Search Results for "training"

Training in a few hours and with small data thanks to 25+ pre-trained models. Full Open Source, with an ecosystem of tools (API clients, video, annotation, ...) Fast Server written in pure C++, a single codebase for Cloud, Desktop & Embedded.

PaddleOCR offers exceptional, multilingual, and practical Optical Character Recognition (OCR) tools that can help users train better models and apply them into practice. Inspired by PaddlePaddle, PaddleOCR is an ultra lightweight OCR system, with multilingual recognition, digit recognition, vertical text recognition, as well as long text recognition. It features a PPOCR series of high-quality pre-trained models, which includes: ultra lightweight ppocr_mobile series models, general...

Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc. EasyOCR is a python module for extracting text from image. It is a general OCR that can read both natural scene text and dense text in document. We are currently supporting 80+ languages and expanding. Second-generation models: multiple times smaller size, multiple times faster inference, additional characters and comparable accuracy to the first...

...It wraps the PaddleOCR models, which are capable of detecting and recognizing text in a wide variety of languages and layouts, into a self-contained executable that can be run locally without needing a deep learning environment configured manually. This makes it practical for developers or system integrators who want reliable OCR output in JSON while avoiding the complexity of training or managing models by hand. Projects and wrappers built around PaddleOCR-json demonstrate how it can be integrated into other applications, such as desktop OCR utilities or language-specific bindings, because the JSON output is easy to parse and consume.

Nougat is a multi-modal generative modeling framework that bridges vision and text modalities with structured generation control (e.g. layout, scene composition) rather than treating images as flat contexts. It combines object-centric modules with transformer-based reasoning to propose, refine, and render scenes in a generative pipeline. The architecture allows you to specify or prompt a layout (which objects should be where) and then the model fills in appearance, context, lighting, and...

...A Tesseract Trainer GUI is also shipped with this package. Forum : https://groups.google.com/forum/#!forum/lios Video Tutorial : https://www.youtube.com/playlist?list=PLn29o8rxtRe1zS1r2-yGm1DNMOZCgdU0i Tesseract Training Tutorial (beta) : https://www.youtube.com/watch?v=qLpCld4cdtk Source Code Github : https://github.com/Nalin-x-Linux/lios-3 Gitlab : https://gitlab.com/Nalin-x-Linux/lios-3 User guide is available in download page

.... ***** Following is OLD information - saved only for archival purposes. Tesseract OCR 3.02 provides hin.traineddata for recognizing texts in devanagari scripts. However the Hindi training texts, images and box files are not provided, so it is difficult to improve the accuracy by further improving the traineddata. It is noted that recognition is more accurate and faster if the training is done with the same /similar font as used in the text to be OCRed. See https://sourceforge.net/p/tesseracthindi/wiki/OCR%20for%20Devanagari/ for more details.

For several purposes of our OCR research we needed a converter that can generate an image from any given Bangla/ Bengali text. One of the reasons was to prepare artificial training and testing data. For this reason we finally created a very simple text to image converter. A Text to Image Converter. Systrem Requirement: .net Framework 4.0 and up 1. Select your Font Type, style and size. 2. First Browse your file, which will contain your text (Supporetd File Type .txt) 3. Select Single or Multi Line option. 4. ...

Classnotes is an OCR intended to translate handwritten scans into text. In order for the program to translate the scans the user must create a handwriting profile by training the OCR with scans.