project_name large_stringclasses 1
value | filename large_stringclasses 4
values | region_id large_stringclasses 13
values | line_id large_stringlengths 4 23 | line_augmentation large_stringlengths 8 51 | image dict | text large_stringlengths 0 61 | line_reading_order int64 0 39 | line_coords listlengths 4 23 | line_baseline listlengths 2 21 | region_reading_order int64 0 8 | region_type large_stringclasses 2
values | region_coords listlengths 4 4 | inference_20260611_163016_468653_model_dh-unibe_trocr-towerbooks stringlengths 0 61 |
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End of preview. Expand in Data Studio
Dataset Card for towerbooks-line-test-test-with-inference
This dataset is derived from dh-unibe/towerbooks-line-test-test-with-inference and has been enriched with inference results.
Dataset Summary
This dataset contains 729 samples across 1 split(s).
Projects Included
B_IX_490_duplicated
Evaluation Results
This repository includes evaluation artifacts for the latest inference output.
- Timestamp: 2026-06-11T16:36:48
- CER: 0.16961176318844318
- Evaluated rows: 237
- Evaluated split: train
- Inference column:
inference_20260611_163016_468653_model_dh-unibe_trocr-towerbooks
Evaluation Files
evaluation/2026-06-11T16_36_48/
├── gt.txt
├── hypothesis.txt
└── evaluation_report.json
Dataset Structure
Data Splits
- train: 729 samples
Dataset Size
- Approximate total size: 55.61 MB
- Total samples: 729
Features
- project_name:
Value('large_string') - filename:
Value('large_string') - region_id:
Value('large_string') - line_id:
Value('large_string') - line_augmentation:
Value('large_string') - image:
{'bytes': Value('binary'), 'path': Value('null')} - text:
Value('large_string') - line_reading_order:
Value('int64') - line_coords:
List(List(Value('int64'))) - line_baseline:
List(List(Value('int64'))) - region_reading_order:
Value('int64') - region_type:
Value('large_string') - region_coords:
List(List(Value('int64'))) - inference_20260611_163016_468653_model_dh-unibe_trocr-towerbooks:
Value('string')
Data Organization
Data is organized as parquet shards by split and project:
data/
├── <split>/
│ └── <project_name>/
│ └── <timestamp>-<shard>.parquet
The HuggingFace Hub automatically merges all parquet files when loading the dataset.
Usage
from datasets import load_dataset
# Load entire dataset
dataset = load_dataset("dh-unibe/towerbooks-line-test-test-with-inference")
# Load specific split
dataset_split = load_dataset("dh-unibe/towerbooks-line-test-test-with-inference", split="train")
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