# L-CAMP: Language-Conditioned Axis and Motion Prediction for Articulated Object Manipulation
[Ikechukwu Daniel Adebi](https://danieladebi.github.io), [Mitchell Pryor](https://www.me.utexas.edu/people/faculty-directory/pryor)
## Setup
1. Create the conda/micromamba environment from `environment_lcamp.yml`:
```bash
micromamba create -f environment_lcamp.yml # or: conda env create -f environment_lcamp.yml
micromamba activate lcamp
```
2. Build the LCAMP dataset (only needed once per dataset version), see
`process_lcamp_dataset.py` / `process_lcamp_dataset.slurm`. This produces a
dataset directory containing `train_dataset.json`, `test_dataset.json`,
and `intrinsics.npy`, referenced below as `--data_root`/`--data_dir`.
All commands below (`train.py`, `eval.py`) assume the `lcamp` environment is
active.
### Download Model
A pretrained checkpoint is available on HuggingFace:
[danieladebi/lcamp-model](https://huggingface.co/danieladebi/lcamp-model).
Download it i…
