Shulk97/daniel
This repository contain the implementation of DANIEL. (A fast Document Attention Network for Information Extraction and Labeling of handwritten documents)
This project helps specialists extract information from scanned handwritten documents, like historical archives or forms. It takes images of handwritten pages as input and outputs the text, along with identified key information (like names or dates). This is ideal for researchers, archivists, or data entry professionals dealing with large volumes of challenging handwritten material.
Use this if you need to automatically recognize handwritten text and label specific entities within those documents, especially if you have an existing dataset to train or fine-tune the system.
Not ideal if you're looking for a simple, off-the-shelf solution for printed text, or if you lack the technical expertise and hardware (like high-VRAM GPUs) required for setup and training.
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Python
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Last pushed
Jan 12, 2026
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