Full Page Handwriting Recognition on CUDA enabled Docker

-Handwritten text recognition is essential for document digitization but often struggles with multiline content. This paper presents an integrated approach using TrOCR, a pre-trained Transformer model, combined with PaddleOCR for enhanced text detection. The integration, optimized with GPU acceleration and multi-threading within a CUDA-enabled Docker environment, addresses the challenges of full-page handwriting recognition. A user-friendly Flask API with a Gradio demo was developed for deployment. Experimental results demonstrate that the system significantly improves the accuracy of multiline text recognition, outperforming existing models. This approach offers a scalable, efficient solution for accurate handwriting recognition in complex document layouts, advancing the field of document digitization.