---
license: mit
library_name: coreml
pipeline_tag: keypoint-detection
tags:
- coreml
- core-ml
- ios
- macos
- apple
- on-device
- face-alignment
- 3dmm
- head-pose
- arxiv:2009.09960
---
# 3DDFA V2 — Core ML
*3D Face Reconstruction, 2020*
Single-image 3D face reconstruction. Predicts 6 DoF pose + expression parameters.

Core ML conversion of [cleardusk/3DDFA_V2](https://github.com/cleardusk/3DDFA_V2) 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 | keypoint detection |
| Upstream | [cleardusk/3DDFA_V2](https://github.com/cleardusk/3DDFA_V2) |
| Packages | 1 |
| Download size | 6 MB |
| Minimum iOS | 17.0 |
| Peak RAM | ~200 MB |
## Files
| File | Size | Compute units | SHA-256 |
|---|---:|---|---|
| `3DDFA_V2.mlpackage.zip` | 6 MB | `all` | `0f715dc220c046f5…` |
| **Total** | **6 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 "face3d/*" --local-dir ./face3d
unzip './face3d/face3d/*.zip' -d ./face3d
```
## 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 3DDFA_V2(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/Face3DDemo`](https://github.com/john-rocky/CoreML-Models/tree/master/sample_apps/Face3DDemo), 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
- 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: [cleardusk/3DDFA_V2](https://github.com/cleardusk/3DDFA_V2), 2020
- Core ML conversion: john-rocky (Daisuke Majima)