---
license: apache-2.0
tags:
  - onnx
  - depth-estimation
  - monocular-depth
  - controlnet
  - qtmesheditor
library_name: onnx
pipeline_tag: depth-estimation
base_model: depth-anything/Depth-Anything-V2-Small-hf
---

# Depth-Anything-V2-Small — ONNX (monocular photo depth)

**Depth-Anything-V2-Small** (Yang et al., 2024) exported to ONNX. Relative
(inverse) depth from a single photograph. All credit to the Depth Anything
authors.

Mirrored for **[QtMeshEditor](https://github.com/fernandotonon/QtMeshEditor)**
(issue #1018, epic #818 Track C4), where it depth-conditions the Stable
Diffusion ControlNet texture path from a **reference photo** rather than only
from mesh-rendered depth: `qtmesh material --photo-depth`, the Material Editor's
"Depth from photo…" button, and the `photo_depth` MCP tool.

> The file QtMeshEditor downloads at runtime lives in the shared
> [`fernandotonon/QtMeshEditor-models`](https://huggingface.co/fernandotonon/QtMeshEditor-models)
> repo under `depth/`. This repo is the standalone model card + mirror.

## Why only the Small variant

**Small is Apache-2.0. Base and Large are `cc-by-nc-4.0`** and are deliberately
NOT mirrored here or shipped by QtMeshEditor — non-commercial terms fail the
project's permissive-redistribution bar (the same reason SF3D and Hunyuan3D were
rejected). The exporter enforces this in code: it queries the HF model API and
hard-fails on any licence outside its allow-list *before* downloading weights.

## I/O

```
input   pixel_values     float32 [1,3,518,518]   ImageNet-normalised RGB (NCHW)
output  predicted_depth  float32 [1,518,518]     relative inverse depth
```

**Larger = NEARER.** QtMeshEditor normalises to 8-bit grayscale with
*near = bright*, matching the convention its mesh-depth renderer emits, so a
photo and a rendered mesh are interchangeable as ControlNet conditioning images.

Normalisation constants (upstream `preprocessor_config.json`):
`mean = [0.485, 0.456, 0.406]`, `std = [0.229, 0.224, 0.225]`.

## The spatial dims are PINNED, not dynamic

Only the batch axis is dynamic. This is deliberate: a dynamic-axis export traces
cleanly but **drifts away from the traced resolution**, because the ViT
position-embedding interpolation is only partly captured. Measured against
torch, max abs difference on a smooth image:

| input | relative error |
|---|---|
| 518×518 (traced) | **2.7e-06** |
| 462×462 | 2.3e-02 |
| 392×392 | 4.9e-02 |

An earlier dynamic export was worse still — it advertised dynamic height/width
but **froze the output size**, returning a 518×518 map for a 462×462 input
(`int()` casts in the HF head bake the interpolate target into a constant).

Since the reference preprocessor resizes every input to 518 anyway
(`size: 518`, `keep_aspect_ratio`, `ensure_multiple_of: 14`), pinning costs
nothing and removes a silent-wrong-answer failure mode. Resize to 518×518
before inference.

## Parity

The export asserts torch-vs-onnxruntime agreement before upload, on both random
noise and a smooth structured image, and refuses to write a graph containing any
non-finite output:

```
[parity] torch vs onnxruntime
  shape (1, 518, 518)  max|diff| 4.053e-06
[parity] smooth image  max|diff| 6.914e-06
```

Export script:
[`scripts/export-depth-anything-onnx.py`](https://github.com/fernandotonon/QtMeshEditor/blob/master/scripts/export-depth-anything-onnx.py)
(opset 18).

## License

Apache-2.0, inherited from
[`depth-anything/Depth-Anything-V2-Small-hf`](https://huggingface.co/depth-anything/Depth-Anything-V2-Small-hf).
Credit: Lihe Yang, Bingyi Kang, Zilong Huang, Zhen Zhao, Xiaogang Xu, Jiashi
Feng, Hengshuang Zhao.