Codesota · Computer Vision · Optical Character Recognition · IMPACT-PSNCTasks/Computer Vision/Optical Character Recognition
Optical Character Recognition · benchmark dataset · 2012 · PL

IMPACT Polish Digital Libraries Ground Truth.

478 pages of ground truth from four Polish digital libraries at 99.95% accuracy. Includes annotations at region, line, word, and glyph levels. Gothic and antiqua fonts.

Paper ↗Submit a result ↵
§ 01 · Leaderboard

Best published scores.

No results indexed yet — be the first to submit a score.

Primary
cer · lower is better
No benchmark results indexed yet
§ 06 · Contribute

Have a score that beats
this table?

Submit a checkpoint and a reproduction script. We will run it, publish the score, and — if it takes the top — annotate the step on the progress chart with your name.

Submit a result ↵Read submission guide
What a submission needs
  • 01A public checkpoint or API endpoint
  • 02A reproduction script with frozen commit + seed
  • 03Declared evaluation environment (Python, deps)
  • 04One row per metric declared by this dataset
  • 05A contact so we can follow up on discrepancies