Instructions to use xtli/lehome with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use xtli/lehome with LeRobot:
- Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| tags: | |
| - lerobot | |
| - lehome | |
| - act | |
| - robotics | |
| # ACT Policy For LeHome Challenge | |
| This repository contains a LeRobot-format ACT checkpoint exported from: | |
| - Experiment: `outputs/train/act_top_longee_depth_bs32` | |
| - Checkpoint: `outputs/train/act_top_longee_depth_bs32/checkpoints/0000125000` | |
| - Team: `HandX` | |
| - Registration ID: `r26` | |
| - Contact: `xtli312@163.com` | |
| ## Expected Layout | |
| - `pretrained_model/` | |
| - `train_act_1.yaml` | |
| - `LEHOME_REPO_README.md` | |
| ## Evaluation | |
| Use this checkpoint with the LeHome evaluation script: | |
| ```bash | |
| python -m scripts.eval \ | |
| --policy_type lerobot \ | |
| --policy_path "<downloaded_bundle>/pretrained_model" \ | |
| --dataset_root "Datasets/example/top_long_merged" \ | |
| --garment_type "custom" \ | |
| --num_episodes 5 \ | |
| --task_description "fold the garment on the table" \ | |
| --enable_cameras \ | |
| --device cpu | |
| ``` | |
| ## Required Dependencies | |
| - Python 3.11 | |
| - Isaac Sim 5.1.0 | |
| - Isaac Lab 2.3.1 | |
| - `lerobot` | |
| - LeHome repository source code | |
| ## Notes | |
| - The challenge organizers also need the official assets and dataset metadata. | |
| - If you upload this bundle to Hugging Face, point the Google Form `Policy Submission` field to that repository URL. | |
| - Local self-reported evaluation on `Release_test_list.txt` with 5 episodes per garment: | |
| - Total Episodes: `15` | |
| - Average Return: `183.60 +- 67.87` | |
| - Success Rate: `20.00%` | |
| - `Top_Long_Seen_6`: `20.00%` success, `224.89` avg return | |
| - `Top_Long_Seen_7`: `0.00%` success, `205.17` avg return | |
| - `Top_Long_Unseen_1`: `40.00%` success, `120.74` avg return | |
| - Generated on 2026-04-02T12:02:18. | |