DetAny3D

DetAny3D predicts three-dimensional boxes from a single image.

Task: 3d detection
Ukuran: h at 896 px
Instalasi: pip install "libreyolo[hf]"
Tier dukungan: Tier sejajar, sejak v1.6.0. Permukaan produk terpisah dengan factory dan kontraknya sendiri.
Proyek upstream: DetAny3D oleh OpenDriveLab, Apache-2.0 code; no separate weights license declared by the publisher. Makalah, sumber
Lisensi: Kode MIT, bobot No separate license declared by the publisher. Penggunaan komersial

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

Periksa lisensi di repositori Hugging Face untuk bobot tertentu yang diunduh. Setiap checkpoint di organisasi LibreYOLO memiliki lisensi, dan lisensinya tidak selalu sama dalam satu family. Repositori tersebut adalah sumber resmi. Ringkasan di bawah menjelaskan ketentuan yang berlaku saat halaman ini terakhir diverifikasi.

Ini adalah deskripsi lisensi yang terlibat, bukan nasihat hukum. Jika jawabannya penting secara komersial, baca sendiri lisensinya dan mintalah nasihat dari penasihat hukum Anda.

Karya asli: DetAny3D, OpenDriveLab
Lisensi upstream: Apache-2.0 code; no separate weights license declared by the publisher
Sumber upstream: github.com/OpenDriveLab/DetAny3D
Kode LibreYOLO: MIT
Bobot: No separate license declared by the publisher, dipublikasikan ulang di huggingface.co/LibreYOLO
Interpretasi: 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}
}

Disalin dari blok sitasi penulis di raw.githubusercontent.com/OpenDriveLab/DetAny3D/main/README.md.