Showing 4 open source projects for "art of"

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    EasyOCR

    EasyOCR

    Ready-to-use OCR with 80+ supported languages

    ...Model weights for the chosen language will be automatically downloaded or you can download them manually from the model hub. The idea is to be able to plug-in any state-of-the-art model into EasyOCR. There are a lot of geniuses trying to make better detection/recognition models, but we are not trying to be geniuses here. We just want to make their works quickly accessible to the public.
    Downloads: 29 This Week
    Last Update:
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  • 2
    DocTR

    DocTR

    Library for OCR-related tasks powered by Deep Learning

    ...Robust 2-stage (detection + recognition) OCR predictors with pretrained parameters. User-friendly, 3 lines of code to load a document and extract text with a predictor. State-of-the-art performances on public document datasets, comparable with GoogleVision/AWS Textract. Easy integration (available templates for browser demo & API deployment). End-to-End OCR is achieved in docTR using a two-stage approach: text detection (localizing words), then text recognition (identify all characters in the word). As such, you can select the architecture used for text detection, and the one for text recognition from the list of available implementations.
    Downloads: 3 This Week
    Last Update:
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  • 3
    dots.ocr

    dots.ocr

    Multilingual Document Layout Parsing in a Single Vision-Language Model

    ...Unlike traditional OCR pipelines that rely on multiple specialized components, dots.ocr integrates these processes end-to-end, reducing error propagation and improving consistency across tasks. The model is designed to recognize virtually any human script, making it highly effective for global and low-resource language scenarios. It achieves state-of-the-art performance on document parsing benchmarks while maintaining a relatively compact model size, demonstrating efficiency without sacrificing accuracy. Beyond standard OCR tasks, it extends its capabilities to parse complex visual elements such as charts, diagrams, and web interfaces, converting them into structured outputs like SVG code.
    Downloads: 0 This Week
    Last Update:
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  • 4
    LayoutParser

    LayoutParser

    A Unified Toolkit for Deep Learning Based Document Image Analysis

    With the help of state-of-the-art deep learning models, Layout Parser enables extracting complicated document structures using only several lines of code. This method is also more robust and generalizable as no sophisticated rules are involved in this process. A complete instruction for installing the main Layout Parser library and auxiliary components. Learn how to load DL Layout models and use them for layout detection.
    Downloads: 3 This Week
    Last Update:
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