git clone https://github.com/yifita/idf.git
cd idf
# conda environment and dependencies
# update conda
conda update -n base -c defaults conda
# install requirements
conda env create --name idf -f environment.yml
conda activate idf
# download data. This will download 8 mesh and point clouds to data/benchmark_shapes
sh data/get_data.sh

# surface reconstruction from point cloud
# replace {asian_dragon} with another model name inside the benchmark_shape folder
python net/classes/runner.py net/experiments/displacement_benchmark/ablation/ablation_phased_scaledTanh_yes_act_yes_baseLoss_yes.json --name asian_dragon

sh data/get_dt_shapes.sh
# evaluation of the pretrained examples. This will save the results in 'runs/shorts_residual_filmsiren'
python net/classes/runner.py net/experiments/transfer/shorts_2phase.json

sh data/get_dt_shapes.sh
# this will train the base shapes for the source and target shapes, then train the transferable idf
python net/classes/executor.py net/experiments/transfer/exec.json