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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()
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