Layout-based Causal Inference for Object Navigation
- Clone the repository and move into the top-level directory
cd Layout-based-sTDE
- Create conda environment.
conda env create -f environment.yml
- Activate the environment.
conda activate ng
- We provide pre-trained model of ORG+L-sTDE. Please download and put it in the
./trained_models
folder.
- Our settings of dataset follows previous works, please refer to HOZ for AI2THOR and SemExp for Gibson.
Train our Layout-based model
python main.py \
--title layoutmodel \
--model LayoutModel \
--workers 12 \
--gpu-ids 0
Evaluate our model with sTDE (our Layout-based sTDE model)
python full_eval.py \
--title layoutmodel \
--model LayoutModel \
--results-json layoutmodel_sTDE.json \
--gpu-ids 0 \
--TDE_self True \
--TDE_threshold 0.5 \
--TDE_mode zero