GAAS

#!/usr/bin/env python
import os.path, sys
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
import argparse

import json
import numpy as np

import opensfm.dataset as dataset
import opensfm.io as io


if __name__ == "__main__":
    parser = argparse.ArgumentParser(description='Convert OpenSfM reconstructions to Bundler output format')
    parser.add_argument('dataset', help='path to the dataset to be processed')
    parser.add_argument('--list_path', help='path to the list.txt file')
    parser.add_argument('--bundle_path', help='path to the bundle.out file')
    parser.add_argument('--undistorted',
                        action='store_true',
                        help='export the undistorted reconstruction')

    args = parser.parse_args()

    # Assume that bundle.out, list.txt and all the images are in datapath
    data_path = args.dataset

    # converting reconstruction from bundler to OpenSfM reconstruction
    if args.list_path:
        list_file_path = args.list_path
    else:
        list_file_path = data_path
    if args.bundle_path:
        bundle_file_path = args.bundle_path
    else:
        bundle_file_path = data_path
    data = dataset.DataSet(args.dataset)
    images = data.images()

    if args.undistorted:
        reconstructions = data.load_undistorted_reconstruction()
        track_graph = data.load_undistorted_tracks_graph()
        images = reconstructions[0].shots.keys()
    else:
        reconstructions = data.load_reconstruction()
        track_graph = data.load_tracks_graph()
        images = data.images()

    io.export_bundler(images, reconstructions, track_graph, bundle_file_path, list_file_path)