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1conda create -n interact_garment python=3.10
2conda activate interact_garment
3pip install torch torchvision
4pip install -r src/requirements.txt
5export PYTHONPATH=$PWD/src:$PYTHONPATHsrc/checkpoints/ and run the inference script from the src directory.1torchrun --standalone --nproc_per_node=1 inference/infer_twostage.py \
2 eval.sample_per_batch=1 eval.n_samples=0 eval.evaluate=False \
3 train.exp_name=uncond_samples sample.num_sampling_steps=100 \
4 gpf_ckpt=null \
5 dataset.front_only=True dataset.use_all_captions=True \
6 dataset.img_drop_prob=1 dataset.text_drop_prob=1 \
7 model.use_qknorm=True \
8 edge_model.use_qknorm=True \
9 edge_model_ckpt=checkpoints/edge \
10 model=sparse_lightningdit_v3_xl1_w_text_fsdp2 \
11 pgf_weight_init=checkpoints/pgf_text \
12 --config-name sparselightningdit_xl_garment_particle_inference1torchrun --standalone --nproc_per_node=1 inference/infer_twostage.py \
2 eval.sample_per_batch=1 eval.n_samples=0 eval.evaluate=False \
3 train.exp_name=img_cond_samples sample.num_sampling_steps=100 \
4 gpf_ckpt=null \
5 dataset.front_only=True dataset.use_all_captions=True \
6 dataset.img_drop_prob=0 dataset.text_drop_prob=1 \
7 model.use_qknorm=True model.use_rope=False model.in_channels=6 model.freeze_everything=False \
8 edge_model.use_qknorm=True \
9 edge_model_ckpt=checkpoints/edge \
10 model=sparse_lightningdit_v3_xl1_w_img_text_v2 \
11 pgf_weight_init=checkpoints/pgf_image \
12 --config-name sparselightningdit_xl_garment_particle_inference1@inproceedings{garmentparticles2026,
2 title={Garment Particles: A 2D--3D Symmetric Garment Representation for Generation and Editing},
3 author={George Nakayama and others},
4 booktitle={SIGGRAPH Conference Papers},
5 year={2026}
6}