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license: agpl-3.0
library_name: ultralytics
pipeline_tag: object-detection
tags:
- darts
- dartboard
- yolo11
- onnx
datasets:
- geforcefan/dartscribe
---
# dartscribe networks
The three networks of [dartscribe](https://github.com/geforcefan/dartscribe). Two calibrate: they find the bull and
the crossings of a dartboard in an image and tell where the 20 is. One finds the dart tips.
| file | network | input | output |
|---|---|---|---|
| `crossings.onnx` | YOLO11n detect | 1×3×960×960 | 1×9×18900 |
| `orientation.onnx` | YOLO11n classify | 1×3×512×512 | 1×20 |
| `darts.onnx` | YOLO11n detect | 1×3×1280×1280 | 1×5×33600 |
RGB, values divided by 255, NCHW, no NMS in the ONNX.
## Crossings
Input: the image letterboxed to 960×960.
Output: one column per candidate box.
| row | value |
|---|---|
| 0, 1 | center x, y |
| 2, 3 | width, height |
| 4 | bull |
| 5 | double outer |
| 6 | double inner |
| 7 | treble outer |
| 8 | treble inner |
The classes do not name the crossing, the board is symmetric.
## Orientation
Input: the board warped into a 512×512 square with the projection, board center in the middle, 1.6 double outer radii
to the edge.
Output: one score per class, class k means the 20 is k segments clockwise from the top.
## Darts
Input: the image letterboxed to 1280×1280.
Output: one column per candidate box.
| row | value |
|---|---|
| 0, 1 | center x, y |
| 2, 3 | width, height |
| 4 | tip |
## Letterbox
The image is scaled into the square with its aspect ratio kept, the rest is gray (114), the YOLO convention.
|