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---
license: mit
tags:
- object-detection
- rf-detr
- coreml
- macos
- gui-agents
library_name: coreml
pipeline_tag: object-detection
---
# focused-window-detector (RF-DETR nano, CoreML)
Single-pass RF-DETR (nano) that detects macOS windows and the cursor from a
live screen capture. Exported to CoreML for on-device inference on Apple
Silicon.
**Classes:** `focused_window`, `unfocused_window`, `cursor`.
Strong at separating focused vs unfocused windows in real time.
## Files
```
rf-detr-nano-checkpoint_best_total-2-fp32.mlpackage/ # CoreML model
```
## Input / output
- **Input:** image `384 x 384` (RGB, scale 1/255).
- **Outputs:** `var_2267` = boxes `[1, 300, 4]` (cxcywh, normalised),
`var_2270` = logits `[1, 300, 4]`.
## Usage
Runner (Swift + ScreenCaptureKit live overlay):
https://github.com/cianmcnally/focused_window_detector
```bash
hf download Cianmcnally/focused-window-detector --local-dir ./model
```
## Known limitations
- Cursor recognition covers only a narrow range of cursor shapes/sizes.
- Cursor bounding boxes are loose (not pixel-tight).
- The Dock is sometimes misdetected as `unfocused_window` on hover.
These are training-data gaps; see the runner repo for the improvement plan.