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colorize-ddcolor-tiny

Image-to-Image
Core ML
colorization
image-colorization
on-device
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metadata 
license: apache-2.0
library_name: coreml
pipeline_tag: image-to-image
tags:
  - coreml
  - colorization
  - image-colorization
  - on-device
  - arxiv:2212.11613
base_model: piddnad/ddcolor_paper_tiny

DDColor Tiny — Core ML (for img colorize)

Automatic colorization of black-and-white photographs, on-device. This is the model behind img colorize in swift-img-cli, through the public swift-image-colorizer library, which downloads it on first use.

  • Model: DDColor (Kang et al., DDColor: Towards Photo-Realistic Image Colorization via Dual Decoders, ICCV 2023, arXiv:2212.11613) — piddnad/DDColor, Apache-2.0, the paper_tiny (ConvNeXt-T) checkpoint.
  • Conversion: coremltools, by mlboydaisuke/DDColor-Tiny-CoreML (Apache-2.0), commit 48c9a506b578460681078e31378e2eaae424a044. These files are that package byte for byte, re-hosted so the tools pin one commit they were measured against.
  • Licence: Apache-2.0 — see LICENSE (DDColor's own).

Interface

Field Value
Input image float32 [1, 3, 512, 512], RGB 0…1 — the photo's CIELAB L with a = b = 0, back in sRGB
Output ab_channels [1, 2, 512, 512], CIELAB a and b
Compute units all

The library keeps the photograph's own luminance at full resolution and takes only the predicted a/b, upsampled — so no edge, face or detail moves; only colour is added.