LloydAI/DepthAnything_v2-Small-CoreML

Depth Anything V2 Small (mlpackage)

In this repo you can find:

• The notebook which was used to convert depth-anything/Depth-Anything-V2-Small into a CoreML package.
• Both mlpackage files which can be opened in Xcode and used for Preview (of both images and videos) and development of macOS and iOS Apps
• Performence and compute unit mapping report for these models as meassured on an iPhone 16 Pro Max
• One model uses internal resolution of 518x518 ("Box") and the other 518x392 ("Landscape").
• The "Landscape" is much faster than "Box" but will also give more "juggy" edges, due to the patch I applied to avoid bicubing upsampling (.diff file is also present in this repo)

As a derivative work of Depth-Anything-V2-Small this port is also under apache-2.0

Download

Install huggingface-cli

brew install huggingface-cli

To download one of the .mlpackage folders to the models directory:

huggingface-cli download \
  --local-dir models --local-dir-use-symlinks False \
  LloydAI/DepthAnything_v2-Small-CoreML \
  --include "DepthAnything_v2_Small_518x392_Landscape.mlpackage/*"

Citation of original work

If you find this project useful, please consider citing:

@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}
}