From Pixels to Points: Inferring Archery Scores with Computer Vision @PyConAU
From Pixels to Points: Inferring Archery Scores with Computer Vision  @PyConAU
Uploaded August 2026 | Updated September 2026, 17 minutes ago
(Jacob Seiler) Improving in archery often goes beyond simply increasing your score; it also means building consistency, tightening groupings, and recognising patterns such as shots drifting off-centre.  However, tracking the final position of arrows after each shot is a slow, imprecise, and awkward process.

In this talk, I show how I trained and validated a computer vision pipeline using oriented object detection to infer arrow locations and scores directly from a target image. By deploying this system on a Raspberry Pi, the process becomes simple enough to use during regular practice, while also creating a record of shot placement that can be analysed over time. This makes it possible to look beyond individual scores and start tracking broader patterns in accuracy and consistency.

https://2026.pycon.org.au/schedule/YGUJEG/

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Thu Aug 27 12:40:00 2026 AEST (UTC+10) at Ballroom 3
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From Pixels to Points: Inferring Archery Scores with Computer Vision

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