From f7f10903bebc0673cb753bd848c4f0e2d45f0e77 Mon Sep 17 00:00:00 2001 From: wang-ps Date: Fri, 22 Mar 2019 12:52:34 +0800 Subject: [PATCH] Update docker --- README.md | 11 +++++------ docker/Dockerfile | 4 ++-- ocnn/octree/CMakeLists.txt | 1 + 3 files changed, 8 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index 11923ac0..02f12e63 100644 --- a/README.md +++ b/README.md @@ -49,8 +49,7 @@ O-CNN is built upon the [Caffe](https://github.com/BVLC/caffe) framework and it After the building, you will get the executable files which is useful for conducting the experiments: - [`virtualscanner`](https://github.com/wang-ps/O-CNN/tree/master/virtual_scanner) - used to convert obj/off files to points files -- [`octree`](#octree) - used to convert point files to octree files - +- [`octree`](#octree) - used to convert point files to octree files - [`convert_octree_data`](#convert-octree-data) - used to convert octree files to lmdb files - `caffe` - executable for training / evaluating models - `feature_pooling` - pools features and outputs them to an lmdb @@ -59,13 +58,13 @@ After the building, you will get the executable files which is useful for conduc -### 1.2   Docker Setup +### 1.2   Docker Setup (For Ubuntu only) A docker build file is provided to automatically build your environments so you don't have to worry about project dependencies. To get your environment up and running, execute the following: ``` cd docker -docker build -t ocnn . -docker run --name ocnn -it ocnn /bin/bash +docker build --network=host --tag=ocnn . +docker run --runtime=nvidia --network=host --name=ocnn -it ocnn /bin/bash ``` You will now find yourself in a container environment where you can automatically prepare datasets and train/test an o-cnn. @@ -126,7 +125,7 @@ Example: convert_octree_data D:/octrees/ D:/octrees/list.txt D:/octrees_lmdb ``` -### 2.2   Automated Dataset Setup +### 2.2   Automated Dataset Setup (For Ubuntu only) For the dataset `ModelNet10` and `ModelNet40`, we provide some scripts to automatically prepare the datasets. The code is contained in the python folder. (We will update the prepare_dataset.py to support other datasets such as ShapeNet55.) ``` Usage: diff --git a/docker/Dockerfile b/docker/Dockerfile index 24c23a62..3a7320bd 100755 --- a/docker/Dockerfile +++ b/docker/Dockerfile @@ -46,7 +46,7 @@ WORKDIR $WORKSPACE_BIN ARG OCNN_ROOT=$WORKSPACE/ocnn WORKDIR $OCNN_ROOT -ARG OCNN_COMMIT=origin/pre-release +ARG OCNN_COMMIT=origin/master RUN git clone https://github.com/Microsoft/O-CNN.git . && git reset --hard $OCNN_COMMIT RUN cd ocnn/octree && mkdir build && cd build && cmake -DCMAKE_BUILD_TYPE=Release -DOUTPUT_DIRECTORY=$WORKSPACE_BIN .. && \ make && cd ../ && rm -rf build @@ -74,7 +74,7 @@ RUN cd ocnn/octree && pip install . && cd ../caffe && pip install . ARG OCNN_TOOLS_ROOT=$WORKSPACE/ocnn_tools WORKDIR $OCNN_TOOLS_ROOT -ARG OCNN_TOOLS_COMMIT=origin/pre-release +ARG OCNN_TOOLS_COMMIT=origin/master RUN git clone https://github.com/wang-ps/O-CNN.git . && git reset --hard $OCNN_TOOLS_COMMIT RUN cd virtual_scanner && mkdir build && cd build && cmake -DCMAKE_BUILD_TYPE=Release .. && make && \ cp virtualscanner $WORKSPACE_BIN && cd ../ && rm -rf build && \ diff --git a/ocnn/octree/CMakeLists.txt b/ocnn/octree/CMakeLists.txt index 0dada2fa..396b37fb 100644 --- a/ocnn/octree/CMakeLists.txt +++ b/ocnn/octree/CMakeLists.txt @@ -55,6 +55,7 @@ if(NOT src_rply) endif() include_directories("${PROJECT_SOURCE_DIR}/external/rply-1.1.4") add_library(rply ${src_rply}) +set_target_properties(rply PROPERTIES LINKER_LANGUAGE CXX) # files file(GLOB src_octree_lib