--- license: cc-by-nc-4.0 language: - en pipeline_tag: depth-estimation tags: - depth - relative depth --- # Depth-Anything-V2_Safetensors ## Introduction Depth Anything V2 is trained from 595K synthetic labeled images and 62M+ real unlabeled images, providing the most capable monocular depth estimation (MDE) model with the following features: - more fine-grained details than Depth Anything V1 - more robust than Depth Anything V1 and SD-based models (e.g., Marigold, Geowizard) - more efficient (10x faster) and more lightweight than SD-based models - impressive fine-tuned performance with our pre-trained models - models have been converted into .safetensors ## Installation ```bash git clone https://github.com/MackinationsAi/Upgraded-Depth-Anything-V2.git cd Upgraded-Depth-Anything-V2 one_click_install.bat ``` ## Usage - Download the Depth-Anything-V2-Large model | 654.9M | [Download](https://huggingface.co./MackinationsAi/Depth-Anything-V2_Safetensors/resolve/main/depth_anything_v2_vitl.safetensors?download=true) | first and put it under the `checkpoints` directory. - Download the Depth-Anything-V2-Base model | 190.4M | [Download](https://huggingface.co./MackinationsAi/Depth-Anything-V2_Safetensors/resolve/main/depth_anything_v2_vitb.safetensors?download=true) | second and put it under the `checkpoints` directory. - Download the Depth-Anything-V2-Small model | 48.4M | [Download](https://huggingface.co./MackinationsAi/Depth-Anything-V2_Safetensors/resolve/main/depth_anything_v2_vits.safetensors?download=true) | third and put it under the `checkpoints` directory. - Download the Depth-Anything-V2-Giant model | 1.3B | Coming soon (Still not available) | [Download Doesn't Work - Model is still a WIP](https://huggingface.co./MackinationsAi/Depth-Anything-V2_Safetensors/resolve/main/depth_anything_v2_vitg.safetensors?download=true) | fourth and put it under the `checkpoints` directory. ## Citation If you find this project useful, please consider citing below, give these converted models & upgraded linked repo a star/follow & share it w/ others in the community! ```bibtex @article{depth_anything_v2, title={Depth Anything V2}, author={Yang, Lihe and Kang, Bingyi and Huang, Zilong and Zhao, Zhen and Xu, Xiaogang and Feng, Jiashi and Zhao, Hengshuang}, journal={arXiv:2406.09414}, year={2024} } @inproceedings{depth_anything_v1, title={Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data}, author={Yang, Lihe and Kang, Bingyi and Huang, Zilong and Xu, Xiaogang and Feng, Jiashi and Zhao, Hengshuang}, booktitle={CVPR}, year={2024} }