klanderfri / klanderfri/CardReaderLibrary
Create better Tesseract trained data
- Dominant language
- C++
- Stars
- 10
- Forks
- 3
- PR merge metrics
- No merged PRs in 30d
Description
The *eng.traineddata* isn't optimal for identifying Magic titles.
* The Æ for example isn't correctly identified.
* The 'F' in *Spires of Orazca* (transformed from *Thaumatic Compass*) is identified as 'r'.
* 'I' and 'J' in the new font is mistaken for 'l'.
We need to
- [ ] Create a better traineddata-file.
- [ ] Name it *mtg.traineddata* and replace *eng.traineddata* with it.
https://sv.wikipedia.org/wiki/%C3%86
Contributor guide
Research direction
Start by reviewing the existing eng.traineddata usage and the OCR workflow in this repository. Determine how Magic card title samples are collected and trained, then verify that a new mtg.traineddata replaces eng.traineddata and correctly recognizes Æ, the transformed F, and the new-font I and J.
Written by the indexing model from the issue text.
Assessment
- Domain
- computer-vision
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100