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Short summary

Build a specialized AI text enhancer using RCAN models to reconstruct blurry text, remove JPEG compression artifacts, and restore faded receipts—outperforming generic enhancers that treat text as texture. This guide covers the full stack: why general models fail, React frontend + FastAPI backend, tile-based inference for large images, and production-ready code. Deploy a watermark-free in-browser tool supporting receipts, screenshots, handwriting, and documents.

• •Generic image enhancers fail on text by applying smoothing meant for natural images; this guide builds a specialized text-clarity model trained on typography
• •Full-stack implementation: React upload UI, FastAPI backend with RCAN model caching, tile-based 256px inference, mode-specific post-processing (contrast, artifact removal)
• •Production-ready tool for receipts, screenshots, documents, handwriting—deployed in-browser with no watermark, handles up to 5MB images

Generated with AI, which can make mistakes.