Textrecognition Model for Essoins (England) in Latin
Part of the developments within the Flow-Project. Developed by Jonas Widmer, Christopher Kuhlmann, and Melvin Wilde.
Base model: magistermilitum/tridis_HTR v1
Train Lines: 15356
Eval Lines: 394
Test Lines: 2288
Epochs: 14.1667 / 20
Eval CER: 0.0544
Test CER: 0.0622
Testresults with CERberus
CERberus on GitHub with explanations
CERberus gets 2288 lines of the test set and evaluates them.
| Metric | Value |
|---|---|
| Character Error Rate | 6.22 |
| Number of Correct Characters | 186998 |
| Number of Substitutions | 5425 |
| Number of Insertions | 2933 |
| Number of Deletions | 3849 |
| Total Character Count | 196272 |
| Original Lines Count | 2288 |
| Discarded Lines Count | 0 |
| Block | Count | Correct | Incorrect | Correct Ratio | Incorrect Ratio |
|---|---|---|---|---|---|
| Digits | 0 | 0 | 0 | nan | nan |
| Lowercase Latin alphabet | 154731 | 147241 | 7490 | 95.16 | 4.84 |
| MUFI Glyphs | 0 | 0 | 0 | nan | nan |
| Punctuation | 9 | 4 | 5 | 44.44 | 55.56 |
| Uppercase Latin alphabet | 6883 | 6450 | 433 | 93.71 | 6.29 |
The handwritten texts in Latin (with some Middle-English and Anglo-Norman wording) that were used for training are from the 13th and 14th centuries. They come from England and were written in 'Court Hand', also known as 'Anglicana'. They come from the 'Court of Common Pleas', the second highest court of the time, and deal primarily with civil disputes, such as inheritances or dowries, and from the Justices, which also dealt with civil pleas, but covered crown pleas as well.
The model has not been extensively tested.
Errors often occur in the Punctuation, which itself has an error rate of 44.44% which mostly consits of missed ‧ dots.
Potential biases are still to be identified.
Input: one line, not a page
This is a VisionEncoderDecoderModel for line images: it reads one cropped
text line per call, which is also what the CER above was measured on. A whole
page is not an input it has — pass one and it returns a fragment of it.
Segment the page first (kraken, eScriptorium, Transkribus, or any line
segmenter) and pass the crops one at a time. In the DH Bern serving stack the
model is registered level: line and the gateway segments with kraken before
calling it; the reasoning and the measurements behind that rule are in
thodel/serving-atr-inference#165.