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Running
on
Zero
Running
on
Zero
| import os | |
| import copy | |
| import sys | |
| import importlib | |
| import argparse | |
| import pandas as pd | |
| from easydict import EasyDict as edict | |
| from functools import partial | |
| import numpy as np | |
| import open3d as o3d | |
| import utils3d | |
| def _voxelize(file, sha256, output_dir): | |
| mesh = o3d.io.read_triangle_mesh(os.path.join(output_dir, 'renders', sha256, 'mesh.ply')) | |
| # clamp vertices to the range [-0.5, 0.5] | |
| vertices = np.clip(np.asarray(mesh.vertices), -0.5 + 1e-6, 0.5 - 1e-6) | |
| mesh.vertices = o3d.utility.Vector3dVector(vertices) | |
| voxel_grid = o3d.geometry.VoxelGrid.create_from_triangle_mesh_within_bounds(mesh, voxel_size=1/64, min_bound=(-0.5, -0.5, -0.5), max_bound=(0.5, 0.5, 0.5)) | |
| vertices = np.array([voxel.grid_index for voxel in voxel_grid.get_voxels()]) | |
| assert np.all(vertices >= 0) and np.all(vertices < 64), "Some vertices are out of bounds" | |
| vertices = (vertices + 0.5) / 64 - 0.5 | |
| utils3d.io.write_ply(os.path.join(output_dir, 'voxels', f'{sha256}.ply'), vertices) | |
| return {'sha256': sha256, 'voxelized': True, 'num_voxels': len(vertices)} | |
| if __name__ == '__main__': | |
| dataset_utils = importlib.import_module(f'datasets.{sys.argv[1]}') | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument('--output_dir', type=str, required=True, | |
| help='Directory to save the metadata') | |
| parser.add_argument('--filter_low_aesthetic_score', type=float, default=None, | |
| help='Filter objects with aesthetic score lower than this value') | |
| parser.add_argument('--instances', type=str, default=None, | |
| help='Instances to process') | |
| parser.add_argument('--num_views', type=int, default=150, | |
| help='Number of views to render') | |
| dataset_utils.add_args(parser) | |
| parser.add_argument('--rank', type=int, default=0) | |
| parser.add_argument('--world_size', type=int, default=1) | |
| parser.add_argument('--max_workers', type=int, default=None) | |
| opt = parser.parse_args(sys.argv[2:]) | |
| opt = edict(vars(opt)) | |
| os.makedirs(os.path.join(opt.output_dir, 'voxels'), exist_ok=True) | |
| # get file list | |
| if not os.path.exists(os.path.join(opt.output_dir, 'metadata.csv')): | |
| raise ValueError('metadata.csv not found') | |
| metadata = pd.read_csv(os.path.join(opt.output_dir, 'metadata.csv')) | |
| if opt.instances is None: | |
| if opt.filter_low_aesthetic_score is not None: | |
| metadata = metadata[metadata['aesthetic_score'] >= opt.filter_low_aesthetic_score] | |
| if 'rendered' not in metadata.columns: | |
| raise ValueError('metadata.csv does not have "rendered" column, please run "build_metadata.py" first') | |
| metadata = metadata[metadata['rendered'] == True] | |
| if 'voxelized' in metadata.columns: | |
| metadata = metadata[metadata['voxelized'] == False] | |
| else: | |
| if os.path.exists(opt.instances): | |
| with open(opt.instances, 'r') as f: | |
| instances = f.read().splitlines() | |
| else: | |
| instances = opt.instances.split(',') | |
| metadata = metadata[metadata['sha256'].isin(instances)] | |
| start = len(metadata) * opt.rank // opt.world_size | |
| end = len(metadata) * (opt.rank + 1) // opt.world_size | |
| metadata = metadata[start:end] | |
| records = [] | |
| # filter out objects that are already processed | |
| for sha256 in copy.copy(metadata['sha256'].values): | |
| if os.path.exists(os.path.join(opt.output_dir, 'voxels', f'{sha256}.ply')): | |
| pts = utils3d.io.read_ply(os.path.join(opt.output_dir, 'voxels', f'{sha256}.ply'))[0] | |
| records.append({'sha256': sha256, 'voxelized': True, 'num_voxels': len(pts)}) | |
| metadata = metadata[metadata['sha256'] != sha256] | |
| print(f'Processing {len(metadata)} objects...') | |
| # process objects | |
| func = partial(_voxelize, output_dir=opt.output_dir) | |
| voxelized = dataset_utils.foreach_instance(metadata, opt.output_dir, func, max_workers=opt.max_workers, desc='Voxelizing') | |
| voxelized = pd.concat([voxelized, pd.DataFrame.from_records(records)]) | |
| voxelized.to_csv(os.path.join(opt.output_dir, f'voxelized_{opt.rank}.csv'), index=False) | |