--- license: apache-2.0 library_name: coreml pipeline_tag: mask-generation tags: - coreml - core-ml - ios - macos - apple - on-device - segment-anything - sam - promptable-segmentation - arxiv:2306.14289 --- # MobileSAM — Core ML *Segment Anything, 2023* Lightweight Segment Anything. Tap any point to generate a segmentation mask. ViT-Tiny encoder + lightweight decoder. ~60× smaller than SAM.

MobileSAM demo

Core ML conversion of [ChaoningZhang/MobileSAM](https://github.com/ChaoningZhang/MobileSAM) 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 | mask generation | | Upstream | [ChaoningZhang/MobileSAM](https://github.com/ChaoningZhang/MobileSAM) | | Packages | 1 | | Download size | 19 MB | | Minimum iOS | 17.0 | | Peak RAM | ~300 MB | ## Files | File | Size | Compute units | SHA-256 | |---|---:|---|---| | `MobileSAM.zip` | 19 MB | `all` | `0d8d48cb90a48cd8…` | | **Total** | **19 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 "mobilesam/*" --local-dir ./mobilesam unzip './mobilesam/mobilesam/*.zip' -d ./mobilesam ``` ## 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 MobileSAM.zip(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** — [SamKit](https://github.com/john-rocky/SamKit), a standalone iOS 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: **Apache-2.0**. ## Credits - Upstream authors: [ChaoningZhang/MobileSAM](https://github.com/ChaoningZhang/MobileSAM), 2023 - Core ML conversion: john-rocky (Daisuke Majima)