def main(_):
from shapenet.core import to_cat_id
from shapenet.core.renderings.renderings_manager import get_base_manager
from shapenet.core.frustrum_voxels import create_frustrum_voxels
from shapenet.core.frustrum_voxels import create_temp_frustrum_voxels
from shapenet.core.voxels.config import get_config
if FLAGS.src_voxel_dim is None:
FLAGS.src_voxel_dim = FLAGS.voxel_dim
voxel_config = get_config(
FLAGS.src_voxel_dim, alt=False).filled(FLAGS.fill_alg)
manager = get_base_manager(
dim=FLAGS.dim, turntable=FLAGS.turntable,
n_views=FLAGS.n_views)
cats = FLAGS.cat
if cats is None:
from shapenet.r2n2 import get_cat_ids
cats = get_cat_ids()
for cat in cats:
cat_id = to_cat_id(cat)
args = manager, voxel_config, FLAGS.voxel_dim, cat_id
if FLAGS.temp_only:
create_temp_frustrum_voxels(*args, compression=FLAGS.compression)
else:
create_frustrum_voxels(*args, compression=FLAGS.compression)
def main(_):
from shapenet.core.voxels.config import get_config
from shapenet.core import to_cat_id
from shapenet.r2n2 import get_cat_ids
config = get_config(FLAGS.voxel_dim, alt=FLAGS.alt)
fill = FLAGS.fill
if fill is not None:
config = config.filled(fill)
if FLAGS.cat is None:
cat_ids = get_cat_ids()
else:
cat_ids = [to_cat_id(c) for c in FLAGS.cat]
if FLAGS.fill is not None:
config = config.filled(FLAGS.fill)
for cat_id in cat_ids:
config.create_voxel_data(cat_id)
def main(_):
from progress.bar import IncrementalBar
import numpy as np
from shapenet.core import to_cat_id
from shapenet.core.renderings.renderings_manager import get_base_manager
from shapenet.core.frustrum_voxels import get_frustrum_voxels_data
from shapenet.core.frustrum_voxels import GROUP_KEY
from shapenet.core.voxels.config import get_config
from util3d.voxel import rle
voxel_config = get_config(FLAGS.src_voxel_dim,
alt=False).filled('orthographic')
manager = get_base_manager(dim=FLAGS.dim,
turntable=FLAGS.turntable,
n_views=FLAGS.n_views)
cats = FLAGS.cat
if cats is None:
from shapenet.r2n2 import get_cat_ids
cats = get_cat_ids()
expected_length = FLAGS.voxel_dim**3
for ci, cat in enumerate(cats):
# if ci >= 3:
# continue
cat_id = to_cat_id(cat)
print('Checking cat %s: %d / %d' % (cat_id, ci + 1, len(cats)))
with get_frustrum_voxels_data(manager.root_dir, voxel_config,
FLAGS.voxel_dim, cat_id) as root:
data = root[GROUP_KEY]
ne, nr = data.shape[:2]
bar = IncrementalBar(max=ne)
for i in range(ne):
bar.next()
di = np.array(data[i])
for j in range(nr):
actual_length = rle.length(di[j])
# actual_length = len(rle.rle_to_dense(di[j]))
if actual_length != expected_length:
raise ValueError(
'Incorrect length at %s, %d, %d\n'
'Expected %d, got %d' %
(cat_id, i, j, expected_length, actual_length))
bar.finish()
def main(_):
from shapenet.core.renderings.renderings_manager import get_base_manager
from shapenet.core import cat_desc_to_id
from shapenet.core import cat_id_to_desc
cat = FLAGS.cat
if cat is None or len(cat) == 0:
from shapenet.r2n2 import get_cat_ids
cat_ids = get_cat_ids()
else:
cat_ids = [cat_desc_to_id(c) for c in FLAGS.cat]
print('Required renderings:')
for cat_id in cat_ids:
manager = get_base_manager(
dim=FLAGS.dim,
turntable=FLAGS.turntable,
n_views=FLAGS.n_views,
)
n = len(tuple(manager.needs_rendering_keys(cat_ids=[cat_id])))
n_total = len(tuple(manager.view_manager.keys(cat_ids=[cat_id])))
cat = cat_id_to_desc(cat_id)
print('%s: %s\n %d / %d' % (cat_id, cat, n, n_total))
def main(_):
from shapenet.core.renderings.archive_manager import get_archive_manager
from shapenet.core.renderings.renderings_manager import get_base_manager
rend_manager = get_base_manager(
dim=FLAGS.dim, turntable=FLAGS.turntable,
n_views=FLAGS.n_renderings)
if FLAGS.cat is None:
from shapenet.r2n2 import get_cat_ids
cats = get_cat_ids()
else:
cats = FLAGS.cat
format = FLAGS.format
mode = 'r' if FLAGS.check else 'a'
for cat in cats:
archive_manager = get_archive_manager(
rend_manager, cat, base_only=not FLAGS.full,
format=format, mode=mode)
with archive_manager.archive:
if FLAGS.check:
archive_manager.check()
else:
archive_manager.add()
#!/usr/bin/python
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from shapenet.r2n2 import get_cat_ids
from shapenet.r2n2.hdf5 import Hdf5Manager, meta_index
az_index = meta_index('azimuth')
el_index = meta_index('elevation')
az = []
el = []
for cat_id in get_cat_ids():
with Hdf5Manager(cat_id) as manager:
g = manager.meta_group
az.append(np.array(g[..., az_index]))
el.append(np.array(g[..., el_index]))
az = np.concatenate(az, axis=0).flatten()
el = np.concatenate(el, axis=0).flatten()
def vis(az, el):
import matplotlib.pyplot as plt
_, (ax0, ax1) = plt.subplots(1, 2)
ax0.hist(az, bins=36)
ax1.hist(el, bins=36)
plt.show()
#!/usr/bin/python
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from shapenet.r2n2 import get_cat_ids
from shapenet.core.voxels.datasets import get_manager, convert
from shapenet.core.voxels import get_config
cat_ids = get_cat_ids()
voxel_dims = (32, 64, 128, 256)
n_configs = 2
n = len(cat_ids) * len(voxel_dims) * n_configs
i = 1
for voxel_dim in voxel_dims:
for config in (
get_config(voxel_dim).filled('orthographic'),
get_config(voxel_dim, alt=True),
):
for cat_id in cat_ids:
dst = get_manager(config,
cat_id,
key='brle',
compression='lzf',
pad=True)
src_kwargs = dict(key='file')
print('Converting %d / %d' % (i, n))
convert(dst, overwrite=False, delete_src=False, **src_kwargs)
i += 1