For this project, we used Surya instead of Tesseract (while keeping Tesseract as a fallback if Surya OCR is unavailable). We observed several improvements:
- Uses a transformer-based (deep learning) approach rather than a traditional computer vision pipeline
- Supports 90+ languages with automatic detection
- Performs significantly better on mixed-language where traditional methods often struggle with complex layouts (rotated, or noisy scans)
- Natively returns word-level bounding boxes
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