🍎 Native YOLO-Master Core ML Runner for MacOS
For MacOS: YOLO-Master Core ML Runner 1.0.0
On-device YOLO-Master object detection and instance segmentation for macOS, accelerated via Apple Core ML. A native SwiftUI app that features a pick a model and a source (image, folder, video, or the live webcam) and it infers on-device: no command line, no cloud, nothing leaves your Mac.
This is the first public release.
✨ Features
- Detection & Segmentation: Runs both bounding-box detectors and instance-segmentation models. Masks are anti-aliased (no serrated edges), with a Masks / Boxes / Both overlay toggle.
- Images, Video & Live Camera: Single images, whole-folder batches, and MP4 video, plus a low-latency live webcam mode with a real-time FPS / ms-per-frame HUD and a mirror toggle.
- Real-Time Tuning: Confidence, IoU (NMS), box style, and labels redraw instantly; the forward pass is cached, so it does not require to re-run inference at any time. Letterbox vs. stretch preprocessing is also switchable.
- Two-Phase Pipeline: Folders and videos are inferred once with a progress bar, then browsed, scrubbed, and exported with the tuned parameters.
- Export: Write annotated images or MP4 with the current overlay and style.
- Bundled Default Model: Ships with a segmentation model, so it runs the moment you open it; load any other exported Core ML model at any time.
- LoRA Support: Supports LoRA checkpoints of most YOLO-Master models, including but not limited to the EsMoE and the v0.1 families.
🚀 Performance
Live camera inference speed (ms/frame) on Apple Silicon, .mlpackage models via the Core ML CPU + GPU compute unit:
| Model | M1 (MacBook Pro 13") | M3 Pro (MacBook Pro 14") | M4 Max (MacBook Pro 16") |
|---|---|---|---|
| v0.1-seg-N | 21.2 | 19.9 | 20.0 |
| v0.1-seg-N-LoRA | 21.3 | 22.8 | 21.0 |
| v0.1-N | 19.6 | 19.4 | 19.8 |
| EsMoE-N | 15.5 | 15.4 | 15.2 |
| UoMoE-N | 14.9 | 14.1 | 14.3 |
| YOLOv12-X | 45.0 | 33.7 | 30.0 |
Now you can run an X-scale model on a laptop SoC in real-time.
🖥️ Demo Screenshot
Every model runs comfortably in real time even on the base M1; throughput scales with the Mac's GPU and the selected compute unit.
📥 Installation
- Download
YOLO-Master-CoreML-Runner-1.0.0.zipbelow and unzip it. - Double-click YOLO-Master CoreML Runner.app.
That's it. The app is signed and notarized by Apple. Camera access is requested on first use of Live Camera (processed entirely on-device, no internet access needed).
💻 Requirements
- macOS Sonoma or later is recommended
- Supports both Apple Silicon or Intel
- No dependencies to install; the Core ML backend and default model are bundled
🤝 Acknowledgements
Built as an extention tool of YOLO-Master.
We thank Ultralytics and Apple Core ML / coremltools for their great work. Licensed under AGPL-3.0.
🔖 Future Work
I'm currently building a runner for Windows 10/11 as a refinement of the Windows CPU runner (CLI). It will feature a GUI similar to the MacOS runner. However, I'm currently struggling with CUDA compatibility issues. I'll make an update when the Windows version is ready to ship.