252 lines
8.0 KiB
Python
252 lines
8.0 KiB
Python
|
# Copyright 2019 The TensorFlow Authors. All Rights Reserved.
|
||
|
|
#
|
||
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
||
|
|
# you may not use this file except in compliance with the License.
|
||
|
|
# You may obtain a copy of the License at
|
||
|
|
#
|
||
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
||
|
|
#
|
||
|
|
# Unless required by applicable law or agreed to in writing, software
|
||
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
||
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||
|
|
# See the License for the specific language governing permissions and
|
||
|
|
# limitations under the License.
|
||
|
|
# ==============================================================================
|
||
|
|
"""Mesh summaries and TensorFlow operations to create them.
|
||
|
|
|
||
|
|
This file is deprecated. See `summary_v2.py` instead.
|
||
|
|
"""
|
||
|
|
|
||
|
|
import json
|
||
|
|
import tensorflow as tf
|
||
|
|
|
||
|
|
from tensorboard.plugins.mesh import metadata
|
||
|
|
from tensorboard.plugins.mesh import plugin_data_pb2
|
||
|
|
from tensorboard.plugins.mesh import summary_v2
|
||
|
|
|
||
|
|
# Export V2 versions.
|
||
|
|
mesh = summary_v2.mesh
|
||
|
|
mesh_pb = summary_v2.mesh_pb
|
||
|
|
|
||
|
|
|
||
|
|
def _get_tensor_summary(
|
||
|
|
name,
|
||
|
|
display_name,
|
||
|
|
description,
|
||
|
|
tensor,
|
||
|
|
content_type,
|
||
|
|
components,
|
||
|
|
json_config,
|
||
|
|
collections,
|
||
|
|
):
|
||
|
|
"""Creates a tensor summary with summary metadata.
|
||
|
|
|
||
|
|
Args:
|
||
|
|
name: Uniquely identifiable name of the summary op. Could be replaced by
|
||
|
|
combination of name and type to make it unique even outside of this
|
||
|
|
summary.
|
||
|
|
display_name: Will be used as the display name in TensorBoard.
|
||
|
|
Defaults to `tag`.
|
||
|
|
description: A longform readable description of the summary data. Markdown
|
||
|
|
is supported.
|
||
|
|
tensor: Tensor to display in summary.
|
||
|
|
content_type: Type of content inside the Tensor.
|
||
|
|
components: Bitmask representing present parts (vertices, colors, etc.) that
|
||
|
|
belong to the summary.
|
||
|
|
json_config: A string, JSON-serialized dictionary of ThreeJS classes
|
||
|
|
configuration.
|
||
|
|
collections: List of collections to add this summary to.
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
Tensor summary with metadata.
|
||
|
|
"""
|
||
|
|
tensor = tf.convert_to_tensor(value=tensor)
|
||
|
|
shape = tensor.shape.as_list()
|
||
|
|
shape = [dim if dim is not None else -1 for dim in shape]
|
||
|
|
tensor_metadata = metadata.create_summary_metadata(
|
||
|
|
name,
|
||
|
|
display_name,
|
||
|
|
content_type,
|
||
|
|
components,
|
||
|
|
shape,
|
||
|
|
description,
|
||
|
|
json_config=json_config,
|
||
|
|
)
|
||
|
|
tensor_summary = tf.compat.v1.summary.tensor_summary(
|
||
|
|
metadata.get_instance_name(name, content_type),
|
||
|
|
tensor,
|
||
|
|
summary_metadata=tensor_metadata,
|
||
|
|
collections=collections,
|
||
|
|
)
|
||
|
|
return tensor_summary
|
||
|
|
|
||
|
|
|
||
|
|
def _get_display_name(name, display_name):
|
||
|
|
"""Returns display_name from display_name and name."""
|
||
|
|
if display_name is None:
|
||
|
|
return name
|
||
|
|
return display_name
|
||
|
|
|
||
|
|
|
||
|
|
def _get_json_config(config_dict):
|
||
|
|
"""Parses and returns JSON string from python dictionary."""
|
||
|
|
json_config = "{}"
|
||
|
|
if config_dict is not None:
|
||
|
|
json_config = json.dumps(config_dict, sort_keys=True)
|
||
|
|
return json_config
|
||
|
|
|
||
|
|
|
||
|
|
def op(
|
||
|
|
name,
|
||
|
|
vertices,
|
||
|
|
faces=None,
|
||
|
|
colors=None,
|
||
|
|
display_name=None,
|
||
|
|
description=None,
|
||
|
|
collections=None,
|
||
|
|
config_dict=None,
|
||
|
|
):
|
||
|
|
"""Creates a TensorFlow summary op for mesh rendering.
|
||
|
|
|
||
|
|
DEPRECATED: see `summary_v2.py` instead.
|
||
|
|
|
||
|
|
Args:
|
||
|
|
name: A name for this summary operation.
|
||
|
|
vertices: Tensor of shape `[dim_1, ..., dim_n, 3]` representing the 3D
|
||
|
|
coordinates of vertices.
|
||
|
|
faces: Tensor of shape `[dim_1, ..., dim_n, 3]` containing indices of
|
||
|
|
vertices within each triangle.
|
||
|
|
colors: Tensor of shape `[dim_1, ..., dim_n, 3]` containing colors for each
|
||
|
|
vertex.
|
||
|
|
display_name: If set, will be used as the display name in TensorBoard.
|
||
|
|
Defaults to `name`.
|
||
|
|
description: A longform readable description of the summary data. Markdown
|
||
|
|
is supported.
|
||
|
|
collections: Which TensorFlow graph collections to add the summary op to.
|
||
|
|
Defaults to `['summaries']`. Can usually be ignored.
|
||
|
|
config_dict: Dictionary with ThreeJS classes names and configuration.
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
Merged summary for mesh/point cloud representation.
|
||
|
|
"""
|
||
|
|
display_name = _get_display_name(name, display_name)
|
||
|
|
json_config = _get_json_config(config_dict)
|
||
|
|
|
||
|
|
# All tensors representing a single mesh will be represented as separate
|
||
|
|
# summaries internally. Those summaries will be regrouped on the client before
|
||
|
|
# rendering.
|
||
|
|
summaries = []
|
||
|
|
tensors = [
|
||
|
|
metadata.MeshTensor(
|
||
|
|
vertices, plugin_data_pb2.MeshPluginData.VERTEX, tf.float32
|
||
|
|
),
|
||
|
|
metadata.MeshTensor(
|
||
|
|
faces, plugin_data_pb2.MeshPluginData.FACE, tf.int32
|
||
|
|
),
|
||
|
|
metadata.MeshTensor(
|
||
|
|
colors, plugin_data_pb2.MeshPluginData.COLOR, tf.uint8
|
||
|
|
),
|
||
|
|
]
|
||
|
|
tensors = [tensor for tensor in tensors if tensor.data is not None]
|
||
|
|
|
||
|
|
components = metadata.get_components_bitmask(
|
||
|
|
[tensor.content_type for tensor in tensors]
|
||
|
|
)
|
||
|
|
|
||
|
|
for tensor in tensors:
|
||
|
|
summaries.append(
|
||
|
|
_get_tensor_summary(
|
||
|
|
name,
|
||
|
|
display_name,
|
||
|
|
description,
|
||
|
|
tensor.data,
|
||
|
|
tensor.content_type,
|
||
|
|
components,
|
||
|
|
json_config,
|
||
|
|
collections,
|
||
|
|
)
|
||
|
|
)
|
||
|
|
|
||
|
|
all_summaries = tf.compat.v1.summary.merge(
|
||
|
|
summaries, collections=collections, name=name
|
||
|
|
)
|
||
|
|
return all_summaries
|
||
|
|
|
||
|
|
|
||
|
|
def pb(
|
||
|
|
name,
|
||
|
|
vertices,
|
||
|
|
faces=None,
|
||
|
|
colors=None,
|
||
|
|
display_name=None,
|
||
|
|
description=None,
|
||
|
|
config_dict=None,
|
||
|
|
):
|
||
|
|
"""Create a mesh summary to save in pb format.
|
||
|
|
|
||
|
|
DEPRECATED: see `summary_v2.py` instead.
|
||
|
|
|
||
|
|
Args:
|
||
|
|
name: A name for this summary operation.
|
||
|
|
vertices: numpy array of shape `[dim_1, ..., dim_n, 3]` representing the 3D
|
||
|
|
coordinates of vertices.
|
||
|
|
faces: numpy array of shape `[dim_1, ..., dim_n, 3]` containing indices of
|
||
|
|
vertices within each triangle.
|
||
|
|
colors: numpy array of shape `[dim_1, ..., dim_n, 3]` containing colors for
|
||
|
|
each vertex.
|
||
|
|
display_name: If set, will be used as the display name in TensorBoard.
|
||
|
|
Defaults to `name`.
|
||
|
|
description: A longform readable description of the summary data. Markdown
|
||
|
|
is supported.
|
||
|
|
config_dict: Dictionary with ThreeJS classes names and configuration.
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
Instance of tf.Summary class.
|
||
|
|
"""
|
||
|
|
display_name = _get_display_name(name, display_name)
|
||
|
|
json_config = _get_json_config(config_dict)
|
||
|
|
|
||
|
|
summaries = []
|
||
|
|
tensors = [
|
||
|
|
metadata.MeshTensor(
|
||
|
|
vertices, plugin_data_pb2.MeshPluginData.VERTEX, tf.float32
|
||
|
|
),
|
||
|
|
metadata.MeshTensor(
|
||
|
|
faces, plugin_data_pb2.MeshPluginData.FACE, tf.int32
|
||
|
|
),
|
||
|
|
metadata.MeshTensor(
|
||
|
|
colors, plugin_data_pb2.MeshPluginData.COLOR, tf.uint8
|
||
|
|
),
|
||
|
|
]
|
||
|
|
tensors = [tensor for tensor in tensors if tensor.data is not None]
|
||
|
|
components = metadata.get_components_bitmask(
|
||
|
|
[tensor.content_type for tensor in tensors]
|
||
|
|
)
|
||
|
|
for tensor in tensors:
|
||
|
|
shape = tensor.data.shape
|
||
|
|
shape = [dim if dim is not None else -1 for dim in shape]
|
||
|
|
tensor_proto = tf.compat.v1.make_tensor_proto(
|
||
|
|
tensor.data, dtype=tensor.data_type
|
||
|
|
)
|
||
|
|
summary_metadata = metadata.create_summary_metadata(
|
||
|
|
name,
|
||
|
|
display_name,
|
||
|
|
tensor.content_type,
|
||
|
|
components,
|
||
|
|
shape,
|
||
|
|
description,
|
||
|
|
json_config=json_config,
|
||
|
|
)
|
||
|
|
tag = metadata.get_instance_name(name, tensor.content_type)
|
||
|
|
summaries.append((tag, summary_metadata, tensor_proto))
|
||
|
|
|
||
|
|
summary = tf.compat.v1.Summary()
|
||
|
|
for tag, summary_metadata, tensor_proto in summaries:
|
||
|
|
tf_summary_metadata = tf.compat.v1.SummaryMetadata.FromString(
|
||
|
|
summary_metadata.SerializeToString()
|
||
|
|
)
|
||
|
|
summary.value.add(
|
||
|
|
tag=tag, metadata=tf_summary_metadata, tensor=tensor_proto
|
||
|
|
)
|
||
|
|
return summary
|