import os import argparse import json import numpy as np import pprint import time import multiprocessing as mp from functools import partial from plyfile import PlyData from tqdm import tqdm import torch dict_align_matrix ={} def process_per_scan(scan_id, scan_dir): global dict_align_matrix # Load point clouds with colors with open(os.path.join(scan_dir, scan_id, '%s_vh_clean_2.ply'%(scan_id)), 'rb') as f: plydata = PlyData.read(f) # elements: vertex, face points = np.array([list(x) for x in plydata.elements[0]]) # [[x, y, z, r, g, b, alpha]] coords = np.ascontiguousarray(points[:, :3]) colors = np.ascontiguousarray(points[:, 3:6]) # # TODO: normalize the coords and colors # coords = coords - coords.mean(0) # colors = colors / 127.5 - 1 align_matrix = np.eye(4) with open(os.path.join(scan_dir, scan_id, '%s.txt'%(scan_id)), 'r') as f: for line in f: if line.startswith('axisAlignment'): align_matrix = np.array([float(x) for x in line.strip().split()[-16:]]).astype(np.float32).reshape(4, 4) break # Transform the points pts = np.ones((coords.shape[0], 4), dtype=coords.dtype) pts[:, 0:3] = coords coords = np.dot(pts, align_matrix.transpose())[:, :3] # Nx4 dict_align_matrix[scan_id] = align_matrix.tolist() # Make sure no nans are introduced after conversion assert (np.sum(np.isnan(coords)) == 0) def parse_args(): parser = argparse.ArgumentParser() parser.add_argument('--scannet_dir', required=True, type=str, help='the path to the downloaded ScanNet scans') # Optional arguments. parser.add_argument('--num_workers', default=-1, type=int, help='the number of processes, -1 means use the available max') parser.add_argument('--apply_global_alignment', default=True, action='store_true', help='rotate/translate entire scan globally to aligned it with other scans') args = parser.parse_args() # Print the args args_string = pprint.pformat(vars(args)) print(args_string) return args def main(): args = parse_args() # for split in ['scans', 'scans_test']: for split in ['scans']: scannet_dir = os.path.join(args.scannet_dir, split) scan_ids = os.listdir(scannet_dir) scan_ids.sort() print(split, '%d scans' % (len(scan_ids))) for scan_id in tqdm(scan_ids): process_per_scan(scan_id=scan_id,scan_dir=scannet_dir) global dict_align_matrix json.dump(dict_align_matrix,open("scannet_align_matrix.json","w")) if __name__ == '__main__': main()