import argparse from pathlib import Path from pprint import pformat from ... import ( colmap_from_nvm, extract_features, localize_sfm, logger, match_features, pairs_from_covisibility, pairs_from_retrieval, triangulation, ) def run(args): # Setup the paths dataset = args.dataset images = dataset / "images_upright/" outputs = args.outputs # where everything will be saved sift_sfm = outputs / "sfm_sift" # from which we extract the reference poses reference_sfm = outputs / "sfm_superpoint+superglue" # the SfM model we will build sfm_pairs = ( outputs / f"pairs-db-covis{args.num_covis}.txt" ) # top-k most covisible in SIFT model loc_pairs = ( outputs / f"pairs-query-netvlad{args.num_loc}.txt" ) # top-k retrieved by NetVLAD results = outputs / f"Aachen_hloc_superpoint+superglue_netvlad{args.num_loc}.txt" # list the standard configurations available logger.info("Configs for feature extractors:\n%s", pformat(extract_features.confs)) logger.info("Configs for feature matchers:\n%s", pformat(match_features.confs)) # pick one of the configurations for extraction and matching retrieval_conf = extract_features.confs["netvlad"] feature_conf = extract_features.confs["superpoint_aachen"] matcher_conf = match_features.confs["superglue"] features = extract_features.main(feature_conf, images, outputs) colmap_from_nvm.main( dataset / "3D-models/aachen_cvpr2018_db.nvm", dataset / "3D-models/database_intrinsics.txt", dataset / "aachen.db", sift_sfm, ) pairs_from_covisibility.main(sift_sfm, sfm_pairs, num_matched=args.num_covis) sfm_matches = match_features.main( matcher_conf, sfm_pairs, feature_conf["output"], outputs ) triangulation.main( reference_sfm, sift_sfm, images, sfm_pairs, features, sfm_matches ) global_descriptors = extract_features.main(retrieval_conf, images, outputs) pairs_from_retrieval.main( global_descriptors, loc_pairs, args.num_loc, query_prefix="query", db_model=reference_sfm, ) loc_matches = match_features.main( matcher_conf, loc_pairs, feature_conf["output"], outputs ) localize_sfm.main( reference_sfm, dataset / "queries/*_time_queries_with_intrinsics.txt", loc_pairs, features, loc_matches, results, covisibility_clustering=False, ) # not required with SuperPoint+SuperGlue if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument( "--dataset", type=Path, default="datasets/aachen", help="Path to the dataset, default: %(default)s", ) parser.add_argument( "--outputs", type=Path, default="outputs/aachen", help="Path to the output directory, default: %(default)s", ) parser.add_argument( "--num_covis", type=int, default=20, help="Number of image pairs for SfM, default: %(default)s", ) parser.add_argument( "--num_loc", type=int, default=50, help="Number of image pairs for loc, default: %(default)s", ) args = parser.parse_args() run(args)