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"""
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"]
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