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| license: apache-2.0 | |
| base_model: Wan-AI/Wan2.2-TI2V-5B | |
| datasets: | |
| - RimbotAI/LOOM | |
| tags: | |
| - robotics | |
| - reward-model | |
| # NimCritic | |
| NimCritic 根据机器人视频和任务指令,逐帧估计任务进度与是否完成。 | |
| [Project page](https://rimbot.com/en/research/nimcritic/) · [Paper](https://arxiv.org/abs/2610.32776) | |
| ## 目录里有什么 | |
| | 路径 | 内容 | | |
| |---|---| | |
| | `infer_nimcritic.py` | 读帧、滑窗和命令行参数。 | | |
| | `nimcritic_model.py` | 模型:video DiT、value DiT、VAE、文本编码器。 | | |
| | `nimcritic_step_128000.pt` | step 128000。video expert 5.00B,value expert 1.02B,bfloat16。 | | |
| | `base/` | Wan2.2 VAE、UMT5-XXL 编码器和分词器。不含 Wan2.2 DiT:video expert 的完整权重已经在 `.pt` 里。 | | |
| `base/` 包含: | |
| - `DiffSynth-Studio/Wan-Series-Converted-Safetensors/Wan2.2_VAE.safetensors` | |
| - `DiffSynth-Studio/Wan-Series-Converted-Safetensors/models_t5_umt5-xxl-enc-bf16.safetensors` | |
| - `Wan-AI/Wan2.1-T2V-1.3B/google/umt5-xxl/`(分词器) | |
| 许可见 Apache-2.0。 | |
| ## 环境 | |
| Python 3.12+。在本目录安装推理依赖: | |
| ```bash | |
| uv sync | |
| ``` | |
| 依赖写在 `pyproject.toml`:PyTorch、`transformers`(4.57,低于 4.58)、`safetensors`、`einops`、`opencv-python-headless`、`Pillow`、`numpy`、`tqdm`。 | |
| 模型代码在 `nimcritic_model.py`,权重与 `base/` 在同目录。推理不访问其他路径,也不下载额外文件。 | |
| ## 推理 | |
| 在本目录执行。默认读取同目录的 `nimcritic_step_128000.pt` 与 `base/`。 | |
| ```bash | |
| uv run python infer_nimcritic.py \ | |
| --video clip.mp4 \ | |
| --task "pick up the cup" \ | |
| --output result.json | |
| ``` | |
| 输入为视频文件时,按容器帧率采样至 2Hz(`--sample-hz`,默认 2),并保留最后一帧。输入已是 2Hz 帧序列时使用 `--frames`,不再按 2Hz 重采样: | |
| ```bash | |
| uv run python infer_nimcritic.py \ | |
| --frames frames_dir/ \ | |
| --task "pick up the cup" \ | |
| --output result.json | |
| ``` | |
| `--base` 指向 `base/` 这一层,不是里面的 `DiffSynth-Studio/`。 | |
| 默认口径:帧拉到 256×448(`stretch`),progress 是相对当前窗口条件帧的增量,写回前还原成 0–1,`rollout_stride=1`,`distance` 聚合,20 步,seed 42。和论文短任务表同一口径时加上 `--rollout-stride 2`。 | |
| 每个参数的含义、可选项和默认值: | |
| ```bash | |
| uv run python infer_nimcritic.py --help | |
| ``` | |
| 不加载权重、只检查抽帧和参数: | |
| ```bash | |
| uv run python infer_nimcritic.py --self-check | |
| ``` | |
| GPU 推理建议预留不少于 24 GB 显存。CPU 推理通过 `--device cpu` 指定,耗时高于 GPU。 | |
| 结果 JSON 中,`progress` 与 `success` 为逐帧的 0–1 数值。`sampling` 记录所采用的帧下标。 | |
| ## 引用 | |
| ```bibtex | |
| @article{xu2026nimcritic, | |
| title = {Predictive Long-Horizon Progress Modeling with Action-Aware Quantification}, | |
| author = {Xu, Tianchi and Zheng, Yalin and Zhu, Yangxin and Ren, Ruonan and Fu, Zheng and Wang, Yunlong and Zhong, Yuanxin}, | |
| journal = {arXiv preprint arXiv:2610.32776}, | |
| year = {2026}, | |
| url = {https://arxiv.org/abs/2610.32776} | |
| } | |
| ``` | |
| 基准请同时引用 [LOOM][hf-benchmark]。 | |
| [hf-model]: https://huggingface.co/RimbotAI/NimCritic | |
| [hf-benchmark]: https://huggingface.co/datasets/RimbotAI/LOOM | |
| [arxiv]: https://arxiv.org/abs/2610.32776 | |
| [project]: https://rimbot.com/en/research/nimcritic/ | |
| [demo]: https://critic.rimbot.com/ | |