| """ | |
| PosterSentry — Multimodal Scientific Poster Classifier | |
| ======================================================= | |
| Classifies PDFs as scientific posters vs. non-posters using both | |
| text embeddings (model2vec) and visual features (image analysis). | |
| Trained on 30K+ real scientific posters from Zenodo and Figshare | |
| via the posters.science initiative at FAIR Data Innovations Hub. | |
| Usage: | |
| from poster_sentry import PosterSentry | |
| sentry = PosterSentry() | |
| sentry.initialize() | |
| result = sentry.classify("document.pdf") | |
| # {'is_poster': True, 'confidence': 0.97, 'text_score': 0.95, 'visual_score': 0.99} | |
| """ | |
| from .classifier import PosterSentry | |
| from .features import VisualFeatureExtractor, PDFStructuralExtractor | |
| __version__ = "0.1.0" | |
| __all__ = ["PosterSentry", "VisualFeatureExtractor", "PDFStructuralExtractor"] | |