apple/coreml-depth-anything-v2-small

Depth Anything V2 Core ML Models

Depth Anything V2 was introduced in the paper of the same name by Lihe Yang et al. It uses the same architecture as the original Depth Anything release, but uses synthetic data and a larger capacity teacher model to achieve much finer and robust depth predictions. The original Depth Anything model was introduced in the paper Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data by Lihe Yang et al., and was first released in this repository.

Model description

Depth Anything V2 leverages the DPT architecture with a DINOv2 backbone.

The model is trained on ~600K synthetic labeled images and ~62 million real unlabeled images, obtaining state-of-the-art results for both relative and absolute depth estimation.

Depth Anything overview. Taken from the original paper.

Evaluation - Variants

Variant	Parameters	Size (MB)	Weight precision	Act. precision	abs-rel error	abs-rel reference
small-original (PyTorch)	24.8M	99.2	Float32	Float32
DepthAnythingV2SmallF32	24.8M	99.2	Float32	Float32	0.0072	small-original
DepthAnythingV2SmallF16	24.8M	49.8	Float16	Float16	0.0089	small-original

Evaluated on 512 landscape images from the COCO dataset with aspect ratio similar to 4:3. Images were streched to a fixed size of 518x396, and the groundtruth corresponds to the results from the PyTorch model running on CUDA with float32 precision.

Evaluation - Inference time

The following results use the small-float16 variant.

Device	OS	Inference time (ms)	Dominant compute unit
iPhone 12 Pro Max	18.0	31.10	Neural Engine
iPhone 15 Pro Max	17.4	33.90	Neural Engine
MacBook Pro (M1 Max)	15.0	32.80	Neural Engine
MacBook Pro (M3 Max)	15.0	24.58	Neural Engine

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 \
  apple/coreml-depth-anything-v2-small \
  --include "DepthAnythingV2SmallF16.mlpackage/*"

To download everything, skip the --include argument.

Integrate in Swift apps

The huggingface/coreml-examples repository contains sample Swift code for DepthAnythingV2SmallF16.mlpackage and other models. See the instructions there to build the demo app, which shows how to use the model in your own Swift apps.