Source codes of SIGGRAPH Asia 2023 Paper : "Scene-aware Activity Program Generation with Language Guidance"
We use two virtual environments in our project. The configuration of the virtual environment are:
- Python 3.11
- cuda 11.3
- Pytorch 1.13.0
You can create it using the following scripts:
conda create -n LVHomeEnv python=3.11
conda activate LVHomeEnv
git clone https://github.com/ToddBear/LangGuidedProgram
cd LangGuidedProgram
pip install -r requirements.txt
cd ..
mkdir Data
Download the program dataset here, and organize it as follows:
Data
└── augment_programs
├── augment_exception
└── augment_location
└── original_programs
Download the pre-computed future link here for training the adjacency constraint moduel, and place it in Data folder:
Data
└── future_link.pkl
Fill in LangGuidedProgram/program/dataset.py
line 28 with the absolute path to the parent folder PARENT_PATH
of LangGuidedProgram
.
PARENT_PATH = ""
program_path = PARENT_PATH + "/Data/original_programs/executable_programs/*/*/*txt"
augment_program_path = PARENT_PATH + "/Data/augment_programs/*/executable_programs/*/*/*/*txt"
sketch_path = PARENT_PATH + "/LangGuidedProgram/dataset/VirtualHome-Env/sketch_annotation.json"
Run the following scripts for training:
cd LangGuidedProgram/src
sh train.sh
Download the pre-trained weights here, put it into the LangGuidedProgram/src/output
folder, and run the following scripts:
cd LangGuidedProgram/src
sh test.sh
If you find the code useful in your research, please consider citing:
@article{su2023scene,
title={Scene-aware Activity Program Generation with Language Guidance Supplementary Material},
author={Su, Zejia and Fan, Qingnan and Chen, Xuelin and Van Kaick, Oliver and Huang, Hui and Hu, Ruizhen},
journal={ACM Trans. Graph},
volume={42},
number={6},
year={2023}
}
Our project is build upon VirtualHome and ResActGraph. Thanks for your great constributions!
Our code is released under MIT License. See LICENSE file for details.