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    Models/Text Extraction/PaddlePaddle/paddleocr
    PyTorchOCRApache 2.0

    paddleocr

    by PaddlePaddle

    Ultra-lightweight, production-ready multilingual OCR system

    dl/month
    12Mparams
    Identifiers
    Model ID
    PaddlePaddle/paddleocr
    Feature URI
    mixpeek://image_extractor@v1/paddle_ocr_v1

    Overview

    PaddleOCR is a comprehensive OCR toolkit supporting 80+ languages with extremely lightweight models suitable for both server and mobile deployment. It combines text detection (DB), text direction classification, and text recognition (CRNN) in a unified pipeline.

    On Mixpeek, PaddleOCR is the go-to choice for multilingual text extraction and high-throughput OCR processing of documents, images, and video frames.

    Architecture

    Three-stage pipeline: (1) DB text detector for localizing text regions, (2) text direction classifier, (3) CRNN-based text recognizer. PP-OCRv4 variant uses knowledge distillation for 4x smaller model with minimal accuracy loss.

    Mixpeek SDK Integration

    import { Mixpeek } from "mixpeek";
    const mx = new Mixpeek({ apiKey: "API_KEY" });
    await mx.collections.ingest({
    collection_id: "my-collection",
    source: { url: "https://example.com/document.pdf" },
    feature_extractors: [{
    name: "ocr",
    version: "v1",
    params: {
    model_id: "PaddlePaddle/paddleocr"
    }
    }]
    });

    Capabilities

    • 80+ language support including CJK, Arabic, Devanagari
    • Text detection, recognition, and layout analysis
    • Ultra-lightweight models (< 10MB for mobile)
    • Table recognition and key-value extraction

    Use Cases on Mixpeek

    Multilingual document processing across global content libraries
    High-throughput OCR for large-scale document digitization
    Real-time text extraction from live video feeds

    Benchmarks

    DatasetMetricScoreSource
    ICDAR 2015 (detection)F187.1%PaddleOCR benchmarks — README
    ICDAR 2015 (recognition)Accuracy79.4%PaddleOCR benchmarks — README

    Performance

    Input Sizevariable (auto-resize)
    GPU Latency~12ms / page (A100)
    CPU Latency~85ms / page
    GPU Throughput~83 pages/sec (A100)
    GPU Memory~0.6 GB

    Includes detection + recognition pipeline

    Specification

    FrameworkPyTorch
    OrganizationPaddlePaddle
    FeatureOCR
    Outputtext + bbox
    Modalitiesvideo, image, document
    RetrieverText-in-Image
    Parameters12M
    LicenseApache 2.0
    Downloads/mo

    Build a pipeline with paddleocr

    Add this model to a processing pipeline alongside other extractors. Combine with retrieval stages for end-to-end search.

    Open Pipeline Builder