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Awesome GitHub RepositoriesMulti-Crop Processing
Dividing large documents into smaller overlapping sections to maintain recognition detail.
Distinct from Optical Character Recognition: Specific tiling strategy for OCR accuracy, distinct from general OCR parsing.
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Awesome Multi-Crop Processing GitHub Repositories
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- ucas-haoranwei/got-ocr2.0
Ucas-HaoranWei/GOT-OCR2.0
8,141Auf GitHub ansehenGOT-OCR2.0 is an end-to-end optical character recognition system and document text extractor. It utilizes a unified transformer architecture to recognize and extract plain and formatted text from diverse images and documents. The system features a multi-crop processing method that divides high-resolution or dense documents into smaller sections to maintain recognition detail. It also includes a renderer that transforms recognized text into HTML to preserve the original structure and layout of the document. The project provides a framework for fine-tuning pre-trained models on custom datasets
Captures high-detail text across large or dense documents by dividing complex images into smaller sections.
Python
