BSICLE
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Source du modèle
- Type
- Other
- Taille du fichier
- 6,08–18,0 MB
- Modèle de base
- apple/mobilevitv2-1.0-imagenet1k-256
- Version
- vRevision e00397b
- Mis à jour
- 28 sept. 2026
- Téléchargements
- 0
- Source
- Hugging Face
Extrait de la source
Open in Spaces GitHub Pages
Sources
1 source
Sources
1 sourceVérifié 28 sept.
Artefacts du modèle
4 artefacts
Artefacts du modèle
4 artefactsmobilenetv3_large/onnx/model.onnx
onnx · 16,3 MB · SHA-256 2407e4aa74ea…36a6 · Hugging Face
Téléchargermobilenetv3_small/onnx/model.onnx
onnx · 6,08 MB · SHA-256 69e23671aff2…5374 · Hugging Face
TéléchargerExtraits de sources
2 extraits
Extraits de sources
2 extraits--- library_name: onnxruntime pipeline_tag: image-classification tags: - onnx - image-classification - medieval-manuscripts - illumination-detection - mobilenet - mobilevit - glam - iiif - cultural-heritage - digital-humanities - medieval-folio - medieval - medieval-illuminations - MobileNet - MobileVit license: apache-2.0 datasets: - ENC-PSL/BSICLE-medieval-illumination-folio-bin-class-dataset base_model: - timm/mobilenetv3_small_100.lamb_in1k - timm/mobilenetv3_large_100.ra_in1k - timm/mobilenetv2_100.ra_in1k - apple/mobilevitv2-1.0-imagenet1k-256 --- # BSICLE — Binary System for Illuminated Folio Classification with Lightweight Engines [](https://huggingface.co/spaces/ENC-PSL/Medieval-Illumination-Detector) [](https://odil-ai.github.io/medieval-illumination-detector/) BSICLE (pronounced bé-si-cle ; /be.zikl/) is a family of lightweight binary models for classify **illuminated folios in medieval manuscripts**. Theses models are developed at the [École nationale des chartes – PSL](https://www.chartes.psl.eu/) in context of [O.D.I.L. project](https://projet.biblissima.fr/fr/appels-projets/projets-retenus/odil-objet-detection-illuminations). These models classify manuscript pages as: - **illuminated** (miniatures, historiated initials, decorated pages etc.) - **non-illuminated** (plain text folio, printer marks, tables, cover, blank folios etc.) # Use cases Models are optimized to run **locally (CPU) or in the browser** using **edge-compatibility architecture** (MobileNet, MobileViT) and **ONNX inference** for exemple to build **IIIF filter pipelines** or to build **specialized corpora**. Try the demo web application on [HF Spaces](https://huggingface.co/spaces/ENC-PSL/Medieval-Illumination-Detector) or on [GH Pages](https://odil-ai.github.io/medieval-illumination-detector/) # Models & Results The finetuned models available in this repository are based on following architecture: - [MobileNetV2](https://huggingface.co/timm/mobilenetv2_100.ra_in1k) - [MobileNetV3](https://huggingface.co/timm/mobilenetv3_small_100.lamb_in1k) (small and large version) - [MobileViT v2](https://huggingface.co/apple/mobilevitv2-1.0-imagenet1k-256) | Architecture | Validation Ac...
Source context: 0 downloads · 1 likes · Pipeline image-classification · Library onnxruntime · Repo ENC-PSL/BSICLE
