Saravanan666/pypi-org huggingface dataset:
Package: ocrhelper
EN|RUAdvanced Screen Assistant.OCRHelperis able to translate text from the selected area. It is also possible to search for the meaning of a word using ChatGPT, as well as simply copy it to the clipboard.Main featuresHigh text recognition precisionOCR Helper for text recognition uses EasyOCR, which handles most of the daily text reading requirements.Simple interfaceThe main idea was to make tool, that does not require manual adjustments for each case and convenient for everyday use.Available translators:Google Translate, ChatGPT, ChatGPT with streaming displayAvailable recognition and translation languages:English, Russian, JapaneseDictionary:mode for finding the meaning of a word using ChatGPTRecognition:mode for only text recognition, can be used with the option to copy text to the clipboardSystem requirementsWindows 10 build 19041 (20H1) / Windows 11DirectX111 GB free RAM5 GB free storage space/ 1 GB for without_cuda versionNvidia GPU with CUDA SDK 11.8 support (GTX 750, 8xxM, 9xx series or later)(for mode using CUDA)How to useChoose the version that suits you: the regular version weighs more and takes more time to start, but reads text faster, the without_cuda version is the opposite (you can download any of themhere)Launch the application (The first launch will take much longer than the subsequent ones)Open the menu using CTRL + ALT + X or via the trayOpen the settingsSelect the necessary languages for recognition (the fewer selected, the more accurate the recognition)Select a translator (you will need to enter an API-key to use GPT)(Optional) Change the color of the area selection in the palettePress CTRL + SHIFT + X to select an area and then translateWait for the translation resultUsage TipsShould install a non-standard fontThis should be done to better display the application windowTo do this, go to "ocrhelper/additional files", run "Rubik.ttf", click "install"Use Borderless/Windowed modes in games (not Fullscreen)It is necessary to display the translation window overlay correctly.If the game doesn't have such mode, you can use external tools to make it borderless (e.g.Borderless Gaming)Install the application on SSDTo reduce cold launch time with enabled EasyOCR engine (loading large EasyOCR model into RAM).ErrorIf an error occurs while running the application, please create a new issue in the Issues tab. I will try to respond to the problem as soon as I see it.TODOMove app on PyQTAdd gamepad support for selecting areaFor devClone repositorygitclonehttps://github.com/ReYaNOW/OCRHelper.gitInstall dependenciesmakeinstallormakeinstall_without_cudaDependenciesPython 3.11+PoetryPython librariesCustomTkinterDeep-translatorPystrayKeyboardPillowNumpyKeyringCTkMessagebox
Package: ocr-license
OverviewOCR Meter ReadingSetupconda create -n ocr_license python=3.7conda activate ocr_licensepip install ocr-license==0.0.2Example code:from ocr import ocr_license
img_path = "tests/1.png"
ocr = ocr_license.OcrLicense()
# license_type choice in (my_number_card, driver_license)
ocr.inference_single(img_path, license_type="my_number_card")
Package: ocr-meter
OverviewOCR Meter ReadingSetupconda create -n ocr_meter python=3.8conda activate ocr_meterpip install ocr-meter==0.0.6Example code:from ocr import ocr
img_path = "tests/meter/5/1.png"
ocr_meter = ocr.OcrMeter()
# num_digit: number black digits
# meter_type choice in (water, electicity, gas)
ocr_meter.inference_single(img_path, num_digit=5, meter_type="water")
Package: ocrmymanga
OCRMyMangaOCR My Manga is a tool to help you OCR your manga. Utilizing the Google Cloud Vision API, it can automatically detect text in your manga and output it to a text file.OCRMyManga is written in Python. It is still in development, so there may be bugs.SINCE THIS TOOL USES THE GCLOUD LIBRARY, YOU WILL NEED TO HAVE A GOOGLE CLOUD ACCOUNT TO USE IT. THIS MAY INCUR MONETARY COSTS FOR LARGE OCR TASKS > 1000 pagesInstallationThis tool REQUIRES a Google Cloud Vision API Key. Follow these instructions to get one:https://cloud.google.com/vision/docs/setupThen, install OCRMyManga from pip with the following command:pip install ocrmymangaUsageOCRMyManga is a command line tool. It can be run with the following command:
It will ONLY output into pdf format.ocrmymanga [-h] [INPUT] [-o OUTPUT] [-b] [-c CREDS] [-v]-h: help
-b: batch process
-c: credential file for google vision
-v: verbosePermitted file typesOCRMyManga can only OCR the following file types:
.png
.jpg
.jpeg
.cbzSupport for other file types may be added in the future.CookbookOCR a single fileocrmymanga input.jpg -o output.pdfBatch OCR a directoryocrmymanga input_dir -o output_dir -bOCR with a custom credential fileocrmymanga input.jpg -o output.pdf -c creds.json(-c will default to credentials.json)Github Linkhttps://github.com/D0rkKnight/OCRMyManga
Package: ocrmypdfgui
ocrmypdfguiI use James R. Barlow's OCRmyPDF heavily in my paperless Office and have created this Python Project as a GUI wrapper to run batch jobs on my filesystem. This is strictly a Hobby Project and is not "official". Feel free to use it if you like.Icons made by Freepik fromwww.flaticon.comInstallationYou can find the most up-to-date version of ocrmypdfgui on pypi which is based on GTK3.pip install ocrmypdfguiThere is also an (older) tkinter based version snap package on snapcraft.io:or you can get if from the commandline:sudo snap install ocrmypdfgui
Package: ocrodjvu
Overviewocrodjvuis a wrapper for OCR systems that allows you to perform OCR onDjVufiles.Example$wget-q'https://sources.debian.org/data/main/o/ocropus/0.3.1-3/data/pages/alice_1.png'$gmconvert-threshold50%'alice_1.png''alice.pbm'$cjb2'alice.pbm''alice.djvu'$ocrodjvu--in-place'alice.djvu'Processing 'alice.djvu':
- Page #1$djvused-eprint-txt'alice.djvu'(page 0 0 2488 3507
 (column 470 2922 1383 2978
  (para 470 2922 1383 2978
   (line 470 2922 1383 2978
    (word 470 2927 499 2976 "1")
    (word 588 2926 787 2978 "Down")
    (word 817 2925 927 2977 "the")
    (word 959 2922 1383 2976 "Rabbit-Hole"))))
 (column 451 707 2076 2856
  (para 463 2626 2076 2856
   (line 465 2803 2073 2856
    (word 465 2819 569 2856 "Alice")
    (word 592 2819 667 2841 "was")
    (word 690 2808 896 2854 "beginning")
⋮RequisitesThe following software is required to run ocrodjvu:Python3an OCR engine:Cuneiform≥ 0.7Ocrad≥ 0.10GOCR≥ 0.40Tesseract≥ 2.00DjVuLibre≥ 3.5.21python-djvulibre≥ 0.4lxml≥ 2.0Additionally, some optional features require the following software:PyICU≥ 1.0.1 —
required for the--word-segmentation=uax29optionhtml5lib—
required for the--html5optionThe following software is required to rebuild the manual pages from source:xsltprocDocBook XSL stylesheetsInstallationYou can use ocrodjvu without installing it, straight out of unpacked source tarball or a VCS checkout.It’s also possible to install it system-wide with:pip install .The man pages can be deployed using:make install_manpageBy default,make install_manpageinstalls them to/usr/local/. You can specify a different installation prefix by setting thePREFIXvariable, e.g.:make install PREFIX="$HOME/.local"About this forkThis repository is a port of the original repository to Python 3.The process involved the2to3tool and manual fixes afterwards to get the existing tests to pass. While this port started from scratch to already include the latest upstream changes, the fork by@rmastwhich accumulated previous porting attempts provided some great help (seeIssue #39as well).Due to the upstream repository having been archived (Issue #46), this fork will now be maintained on its own. Please note that I do not have any plans on implementing completely new features for now. Nevertheless, I am going to try to keep this fork working for at least the parts which I actually use on a regular basis.Differences from upstreamPackage requires Python ≥ 3.6.Migrate fromnoseto plainunitteststdlib module.Conform to PEP8 coding style.Use standardizedsetup.py-based installation.Renamelibtoocrodjvuand migrateocrodjvubinary to__main__.pyand console script version.Drop support forocropus/ocropyas only the rather old legacy versions ≤ 0.3.1 from 2008 have been supported.Acknowledgmentocrodjvu development was supported by the Polish Ministry of Science
and Higher Education’s grant no. N N519 384036 (2009–2012,https://bitbucket.org/jsbien/ndt).
Package: ocr-ops
ocr-opsOCR-Ops is infrastructure to perform Optimal Character Recognition (OCR) at scale on a large number of images and videos.
Built on top of the algo-ops framework, OCR-Ops is modular and extensible in its data processing operations.Key Features:Supports building an OCRPipeline that can utilize multiple popular OCR annotation methods (e.g. PyTesseract, EasyOCR,
etc.) and return the results in structured and efficient fashion within a unified framework.Enables multi-levels of information of the OCR application (e.g. text-only, bounding boxes, etc.)Allows definition of an image pre-processing pipeline (before OCR) and a text-cleaning pipeline (after OCR) of
detected but noisy text to enable optimal and robust OCR performance.Supports several nice presets that are plug-and-play for the above purpose!
Package: ocrpy
ocrpyUnified interface to google vision, aws textract, azure, tesseract and other OCR toolsThe Core objective of OcrPy is to let users OCR, Archive, Index and Search any documents with ease,
with a simple and intuitive interface and a powerful Pipeline API.ocrpy achieves this by wrapping around various OCR engines likeTesseract OCR,Aws Textract,Google Cloud VisionandAzure Computer Vision. It unifies the multitude of interfaces provided by a wide range of cloud tools & other open-source libraries and provides a simple, easy-to-use interface for the user.Getting Startedocrpyis a Python-only package hosted onPyPI.
The recommended installation method ispippipinstallocrpyDay-to-Day UsageOcrpy Provides various levels of abstraction for the user to perform OCR on various types of documents.
The recommended and the best way to use Ocrpy is to use it through it'spipelinesAPI as shown below.The Pipeline API can be invoked in two ways. The first method is to define the config for running the
pipeline as a yaml file and and then run the pipeline by loading it as follows:fromocrpyimportTextOcrPipelineocr_pipeline=TextOcrPipeline.from_config("ocrpy_config.yaml")ocr_pipeline.process()alternatively you can also run a pipeline by directly instantiating the pipeline class as follows:fromocrpyimportTextOcrPipelinepipeline=TextOcrPipeline(source_dir='s3://document_bucket/',destination_dir="gs://processed_document_bucket/outputs/",parser_backend='aws-textract',credentials_config={"AWS":"path/to/aws-credentials.env/file","GCP":"path/to/gcp-credentials.json/file"})pipeline.process():memo: For a more detailed set of examples and tutorials on how you could use ocrpy for your usecase can be found atocrpy documentation.Support and DocumentationFor an in-depth reference of the ocrpy API refer ourAPI docs.For inspiration on how to use ocrpy for your usecase, check out ourtutorialsor ourexamples.If you're interested in understanding how ocrpy works, check out ourOcrpy Overview.Feedback and ContributionsIf you have any questions, Feedback or notice something wrong, please open an issue onGitHub Issues.If you are interested in contributing to the project, please open a PR onGitHub Pull Requests.Or if you just want to say hi, feel free tocontact us.CitationIf you wish to cite this project, feel free to use thisBibTeXreference:@misc{ocrpy,title={Ocrpy: OCR, Archive, Index and Search any documents with ease},author={maxentlabs},year={2022},publisher={GitHub},howpublished={\url{https://github.com/maxent-ai/ocrpy}}}License and Creditsocrpyis licensed under theMITlicense.
The full license text can be also found in thesource code repository.ocrpyis written and maintained byBharath G.SandRita Anjana.A full list of contributors can be found inGitHub's overview.
Package: ocrscreen
# ocrscreenocr for recognizing text on computer screen## Install` pip install ocrscreen `## UseTo create recognition database you need to create few (tens to hundreds) training samples in form of file pairs: png image file containing image of one line of text, and text file containing same line of text. Image and text should have same name except extension:.pngfor image and.gt.txtfor text. Each character you want to recognize should be present in at least three samples.If you have samples you can convert it into database with this command:`ocrscreen-learnpath/to/samples-opath/to/database `Recognintion database is a list of directories, each directory contains.pngfiles (one or many) representing character and.idfile with text containing character (to avoid filesystem limitations). Directory name and file name does not matter. This form allows easy tuning and troubleshooting recognition problems.When you have database you can run ocr on image`ocrscreen-recognize-dpath/to/database-ipath/to/image `or on screen`ocrscreen-recognize-dpath/to/database--screen`or on portion of screen with –rect x y w h`ocrscreen-recognize-dpath/to/database--screen--rect10 10 640 480 `Inspectsamplesanddatabasedirectory in the sources to get better understanding of data format.## NotesThis ocr uses black and white bitmaps as search pattern to search on binarized image and only perfect equality counts as match. It doesn’t use dpi and neural networks, it cannot recognize scanned text or text in photo images, it is only for recognizing perfect digital text.If you have linux and wayland you need to installpyscreenshotpackage.` pip install pyscreenshot `
Package: ocr-shell
OCR ShellOCR Shell is a convenient command-line tool for quick and easy text extraction from images. Whether you have an image in your clipboard or a saved file, OCR Shell makes it easy to extract text without the hassle of manual handling.PrerequisiteTesseract OCROn Windows, you can download an installer from theTesseract GitHub repository.On macOS, you can install Tesseract using Homebrew with the commandbrew install tesseract.Make sure thetesseractis found on your executable PATH.InstallationTo install OCR Shell, simply run:pipinstallocr-shellThis command will install OCR Shell and all its dependencies.UsageFrom ClipboardTo extract text from an image in your clipboard, just type:$ocr
...textfoundinthecopiedimage...From a FileOCR Shell also works with saved images. Just provide the path to the image:$ocr~/Desktop/Screenshot.png
...moretextextracted...Unit Tests$python-munittestdiscover
..
----------------------------------------------------------------------
Ran2testsin0.407s

OKContributingContributions to OCR Shell are welcome! Whether it's bug reports, feature requests, or code contributions, your input is valuable. To contribute:Fork the repository.Create a new branch for your feature or bug fix.Commit your changes.Push to your branch.Submit a pull request.Please make sure to update tests as appropriate.LicenseThis project is licensed under the MIT License - see theLICENSEfile for details.AcknowledgmentsThanks to the Tesseract OCR team for their amazing work.Matt King for initial development.All contributors who help to improve OCR Shell.
Package: ocr-tesseract-wrapper
ocr-tesseract-wrapperTiny wrapper around pytesseract with image preprocessing and OCR configurationsRequirementstesseract installed (https://github.com/tesseract-ocr/tesseract/wiki#installation)Basic usagefromocr_tesseract_wrapperimportOCRocr_tool=OCR()results=ocr_tool.ocr([image])# where image is Pillow image or string image pathAdvanced usagefromocr_tesseract_wrapperimportOCRocr_tool=OCR()results=ocr_tool.ocr([image1,image2],config=[])"""where config parameter is list of additional configs and restrictions for each of theimages given to the OCR. for instance: [None, 'tessedit_char_whitelist=0123456789'] willapply no restriction to the first but will only return numeric characters from the second image."""
Package: ocrticle
OCRticleGUI application capable of extracting text from an image, while keeping the text's original structure. OCRticle works best with articles (hence the name), but it should function with any kind of text.InstallationOCRticle requires Python >= 3.10 and the Tesseract OCR engine. Instructions for installing Tesseract can be foundhere. Currently, OCRticle supports OCR for text in English and in Portuguese. For detecting text in Portuguese, the corresponding Tesseract language pack must be installed.Linux users should be able to install OCRticle by just running:pip install ocrticleFor Windows users, a pre-compiled binary can be downloaded fromhere.UsageWhen invoked from the command line, OCRticle can be given an image path as an optional argument. Otherwise, the application will ask the user to select an image from the computer.After an image has been selected, the next window of the application allows the user to draw rectangles to select the articles present in the image. Each rectangle or group of intersecting rectangles should correspond to one article. Alternatively, the user can draw rectangles to exclude certain parts of the image from being scanned by selecting the corresponding option. There are also options to change the brightness, contrast and saturation of the source image. For example, to convert an image to black and white, the saturation can be set to 0.Once this step is concluded, OCRticle will use Tesseract to scan the image or the selected rectangles and extract the text found in each. Then, OCRticle will try to automatically join the text in different blocks. This behavior is largely dependent on Tesseract's detection, which is not perfect, therefore the blocks may not exactly match the original text.The user is able to tag each block, according to its contents. These tags are: Title, Text, Quote, and Code. OCRticle will try to automatically "guess" which block is the article's title, but, if it fails, the user can fix the mislabeling. OCRticle will also remove some line breaks, when it believes that two lines are part of the same paragraph. This behavior can be toggled during this step.Finally, the user can save the scanned articles in a Markdown file, where the blocks will be identified according to their tags.
Package: ocrtool
ocrtool使用百度ORC做的照片转文字Free software: BSD licenseDocumentation:https://ocrtool.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2016-07-28)First release on PyPI.
Package: ocrtoolkit
Parse bank chequesQuickstartocrtoolkit is available on PyPI and can be installed withpip.$pipinstallocrtoolkitAfter installing ocrtoolkit you can use it like any other Python module.Here is a simple example:importocrtoolkit# Fill this section in with the common use-case.TheAPI Referenceprovides API-level documentation.Change LogVersion History0.0.1Project created.
Package: ocrtools
# OCR Tools
Open Climate Research is an ongoing project that aims to facilitate creative experimentation with modeled climate data. OCR Tools aims to be much more than a climate data viewer by enabling non-scientists to utilize a wide range of datasets and providing users with simple feedback conducive to learning. In addition to providing basic analysis functions, OCR Tools includes organizational and creative tools.## Installing / Getting startedRun the following to install:`python pip install ocrtools `## ExamplesOpen a NetCDF dataset with` python import ocrtools as ocr cesm_TS =ocr.load('path/to/cesm_TS_data.nc',var='TS')`Ifvaris omitted, ocrtools will print out all variables in the dataset and ask you to specify a variable(s) of interest via command line. The dataset is then opened as an Xarray DatasetCreate ascopeobject` python lima_peru =ocr.scope(location='Lima,Peru', yr0=1950, yrf=2000) `Location can also be specified by keyword argumentslat_min,lat_max,lon_min, andlon_max; or if none of these are given, location can be specified interactively by selecting areas on a mapSubset your data`python lima_TS = ocr.subset(cesm_TS, lima_peru) `Select an area on a map and take the spatial average`python from ocrtools import plt map_selection = ocr.scope() ``shell [OCR] Creating new scope object Enter yr0: Enter yrf: Select area(s) on map and close thepop-upwindow `<img src=”http://andreschang.com/unlinked/tk_selector_screenshot.png” width=70%/>`shell [OCR] Finished writing new scope object ``python peru_TS = ocr.subset(cesm_TS, map_selection) peru_avg_TS = ocr.spatial_average(peru_TS)peru_avg_TS['TS'].plot()plt.show() `
Package: ocr_translate-easyocr
Plugin ocr_translate_easyocrThis is a plugin for theocr_translate.
Plugins to enable usage of Easyocr in ocr_translateUsageInstall this by runningpip install ocr_translate-easyocrAddocr_translate_easyocrto yourINSTALLED_APPSinsettings.pyRun the server withAUTOCREATE_VALIDATED_MODELSonce
Package: ocr_translate-google
Plugin for using googletrans with ocr_translateThis is a plugin for theocr_translateserver for implementing translations using google_translateUsageInstall this by runningpip install ocr_translate-googleAddocr_translate_googleto yourINSTALLED_APPSinsettings.pyRun the server withAUTOCREATE_VALIDATED_MODELSonce:
Package: ocr_translate-hugging_face
Plugin ocr_translate_hugging_faceThis is a plugin for theocr_translate.
Plugins to enable usage of HuggingFace Models in ocr_translateUsageInstall this by runningpip install ocr_translate-hugging_faceAddocr_translate_hugging_faceto yourINSTALLED_APPSinsettings.pyRun the server withAUTOCREATE_VALIDATED_MODELSonce
Package: ocr_translate-tesseract
Plugin for using tesseract with ocr_translateThis is a plugin for theocr_translateserver for implementing translations usingtesseractIMPORANT: This plugin required tesseract to be installed to worklinkUsageInstall this by runningpip install ocr_translate-tesseractAddocr_translate_tesseractto yourINSTALLED_APPSinsettings.pyRun the server withAUTOCREATE_VALIDATED_MODELSonce
Package: ocr-varianrpm
Optical Character Recognition for Varian Real-time Position Management systemThe Varian Real-time Position Management (RPM) system is a video-based system that
compensates for target motion, enabling improved treatment in cancer by tracking the position
of a reflective marker placed on the patient in three dimensions (vertical, longitudinal and
lateral). The RPM system can detect unexpected motion, providing additional confidence that
the target is always accurately positioned for treatment, so the planned dose is delivered to the
tumor. If there is movement, the RPM system detects the interruption and instantly gates the
beam off. The RPM system uses an infrared tracking camera and a reflective marker placed on
the patient and measures the patient’s respiratory pattern and range of motion. It displays them
as three waveforms (vertical, longitudinal, and lateral. 1 ) These will be smooth given that the
beam is stopped if there is any patient movement.In order to determine the position of the Varian Infrared Block on the true beam radiotherapy
system when the couch is moving, we take a video of the signal coming from the Infrared
tracking camera of the RPM system. The camera should be perpendicular to the system and
taken with a tripod to minimize noise due to movement. From there, we use computer vision
techniques, machine learning based optical character recognition (OCR), and develop anomaly
detection techniques to reproduce the three waveforms described above. Due to FDA approval
limitations, currently only 30 seconds of these waveforms can be extracted directly from the
RPM system. With our method, an unlimited time period of movement can be analyzed and
extracted.