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README.md

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+---
+license: apache-2.0
+library_name: onnx
+pipeline_tag: depth-estimation
+tags:
+  - depth-anything
+  - onnx
+  - depth-estimation
+  - visionserve
+base_model: depth-anything/Depth-Anything-V2-Small-hf
+---
+
+# Depth Anything V2 Small — ONNX with dynamic input size
+
+ONNX export of [`depth-anything/Depth-Anything-V2-Small-hf`](https://huggingface.co/depth-anything/Depth-Anything-V2-Small-hf)
+(Apache-2.0) for [VisionServe](https://hub.docker.com/r/mtbui2010/visionserve):
+
+```bash
+visionserve pull depth-anything-v2
+```
+
+Only the **Small** variant is published: Depth Anything V2 Base and Large are CC-BY-NC-4.0.
+
+## Why another export
+
+The input is `[1, 3, H, W]` with **dynamic H and W**, so the image can be fed at the size the
+reference `DPTImageProcessor` uses (keep the aspect ratio, scale by whichever of 518/W, 518/H is
+closer to 1, each side rounded to a multiple of 14, bicubic). For example, an 848×480 photo is
+fed at 910×518 instead of being squashed to 518×518.
+
+A plain dynamic-axes export of this model is wrong. The legacy tracer bakes the 518×518 output
+size into the head (`int(patch_h * 14)` in `modeling_depth_anything.py`), so every input returns
+a 518×518 map. This export keeps that size traced, and it is checked against PyTorch at three
+input shapes (518×518, 910×518 and 518×686).
+
+## I/O contract
+
+| | name | shape | |
+|---|---|---|---|
+| input | `pixel_values` | `[1, 3, H, W]` f32 | H, W multiples of 14; /255, ImageNet mean/std |
+| output | `predicted_depth` | `[1, H, W]` f32 | relative inverse depth (disparity), unnormalised |
+
+## Verification (VisionServe converter, 7 non-square photos)
+
+| check | result |
+|---|---|
+| ONNX vs PyTorch, 3 input shapes | max \|Δ\|/scale 1.05e-05 |
+| served preprocessing vs `DPTImageProcessor` | mean 0.25 grey levels, same shapes on 7/7 images |
+| served depth map vs `predicted_depth` | Pearson r min 0.9999, mean 1.000 |
+
+## License
+
+Apache-2.0, inherited from `depth-anything/Depth-Anything-V2-Small-hf`. The weights are not modified.