paddleocr-npu-mobile

PaddleOCR v4 (PP-OCRv4) for Android

Quickstart

See Documentation

Model Description

PP-OCRv4 is the fourth-generation end-to-end optical character recognition system from the PaddlePaddle team.
It combines a lightweight text detection → angle classification → text recognition pipeline with improved training techniques and data augmentation, delivering higher accuracy and robustness while staying efficient for real-time use.

PP-OCRv4 supports multilingual OCR (Latin and non-Latin scripts), irregular layouts (rotated/curved text), and challenging inputs such as noisy or low-resolution images often found in mobile and document-scan scenarios.

Features

• End-to-end OCR: text detection, optional angle classification, and text recognition in one pipeline.
• Multilingual support: pretrained models for English, Chinese, and dozens of other languages; easy finetuning for domain text.
• Robust in real-world conditions: handles rotation, perspective distortion, blur, low light, and complex backgrounds.
• Lightweight & fast: practical for both mobile apps and large-scale server deployments.
• Flexible I/O: works with photos, scans, screenshots, receipts, invoices, ID cards, dashboards, and UI text.
• Extensible: swap components (detector/recognizer), add language packs, or finetune on domain datasets.

Use Cases

• Document digitization (invoices, receipts, forms, contracts)
• RPA and back-office automation (screen/OCR flows)
• Mobile scanning apps and camera-based translation/read-aloud
• Industrial and retail analytics (labels, price tags, shelf tags)
• Accessibility (screen-readers and read-aloud applications)

Inputs and Outputs

Input: Image (photo, scan, or screenshot).
Output: A list of detected text regions, each with:

• bounding box (rectangular or polygonal)
• recognized text string
• optional confidence score and orientation

License

This model is released under the Creative Commons Attribution–NonCommercial 4.0 (CC BY-NC 4.0) license.
Non-commercial use, modification, and redistribution are permitted with attribution.
For commercial licensing, please contact [email protected].

References

• GitHub repo: https://github.com/PaddlePaddle/PaddleOCR
• Model zoo & documentation: Models list