tree_is_all_you_need
Predicting tree deformation using GNN
Science Score: 44.0%
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Low similarity (11.6%) to scientific vocabulary
Repository
Predicting tree deformation using GNN
Basic Info
- Host: GitHub
- Owner: chjohnkim
- License: mit
- Language: Python
- Default Branch: main
- Size: 15.4 MB
Statistics
- Stars: 3
- Watchers: 4
- Forks: 4
- Open Issues: 1
- Releases: 0
Metadata Files
README.md
"Tree is All You Need" : Predicting tree deformation using GNN
Mark Lee, Joe Huang, John Kim
We provide PyTorch code for our 11-785 Introduction to Deep Learning course project.
Our goal for this project is to learn the complex physics model of trees. More specifically, we want to predict the deformation of trees when an external force is applied. Obtaining a more accurate model of tree is important for the robot, as it can lead to safer and more robust manipulation in agriculture. For this purpose, we use recent advancements in Graph Neural Networks and take advantage of graph-like tree structures to learn and predict the dynamics of tree deformation. We share our custom collected synthetic dataset as well as our codebase.
Paper: Coming Soon
Video: Click Here
Prerequisites
This code is developed with Python3 (python3).
It is recommended use Anaconda to set up the environment. Install the dependencies and activate the environment tree-env with
bash
conda env create --file requirements.yaml python=3
conda activate tree-env
Dataset
- #### Synthetic data
We collected a tree deformation dataset simulated in Isaac Gym, which can be found in the Google Drive. For convenience, you can download them with the following script: (under this repo)
bash gdown --id 1YwUABOUg7ukxlmDqN1GojCtuJsZQ57J5 # download tree_dataset.zip unzip tree_dataset.zip rm -f tree_dataset.zip mv tree_dataset data/tree_datasetThedatadirectory should contain the subdirectorytree_dataset.
Running the code
- #### Training:
bash python main_train.py - #### Testing:
bash python main_test.py - #### Generating GIF animations:
bash python main_gif.pyAll the results will be stored in the directoryoutput/.
Code contributed and maintained by:
- John Kim: chunghek@andrew.cmu.edu
- Joe Huang: hungjuih@andrew.cmu.edu
- Mark Lee: moonyoul@andrew.cmu.edu
Owner
- Name: John
- Login: chjohnkim
- Kind: user
- Location: Pittsburgh, PA
- Company: Carnegie Mellon University
- Repositories: 2
- Profile: https://github.com/chjohnkim
PhD student, CMU Robotics Institute
Citation (CITATION.cff)
cff-version: 1.2.0 message: "If you use this software, please cite it as below." authors: - family-names: "Huang" given-names: "Hung-Jui" orcid: "https://orcid.org/0000-0003-0184-5155" - family-names: "Kim" given-names: "Chung Hee" orcid: "https://orcid.org/0000-0001-7710-5984" - family-names: "Lee" given-names: "Moonyoung" orcid: "https://orcid.org/0000-0003-3275-5304" title: "tree_is_all_you_need" version: 1.0.0 date-released: 2022-07-24 url: "https://github.com/chjohnkim/tree_is_all_you_need"
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