def _archive(self):
"""The backing npz file contents."""
if self.__archive is None:
t = time.time()
try:
self.__archive = file_util.read_npz(self.npz_path)
except:
raise ValueError('Failed to read %s' % self.npz_path)
log('Time loading input archive: %0.2f' % (time.time() - t))
return self.__archive
def testBatchedDodecaDepthToXYZ(self):
npz_fnames = [
'53502c15c30d06496e4e9b7d32a4f90d.npz',
'53a60f2eb6b1a3e9afe717997470b28d.npz'
]
all_depth_ims = []
for fname in npz_fnames:
npz_filename = os.path.join(self.test_data_directory, fname)
all_depth_ims.append(
file_util.read_npz(npz_filename)['gaps_depth'] / 1000.0)
depth_ims_tf = tf.stack(all_depth_ims)
xyz_tf = geom_util.transform_depth_dodeca_to_xyz_dodeca(depth_ims_tf)
with self.test_session() as session:
xyz_np = session.run(xyz_tf)
output_dir = path_util.create_test_output_dir()
for i in range(len(npz_fnames)):
np.save(output_dir + '/xyz_im_%i.npy' % i, xyz_np[i, ...])
def testAllToXYZ(self):
npz_filename = '53a60f2eb6b1a3e9afe717997470b28d.npz'
npz_filename = os.path.join(self.test_data_directory, npz_filename)
npz = file_util.read_npz(npz_filename)
depth_ims = npz['gaps_depth'] / 1000.0
surface_pts = npz['surface_points']
depth_ims_tf = tf.reshape(tf.constant(depth_ims, dtype=tf.float32),
[1, 20, 224, 224, 1])
xyz_images = geom_util.transform_depth_dodeca_to_xyz_dodeca(
depth_ims_tf)
with self.test_session() as session:
xyz_np = session.run(xyz_images)
output_dir = path_util.create_test_output_dir()
valid_locations = depth_ims != 0.0
valid_locations = np.reshape(valid_locations, [1, 20, 224, 224])
filtered_xyz = xyz_np[valid_locations, :]
xyz_from_depth = np.reshape(filtered_xyz, [-1, 3])
np.random.shuffle(xyz_from_depth)
xyz_from_depth = xyz_from_depth[:10000, :]
np.save(output_dir + '/surface_pts.npy', surface_pts)
np.save(output_dir + '/depth_xyz.npy', xyz_np)
np.save(output_dir + '/depth.npy', depth_ims)
np.save(output_dir + '/filtered_xyz.npy', filtered_xyz)
np.save(output_dir + '/xyz_from_depth.npy', xyz_from_depth)
def _load_max_depth_normals(self): path = self.max_depth_normals_path dn = file_util.read_npz(path)['arr_0'] depth = dn[:, :, :, 0:1] normals = dn[:, :, :, 1:] return depth, normals
def load_depth_and_normal_npz(self, path): depth_normal_arr = file_util.read_npz(path)['arr_0'] depth = depth_normal_arr[..., 0] # For backwards compat. normals = depth_normal_arr[..., 1:] return depth, normals