Author: Thiago T. Santos, Embrapa Agricultural Informatics
3dmcap is an application for three-dimensional reconstruction of objects from digital images. It allows an ordinary camera and a computer to operate as a simple 3-D scanner. The application assists the user on imaging and computing a cloud of 3-D points, sampling the objects surfaces in three dimensions. Its purpose within Embrapa is the 3-D reconstruction of plants for purposes of automatic measurement in phenotyping and precision agriculture.
Santos, T. T., Bassoi, L. H., Oldoni, H., & Martins, R. L. (2017). Automatic grape bunch detection in vineyards based on affordable 3D phenotyping using a consumer webcam. In J. G. A. Barbedo, M. F. Moura, L. A. S. Romani, T. T. Santos, & D. P. Drucker (Eds.), Anais do XI Congresso Brasileiro de Agroinformática (SBIAgro 2017) (pp. 89–98). Campinas: Unicamp. PDF
3dmcap is released under a GPLv3 license. This software relies on other open-source components as PMVS, ORB_SLAM2, g2o and OpenCV.
If you need 3dmcap for commercial purposes, please contact Embrapa Agricultural Informatics Technology Transfer Office.
If you use 3dmcap in an academic work, please cite:
@inproceedings{Santos2017,
address = {Campinas},
author = {Santos, Thiago Teixeira and Bassoi, Luis Henrique and Oldoni, Henrique and Martins, Roberto Luvisutto},
title = {{Automatic grape bunch detection in vineyards based on affordable 3D phenotyping using a consumer webcam}},
booktitle = {Anais do XI Congresso Brasileiro de Agroinform{\'{a}}tica (SBIAgro 2017)},
editor = {Barbedo, Jayme Garcia Arnal and Moura, Maria Fernanda and Romani, Luciana Alvim Santos and Santos, Thiago Teixeira and Drucker, D{\'{e}}bora Pignatari},
number = {October},
pages = {89--98},
publisher = {Unicamp},
year = {2017}
}
The easiest way to install and run 3dmcap is using our Docker image, thsant/3dmcap. If you
have Docker running in a Ubuntu Linux host and a camera connected as /dev/video0, the following command should install and run 3dmcap for you:
docker run -it --rm -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix --device /dev/video0 -v $HOME/.3dmcap:/home/demeter/.3dmcap -v $HOME/workdir:/home/demeter/workdir thsant/3dmcap capture.py
Note the command above assumes you have, in your home directory, a .3dmcap directory, containing the configuration file, and a workdir directory for saving the results produced by
the application running in the Docker container.
If you have problems loading the graphical interface, try to execute
xhost +local:root
before the docker run. After the execution, run
xhost -local:root
to return the access controls.
If you are facing crashes presenting the following error message:
libGL error: No matching fbConfigs or visuals found
libGL error: failed to load driver: swrast
then you are having issues regarding NVIDIA drivers and OpenGL from Docker. In this case, consider NVIDIA Docker as a workaround.
The software depends on:
- Eigen 3;
- OpenCV with Python 2.7 support;
- Our modified version of ORB_SLAM2. It includes DBoW2 and g2o as the original ORB_SLAM2.
The Python components depends on:
- numpy
- scipy
- Pillow
- wxPython
- ObjectListView
- traits
- traitsui
- mayavi
- PyYAML
3dmcap have beend tested in Ubuntu 16.04 and 16.10.
For users that prefer build the entire system in their own hosts, this section describes the detailed building process. We
assume /usr/local as the install directory.
INSTALL_PREFIX=/usr/local
Add Eigen (needed by OpenCV and g2o), build-essential and cmake:
apt-get install -y build-essential libeigen3-dev cmake
Add OpenCV 3.4 dependencies:
apt-get install -y git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev
apt-get install -y python-dev python-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libjasper-dev libdc1394-22-dev
Get the OpenCV 3.4.1 sources and extract the files to /usr/local/src. Then build OpenCV:
cd /usr/local/src/opencv-3.4.1
mkdir build
cd build
cmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_INSTALL_PREFIX=$INSTALL_PREFIX ..
make -j4
make install
Check if the Python module is OK:
python -c 'import cv2; print cv2.__version__'
Install Pangolin:
apt-get install -y libglew-dev
cd /usr/local/src
git clone https://github.com/stevenlovegrove/Pangolin.git
cd Pangolin
mkdir build
cd build
cmake -D CMAKE_INSTALL_PREFIX=$INSTALL_PREFIX ..
make -j4
make install
Install our modified ORB-SLAM2 version:
apt-get install -y python-pip
pip install cython
cd /usr/local/src
git clone https://github.com/thsant/ORB_SLAM2.git
cd ORB_SLAM2
./build.sh
cp lib/libORB_SLAM2.so /usr/local/lib
cp Thirdparty/DBoW2/lib/libDBoW2.so /usr/local/lib
cp Thirdparty/g2o/lib/libg2o.so /usr/local/lib
cp python/slam.so /usr/local/lib/python2.7/dist-packages/
mkdir /usr/local/share/3dmcap
cp Vocabulary/ORBvoc.txt /usr/local/share/3dmcap/
Install PMVS. We recommend pmoulon's version at GitHub:
cd /usr/local/src
git clone https://github.com/pmoulon/CMVS-PMVS.git
cd CMVS-PMVS/program
mkdir build
cd build/
cmake -D CMAKE_INSTALL_PREFIX=$INSTALL_PREFIX ..
make -j4
make install
Add other 3-Demeter dependencies:
apt-get install -y python-wxgtk3.0 python-vtk python-tk v4l-utils
Finally, get 3dmcap code:
cd /usr/local/src
git clone https://github.com/thsant/3dmcap.git
cd 3dmcap
pip install -r requirements.txt
Configure the environment:
cd /usr/local/src/3dmcap
cp -r dmcap/ /usr/local/lib/python2.7/dist-packages
cp -r ./resources/* /usr/local/share/3dmcap
cp ./dmcap/camcal.py ./dmcap/capture.py /usr/local/bin
Edit the 3dmcap.cfg file and save it to your $HOME/.3dmcap directory. You can run capture.py to start 3dmcap.
For a tutorial about how to use the application, including details about configuration, see the PDF manual.