def property_reference(run_name="property_reference"):
"""Produces identical visualization to small_scale, but does not store
repeated properties of ``vertex_positions`` and ``vertex_normals``.
"""
logdir = os.path.join(BASE_LOGDIR, run_name)
writer = SummaryWriter(logdir)
cube = o3d.geometry.TriangleMesh.create_box(1, 2, 4)
cube.compute_vertex_normals()
cylinder = o3d.geometry.TriangleMesh.create_cylinder(radius=1.0,
height=2.0,
resolution=20,
split=4)
cylinder.compute_vertex_normals()
colors = [(1.0, 0.0, 0.0), (0.0, 1.0, 0.0), (0.0, 0.0, 1.0)]
for step in range(3):
cube.paint_uniform_color(colors[step])
cube_summary = to_dict_batch([cube])
if step > 0:
cube_summary['vertex_positions'] = 0
cube_summary['vertex_normals'] = 0
writer.add_3d('cube', cube_summary, step=step)
cylinder.paint_uniform_color(colors[step])
cylinder_summary = to_dict_batch([cylinder])
if step > 0:
cylinder_summary['vertex_positions'] = 0
cylinder_summary['vertex_normals'] = 0
writer.add_3d('cylinder', cylinder_summary, step=step)
def small_scale(run_name="small_scale"):
"""Basic demo with cube and cylinder with normals and colors.
"""
logdir = os.path.join(BASE_LOGDIR, run_name)
writer = tf.summary.create_file_writer(logdir)
cube = o3d.geometry.TriangleMesh.create_box(1, 2, 4, create_uv_map=True)
cube.compute_vertex_normals()
cylinder = o3d.geometry.TriangleMesh.create_cylinder(radius=1.0,
height=2.0,
resolution=20,
split=4,
create_uv_map=True)
cylinder.compute_vertex_normals()
colors = [(1.0, 0.0, 0.0), (0.0, 1.0, 0.0), (0.0, 0.0, 1.0)]
with writer.as_default():
for step in range(3):
cube.paint_uniform_color(colors[step])
summary.add_3d('cube',
to_dict_batch([cube]),
step=step,
logdir=logdir)
cylinder.paint_uniform_color(colors[step])
summary.add_3d('cylinder',
to_dict_batch([cylinder]),
step=step,
logdir=logdir)
def large_scale(n_steps=16,
batch_size=1,
base_resolution=200,
run_name="large_scale"):
"""Generate a large scale summary. Geometry resolution increases linearly
with step. Each element in a batch is painted a different color.
"""
logdir = os.path.join(BASE_LOGDIR, run_name)
writer = tf.summary.create_file_writer(logdir)
colors = []
for k in range(batch_size):
t = k * np.pi / batch_size
colors.append(((1 + np.sin(t)) / 2, (1 + np.cos(t)) / 2, t / np.pi))
with writer.as_default():
for step in range(n_steps):
resolution = base_resolution * (step + 1)
cylinder_list = []
moebius_list = []
cylinder = o3d.geometry.TriangleMesh.create_cylinder(
radius=1.0, height=2.0, resolution=resolution, split=4)
cylinder.compute_vertex_normals()
moebius = o3d.geometry.TriangleMesh.create_moebius(
length_split=int(3.5 * resolution),
width_split=int(0.75 * resolution),
twists=1,
raidus=1,
flatness=1,
width=1,
scale=1)
moebius.compute_vertex_normals()
for b in range(batch_size):
cylinder_list.append(copy.deepcopy(cylinder))
cylinder_list[b].paint_uniform_color(colors[b])
moebius_list.append(copy.deepcopy(moebius))
moebius_list[b].paint_uniform_color(colors[b])
summary.add_3d('cylinder',
to_dict_batch(cylinder_list),
step=step,
logdir=logdir,
max_outputs=batch_size)
summary.add_3d('moebius',
to_dict_batch(moebius_list),
step=step,
logdir=logdir,
max_outputs=batch_size)
def test_tensorflow_summary(geometry_data, tmp_path):
"""Test writing summary from TensorFlow
"""
tf = pytest.importorskip("tensorflow")
logdir = str(tmp_path)
writer = tf.summary.create_file_writer(logdir)
rng = np.random.default_rng()
tensor_converter = (tf.convert_to_tensor, o3d.core.Tensor.from_numpy,
np.array)
cube, material = geometry_data['cube'], geometry_data['material']
cube_ls, material_ls = geometry_data['cube_ls'], geometry_data[
'material_ls']
colors = geometry_data['colors']
max_outputs = geometry_data['max_outputs']
with writer.as_default():
for step in range(3):
cube[0].paint_uniform_color(colors[step][0])
cube[1].paint_uniform_color(colors[step][1])
cube_summary = to_dict_batch(cube)
cube_summary.update(material)
# Randomly convert to TF, Open3D, Numpy tensors, or use property
# reference
if step > 0:
cube_summary['vertex_positions'] = 0
cube_summary['vertex_normals'] = 0
cube_summary['vertex_colors'] = rng.choice(tensor_converter)(
cube_summary['vertex_colors'])
else:
for prop, tensor in cube_summary.items():
# skip material scalar and vector props
if (not prop.startswith("material_")
or prop.startswith("material_texture_map_")):
cube_summary[prop] = rng.choice(tensor_converter)(
tensor)
summary.add_3d('cube',
cube_summary,
step=step,
logdir=logdir,
max_outputs=max_outputs)
for key in tuple(cube_summary): # Convert to PointCloud
if key.startswith(('triangle_', 'material_texture_map_')):
cube_summary.pop(key)
summary.add_3d('cube_pcd',
cube_summary,
step=step,
logdir=logdir,
max_outputs=max_outputs)
cube_ls[0].paint_uniform_color(colors[step][0])
cube_ls[1].paint_uniform_color(colors[step][1])
cube_ls_summary = to_dict_batch(cube_ls)
cube_ls_summary.update(material_ls)
for prop, tensor in cube_ls_summary.items():
if (not prop.startswith("material_")
or prop.startswith("material_texture_map_")):
cube_ls_summary[prop] = rng.choice(tensor_converter)(
tensor)
summary.add_3d('cube_ls',
cube_ls_summary,
step=step,
logdir=logdir,
max_outputs=max_outputs)
sleep(0.25) # msgpack writing disk flush time
dirpath_ref = [
logdir,
os.path.join(logdir, 'plugins'),
os.path.join(logdir, 'plugins/Open3D')
]
filenames_ref = [['events.out.tfevents.*'], [], ['cube.*.msgpack']]
dirpath, filenames = [], []
for dp, unused_dn, fn in os.walk(logdir):
dirpath.append(dp)
filenames.append(fn)
assert (dirpath[:2] == dirpath_ref[:2]
and dirpath[2][0][:20] == dirpath_ref[2][0][:20])
assert filenames[0][0][:20] == filenames_ref[0][0][:20]
assert set(x.split('.')[0] for x in filenames[2]) == set(
('cube', 'cube_pcd', 'cube_ls'))
assert filenames_ref[2][0][-8:] == '.msgpack'
# Note: The event file written during this test cannot be reliably verified
# in the same Python process, since it's usually buffered by GFile / Python
# / OS and written to disk in increments of the filesystem blocksize.
# Complete write is guaranteed after Python has exited.
shutil.rmtree(logdir)
def test_pytorch_summary(geometry_data, tmp_path):
"""Test writing summary from PyTorch"""
torch = pytest.importorskip("torch")
torch_tb = pytest.importorskip("torch.utils.tensorboard")
SummaryWriter = torch_tb.SummaryWriter
logdir = str(tmp_path)
writer = SummaryWriter(logdir)
rng = np.random.default_rng()
tensor_converter = (torch.from_numpy, o3d.core.Tensor.from_numpy, np.array)
cube, material = geometry_data['cube'], geometry_data['material']
cube_custom_prop = geometry_data['cube_custom_prop']
cube_ls, material_ls = geometry_data['cube_ls'], geometry_data[
'material_ls']
colors = geometry_data['colors']
cube_labels = geometry_data['cube_labels']
label_to_names = geometry_data['label_to_names']
max_outputs = geometry_data['max_outputs']
bboxes = geometry_data['bboxes']
for step in range(3):
cube[0].paint_uniform_color(colors[step][0])
cube[1].paint_uniform_color(colors[step][1])
cube_summary = to_dict_batch(cube)
cube_summary.update(material)
# Randomly convert to PyTorch, Open3D, Numpy tensors, or use property
# reference
if step > 0:
cube_summary['vertex_positions'] = 0
cube_summary['vertex_normals'] = 0
cube_summary['vertex_colors'] = rng.choice(tensor_converter)(
cube_summary['vertex_colors'])
else:
for prop, tensor in cube_summary.items():
# skip material scalar and vector props
if (not prop.startswith("material_")
or prop.startswith("material_texture_map_")):
cube_summary[prop] = rng.choice(tensor_converter)(tensor)
writer.add_3d('cube', cube_summary, step=step, max_outputs=max_outputs)
for key in tuple(cube_summary): # Convert to PointCloud
if key.startswith(('triangle_', 'material_texture_map_')):
cube_summary.pop(key)
cube_summary['vertex_custom'] = tuple(
rng.choice(tensor_converter)(tensor)
for tensor in cube_custom_prop[step]) # Add custom prop
cube_summary['vertex_labels'] = tuple(
rng.choice(tensor_converter)(tensor)
for tensor in cube_labels[step]) # Add labels
writer.add_3d('cube_pcd',
cube_summary,
step=step,
max_outputs=max_outputs,
label_to_names=label_to_names)
cube_ls[0].paint_uniform_color(colors[step][0])
cube_ls[1].paint_uniform_color(colors[step][1])
cube_ls_summary = to_dict_batch(cube_ls)
cube_ls_summary.update(material_ls)
for prop, tensor in cube_ls_summary.items():
if (not prop.startswith("material_")
or prop.startswith("material_texture_map_")):
cube_ls_summary[prop] = rng.choice(tensor_converter)(tensor)
writer.add_3d('cube_ls',
cube_ls_summary,
step=step,
max_outputs=max_outputs)
if len(bboxes) > 0:
writer.add_3d('bboxes', {'bboxes': bboxes[step]},
step=step,
logdir=logdir,
max_outputs=max_outputs,
label_to_names=label_to_names)
sleep(0.25) # msgpack writing disk flush time
tags_ref = geometry_data['tags']
dirpath_ref = [
logdir,
os.path.join(logdir, 'plugins'),
os.path.join(logdir, 'plugins/Open3D')
]
filenames_ref = geometry_data['filenames']
dirpath, filenames = [], []
for dp, unused_dn, fn in os.walk(logdir):
dirpath.append(dp)
filenames.append(fn)
assert dirpath == dirpath_ref
assert filenames[0][0].startswith(filenames_ref[0][0][:20])
assert sorted(x.split('.')[0] for x in filenames[2]) == tags_ref
assert all(fn.endswith('.msgpack') for fn in filenames[2])
# Note: The event file written during this test cannot be reliably verified
# in the same Python process, since it's usually buffered by GFile / Python
# / OS and written to disk in increments of the filesystem blocksize.
# Complete write is guaranteed after Python has exited.
shutil.rmtree(logdir)
def test_pytorch_summary(geometry_data):
"""Test writing summary from PyTorch"""
torch = pytest.importorskip("torch")
torch_tb = pytest.importorskip("torch.utils.tensorboard")
SummaryWriter = torch_tb.SummaryWriter
logdir = tempfile.mkdtemp(prefix='open3d_tb_plugin_test')
writer = SummaryWriter(logdir)
rng = np.random
tensor_converter = (torch.from_numpy, o3d.core.Tensor.from_numpy, np.array)
cube = geometry_data['cube']
cube_ls = geometry_data['cube_ls']
colors = geometry_data['colors']
max_outputs = geometry_data['max_outputs']
for step in range(3):
cube[0].paint_uniform_color(colors[step][0])
cube[1].paint_uniform_color(colors[step][1])
cube_summary = to_dict_batch(cube)
# Randomly convert to PyTorch, Open3D, Numpy tensors, or use property
# reference
if step > 0:
cube_summary['vertex_positions'] = 0
cube_summary['vertex_normals'] = 0
cube_summary['vertex_colors'] = rng.choice(tensor_converter)(
cube_summary['vertex_colors'])
else:
for prop, tensor in cube_summary.items():
cube_summary[prop] = rng.choice(tensor_converter)(tensor)
writer.add_3d('cube', cube_summary, step=step, max_outputs=max_outputs)
cube_summary.pop('triangle_indices') # Convert to PointCloud
writer.add_3d('cube_pcd',
cube_summary,
step=step,
max_outputs=max_outputs)
cube_ls[0].paint_uniform_color(colors[step][0])
cube_ls[1].paint_uniform_color(colors[step][1])
cube_ls_summary = to_dict_batch(cube_ls)
for prop, tensor in cube_ls_summary.items():
cube_ls_summary[prop] = rng.choice(tensor_converter)(tensor)
writer.add_3d('cube_ls',
cube_ls_summary,
step=step,
max_outputs=max_outputs)
sleep(0.25) # msgpack writing disk flush time
dirpath_ref = [
logdir,
os.path.join(logdir, 'plugins'),
os.path.join(logdir, 'plugins/Open3D')
]
filenames_ref = [['events.out.tfevents.*'], [], ['cube.*.msgpack']]
dirpath, filenames = [], []
for dp, unused_dn, fn in os.walk(logdir):
dirpath.append(dp)
filenames.append(fn)
assert (dirpath[:2] == dirpath_ref[:2] and
dirpath[2][0][:20] == dirpath_ref[2][0][:20])
assert filenames[0][0][:20] == filenames_ref[0][0][:20]
assert set(x.split('.')[0] for x in filenames[2]) == set(
('cube', 'cube_pcd', 'cube_ls'))
assert filenames_ref[2][0][-8:] == '.msgpack'
# Note: The event file written during this test cannot be reliably verified
# in the same Python process, since it's usually buffered by GFile / Python
# / OS and written to disk in increments of the filesystem blocksize.
# Complete write is guaranteed after Python has exited.
shutil.rmtree(logdir)
