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README.md

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+---
+license: apache-2.0
+base_model: depth-anything/DA3MONO-LARGE
+pipeline_tag: depth-estimation
+library_name: coreml
+tags:
+  - coreml
+  - depth-estimation
+  - monocular-depth
+  - depth-anything
+  - apple-silicon
+  - stereo
+---
+
+# DepthAnythingV3Mono-CoreML
+
+A **CoreML conversion** of [`depth-anything/DA3MONO-LARGE`](https://huggingface.co/depth-anything/DA3MONO-LARGE)
+— the monocular-depth variant of Depth Anything 3 (DINOv2 ViT-L backbone + DPT head, ~0.35B params) —
+packaged for on-device inference on Apple Silicon (macOS 14+).
+
+This is a derivative work of the original model, which is licensed **Apache-2.0**; this conversion is
+released under the same license. All credit for the model itself goes to ByteDance / the Depth Anything 3
+authors. See the [original repo](https://github.com/bytedance-seed/depth-anything-3).
+
+## What's in here
+
+- `DepthAnythingV3Mono.mlpackage` — an ML Program, **FP16** weights, minimum deployment target **macOS 14**.
+
+## Interface
+
+- **Input** `image`: an RGB image, **504×504** (a multiple of the DINOv2 patch size, 14).
+  ImageNet normalization is **baked into the graph**; the CoreML `ImageType` only rescales 0–255 → 0–1,
+  so you can hand it a `CVPixelBuffer` built straight from a `CGImage` with no manual preprocessing.
+- **Output** `depth`: a single-channel `MLMultiArray` of shape `(1, 504, 504)` holding **relative** depth
+  (model-relative units). Consumers typically min-max normalize to `0…1`.
+
+## Conversion notes
+
+Converted with `coremltools` from a `torch.jit.trace` of `backbone → head → depth`. The full
+Depth Anything 3 `forward()` also runs camera-pose, sky and Gaussian-splat post-processing; those are
+either inert for the mono model or not traceable (the sky refinement is a data-dependent `torch.quantile`),
+so only the raw relative-depth path is converted. DINOv2's bicubic positional-embedding interpolation is
+substituted with **bilinear** (coremltools has no `upsample_bicubic2d`); this is a sub-pixel approximation.
+
+**Fidelity:** on a structured test image, the CoreML output matches the FP32 PyTorch reference with a
+Pearson correlation of **0.99996** (normalized MAE 0.15%).
+
+## Usage (Swift / CoreML)
+
+```swift
+import CoreML
+import CoreImage
+
+let model = try MLModel(contentsOf: compiledURL)   // compile the .mlpackage first
+// Provide `image` as a 504×504 CVPixelBuffer (32BGRA); read `depth` as an MLMultiArray (1×504×504).
+```
+
+It is used as the default depth model in the SBS 3D image viewer (replacing Depth Anything V2-Large),
+chosen specifically because DA3MONO-LARGE is Apache-2.0 and therefore safe for commercial distribution.
+
+## License & attribution
+
+Apache-2.0, inherited from the upstream model. If you use this, please cite the original Depth Anything 3 work.