PP-OCRv5_mobile_rec

About

What PP-OCRv5_mobile_rec is

PP-OCRv5mobilerec Introduction PP-OCRv5mobilerec is one of the PP-OCRv5rec that are the latest generation text line recognition models developed by PaddleOCR team. It aims to efficiently and accurately support the recognition of four major languages—Simplified Chinese, Traditional Chinese, English, and Japanese—as well as complex text scenarios such as handwriting, vertical text, pinyin, and rare characters using a single model. The key accuracy metrics are as follow: Note: If any character (including punctuation) in a line is incorrect, the entire line is marked as wrong. This ensures higher accuracy in practical applications. Quick Start Installation 1. PaddlePaddle Please refer to the following commands to install PaddlePaddle using pip: For details about PaddlePaddle installation, please refer to the PaddlePaddle official website. 2. PaddleOCR Install the latest version of the PaddleOCR inference package from PyPI: Model Usage You can quickly experience the functionality with a single command: You can also integrate the model inference of the text recognition module into your project. Before running the following code, please download the sample image to your local machine. After running, the obtained result is as follows: The visualized image is as follows: For details about usage command and descriptions of parameters, please refer to the Document. Pipeline Usage The ability of a single model is limited. But the pipeline consists of several models can provide more capacity to resolve difficult problems in real-world scenarios. PP-OCRv5 The general OCR pipeline is used to solve text recognition tasks by extracting text information from images and outputting it in string format. And there are 5 modules in the pipeline: Document Image Orientation Classification Module (Optional) Text Image Unwarping Module (Optional) Text Line Orientation Classification Module (Optional) Text Detection Module Text Recognition Module Run a single command to quickly experience the OCR pipeline: Results are printed to the terminal: If savepath is specified, the visualization results will be saved under savepath. The visualization output is shown below: The command-line method is

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

How it works

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Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys pp-ocrv5-mobile-rec for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (pp-ocrv5-mobile-rec below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/chat/completions \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"pp-ocrv5-mobile-rec","messages":[{"role":"user","content":"Hello"}]}'

Details

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Papers

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Open weights

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