README.md

---
license: mit
library_name: coreml
pipeline_tag: depth-estimation
base_model: Ruicheng/moge-2-vitb-normal
base_model_relation: quantized
tags:
  - coreml
  - core-ml
  - ios
  - macos
  - apple
  - on-device
  - monocular-depth
  - metric-depth
  - surface-normals
  - dinov2
  - arxiv:2507.02546
---

# MoGe-2 ViT-B (504×504) — Core ML

*Microsoft, CVPR 2025*

Monocular geometry from a single image. Metric depth, surface normals, confidence mask. DINOv2 ViT-B/14 backbone.

<p><img src="https://huggingface.co/mlboydaisuke/MoGe-2-ViT-B-CoreML/resolve/main/media/9c56e5477e.png" alt="MoGe-2 ViT-B (504×504) demo"> <img src="https://huggingface.co/mlboydaisuke/MoGe-2-ViT-B-CoreML/resolve/main/media/2c0d16601f.png" alt="MoGe-2 ViT-B (504×504) demo"> <img src="https://huggingface.co/mlboydaisuke/MoGe-2-ViT-B-CoreML/resolve/main/media/1ae5650ca7.png" alt="MoGe-2 ViT-B (504×504) demo"></p>

Core ML conversion of [microsoft/MoGe](https://github.com/microsoft/MoGe) for on-device inference on iPhone, iPad and Mac. Converted with `coremltools`; the packages are stateless, so all sequencing and buffering lives in your Swift code.

| | |
|---|---|
| Task | depth estimation |
| Upstream | [microsoft/MoGe](https://github.com/microsoft/MoGe) |
| Packages | 1 |
| Download size | 184 MB |
| Minimum iOS | 17.0 |
| Peak RAM | ~600 MB |

## Files

| File | Size | Compute units | SHA-256 |
|---|---:|---|---|
| `MoGe2_ViTB_Normal_504.mlpackage.zip` | 184 MB | `all` | `f60cfb4804707a48…` |
| **Total** | **184 MB** | | |

`compute_units` is not a suggestion -- it is the configuration the conversion was verified against. Moving a package to a different compute unit can silently change the numerics (FP16 attention overflow) or crash on the GPU.

## Download

```bash
hf download mlboydaisuke/coreml-zoo --include "moge2/*" --local-dir ./moge2_vitb_normal_504
unzip './moge2_vitb_normal_504/moge2/*.zip' -d ./moge2_vitb_normal_504
```

## Use in Swift

```swift
import CoreML

let config = MLModelConfiguration()
config.computeUnits = .all   // as converted — see the table above

// Unzip the .mlpackage, drop it into your Xcode target and Xcode compiles it
// at build time:
let model = try MoGe2_ViTB_Normal_504(configuration: config)

// ...or compile a downloaded .mlpackage at runtime:
let compiled = try await MLModel.compileModel(at: mlpackageURL)
let model = try MLModel(contentsOf: compiled, configuration: config)
```

## Demo

- **Sample app** — [`sample_apps/MoGe2Demo`](https://github.com/john-rocky/CoreML-Models/tree/master/sample_apps/MoGe2Demo), a standalone SwiftUI project.
- **Models Zoo** — this model is downloadable and runnable inside the [Models Zoo app](https://apps.apple.com/app/id6762083207) on the App Store, no build required.

## Conversion

- Script: [`convert_moge2.py`](https://github.com/john-rocky/CoreML-Models/blob/master/conversion_scripts/convert_moge2.py)
- Pitfalls hit during conversion (FP16 overflow, ANE buffer limits, stride handling): [`docs/coreml_conversion_notes.md`](https://github.com/john-rocky/CoreML-Models/blob/master/docs/coreml_conversion_notes.md)
- Model index: [CoreML-Models](https://github.com/john-rocky/CoreML-Models)

## License

The conversion inherits the upstream license: **MIT**.

## Credits

- Upstream authors: [microsoft/MoGe](https://github.com/microsoft/MoGe), 2025
- Core ML conversion: john-rocky (Daisuke Majima)