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DocTR download for Windows

Free download DocTR Windows app to run online win Wine in Ubuntu online, Fedora online or Debian online

This is the Windows app named DocTR whose latest release can be downloaded as v0.7.0.zip. It can be run online in the free hosting provider OnWorks for workstations.

Download and run online this app named DocTR with OnWorks for free.

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- 1. Downloaded this application in your PC.

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- 3. Upload this application in such filemanager.

- 4. Start any OS OnWorks online emulator from this website, but better Windows online emulator.

- 5. From the OnWorks Windows OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.

- 6. Download the application and install it.

- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.

Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.

SCREENSHOTS

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DocTR


DESCRIPTION

DocTR provides an easy and powerful way to extract valuable information from your documents. Seemlessly process documents for Natural Language Understanding tasks: we provide OCR predictors to parse textual information (localize and identify each word) from your documents. 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.



Features

  • For automation
  • For research
  • Optimized for inference speed on both CPU & GPU
  • Light package, minimal dependencies
  • Actively maintained by Mindeeq
  • Easy integration


Programming Language

Python


Categories

Libraries, Machine Learning, OCR, Deep Learning Frameworks

This is an application that can also be fetched from https://sourceforge.net/projects/doctr.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.


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