GSoC: Incorporating point-based convolutions in TensorFlow Graphics (12/12)

requirements.txt

@@ -13,3 +13,5 @@ termcolor >= 1.1.0
 trimesh >= 2.37.22
 # Required by trimesh.
 networkx
+# required for pytests of project/point_convolutions
+sklearn

tensorflow_graphics/projects/point_convolutions/.flake8

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+inline-quotes = double
+max-line-length = 79 
+max-complexity = 10
+exclude = .git,
+          .tox,
+          .pytest_cache,
+          __pycache__,
+          tensorflow_graphics/projects/*
+          tensorflow_graphics/submodules/*
+ignore = C901,
+         E101,
+         E111,
+         E114,
+         E121,
+         E125,
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tensorflow_graphics/projects/point_convolutions/LICENSE

@@ -0,0 +1,202 @@
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tensorflow_graphics/projects/point_convolutions/README.md

@@ -0,0 +1,70 @@
+# TensorFlow Graphics Point Cloud Convolutions
+
+This module contains a python TensorFlow module `pylib` and a custom ops package in `tfg_custom_ops`.
+While it is possible to run without the custom ops package, it is strongly advised to install it for performance and memory efficiency.
+
+## Content
+
+This code contains all necessary operations to perform point cloud convolutions
+
+1. Datastructure
+    - Point cloud class for batches of arbitrary sized point clouds.
+    - Memory efficient regular grid data structure
+2. Point cloud operations
+    - Neighborhood computation
+    - Point density estimation
+    - Spatial sampling
+      - Poisson Disk sampling
+      - Cell average sampling
+3. Convolution kernels 
+    - Kernel Point Convolutions
+      - linear interpolation
+      - gaussian interpolation
+      - deformable points with regularization loss as in [KPConv](https://arxiv.org/abs/1904.08889)
+    - MLP
+      - multiple MLPs as in [MCConv](https://arxiv.org/abs/1806.01759)
+      - single MLP as in [PointConv](https://arxiv.org/abs/1811.07246)
+4. Feature aggregation inside receptive fields
+    - Monte-Carlo integration with pdf
+    - Constant summation
+5. Easy to use classes for building models
+    - `PointCloud` class
+    - `PointHierarchy` for sequential downsampling of point clouds
+    - layer classes
+      - `MCConv`
+      - `PointConv`
+      - `KPConv`
+      - `Conv1x1`
+
+## Installation
+
+Precompiled versions of the custom ops package are provided in `custom_ops/pkg_builds/tf_*` for the latest TensorFlow versions.
+For compilation instructions see the [README](custom_ops/README.md) in the `custom_ops` folder.
+
+To install it run the following command (replace `VERSION` with your installed TensorFlow version, e.g. `2.3.0`)
+```bash
+  pip install custom_ops/tf_VERSION/*.whl
+```
+
+## Tutorials
+
+Check out the Colab notebooks for an introduction to the code
+
+- [Introduction](pylib/notebooks/Introduction.ipynb)
+- [Classification on ModelNet40](pylib/notebooks/ModelNet40.ipynb) 
+
+## Unit tests
+
+Unit tests can be evaluated using
+
+```bash
+  pip install -r pytest_requirements.txt
+  pytest pylib/
+```
+
+These include tests of the custom ops if they are installed.
+
+## Additional Information
+
+You may use this software under the
+[Apache 2.0 License](https://github.com/schellmi42/tensorflow_graphics_point_clouds/blob/master/LICENSE).

tensorflow_graphics/projects/point_convolutions/custom_ops/.bazelrc

@@ -0,0 +1,18 @@
+build:cuda --define=using_cuda=true --define=using_cuda_nvcc=true
+build:manylinux2010cuda100 --crosstool_top=//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda10.0:toolchain
+build:manylinux2010cuda101 --crosstool_top=//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda10.1:toolchain
+build --spawn_strategy=standalone
+build --strategy=Genrule=standalone
+build -c opt
+build --action_env TF_HEADER_DIR="/usr/local/lib/python3.6/dist-packages/tensorflow/include"
+build --action_env TF_SHARED_LIBRARY_DIR="/usr/local/lib/python3.6/dist-packages/tensorflow"
+build --action_env TF_SHARED_LIBRARY_NAME="libtensorflow_framework.so.2"
+build --action_env TF_NEED_CUDA="1"
+build --action_env TF_CUDA_VERSION="10.1"
+build --action_env TF_CUDNN_VERSION="7"
+build --action_env CUDNN_INSTALL_PATH="/usr/lib/x86_64-linux-gnu"
+build --action_env CUDA_TOOLKIT_PATH="/usr/local/cuda"
+build --config=cuda
+test --config=cuda
+build --config=manylinux2010cuda101
+test --config=manylinux2010cuda101

tensorflow_graphics/projects/point_convolutions/custom_ops/BUILD

@@ -0,0 +1,10 @@
+sh_binary(
+    name = "build_pip_pkg",
+    srcs = ["build_pip_pkg.sh"],
+    data = [
+        "LICENSE",
+        "MANIFEST.in",
+        "setup.py",
+        "//tfg_custom_ops:tfg_custom_ops_py",
+    ],
+)