---
dataset_info:
  features:
  - name: manuscript
    dtype: string
  - name: archive
    dtype: string
  - name: page
    dtype: string
  - name: segmentation_width
    dtype: int32
  - name: segmentation_height
    dtype: int32
  - name: segmentation_map
    dtype: image
  - name: source_image_credit
    dtype: string
  splits:
  - name: train
    num_bytes: 1494122305
    num_examples: 49994
  download_size: 1066351649
  dataset_size: 1494122305
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
pretty_name: Randall Predicted Segmentations
license_name: predicted-annotations-license-unspecified-source-images-omitted
tags:
- image
- medieval-manuscripts
- semantic-segmentation
- model-predictions
license: other
task_categories:
- image-segmentation
---
# Randall Predicted Segmentations

This dataset contains 49,994 predicted semantic segmentation maps
for 148 medieval manuscripts indexed in Lilian Randall's Images 
in the Margins of Gothic Manuscripts (1966). Each predicted segmentation map
is linked to manuscript, archive, and folio/page metadata.

These segmentations were generated by a model based on a multi-class 
adaptation of the MapSAM model proposed in Xia et al. (2025). 
Further details of the model training can be found in ADD IN.

## Fields

- `manuscript`: normalized public manuscript identifier.
- `archive`: holding institution or image provider.
- `page`: folio or page label from the manuscript inventory.
- `segmentation_width` and `segmentation_height`: prediction dimensions.
- `segmentation_map`: embedded RGB PNG prediction using the colors documented
  in `id2label.json`.
- `source_image_credit`: page-specific credit for the source image from which
  the prediction was derived.

The dataset does not contain source manuscript images.

## Labels

| ID | Label |
|---:|---|
| 0 | unlabeled/background |
| 1 | line filler |
| 2 | marginal images |
| 3 | painted initials |
| 4 | miniatures |
| 5 | borders |
| 6 | pen flourishing |
| 7 | pen flourished texts |

## Attribution and rights

`source_image_credit` records provenance for an omitted source image; it is not
a license and does not mean attribution alone authorizes image reuse. The
represented institutions have mixed image-reuse terms, including open,
conditional, permission-based, and unresolved records. Generic source
identifiers remain explicitly generic rather than being presented as verified
shelfmarks. Users should review current source-record terms and determine 
whether their intended use is permitted.

The predictions are model outputs rather than human-reviewed ground truth.

## Citation
ADD IN