Coin Analysis is a computer-vision and machine-learning tool for recognising, identifying and cataloguing coins from images.

Problem → System → Outcome

Problem. Few modern computer vision tools exist for identifying collectible coins.
System. This app uses machine learning and CV to recognise years and mint marks.
Outcome. Collectors could identify coins from imperfect photos without needing specialist knowledge or manual cross-referencing.

Rationale

A couple of friends in the US were manually identifying 1¢ coins under microscopes. This tool streamlines that: a desktop application that recognises years and mint marks on US cents using ML + CV.

Note: Data availability remains poor, so model accuracy is limited. It's a personal prototype, a fossil of fast coding and I'm okay with that.

What it does

A PySide6 desktop application over OpenCV, scikit-learn and Tesseract that reads the year and mint mark off US cent photographs: a machine-learning classifier and an OCR reader each read the coin independently and a confidence-scored hybrid decides between them, cross-checked against historically valid mint-and-year combinations. Single images or whole folders in batch, partial coins accepted, results exported to CSV or JSON, all local. The full rundown lives on the product site: ernster.dev/coin-analysis.