def read_binary_files_factorized(filename, rootdir='./'):
"""Read from compressed binary files:
1) Compressed latent features.
2) Number of input points.
3) Positions of each cube.
"""
print('===== Read binary files =====')
file_strings = os.path.join(rootdir, filename + '.strings')
file_pointnums = os.path.join(rootdir, filename + '.pointnums')
file_cubepos = os.path.join(rootdir, filename + '.cubepos')
ply_cubepos = os.path.join(rootdir, filename + '_cubepos.ply')
with open(file_strings, 'rb') as f:
shape = np.frombuffer(f.read(2 * 5), dtype=np.int16)
min_v, max_v = np.frombuffer(f.read(1 * 2), dtype=np.int8)
strings = f.read()
with open(file_pointnums, 'rb') as f:
points_numbers = np.frombuffer(f.read(), dtype=np.uint16)
gpcc_decode(file_cubepos, ply_cubepos)
cube_positions = load_ply_data(ply_cubepos)
return strings, points_numbers, cube_positions, min_v, max_v, shape
def read_binary_files_hyper(filename, rootdir='./'):
"""Read from compressed binary files:
1) Compressed latent features.
2) Compressed hyperprior.
3) Number of input points.
4) Positions of each cube.
"""
print('===== Read binary files =====')
file_strings = os.path.join(rootdir, filename + '.strings')
file_strings_head = os.path.join(rootdir, filename + '.strings_head')
file_strings_hyper = os.path.join(rootdir, filename + '.strings_hyper')
file_pointnums = os.path.join(rootdir, filename + '.pointnums')
file_cubepos = os.path.join(rootdir, filename + '.cubepos')
ply_cubepos = os.path.join(rootdir, filename + '_cubepos.ply')
with open(file_strings_head, 'rb') as f:
y_strings_num = int(np.frombuffer(f.read(1 * 2), dtype=np.int16))
y_max_min_vs = np.frombuffer(f.read(y_strings_num * 1),
dtype=np.uint8).astype('int32')
y_max_vs = y_max_min_vs // 16
y_min_vs = -(y_max_min_vs % 16)
# y_min_vs = np.array(y_min_vs).astype('int32')
# y_max_vs = np.array(y_max_vs).astype('int32')
y_strings_lens = []
for i in range(y_strings_num):
l = np.frombuffer(f.read(1 * 1), dtype=np.uint8)
if l == 0:
l = int(np.frombuffer(f.read(1 * 2), dtype=np.int16))
y_strings_lens.append(l)
y_strings_lens = np.array(y_strings_lens, dtype=np.int32)
y_shape = np.frombuffer(f.read(2 * 5), dtype=np.int16)
f.close()
with open(file_strings, 'rb') as f:
y_strings = []
for i, l in enumerate(y_strings_lens):
y_strings.append(f.read(int(l)))
y_strings = np.array(y_strings)
f.close()
with open(file_strings_hyper, 'rb') as f:
z_shape = np.frombuffer(f.read(2 * 5), dtype=np.int16)
z_min_v, z_max_v = np.frombuffer(f.read(1 * 2), dtype=np.int8)
z_strings = f.read()
with open(file_pointnums, 'rb') as f:
points_numbers = np.frombuffer(f.read(), dtype=np.uint16)
gpcc_decode(file_cubepos, ply_cubepos)
cube_positions = load_ply_data(ply_cubepos)
# y_shape = np.array([1, 16, 16, 16, 16])
return y_strings, z_strings, points_numbers, cube_positions, y_min_vs, y_max_vs, y_shape, z_min_v, z_max_v, z_shape