def mesh_to_example(codebase_root_dir, mesh_path, dirpath, skip_existing,
log_level):
# Logging level must be specified because mesh_to_example is an entry point
# for a subprocess call.
log.set_level(log_level)
ldif_path = path_util.get_path_to_ldif_root()
if not skip_existing or not os.path.isfile(
f'{dirpath}/depth_and_normals.npz'):
sp.check_output(
f'{codebase_root_dir}/scripts/process_mesh_local.sh {mesh_path} {dirpath} {ldif_path}',
shell=True)
write_depth_and_normals_npz(dirpath,
f'{dirpath}/depth_and_normals.npz')
else:
log.verbose(f'Skipping shell script processing for {dirpath},'
' the output already exists.')
# Precompute the dodeca samples for later:
e = example.InferenceExample.from_directory(dirpath)
sample_path = e.precomputed_surface_samples_from_dodeca_path
if not skip_existing or not os.path.isfile(sample_path):
e.surface_sample_count = 100000
precomputed_samples = e.surface_samples_from_dodeca
assert precomputed_samples.shape[0] == 100000
assert precomputed_samples.shape[1] == 6
file_util.write_points(sample_path, precomputed_samples)
else:
log.verbose(
f'Skipping surface sample precompution for {dirpath}, it\'s already done.'
)
def get_model_root():
"""Finds the path to the trained model's root directory based on flags."""
ldif_abspath = path_util.get_path_to_ldif_root()
model_dir_is_relative = FLAGS.model_directory[0] != '/'
if model_dir_is_relative:
model_dir_path = os.path.join(ldif_abspath, FLAGS.model_directory)
else:
model_dir_path = FLAGS.model_directory
if not os.path.isdir(model_dir_path):
os.makedirs(model_dir_path)
return model_dir_path
def get_model_root():
"""Finds the path to the trained model's root directory based on flags."""
ldif_abspath = path_util.get_path_to_ldif_root()
model_dir_is_relative = FLAGS.model_directory[0] != '/'
if model_dir_is_relative:
model_dir_path = os.path.join(ldif_abspath, FLAGS.model_directory)
else:
model_dir_path = FLAGS.model_directory
if not os.path.isdir(model_dir_path):
raise ValueError(f'Could not find model directory {model_dir_path}')
return model_dir_path
def get_npz_paths(split, category, modifier=''):
"""Returns the list of npz paths for the split's ground truth."""
t = time.time()
ensure_split_valid(split)
filelist = os.path.join(
path_util.get_path_to_ldif_root(),
'data/basedirs/%s-%s%s.txt' % (split, category, modifier))
try:
filenames = file_util.readlines(filelist)
except:
raise ValueError('Unable to read filelist %s.' % filelist)
tf.logging.info('Loaded filelist in %0.2fms.', (time.time() - t))
return filenames
def mesh_to_example(codebase_root_dir, mesh_path, dirpath, skip_existing,
log_level):
# Logging level must be specified because mesh_to_example is an entry point
# for a subprocess call.
log.set_level(log_level)
ldif_path = path_util.get_path_to_ldif_root()
if not skip_existing or not os.path.isfile(
f'{dirpath}/depth_and_normals.npz'):
sp.check_output(
f'{codebase_root_dir}/scripts/process_mesh_local.sh {mesh_path} {dirpath} {ldif_path}',
shell=True)
# write_depth_and_normals_npz(dirpath, f'{dirpath}/depth_and_normals.npz')
else:
log.verbose(f'Skipping shell script processing for {dirpath},'
' the output already exists.')
def __init__(self, is_local):
if is_local:
self.path = os.path.join(path_util.get_path_to_ldif_root(),
'data/hashlist.csv')
else:
raise ValueError('Remote hashlist no longer supported.')
with file_util.open_file(self.path, 'rt') as f:
self.df = pd.read_csv(
f,
dtype={
'split': str,
'synset': str,
'hash': str,
'synset_inv_freq': np.float32
},
usecols=['split', 'synset', 'hash', 'synset_inv_freq'])
def local_root(self):
return os.path.join(path_util.get_path_to_ldif_root(), 'result_store')
def setUp(self):
super(ModelTest, self).setUp()
self.test_data_directory = os.path.join(
path_util.get_path_to_ldif_root(), 'test_data')