Macro segmentation Computer Vision Project
Auction sale catalogues macro segmentation
Document layout analysis dataset for segmenting the macro structure of sale catalogues.
We follow SegmOnto controlled vocabulary (https://segmonto.github.io/) and the COLaF (Inria, ALMAnaCH and Multispeech) schema.
Dataset
Two random folio have been selected from 8 auction sale catalogues collections, kept in the national library of France (Bibliothèque nationale de France, BnF), and the national institute for art history (Institut national d'histoire de l'art, INHA).
- Bienaimé-Feuardent (BnF)
- Bourgey (BnF)
- Dubois (BnF)
- Naville (BnF)
- Rollin (BnF)
- XVIIIe (BnF)
- Desvouges (INHA)
- Lair-Dubreuil (INHA)
Trained Model API
This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.
YOLOv8
This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
macro-segmentation_dataset,
title = { Macro segmentation Dataset },
type = { Open Source Dataset },
author = { DataCatalogue },
howpublished = { \url{ https://universe.roboflow.com/datacatalogue/macro-segmentation } },
url = { https://universe.roboflow.com/datacatalogue/macro-segmentation },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { mar },
note = { visited on 2024-04-28 },
}
Connect Your Model With Program Logic
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Source
Last Updated
2 months ago
Project Type
Object Detection
Subject
document-macro-structure
Views: 76
Downloads: 4
