Instructions to use tonghuiwang123/so100-diffusion-new60-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use tonghuiwang123/so100-diffusion-new60-ft with LeRobot:
- Notebooks
- Google Colab
- Kaggle
so100-diffusion-new60-ft · step 30000
DIFFUSION policy for SO-ARM100 / SO100 — Grab the white cube to the white cup
- 数据:
tonghuiwang123/4060 episodes / 13454 frames / 2×1280x720 @30fps - Checkpoint: step 30000 ≈ 142.7 epoch(有效 batch 64)
- 两阶段:起点为旧60集(旧相机)训练的 Diffusion Policy 权重;resize_shape=[180,320] crop_ratio=0.95
相机命名(各算法族不同,顺序错了不报错但表现会莫名变差)
| 物理位置 | 设备 | 本模型要求的 key |
|---|---|---|
| 顶部 (top-down) | /dev/video2 |
front |
| 腕部 (wrist) | /dev/video4 |
side |
部署
lerobot-record \
--robot.type=so100_follower --robot.port=/dev/ttyACM0 \
--robot.id=my_awesome_follower_arm \
--robot.cameras="{
front: {type: opencv, index_or_path: /dev/video2, width: 1280, height: 720, fps: 30},
side: {type: opencv, index_or_path: /dev/video4, width: 1280, height: 720, fps: 30},
}" \
--dataset.repo_id=tonghuiwang123/eval_so100-diffusion-new60-ft \
--dataset.single_task="Grab the white cube to the white cup" \
--policy.path=tonghuiwang123/so100-diffusion-new60-ft
分辨率必须 1280x720。推理显存 约 1.1 GB。
中间 checkpoint 用 --policy.pretrained_revision=ckpt-XXXXXX。
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