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mlboydaisuke
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DDColor-Tiny-CoreML

Image-to-Image
Core ML
core-ml
ios
macos
apple
on-device
colorization
image-colorization
arxiv:2212.11613
Model card Files
xet
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DDColor-Tiny-CoreML
File size: 3,097 Bytes
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---
license: apache-2.0
library_name: coreml
pipeline_tag: image-to-image
tags:
  - coreml
  - core-ml
  - ios
  - macos
  - apple
  - on-device
  - colorization
  - image-colorization
  - arxiv:2212.11613
---

# DDColor Tiny — Core ML

*Image Colorization, 2023*

Automatic grayscale image colorization via dual decoders. 512×512 input.

<p><img src="https://huggingface.co/mlboydaisuke/DDColor-Tiny-CoreML/resolve/main/media/0d8f0d4385.jpg" alt="DDColor Tiny demo" width="49%"> <img src="https://huggingface.co/mlboydaisuke/DDColor-Tiny-CoreML/resolve/main/media/c83e15a3b5.png" alt="DDColor Tiny demo" width="49%"></p>

Core ML conversion of [piddnad/DDColor](https://github.com/piddnad/DDColor) 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 | image to image |
| Upstream | [piddnad/DDColor](https://github.com/piddnad/DDColor) |
| Packages | 1 |
| Download size | 203 MB |
| Minimum iOS | 17.0 |
| Peak RAM | ~400 MB |

## Files

| File | Size | Compute units | SHA-256 |
|---|---:|---|---|
| `DDColor_Tiny.mlpackage.zip` | 203 MB | `all` | `bfecea37d66005f6…` |
| **Total** | **203 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 "ddcolor/*" --local-dir ./ddcolor
unzip './ddcolor/ddcolor/*.zip' -d ./ddcolor
```

## 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 DDColor_Tiny(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/DDColorDemo`](https://github.com/john-rocky/CoreML-Models/tree/master/sample_apps/DDColorDemo), 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_ddcolor.py`](https://github.com/john-rocky/CoreML-Models/blob/master/conversion_scripts/convert_ddcolor.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: **Apache-2.0**.

## Credits

- Upstream authors: [piddnad/DDColor](https://github.com/piddnad/DDColor), 2023
- Core ML conversion: john-rocky (Daisuke Majima)