| # PaddleOCR v4 (PP-OCRv4) | |
| ## 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 | |
| --- | |
| ## How to use | |
| > ⚠️ **Hardware requirement:** the model currently runs **only on Qualcomm NPUs** (e.g., Snapdragon-powered AIPC). | |
| > Apple NPU support is planned next. | |
| ### 1) Install Nexa-SDK | |
| - Download and follow the steps under "Deploy Section" Nexa's model page: [Download Windows arm64 SDK](https://sdk.nexa.ai/model/PaddleOCR%20v4) | |
| - (Other platforms coming soon) | |
| ### 2) Get an access token | |
| Create a token in the Model Hub, then log in: | |
| ```bash | |
| nexa config set license '<access_token>' | |
| ``` | |
| ### 3) Run the model | |
| Running: | |
| ```bash | |
| nexa infer NexaAI/paddleocr-npu | |
| ``` | |
| --- | |
| ## License | |
| - Licensed under [Apache-2.0](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.7/LICENSE) | |
| ## References | |
| - GitHub repo: [https://github.com/PaddlePaddle/PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR) | |
| - Model zoo & documentation: [Models list](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.7/doc/doc_en/models_list_en.md) |