clarification about licensing

Dockerfile

@@ -19,7 +19,16 @@ RUN apt --yes install build-essential wget curl rpl
 RUN echo "Build started at: $(date "+%Y-%m-%d %H:%M")"
 
 # NodeJS - LEGACY/DEPRECATED WAY
-RUN curl -fsSL https://deb.nodesource.com/setup_18.x | bash -
+#RUN curl -fsSL https://deb.nodesource.com/setup_18.x | bash -
+#RUN apt --yes install nodejs
+
+# NodeJS - NEW, MORE ANNOYING WAY
+RUN apt --yes install -y ca-certificates gnupg
+RUN mkdir -p /etc/apt/keyrings
+RUN curl -fsSL https://deb.nodesource.com/gpgkey/nodesource-repo.gpg.key | gpg --dearmor -o /etc/apt/keyrings/nodesource.gpg
+ENV NODE_MAJOR=18
+RUN echo "deb [signed-by=/etc/apt/keyrings/nodesource.gpg] https://deb.nodesource.com/node_$NODE_MAJOR.x nodistro main" | tee /etc/apt/sources.list.d/nodesource.list
+RUN apt update
 RUN apt --yes install nodejs
 
 # git and file management
@@ -97,10 +106,36 @@ RUN git clone --recursive https://github.com/MrNeRF/gaussian-splatting-cuda
 
 WORKDIR $HOME/app/gaussian-splatting-cuda
 
-# for quick testing we disabled the rest
+RUN wget https://download.pytorch.org/libtorch/cu118/libtorch-cxx11-abi-shared-with-deps-2.0.1%2Bcu118.zip  
+RUN unzip libtorch-cxx11-abi-shared-with-deps-2.0.1+cu118.zip -d external/
+RUN rm libtorch-cxx11-abi-shared-with-deps-2.0.1+cu118.zip
+
+# Build (on CPU, this will add compute_35 as build target, which we do not want)
+# There seems to be a work around, see this thread:
+# https://github.com/MrNeRF/gaussian-splatting-cuda/issues/14
+# here is the hack:
+#
+# Replace "native" by "all"
+# inspired by https://github.com/ztxz16/fastllm/pull/309/files
+#
+# CUDA architectures are defined as codes
+# by default CMake detected:
+# 3.5;5.0;8.0;8.6;8.9;9.0
+# To see the mapping: https://arnon.dk/matching-sm-architectures-arch-and-gencode-for-various-nvidia-cards/
+# A10G and A100 -> Ampere -> sm_80, sm_86, sm_87 -> 8.0;8.6;8.7
+# Nvidia T4 -> Turing -> sm_75 -> 7.5
+# ? -> Lovelace ->  sm_89 -> 8.6
+# ? -> Hopper -> sm_90 -> 9.0
+RUN find . -name CMakeLists.txt -exec sed -i 's/CUDA_ARCHITECTURES native/CUDA_ARCHITECTURES all/' {} +
+
+#RUN cmake -B build -D CMAKE_BUILD_TYPE=Release -D CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-12.2/ -D CUDA_VERSION=12.2
+# Let's try to downgrade the version
+RUN cmake -B build -D CMAKE_BUILD_TYPE=Release -D CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-11.8/ -D CUDA_VERSION=11.8
+RUN cmake --build build -- -j8
 
 COPY --chown=user . $HOME/app/gaussian-splatting-cuda
 
+# Set the working directory to the user's home directory
 WORKDIR $HOME/app
 
 RUN echo "Build ended at: $(date "+%Y-%m-%d %H:%M")"

GAUSSIAN-SPLATTING-LICENSE.txt

@@ -0,0 +1,83 @@
+Gaussian-Splatting License  
+===========================  
+
+**Inria** and **the Max Planck Institut for Informatik (MPII)** hold all the ownership rights on the *Software* named **gaussian-splatting**.  
+The *Software* is in the process of being registered with the Agence pour la Protection des  
+Programmes (APP).  
+
+The *Software* is still being developed by the *Licensor*.  
+
+*Licensor*'s goal is to allow the research community to use, test and evaluate  
+the *Software*.  
+
+## 1.  Definitions  
+
+*Licensee* means any person or entity that uses the *Software* and distributes  
+its *Work*.  
+
+*Licensor* means the owners of the *Software*, i.e Inria and MPII  
+
+*Software* means the original work of authorship made available under this  
+License ie gaussian-splatting.  
+
+*Work* means the *Software* and any additions to or derivative works of the  
+*Software* that are made available under this License.  
+
+
+## 2.  Purpose  
+This license is intended to define the rights granted to the *Licensee* by  
+Licensors under the *Software*.  
+
+## 3.  Rights granted  
+
+For the above reasons Licensors have decided to distribute the *Software*.  
+Licensors grant non-exclusive rights to use the *Software* for research purposes  
+to research users (both academic and industrial), free of charge, without right  
+to sublicense.. The *Software* may be used "non-commercially", i.e., for research  
+and/or evaluation purposes only.  
+
+Subject to the terms and conditions of this License, you are granted a  
+non-exclusive, royalty-free, license to reproduce, prepare derivative works of,  
+publicly display, publicly perform and distribute its *Work* and any resulting  
+derivative works in any form.  
+
+## 4.  Limitations  
+
+**4.1 Redistribution.** You may reproduce or distribute the *Work* only if (a) you do  
+so under this License, (b) you include a complete copy of this License with  
+your distribution, and (c) you retain without modification any copyright,  
+patent, trademark, or attribution notices that are present in the *Work*.  
+
+**4.2 Derivative Works.** You may specify that additional or different terms apply  
+to the use, reproduction, and distribution of your derivative works of the *Work*  
+("Your Terms") only if (a) Your Terms provide that the use limitation in  
+Section 2 applies to your derivative works, and (b) you identify the specific  
+derivative works that are subject to Your Terms. Notwithstanding Your Terms,  
+this License (including the redistribution requirements in Section 3.1) will  
+continue to apply to the *Work* itself.  
+
+**4.3** Any other use without of prior consent of Licensors is prohibited. Research  
+users explicitly acknowledge having received from Licensors all information  
+allowing to appreciate the adequacy between of the *Software* and their needs and  
+to undertake all necessary precautions for its execution and use.  
+
+**4.4** The *Software* is provided both as a compiled library file and as source  
+code. In case of using the *Software* for a publication or other results obtained  
+through the use of the *Software*, users are strongly encouraged to cite the  
+corresponding publications as explained in the documentation of the *Software*.  
+
+## 5.  Disclaimer  
+
+THE USER CANNOT USE, EXPLOIT OR DISTRIBUTE THE *SOFTWARE* FOR COMMERCIAL PURPOSES  
+WITHOUT PRIOR AND EXPLICIT CONSENT OF LICENSORS. YOU MUST CONTACT INRIA FOR ANY  
+UNAUTHORIZED USE: stip-sophia.transfert@inria.fr . ANY SUCH ACTION WILL  
+CONSTITUTE A FORGERY. THIS *SOFTWARE* IS PROVIDED "AS IS" WITHOUT ANY WARRANTIES  
+OF ANY NATURE AND ANY EXPRESS OR IMPLIED WARRANTIES, WITH REGARDS TO COMMERCIAL  
+USE, PROFESSIONNAL USE, LEGAL OR NOT, OR OTHER, OR COMMERCIALISATION OR  
+ADAPTATION. UNLESS EXPLICITLY PROVIDED BY LAW, IN NO EVENT, SHALL INRIA OR THE  
+AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR  
+CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE  
+GOODS OR SERVICES, LOSS OF USE, DATA, OR PROFITS OR BUSINESS INTERRUPTION)  
+HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT  
+LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING FROM, OUT OF OR  
+IN CONNECTION WITH THE *SOFTWARE* OR THE USE OR OTHER DEALINGS IN THE *SOFTWARE*.  

README.md

@@ -5,7 +5,7 @@ colorFrom: green
 colorTo: yellow
 sdk: docker
 pinned: true
-app_port: 3000
+app_port: 7860
 ---
 
 ## Presentation
@@ -14,7 +14,19 @@ app_port: 3000
 
 Gaussian Splatting API is a REST API to generate 3D Gaussian Splatting scenes from a set of images.
 
-### What is the licence?
+It is a wrapper around [MrNERF/gaussian-splatting-cuda](https://github.com/MrNeRF/gaussian-splatting-cuda).
+
+### License
+
+The server wrapping code is open-source, but the code engine [gaussian-splatting-cuda](https://github.com/MrNeRF/gaussian-splatting-cuda) is based on [project by the Inria and the Max Planck Institut for Informatik (MPII)](https://github.com/graphdeco-inria/gaussian-splatting).
+
+This is a [publicly funded project](https://repo-sam.inria.fr/fungraph/3d-gaussian-splatting/) with a [non-commercial license](GAUSSIAN-SPLATTING-LICENCE.md).
+
+### So I can't use it for commercial apps?
+
+You will have to talk with the original rightholders at the INRIA and MPII.
+
+Also, please tell if you know about any alternative project with a fully permissive open-source licensing.
 
 ## Running on your machine
 

tmp.txt

@@ -1,147 +0,0 @@
-#FROM nvidia/cuda:12.2.0-devel-ubuntu20.04
-# let's try to downgrade the version of CUDA
-FROM nvidia/cuda:11.8.0-devel-ubuntu20.04
-
-LABEL maintainer="Hugging Face"
-
-ARG DEBIAN_FRONTEND=noninteractive
-
-# Use login shell to read variables from `~/.profile` (to pass dynamic created variables between RUN commands)
-SHELL ["sh", "-lc"]
-
-# WORKDIR /workdir
-
-RUN apt update
-
-# base stuff
-RUN apt --yes install build-essential wget curl rpl
-
-RUN echo "Build started at: $(date "+%Y-%m-%d %H:%M")"
-
-# NodeJS - LEGACY/DEPRECATED WAY
-#RUN curl -fsSL https://deb.nodesource.com/setup_18.x | bash -
-#RUN apt --yes install nodejs
-
-# NodeJS - NEW, MORE ANNOYING WAY
-RUN apt --yes install -y ca-certificates gnupg
-RUN mkdir -p /etc/apt/keyrings
-RUN curl -fsSL https://deb.nodesource.com/gpgkey/nodesource-repo.gpg.key | gpg --dearmor -o /etc/apt/keyrings/nodesource.gpg
-ENV NODE_MAJOR=18
-RUN echo "deb [signed-by=/etc/apt/keyrings/nodesource.gpg] https://deb.nodesource.com/node_$NODE_MAJOR.x nodistro main" | tee /etc/apt/sources.list.d/nodesource.list
-RUN apt update
-RUN apt --yes install nodejs
-
-# git and file management
-RUN apt --yes install git git-lfs unzip
-RUN git lfs install
-
-# Python
-RUN apt --yes install python3 python3-pip
-RUN python3 -m pip install --no-cache-dir --upgrade pip
-
-
-# required for CMake it seems
-RUN apt --yes install libtbb-dev libeigen3-dev g++ libssl-dev checkinstall
-
-
-# The app require CMake 3.24+ but this version of Ubuntu only has the 3.16
-# So we need to install a more recent version
-#RUN apt-get update \
-#  && rm -rf /var/lib/apt/lists/* \
-RUN wget https://github.com/Kitware/CMake/releases/download/v3.24.1/cmake-3.24.1-Linux-x86_64.sh \
-  -q -O /tmp/cmake-install.sh \
-  && chmod u+x /tmp/cmake-install.sh \
-  && mkdir /opt/cmake-3.24.1 \
-  && /tmp/cmake-install.sh --skip-license --prefix=/opt/cmake-3.24.1 \
-  && rm /tmp/cmake-install.sh \
-  && ln -s /opt/cmake-3.24.1/bin/* /usr/local/bin
-
-# Install cmake 3.24
-#RUN wget https://github.com/Kitware/CMake/releases/download/v3.24.1/cmake-3.22.1.tar.gz \
-# && tar -zvxf cmake-3.24.1.tar.gz \
-# && cd cmake-3.24.1 \
-# && ./bootstrap \
-# && make -j8 \
-# && checkinstall --pkgname=cmake --pkgversion="3.20-custom" --default
-# Copy contents from 2 levels up
-#COPY . ./
-
-# Download and extract libtorch
-#RUN wget https://download.pytorch.org/libtorch/cu118/libtorch-cxx11-abi-shared-with-deps-2.0.1%2Bcu118.zip \
-# && unzip libtorch-cxx11-abi-shared-with-deps-2.0.1+cu118.zip -d external/
-
-# Set up a new user named "user" with user ID 1000
-RUN useradd -o -u 1000 user
-
-# Switch to the "user" user
-USER user
-
-ENV PYTHON_BIN /usr/bin/python3
-
-#ENV PATH /usr/local/cuda-12.2/bin:$PATH
-#ENV LD_LIBRARY_PATH /usr/local/cuda-12.2/lib64:$LD_LIBRARY_PATH
-# Let's try to downgrade
-ENV PATH /usr/local/cuda-11.8/bin:$PATH
-ENV LD_LIBRARY_PATH /usr/local/cuda-11.8/lib64:$LD_LIBRARY_PATH
-
-
-# Set home to the user's home directory
-ENV HOME=/home/user \
-	PATH=/home/user/.local/bin:$PATH
-
-# Set the working directory to the user's home directory
-WORKDIR $HOME/app
-
-# Install app dependencies
-# A wildcard is used to ensure both package.json AND package-lock.json are copied
-# where available (npm@5+)
-COPY --chown=user package*.json $HOME/app
-
-RUN npm install
-
-# Copy the current directory contents into the container at $HOME/app setting the owner to the user
-COPY --chown=user . $HOME/app
-
-RUN git clone --recursive https://github.com/MrNeRF/gaussian-splatting-cuda
-
-WORKDIR $HOME/app/gaussian-splatting-cuda
-
-RUN wget https://download.pytorch.org/libtorch/cu118/libtorch-cxx11-abi-shared-with-deps-2.0.1%2Bcu118.zip  
-RUN unzip libtorch-cxx11-abi-shared-with-deps-2.0.1+cu118.zip -d external/
-RUN rm libtorch-cxx11-abi-shared-with-deps-2.0.1+cu118.zip
-
-# Build (on CPU, this will add compute_35 as build target, which we do not want)
-# There seems to be a work around, see this thread:
-# https://github.com/MrNeRF/gaussian-splatting-cuda/issues/14
-# here is the hack:
-#
-# Replace "native" by "all"
-# inspired by https://github.com/ztxz16/fastllm/pull/309/files
-#
-# CUDA architectures are defined as codes
-# by default CMake detected:
-# 3.5;5.0;8.0;8.6;8.9;9.0
-# To see the mapping: https://arnon.dk/matching-sm-architectures-arch-and-gencode-for-various-nvidia-cards/
-# A10G and A100 -> Ampere -> sm_80, sm_86, sm_87 -> 8.0;8.6;8.7
-# Nvidia T4 -> Turing -> sm_75 -> 7.5
-# ? -> Lovelace ->  sm_89 -> 8.6
-# ? -> Hopper -> sm_90 -> 9.0
-RUN find . -name CMakeLists.txt -exec sed -i 's/CUDA_ARCHITECTURES native/CUDA_ARCHITECTURES all/' {} +
-
-#RUN cmake -B build -D CMAKE_BUILD_TYPE=Release -D CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-12.2/ -D CUDA_VERSION=12.2
-# Let's try to downgrade the version
-RUN cmake -B build -D CMAKE_BUILD_TYPE=Release -D CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-11.8/ -D CUDA_VERSION=11.8
-RUN cmake --build build -- -j8
-
-COPY --chown=user . $HOME/app/gaussian-splatting-cuda
-
-# Set the working directory to the user's home directory
-WORKDIR $HOME/app
-
-RUN echo "Build ended at: $(date "+%Y-%m-%d %H:%M")"
-
-EXPOSE 7860
-
-# we can't use this (it time out)
-# CMD [ "xvfb-run", "-s", "-ac -screen 0 1920x1080x24", "npm", "run", "start" ]
-CMD [ "npm", "run", "start" ]