---
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.