), cameras[img_idx].R, mask_warped, INTER_NEAREST, BORDER_CONSTANT); // Compensate exposure compensator->apply(img_idx, corners[img_idx], img_warped, mask_warped); img_warped.convertTo(img_warped_s, CV_16S); img_warped.release(); img.release(); mask.release(); dilate(masks_warped[img_idx], dilated_mask, Mat()); resize(dilated_mask, seam_mask, mask_warped.size()); mask_warped = seam_mask & mask_warped; if (static_cast<Blender*>(blender) == 0) { blender = Blender::createDefault(blend_type); 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); else if (blend_type == Blender::MULTI_BAND) { MultiBandBlender* mb = dynamic_cast<MultiBandBlender*>(static_cast<Blender*>(blender)); mb->setNumBands(static_cast<int>(ceil(log(blend_width)/log(2.)) - 1.)); LOGLN("Multi-band blender, number of bands: " << mb->numBands()); } else if (blend_type == Blender::FEATHER) { FeatherBlender* fb = dynamic_cast<FeatherBlender*>(static_cast<Blender*>(blender)); fb->setSharpness(1.f/blend_width); LOGLN("Feather blender, number of bands: " << fb->sharpness()); } blender->prepare(corners, sizes); } // Blend the current image blender->feed(img_warped_s, mask_warped, corners[img_idx]); } Mat result, result_mask; blender->blend(result, result_mask); LOGLN("Compositing, time: " << ((getTickCount() - t) / getTickFrequency()) << " sec"); imwrite(result_name, result); LOGLN("Finished, total time: " << ((getTickCount() - app_start_time) / getTickFrequency()) << " sec"); return 0; }