fuyichen0725/blinkmimic

选用指南

AI 根据 README 整理 · 2026/11/3 15:06:47

使用方式

通过命令行工具进行训练、评估和导出，例如使用 bash 脚本和 Python 工具。

查看 README 依据

uv run python tools/test_env.py # sanity check: FK vs simulator, state round-trip, reference playback ``` ## Train, evaluate, reproduce > **Train on an otherwise idle GPU.** On a shared GPU, `--eprobe_async` can crash with an illegal memory access; > add `--eprobe_async 0` there. ```bash bash scripts/train.sh logs/run_s0 --seed 0 # ~8 min: 3500 iterations, a policy checkpoint every 100 uv run python tools/eval_batch.py --run_dir logs/run_s0 --group 18 --reps 4 # 18 checkpoints per batch uv run python tools/time_to_target.py logs/run_s0

bash scripts/reproduce.sh logs/reproduce # the table above: 3 seeds, evaluation, time to target ``` Other tools: `tools/eval_metrics.py` (accuracy and contact metrics), `tools/render.py` (videos from `python -m blinkmimic.evaluate --record`), `tools/export_onnx.py` and `tools/play_onnx.py` (deployment format and a check of it in the simulator; `play_onnx.py` needs `onnxruntime`: `uv run --with onnxruntime python tools/play_onnx.py ...`). ## Attribution and licenses - **Code.** BlinkMimic builds on [supermimic_vibed](https://github.com/zita-ch/supermimic_vibed) (Chong Zhang,

部署要求

需要 Linux x86_64、支持 CUDA 12.8 的 NVIDIA GPU、uv、git、curl、python3 和 ffmpeg（用于视频）。

查看 README 依据

without flags is the SuperMimic baseline; all methods share simulator, MDP, reward and evaluator. ## Setup Linux x86_64, an NVIDIA GPU with a driver for CUDA 12.8, [uv](https://docs.astral.sh/uv/), `git`, `curl`, `python3` (and `ffmpeg` for videos). ```bash git clone https://github.com/fuyichen0725/blinkmimic.git cd blinkmimic uv sync # .venv with mjlab, MuJoCo Warp, Warp, torch 2.9.0 (CUDA 12.8) tools/download_data.sh # 40 G1-retargeted LAFAN1 clips + G1 description -> data/

已知限制

在共享 GPU 上训练时，--eprobe_async 可能崩溃，需添加 --eprobe_async 0。数据（LAFAN1 等）不包含在仓库中，且数据派生文件仅限非商业研究使用。

查看 README 依据

uv run python tools/test_env.py # sanity check: FK vs simulator, state round-trip, reference playback ``` ## Train, evaluate, reproduce > **Train on an otherwise idle GPU.** On a shared GPU, `--eprobe_async` can crash with an illegal memory access; > add `--eprobe_async 0` there. ```bash bash scripts/train.sh logs/run_s0 --seed 0 # ~8 min: 3500 iterations, a policy checkpoint every 100 uv run python tools/eval_batch.py --run_dir logs/run_s0 --group 18 --reps 4 # 18 checkpoints per batch uv run python tools/time_to_target.py logs/run_s0

- **Data.** LAFAN1 motions by Ubisoft La Forge (Harvey et al., SIGGRAPH 2020), license **CC BY-NC-ND 4.0**; G1 retargets and robot description by Unitree (BSD-3-Clause), via the Hugging Face dataset `lvhaidong/LAFAN1_Retargeting_Dataset`. The data are not included here. The GIF and trained checkpoints are derived from LAFAN1: non-commercial research use only, not under this repository's MIT License. ## Citation ```bibtex @misc{blinkmimic2026, title = {BlinkMimic: Whole-Body Motion Tracking for the Unitree G1 in Minutes on One GPU}, author = {Chen, Fuyi}, year = {2026},