Core ML Model Zoo
Collection
PyTorch models converted to Core ML for on-device inference on iPhone, iPad and Mac. • 46 items • Updated • 1
Pixelization — Core ML
Cell-Controllable Pixel Art, SIGGRAPH Asia 2022
Turn any photo into pixel art. Aliasing-aware generator + anti-alias refinement. Drag the cell-size slider (2–8) to change pixel block size — the network runs once per photo, the slider only re-snaps the grid. 512×512 input. Non-commercial research use only.
Core ML conversion of WuZongWei6/Pixelization 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 | WuZongWei6/Pixelization |
| Packages | 1 |
| Download size | 35 MB |
| Minimum iOS | 17.0 |
| Peak RAM | ~250 MB |
Files
| File | Size | Compute units | SHA-256 |
|---|---|---|---|
Pixelization_512.mlpackage.zip |
35 MB | cpuAndNeuralEngine |
f9eac7e8fa6487a4… |
| Total | 35 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
hf download mlboydaisuke/coreml-zoo --include "pixelization/*" --local-dir ./pixelization
unzip './pixelization/pixelization/*.zip' -d ./pixelization
Use in Swift
import CoreML
let config = MLModelConfiguration()
config.computeUnits = .cpuAndNeuralEngine // 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 Pixelization_512(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/PixelizationDemo, a standalone SwiftUI project. - Models Zoo — this model is downloadable and runnable inside the Models Zoo app on the App Store, no build required.
Conversion
- Script:
convert_pixelization.py - Pitfalls hit during conversion (FP16 overflow, ANE buffer limits, stride handling):
docs/coreml_conversion_notes.md - Model index: CoreML-Models
License
The conversion inherits the upstream license: Research use only. See https://github.com/WuZongWei6/Pixelization.
Upstream ships no LICENSE file; the paper repo states research use only.
Credits
- Upstream authors: WuZongWei6/Pixelization, 2022
- Core ML conversion: john-rocky (Daisuke Majima)
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