-
Notifications
You must be signed in to change notification settings - Fork 26
/
LMDB_Writer.py
52 lines (41 loc) · 2.18 KB
/
LMDB_Writer.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
# Copyright (c) 2020. Author: Hanchen Wang, hw501@cam.ac.uk
import os, argparse, numpy as np
from tensorpack import DataFlow, dataflow
from open3d.open3d.io import read_triangle_mesh, read_point_cloud
def sample_from_mesh(filename, num_samples=16384):
pcd = read_triangle_mesh(filename).sample_points_uniformly(number_of_points=num_samples)
return np.array(pcd.points)
class pcd_df(DataFlow):
def __init__(self, model_list, num_scans, partial_dir, complete_dir, num_partial_points=1024):
self.model_list = [_file for _file in model_list if 'train' in _file]
self.num_scans = num_scans
self.partial_dir = partial_dir
self.complete_dir = complete_dir
self.num_ppoints = num_partial_points
def size(self):
return len(self.model_list) * self.num_scans
@staticmethod
def read_pcd(filename):
pcd = read_point_cloud(filename)
return np.array(pcd.points)
def get_data(self):
for model_id in self.model_list:
complete = sample_from_mesh(os.path.join(self.complete_dir, '%s.obj' % model_id))
for i in range(self.num_scans):
partial = self.read_pcd(os.path.join(self.partial_dir, model_id + '_%d.pcd' % i))
partial = partial[np.random.choice(len(partial), self.num_ppoints)]
yield model_id.replace('/', '_'), partial, complete
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--list_path', default=r'../render/ModelNet_flist_normalised.txt')
parser.add_argument('--num_scans', type=int, default=10)
parser.add_argument('--partial_dir', default=r'../render/dump_modelnet_normalised_supercoarse/pcd')
parser.add_argument('--complete_dir', default=r'../data/ModelNet40')
parser.add_argument('--output_file', default=r'../data/ModelNet40_train_1024_supercoarse.lmdb')
args = parser.parse_args()
with open(args.list_path) as file:
model_list = file.read().splitlines()
df = pcd_df(model_list, args.num_scans, args.partial_dir, args.complete_dir)
if os.path.exists(args.output_file):
os.system('rm %s' % args.output_file)
dataflow.LMDBSerializer.save(df, args.output_file)