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DetAny3D

DetAny3D predicts three-dimensional boxes from a single image.

任务
3d detection
尺寸
h at 896 px
安装
pip install "libreyolo[hf]"
支持层级
兄弟层级,自 v1.6.0 起。一个独立的产品面,有自己的工厂和契约。
上游
DetAny3D,由 OpenDriveLab 发布,采用 Apache-2.0 code; no separate weights license declared by the publisher 许可。论文、源码
许可
代码采用 MIT,权重采用 No separate license declared by the publisher。商用

Install

bash
pip install "libreyolo[hf]"

Predict

Python
from libreyolo import LibreDetAny3D, SAMPLE_IMAGE # Requires the separately installed upstream runtime.model = LibreDetAny3D(device="cpu")result = model.predict(SAMPLE_IMAGE, text="person")print(result.boxes3d)

DetAny3D estimates camera intrinsics internally and accepts text, box or point prompts. Install its separate upstream runtime and its grounding dependencies. Default confidence is 0.37 and the text threshold is 0.25.

result.boxes3d holds centers, dimensions and wxyz quaternions in camera coordinates, plus confidence, class and intrinsics. Plotting projects cuboids into the image. Training, validation, tracking and export are not supported. See 3D detection.

Licensing

请检查你所下载的具体权重在 Hugging Face 仓库中的许可。LibreYOLO 组织里的每个检查点都附有许可,同一家族内也不一定相同。该仓库是权威来源;以下摘要说明本页上次验证时适用的情况。

这里只说明涉及的许可证,不构成法律意见。如果答案对商用很重要,请自行阅读许可证并咨询法律顾问。

原始工作
DetAny3D, OpenDriveLab
上游许可
Apache-2.0 code; no separate weights license declared by the publisher
LibreYOLO 代码
MIT
权重
采用 No separate license declared by the publisher 许可,重新发布在 huggingface.co/LibreYOLO
解读
OpenDriveLab releases the project under Apache-2.0 and declares no separate license for the checkpoint. LibreYOLO mirrors the checkpoint byte-for-byte and adds no terms of its own.

Citation

@article{zhang2025detect,
  title={Detect Anything 3D in the Wild},
  author={Zhang, Hanxue and Jiang, Haoran and Yao, Qingsong and Sun, Yanan and Zhang, Renrui and Zhao, Hao and Li, Hongyang and Zhu, Hongzi and Yang, Zetong},
  journal={arXiv preprint arXiv:2504.07958},
  year={2025}
}

复制自作者在 raw.githubusercontent.com/OpenDriveLab/DetAny3D/main/README.md 上提供的引用块。

已针对 LibreYOLO v1.6.0 验证。本页的支持表、检查点和基准测试数据由已发布的库和权重生成,并非手工编写。