3dfront_proc
Science Score: 57.0%
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Low similarity (6.4%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: AkiraHero
- License: gpl-3.0
- Language: Python
- Default Branch: 3dfront_vis
- Size: 62.5 MB
Statistics
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
BlenderProc2 for 3D-Front
Support BlenderProc2 with multi-GPU batch rendering and 3D visualization for the 3D-Front dataset.
If you feel struggled in rendering 3D-Front or visualizing its 3D assets for your tasks. Here is a solution based on BlenderProc2 and VTK.
2D rendering
| RGB | Depth | Semantics | Instances |
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3D visualization
| Pointcloud | Layout & Camera Poses | CAD models + Oriented Bounding Boxes |
|:------------------------------------------------------------------------:|:------------------------------------------------------------------------:|:--------------------------------------------------------------------:|
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Note: * X server is required for 3D visualization only (i.e., You can render on a remote headless server, then visualize the 3D contents interactively with your local machine). * OpenGL camera setting is used.
Please check the orginal REAME if you want to know all the functions in BlenderProc2.
Install
Use conda to deploy the environment by
commandline cd BlenderProc-3DFront conda env create -f environment.yml conda activate blenderproc pip install -e .Apply for the 3D-Front dataset. Download all the data and link them to the local directory as follows:
examples/datasets/front_3d_with_improved_mat/3D-FRONT examples/datasets/front_3d_with_improved_mat/3D-FRONT-texture examples/datasets/front_3d_with_improved_mat/3D-FUTURE-modelMove our improved 3D-Futuremodel_info.jsonto the3D-FUTURE-modelfolder bymv examples/datasets/front_3d_with_improved_mat/model_info_revised.json examples/datasets/front_3d_with_improved_mat/3D-FUTURE-modelDownload textures data from link by
commandline blenderproc run blenderproc/scripts/download_cc_textures.py ./resources/cctextures
Render
Since I use Ubuntu system, BlenderProc will automatically install blender-3.0.0-linux-x64 in /home/USERNAME/blender/blender-3.0.0-linux-x64. In any case you meet any problems or bugs, here I provide my Blender version. Please download to the same folder before rendering.
- Single scene rendering
Here we take the scene ID 6a0e73bc-d0c4-4a38-bfb6-e083ce05ebe9.json as an example. We can do multi-view renderings by running the script as follows:
commandline
blenderproc run \
examples/datasets/front_3d_with_improved_mat/render_dataset_improved_mat.py \
examples/datasets/front_3d_with_improved_mat/3D-FRONT \
examples/datasets/front_3d_with_improved_mat/3D-FUTURE-model \
examples/datasets/front_3d_with_improved_mat/3D-FRONT-texture \
6a0e73bc-d0c4-4a38-bfb6-e083ce05ebe9.json \
resources/cctextures/ \
examples/datasets/front_3d_with_improved_mat/renderings
* The rendering results will be saved in examples/datasets/front_3d_with_improved_mat/renderings.
* You can also customize your camera FOV, rendering resolution and number of views, etc. in render_dataset_improved_mat.py. Just dive deeper and play with it.
* You can also output normal maps or depth maps by uncomment bproc.renderer.enable_normals_output() and bproc.renderer.enable_depth_output(activate_antialiasing=False).
* I customized the camera pose sampling function to support multi-view renderings. The sampling strategy ensures every camera pose has a reasonable object surface coverage.
* The number of camera poses in a room is proportional to the ratio of its floor area to the whole apartment. Default camera pose number is 100 per apartment.
- Batch scene rendering (support multi-GPU mode for parallel rendering)
This script is built on the above function to support batch rendering. Run the following script to render all scenes in a loop.
commandline
python examples/datasets/front_3d_with_improved_mat/multi_render.py \
examples/datasets/front_3d_with_improved_mat/render_dataset_improved_mat.py \
examples/datasets/front_3d_with_improved_mat/3D-FRONT \
examples/datasets/front_3d_with_improved_mat/3D-FUTURE-model \
examples/datasets/front_3d_with_improved_mat/3D-FRONT-texture \
resources/cctextures/ \
examples/datasets/front_3d_with_improved_mat/renderings \
--n_processes 1
* The rendering results will be saved in examples/datasets/front_3d_with_improved_mat/renderings.
* You can still customize your rendering pipeline by modifying render_dataset_improved_mat.py.
* If you have multiple GPUs and want to render in parallel, change n_processes to your GPU number.
Visualization
After rendering a scene, please run the following code for 2D and 3D visualizations
commandline
python visualization/front3d/vis_front3d.py --json_file 6a0e73bc-d0c4-4a38-bfb6-e083ce05ebe9.json
How to Debug?
Please refer to link if you want to debug with your IDE.
Citation
Some parts of this code base is developed based on the following works. If you find our work helpful, please consider citing ``` @inproceedings{nie2023learning, title={Learning 3d scene priors with 2d supervision}, author={Nie, Yinyu and Dai, Angela and Han, Xiaoguang and Nie{\ss}ner, Matthias}, booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, pages={792--802}, year={2023} }
@article{Denninger2023, doi = {10.21105/joss.04901}, url = {https://doi.org/10.21105/joss.04901}, year = {2023}, publisher = {The Open Journal}, volume = {8}, number = {82}, pages = {4901}, author = {Maximilian Denninger and Dominik Winkelbauer and Martin Sundermeyer and Wout Boerdijk and Markus Knauer and Klaus H. Strobl and Matthias Humt and Rudolph Triebel}, title = {BlenderProc2: A Procedural Pipeline for Photorealistic Rendering}, journal = {Journal of Open Source Software} }
@InProceedings{Paschalidou2021NEURIPS, author = {Despoina Paschalidou and Amlan Kar and Maria Shugrina and Karsten Kreis and Andreas Geiger and Sanja Fidler}, title = {ATISS: Autoregressive Transformers for Indoor Scene Synthesis}, booktitle = {Advances in Neural Information Processing Systems (NeurIPS)}, year = {2021} } ```
Owner
- Login: AkiraHero
- Kind: user
- Repositories: 2
- Profile: https://github.com/AkiraHero
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
title: "BlenderProc2"
version: 2.0.0
date-released: 2021-10-12
licence: GNU General Public License v3.0
authors:
- family-names: Denninger
given-names: Maximilian
affiliation: "German Aerospace Center (DLR)"
email: "maximilian.denninger@dlr.de"
orcid: "https://orcid.org/0000-0002-1557-2234"
- family-names: Sundermeyer
given-names: Martin
affiliation: "German Aerospace Center (DLR)"
email: "martin.sundermeyer@dlr.de"
orcid: "https://orcid.org/0000-0003-0587-9643"
- family-names: Winkelbauer
given-names: Dominik
affiliation: "German Aerospace Center (DLR)"
email: "dominik.winkelbauer@dlr.de"
orcid: "https://orcid.org/0000-0001-7443-1071"
- family-names: Olefir
given-names: Dmitry
affiliation: "German Aerospace Center (DLR)"
orcid: "https://orcid.org/0000-0001-5244-9676"
- family-names: Hodan
given-names: Tomas
affiliation: "Visual Recognition Group, Czech Technical University in Prague"
email: "hodantom@cmp.felk.cvut.cz"
- family-names: Zidan
given-names: Youssef
affiliation: "German Aerospace Center (DLR)"
- family-names: Elbadrawy
given-names: Mohamad
affiliation: "German Aerospace Center (DLR)"
- family-names: Knauer
given-names: Markus
affiliation: "German Aerospace Center (DLR)"
email: "markus.knauer@dlr.de"
orcid: "https://orcid.org/0000-0001-8229-9410"
- family-names: Katam
given-names: Harinandan
affiliation: "German Aerospace Center (DLR)"
- family-names: Lodhi
given-names: Ahsan
affiliation: "German Aerospace Center (DLR)"
- family-names: Penzkofer
given-names: Anna
affiliation: "German Aerospace Center (DLR)"
repository-code: "https://github.com/DLR-RM/BlenderProc/"
url: "https://dlr-rm.github.io/BlenderProc/"
abstract: "BlenderProc is a modular procedural pipeline, which helps in generating real looking images for the training of convolutional neural networks. These can be used in a variety of use cases including segmentation, depth, normal and pose estimation and many others. A key feature of our extension of blender is the simple to use modular pipeline, which was designed to be easily extendable. By offering standard modules, which cover a variety of scenarios, we provide a starting point on which new modules can be created."
keywords:
- "machine learning"
- "deep learning"
- "artificial intelligence"
- "computer vision"
- "simulation"
- "photo realistic rendering"
- "blender"
- "robot framework"
- "dataset generation"
references:
- type: article
title: "BlenderProc"
authors:
- family-names: Denninger
given-names: Maximilian
affiliation: "German Aerospace Center (DLR)"
email: "maximilian.denninger@dlr.de"
orcid: "https://orcid.org/0000-0002-1557-2234"
- family-names: Sundermeyer
given-names: Martin
affiliation: "German Aerospace Center (DLR)"
email: "martin.sundermeyer@dlr.de"
orcid: "https://orcid.org/0000-0003-0587-9643"
- family-names: Winkelbauer
given-names: Dominik
affiliation: "German Aerospace Center (DLR)"
email: "dominik.winkelbauer@dlr.de"
orcid: "https://orcid.org/0000-0001-7443-1071"
- family-names: Zidan
given-names: Youssef
affiliation: "German Aerospace Center (DLR)"
- family-names: Olefir
given-names: Dmitry
affiliation: "German Aerospace Center (DLR)"
orcid: "https://orcid.org/0000-0001-5244-9676"
- family-names: Elbadrawy
given-names: Mohamad
affiliation: "German Aerospace Center (DLR)"
- family-names: Lodhi
given-names: Ahsan
affiliation: "German Aerospace Center (DLR)"
- family-names: Katam
given-names: Harinandan
affiliation: "German Aerospace Center (DLR)"
year: 2019
url: https://arxiv.org/abs/1911.01911
- type: article
title: "BlenderProc: Reducing the Reality Gap with Photorealistic Rendering"
authors:
- family-names: Denninger
given-names: Maximilian
affiliation: "German Aerospace Center (DLR)"
email: "maximilian.denninger@dlr.de"
orcid: "https://orcid.org/0000-0002-1557-2234"
- family-names: Sundermeyer
given-names: Martin
affiliation: "German Aerospace Center (DLR)"
email: "martin.sundermeyer@dlr.de"
orcid: "https://orcid.org/0000-0003-0587-9643"
- family-names: Winkelbauer
given-names: Dominik
affiliation: "German Aerospace Center (DLR)"
email: "dominik.winkelbauer@dlr.de"
orcid: "https://orcid.org/0000-0001-7443-1071"
- family-names: Olefir
given-names: Dmitry
affiliation: "German Aerospace Center (DLR)"
orcid: "https://orcid.org/0000-0001-5244-9676"
- family-names: Hodan
given-names: Tomas
affiliation: "Visual Recognition Group, Czech Technical University in Prague"
email: "hodantom@cmp.felk.cvut.cz"
- family-names: Zidan
given-names: Youssef
affiliation: "German Aerospace Center (DLR)"
- family-names: Elbadrawy
given-names: Mohamad
affiliation: "German Aerospace Center (DLR)"
- family-names: Knauer
given-names: Markus
affiliation: "German Aerospace Center (DLR)"
email: "markus.knauer@dlr.de"
orcid: "https://orcid.org/0000-0001-8229-9410"
- family-names: Katam
given-names: Harinandan
affiliation: "German Aerospace Center (DLR)"
- family-names: Lodhi
given-names: Ahsan
affiliation: "German Aerospace Center (DLR)"
year: 2020
conference: "International Conference on Robotics: Sciene and Systems, RSS 2020"
url: "https://sim2real.github.io/assets/papers/2020/denninger.pdf"
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Dependencies
- actions/checkout v2 composite
- certifi ==2023.5.7
- charset-normalizer ==3.2.0
- contourpy ==1.1.0
- cycler ==0.11.0
- fonttools ==4.40.0
- h5py ==3.9.0
- idna ==3.4
- importlib-resources ==6.0.0
- kiwisolver ==1.4.4
- matplotlib ==3.7.2
- numpy ==1.24.4
- opencv-python ==4.8.0.74
- packaging ==23.1
- pandas ==2.0.3
- pillow ==10.0.0
- progressbar ==2.5
- pyparsing ==3.0.9
- python-dateutil ==2.8.2
- pytz ==2023.3
- requests ==2.31.0
- seaborn ==0.12.2
- six ==1.16.0
- tqdm ==4.65.0
- trimesh ==3.22.3
- tzdata ==2023.3
- urllib3 ==2.0.3
- vtk ==9.2.6
- zipp ==3.16.0
- setuptools *