Datasets:
image imagewidth (px) 441 3.5k | file_name stringlengths 15 19 | date_start int32 800 1.68k | date_end int32 824 1.9k | date_span int32 0 1.07k | date_mid float32 812 1.68k |
|---|---|---|---|---|---|
0_1400_1430.jpg | 1,400 | 1,430 | 30 | 1,415 | |
10000_1200_1299.jpg | 1,200 | 1,299 | 99 | 1,249.5 | |
10001_1445_1455.jpg | 1,445 | 1,455 | 10 | 1,450 | |
10002_1445_1455.jpg | 1,445 | 1,455 | 10 | 1,450 | |
10003_1445_1455.jpg | 1,445 | 1,455 | 10 | 1,450 | |
10004_1445_1455.jpg | 1,445 | 1,455 | 10 | 1,450 | |
10005_1445_1455.jpg | 1,445 | 1,455 | 10 | 1,450 | |
10006_1445_1455.jpg | 1,445 | 1,455 | 10 | 1,450 | |
10007_1445_1455.jpg | 1,445 | 1,455 | 10 | 1,450 | |
10008_1445_1455.jpg | 1,445 | 1,455 | 10 | 1,450 | |
10009_1445_1455.jpg | 1,445 | 1,455 | 10 | 1,450 | |
1000_1433_1465.jpg | 1,433 | 1,465 | 32 | 1,449 | |
10010_1445_1455.jpg | 1,445 | 1,455 | 10 | 1,450 | |
10011_1450_1474.jpg | 1,450 | 1,474 | 24 | 1,462 | |
10012_1450_1474.jpg | 1,450 | 1,474 | 24 | 1,462 | |
10013_1450_1474.jpg | 1,450 | 1,474 | 24 | 1,462 | |
10014_1450_1474.jpg | 1,450 | 1,474 | 24 | 1,462 | |
10015_1450_1474.jpg | 1,450 | 1,474 | 24 | 1,462 | |
10016_1450_1474.jpg | 1,450 | 1,474 | 24 | 1,462 | |
10017_1450_1474.jpg | 1,450 | 1,474 | 24 | 1,462 | |
10018_1450_1474.jpg | 1,450 | 1,474 | 24 | 1,462 | |
10019_1450_1474.jpg | 1,450 | 1,474 | 24 | 1,462 | |
1001_1275_1299.jpg | 1,275 | 1,299 | 24 | 1,287 | |
10020_1450_1474.jpg | 1,450 | 1,474 | 24 | 1,462 | |
10021_1385_1415.jpg | 1,385 | 1,415 | 30 | 1,400 | |
10022_1385_1415.jpg | 1,385 | 1,415 | 30 | 1,400 | |
10023_1385_1415.jpg | 1,385 | 1,415 | 30 | 1,400 | |
10024_1385_1415.jpg | 1,385 | 1,415 | 30 | 1,400 | |
10025_1385_1415.jpg | 1,385 | 1,415 | 30 | 1,400 | |
10026_1385_1415.jpg | 1,385 | 1,415 | 30 | 1,400 | |
10027_1385_1415.jpg | 1,385 | 1,415 | 30 | 1,400 | |
10028_1385_1415.jpg | 1,385 | 1,415 | 30 | 1,400 | |
10029_1385_1415.jpg | 1,385 | 1,415 | 30 | 1,400 | |
1002_1275_1299.jpg | 1,275 | 1,299 | 24 | 1,287 | |
10030_1385_1415.jpg | 1,385 | 1,415 | 30 | 1,400 | |
10031_1450_1474.jpg | 1,450 | 1,474 | 24 | 1,462 | |
10032_1450_1474.jpg | 1,450 | 1,474 | 24 | 1,462 | |
10033_1450_1474.jpg | 1,450 | 1,474 | 24 | 1,462 | |
10034_1450_1474.jpg | 1,450 | 1,474 | 24 | 1,462 | |
10035_1450_1474.jpg | 1,450 | 1,474 | 24 | 1,462 | |
10036_1450_1474.jpg | 1,450 | 1,474 | 24 | 1,462 | |
10037_1450_1474.jpg | 1,450 | 1,474 | 24 | 1,462 | |
10038_1450_1474.jpg | 1,450 | 1,474 | 24 | 1,462 | |
10039_1450_1474.jpg | 1,450 | 1,474 | 24 | 1,462 | |
1003_1275_1299.jpg | 1,275 | 1,299 | 24 | 1,287 | |
10040_1300_1399.jpg | 1,300 | 1,399 | 99 | 1,349.5 | |
10041_1300_1399.jpg | 1,300 | 1,399 | 99 | 1,349.5 | |
10042_1300_1399.jpg | 1,300 | 1,399 | 99 | 1,349.5 | |
10043_1300_1399.jpg | 1,300 | 1,399 | 99 | 1,349.5 | |
10044_1300_1399.jpg | 1,300 | 1,399 | 99 | 1,349.5 | |
10045_1300_1399.jpg | 1,300 | 1,399 | 99 | 1,349.5 | |
10046_1300_1399.jpg | 1,300 | 1,399 | 99 | 1,349.5 | |
10047_1425_1449.jpg | 1,425 | 1,449 | 24 | 1,437 | |
10048_1425_1449.jpg | 1,425 | 1,449 | 24 | 1,437 | |
10049_1425_1449.jpg | 1,425 | 1,449 | 24 | 1,437 | |
1004_1275_1299.jpg | 1,275 | 1,299 | 24 | 1,287 | |
10050_1425_1449.jpg | 1,425 | 1,449 | 24 | 1,437 | |
10051_1425_1449.jpg | 1,425 | 1,449 | 24 | 1,437 | |
10052_1425_1449.jpg | 1,425 | 1,449 | 24 | 1,437 | |
10053_1425_1449.jpg | 1,425 | 1,449 | 24 | 1,437 | |
10054_1425_1449.jpg | 1,425 | 1,449 | 24 | 1,437 | |
10055_1425_1425.jpg | 1,425 | 1,425 | 0 | 1,425 | |
10056_1425_1425.jpg | 1,425 | 1,425 | 0 | 1,425 | |
10057_1425_1425.jpg | 1,425 | 1,425 | 0 | 1,425 | |
10058_1425_1425.jpg | 1,425 | 1,425 | 0 | 1,425 | |
10059_1425_1425.jpg | 1,425 | 1,425 | 0 | 1,425 | |
1005_1275_1299.jpg | 1,275 | 1,299 | 24 | 1,287 | |
10060_1425_1425.jpg | 1,425 | 1,425 | 0 | 1,425 | |
10061_1425_1425.jpg | 1,425 | 1,425 | 0 | 1,425 | |
10062_1425_1425.jpg | 1,425 | 1,425 | 0 | 1,425 | |
10063_1425_1425.jpg | 1,425 | 1,425 | 0 | 1,425 | |
10064_1425_1425.jpg | 1,425 | 1,425 | 0 | 1,425 | |
10065_1450_1499.jpg | 1,450 | 1,499 | 49 | 1,474.5 | |
10066_1450_1499.jpg | 1,450 | 1,499 | 49 | 1,474.5 | |
10067_1450_1499.jpg | 1,450 | 1,499 | 49 | 1,474.5 | |
10068_1450_1499.jpg | 1,450 | 1,499 | 49 | 1,474.5 | |
10069_1450_1499.jpg | 1,450 | 1,499 | 49 | 1,474.5 | |
1006_1275_1299.jpg | 1,275 | 1,299 | 24 | 1,287 | |
10070_1450_1499.jpg | 1,450 | 1,499 | 49 | 1,474.5 | |
10071_1450_1499.jpg | 1,450 | 1,499 | 49 | 1,474.5 | |
10072_1450_1499.jpg | 1,450 | 1,499 | 49 | 1,474.5 | |
10073_1450_1499.jpg | 1,450 | 1,499 | 49 | 1,474.5 | |
10074_1450_1499.jpg | 1,450 | 1,499 | 49 | 1,474.5 | |
10075_1000_1099.jpg | 1,000 | 1,099 | 99 | 1,049.5 | |
10076_1000_1099.jpg | 1,000 | 1,099 | 99 | 1,049.5 | |
10077_1000_1099.jpg | 1,000 | 1,099 | 99 | 1,049.5 | |
10078_1000_1099.jpg | 1,000 | 1,099 | 99 | 1,049.5 | |
10079_1000_1099.jpg | 1,000 | 1,099 | 99 | 1,049.5 | |
1007_1275_1299.jpg | 1,275 | 1,299 | 24 | 1,287 | |
10080_1000_1099.jpg | 1,000 | 1,099 | 99 | 1,049.5 | |
10081_1000_1099.jpg | 1,000 | 1,099 | 99 | 1,049.5 | |
10082_1000_1099.jpg | 1,000 | 1,099 | 99 | 1,049.5 | |
10083_1000_1099.jpg | 1,000 | 1,099 | 99 | 1,049.5 | |
10084_1000_1099.jpg | 1,000 | 1,099 | 99 | 1,049.5 | |
10085_1438_1468.jpg | 1,438 | 1,468 | 30 | 1,453 | |
10086_1438_1468.jpg | 1,438 | 1,468 | 30 | 1,453 | |
10087_1438_1468.jpg | 1,438 | 1,468 | 30 | 1,453 | |
10088_1438_1468.jpg | 1,438 | 1,468 | 30 | 1,453 | |
10089_1438_1468.jpg | 1,438 | 1,468 | 30 | 1,453 | |
1008_1275_1299.jpg | 1,275 | 1,299 | 24 | 1,287 |
ICDAR 2021 Historical Document Classification — Task 2 (Dating)
13,810 manuscript page images labelled with the period in which they were produced. Images come from e-codices, the virtual manuscript library of Switzerland.
| Split | Images | Date range | Median span | Dated to a single year |
|---|---|---|---|---|
| train | 11,294 | 800–1899 | 45 years | 1,409 |
| test | 2,516 | 800–1921 | 49 years | 264 |
The label is an interval, not a year
Palaeographers date a manuscript to a range, and the width of that range encodes their confidence. This dataset preserves that:
date_start,date_end— the range as publisheddate_span—end - start. 0 means dated to a single year.date_mid— midpoint, a convenience point-target
Precision varies enormously: some pages are pinned to one year (1505–1505), others sit inside a
two-century window (1250–1449). Any sensible model or metric has to handle that heterogeneity
— a plain regression on date_mid throws away the confidence signal, and a plain accuracy metric
treats a two-century guess as equal to a one-year one. Consider weighting by date_span, or
scoring interval overlap rather than point error.
Gotchas in the source deposit
Two things will silently corrupt a naive build. Both are handled here.
The two ground-truth files use different delimiters.
dating/training/gt.csv img/0_1400_1430.jpg,1400,1430 <- COMMA
dating/test/gt.csv img/667cd1e1....jpg;1200;1299 <- SEMICOLON
Parse both the same way and the test split collapses into a single junk column — with a plausible-looking row count. Verified: with the right delimiters, all 2,516 test images join to a label, and all 11,294 train images do too.
The test labels are NOT missing — despite appearances. Zenodo publishes a separate
task2-dating-test-meta.csv alongside the archive that maps test images to their source manuscript
and contains no dates at all. It is a provenance file, not the ground truth. The real test
labels live inside dating.tar.gz at dating/test/gt.csv. Anyone glancing at the Zenodo file list
would reasonably conclude this is a competition set with a withheld test split. It isn't.
Also: training filenames encode the range (5639_1467_1467.jpg), but test filenames are opaque
hashes — you must use the CSV.
Load
from datasets import load_dataset
# 28 GB of page images - stream unless you want the whole deposit on disk
ds = load_dataset("biglam/icdar2021-historical-document-dating",
split="train", streaming=True)
# keep only tightly-dated pages; date_span == 0 means dated to a single year
tight = ds.filter(lambda r: r["date_span"] <= 25)
Source & credit
Mathias Seuret, Anguelos Nicolau, Dalia Rodríguez-Salas et al. ICDAR 2021 Historical Document Classification Dataset for Task 2 — Dating. Zenodo, 2021-05-28. https://zenodo.org/records/4836687 — CC-BY-4.0.
Images courtesy of e-codices, Virtual Manuscript Library of Switzerland. This repository converts the 28 GB deposit to Parquet. Please cite the original authors and the ICDAR 2021 competition.
@dataset{seuret_2021_icdar_dating,
author = {Seuret, Mathias and Nicolau, Anguelos and Rodr{\'i}guez-Salas, Dalia and
Weichselbaumer, Nikolaus and Stutzmann, Dominique and Mayr, Martin and
Maier, Andreas and Christlein, Vincent},
title = {{ICDAR 2021 Historical Document Classification Dataset for Task 2 --- Dating}},
year = {2021},
publisher = {Zenodo},
doi = {10.5281/zenodo.4836687}
}
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