3D root model reconstruction

The software package was integrated as a module at PlantIT website at : https://portnoy.cyverse.org/. (Collaborate with Cyverse https://www.cyverse.org/ ) . Users are welcomed to registered as an user to try this package via PlantIT website.

The software package was also available at Dockerhub (https://hub.docker.com/r/computationalplantscience/3d-model-reconstruction) for advanced users to run locally via singularity at Linux environment:

This software can be run by docker container, users do not need to install many libraries and compile complex source files.

Setup Docker container

OS requirements

To install Docker container (https://docs.docker.com/engine/install/ubuntu/): 

To install Docker Engine, you need the 64-bit version of one of these Ubuntu versions:

Ubuntu Groovy 20.10
Ubuntu Focal 20.04 (LTS)
Ubuntu Bionic 18.04 (LTS)
Ubuntu Xenial 16.04 (LTS)

Docker Engine is supported on x86_64 (or amd64), armhf, and arm64 architectures.

Uninstall old versions
$ sudo apt-get remove docker docker-engine docker.io containerd runc

Set up the repository

Update the apt package index and install packages to allow apt to use a repository over HTTPS:

$ sudo apt-get update

$ sudo apt-get install \
    apt-transport-https \
    ca-certificates \
    curl \
    gnupg-agent \
    software-properties-common

Add Docker’s official GPG key:

$ curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -

Verify that you now have the key with the fingerprint 9DC8 5822 9FC7 DD38 854A  E2D8 8D81 803C 0EBF CD88, by searching for the last 8 characters of the fingerprint.

$ sudo apt-key fingerprint 0EBFCD88

pub   rsa4096 2017-02-22 [SCEA]
      9DC8 5822 9FC7 DD38 854A  E2D8 8D81 803C 0EBF CD88
uid           [ unknown] Docker Release (CE deb) <docker@docker.com>
sub   rsa4096 2017-02-22 [S]

$ sudo add-apt-repository \
   "deb [arch=amd64] https://download.docker.com/linux/ubuntu \
   $(lsb_release -cs) \
   stable"

Update the apt package index, and install the latest version of Docker Engine and containerd, or go to the next step to install a specific version:

$ sudo apt-get update
$ sudo apt-get install docker-ce docker-ce-cli containerd.io

Verify that Docker Engine is installed correctly by running the hello-world image.

$ sudo docker run hello-world

Run this container by building it locally:

# Clone source code to your local path
$ git clone https://github.com/Computational-Plant-Science/3D_model_reconstruction_demo.git

# Enter into the source code folder named as "cd 3D_model_reconstruction_demo"
$ cd 3D_model_reconstruction_demo/

# Build docker container locally named as "3d_model_reconstruction" using "Dockerfile" in the same folder, note: docker repository name must be lowercase.
$ docker build -t 3d_model_reconstruction -f Dockerfile .

# Run the docker container by linking docker container data path to user's image data folder local path
# Note: please replace $path_to_image_folder as your local image data folder path, 
# Suggest to check your image folder path using "pwd" command
# Example: $ docker run -v /home/suxing/example/root_images:/images -it 3d_model_reconstruction

$ docker run -v /$path_to_image_folder:/images -it 3d_model_reconstruction

# After launch the docker container, run "pipeline.sh" or "pipeline.sh" insider the container
$ root@0529cde0b988:/opt/code# ./pipeline.sh
or $ root@0529cde0b988:/opt/code# python3 pipeline.py

# Get 3d model result named as "dense.0.ply"
# After the container was executed successfully with image data files, user should be able to see output in your command window like this:
'''
Loading option-0000.ply, 48656 vertices ...
Save to /images/dense.nvm ... done
Save /images/dense.0.ply ...done
----------------------------------------------------------------
'''
The 3D model file was in ply format(https://en.wikipedia.org/wiki/PLY_(file_format)), it is located inside your image folder, its name is "dense.0.ply".
path = "/$path_to_image_folder/dense.0.ply"

To visualize the 3d model file, suggest to install Meshlab(https://www.meshlab.net/) or cloudcompare(https://www.danielgm.net/cc/)

Author

suxing liu(suxingliu@gmail.com)
Wesley Paul Bonelli(wbonelli@uga.edu)

Reference:
VisualSFM
[Anders Damsgaard](mailto:adamsgaard@ucsd.edu) with contributions by Caleb Adams and Connor P Doherty.
Changchang Wu ( wucc1130@gmail.com )
+ Structure from Motion
[1] Changchang Wu, "Towards Linear-time Incremental Structure From Motion", 3DV 2013
[2] Changchang Wu, "VisualSFM: A Visual Structure from Motion System", http://ccwu.me/vsfm/, 2011
+ Bundle Adjustment
[3] Changchang Wu, Sameer Agarwal, Brian Curless, and Steven M. Seitz, "Multicore Bundle Adjustment", CVPR 2011   
+ Feature Detection
[4] Changchang Wu, "SiftGPU: A GPU implementation of Scale Invaraint Feature Transform (SIFT)", http://cs.unc.edu/~ccwu/siftgpu, 2007

COLMAP
https://colmap.github.io
Author: Johannes L. Schoenberger (jsch-at-demuc-dot-de)
@inproceedings{schoenberger2016sfm,
    author={Sch\"{o}nberger, Johannes Lutz and Frahm, Jan-Michael},
    title={Structure-from-Motion Revisited},
    booktitle={Conference on Computer Vision and Pattern Recognition (CVPR)},
    year={2016},
}

@inproceedings{schoenberger2016mvs,
    author={Sch\"{o}nberger, Johannes Lutz and Zheng, Enliang and Pollefeys, Marc and Frahm, Jan-Michael},
    title={Pixelwise View Selection for Unstructured Multi-View Stereo},
    booktitle={European Conference on Computer Vision (ECCV)},
    year={2016},
}

Docker container was maintained by Wesley Paul Bonelli. it was deployed to Plant IT website by Wesley Paul Bonelli (wbonelli@uga.edu).

Singularity container overlay issues were solved by [Saravanaraj Ayyampalayam] (https://github.com/raj76) (mailto:raj76@uga.edu)

Special thanks to Chris Cotter building the container recipe for testing and debugging.

Todo

• GPU cuda version container

License

GNU Public License