| --- |
| 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. |
|
|
