Dataset Open Access

Extracted Illustrations of the Berlin State Library's Digitized Collections (part 1 of 4)

Zellhöfer, David

The dataset consists of various illustrations extracted from 26,233 historical books and other media offered in the Berlin State Library's Digitized Collections. The media objects are older than 1920.

Version 1.0 contains of 594,890 extracted illustrations in total.

The extraction of illustrations is driven by the coordinates given by the ABBYY FineReader OCR engine (in ALTO XML) . The extracted illustrations have not been resized but compressed and saved in JPEG format.

Pre-trained models in order to separate color scales, hand-written signatures, library stamps or the like from interesting content are available under: https://github.com/elektrobohemian/imi-unicorns.

The extracts for each media object are stored in separated sub-folders and tar files named after the PPN (a unique ID used in the library) to facilitate further processing. Additional metadata can be obtained with help of the PPN as described here: https://github.com/elektrobohemian/StabiHacks/blob/master/ppn-howto.md .

The dataset is published as a set of ZIP files, each fitting on a Blu Ray disc. After decompression, the contents will consume ca. 166 GB.

Change Log for Version

  1. original dataset
  2. added color histograms (RGB, separated by channel) in JSON and Python pickle format as extracted by the Pillow package (see https://github.com/elektrobohemian/StabiHacks/tree/master/image-tools)

This is part 1 of 4. The following datasets contain the other ZIP files (8 files in total):

 

Files (50.0 GB)
Name Size
_samples.pdf
md5:f891104c3c5ef49a4a0d54e6467ee716
8.3 MB Download
color_histograms.zip
md5:906115d30daa56d20ea83a0da2528269
1.6 GB Download
extracted_images.zip.001
md5:d8bbbbd4211da19e3a1db5b0e0ecf3a9
24.2 GB Download
extracted_images.zip.002
md5:2532b2978f32221a60eb235637dc47d6
24.2 GB Download
OCR-PPN-Liste.txt
md5:052a22da8c321e790bfc147a65c4981a
2.0 MB Download
ppn_log.log
md5:dacf09da0c95989e7b7f796c5e8ea909
1.3 MB Download
sbbget.py
md5:996e9f0349b7c6e88a569496b7d59f6a
17.6 kB Download
sbbget_error.log
md5:bccc975b04caa971ee74c8240c3bbaa6
49.6 kB Download
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