Saravanan666/pypi-org huggingface dataset:
Package: image-exercise
Projeto: Criacao de pacote de Processamento de ImagensDescricao: O pacote image_exercise e usado para:Processing:
	- Correspondencia de histograma
	- Semelhanca estrutural
	- Redimensionar imagem
Utils:
	- Ler imagem
	- Salvar imagem
	- Plotar imagem
	- Resultado da plotagem
	- Plotar histogramaOverview (template)Este e um overview do que faremos:Fonte: Karina Kato - Machine Learning Engineer/Machine Learning Tech Lead - TakePasso a passo1. Criar um projetoVoce pode realizar um fork deste projeto para utiliza-lo como modelo. Ele ja segue a organizacao da imagem apresentada acima.2. Editar os arquivos "setup.py", "requirements.txt" e "README.md"Apos criado o projeto e editado os arquivos "setup.py", "requirements.txt" e "README.md" e necessario gerar as distribuicoes "wheel" e "sdist".
Para isso, voce deve:3. Acessar a raiz do seu projetoAcesse a raiz do seu projeto para aplicar os proximos passos.4. Aplicar os comandos de instalacaoNo seu terminal, aplique os seguintes comandos:python-mpipinstall--upgradepippython-mpipinstall--usertwinepython-mpipinstall--usersetuptoolspipinstallwheel5. Aplicar o comando para criar a distribuicaoCrie a distribuicao, aplicando o seguinte comando:pythonsetup.pysdistbdist_wheel6. Publicar pacoteRealizada as etapas anteriores com exito, o proximo passo e a publicacao do pacote.
Voce precisa ter uma conta no Test Pypi e no Pypi para realizar essa etapa. A seguir os links:https://test.pypi.org/account/register/https://pypi.org/account/register/Test Pypi6.1. Primeiro, publique no Teste Pypi, aplicando o seguinte comando:python-mtwineupload--repository-urlhttps://test.pypi.org/legacy/dist/*6.2. Agora, instale o pacote de teste:pipinstall-ihttps://test.pypi.org/simple/image_exercisePypi6.3. Com tudo testado, e hora de publicar o pacote no Pypi:python-mtwineupload--repository-urlhttps://upload.pypi.org/legacy/dist/*6.4. Instale o pacote publicado:Utilize o gerenciador de pacotespippara instalar image_exercisepipinstallimage-exerciseAutorProjeto original: by Karina KatoEste exercicio: by Tiago de Freitas FaustinoEste projeto tem o objetivo apenas de exercitar a criacao publicacao e utilizacao de pacotes.
Para este fim, como ainda nao tenho um projeto proprio, foram realizados apenas pequenos
ajustes no projeto original de Karina Kato.LicencaMIT
Package: image-fabio
package_nameDescription.
The package image_fabio is used to:
Processing:
- Histogram matching
- Structural similarity
- Resize image
Utils:
- Read image
- Save image
- Plot image
- Plot result
- Plot histogramInstallationUse the package managerpipto install package_namepipinstallimage_fabioChanges0.0.1 first commit
0.0.2 to correct error on io.py
0.0.3 to correct error on tranformation.py
0.0.4 to correct tranformation.py to transformation.pyAuthorFabio_TolentinoLicenseMIT
Package: imagefacts
imagefacts discovers the screen dimensions of the commonest image formats from
a URL or a bytestring.InstallationInstall the latest imagefacts from PyPI:$ pip install imagefacts
# or
$ easy_install imagefactsUsageUse theimagefacts.facts()function to find an image’s dimensions:>>> import imagefacts
>>> imagefacts.facts(open('localfile.jpg').read())  # byte string
('image/jpeg', 1024, 768)
>>> imagefacts.facts(open('localfile.jpg'))  # file object
('image/jpeg', 1024, 768)
>>> imagefacts.facts('localfile.jpg')  # file name
('image/jpeg', 1024, 768)
>>> imagefacts.facts('http://example.com/image')  # URL
('image/png', 400, 476)
>>>You can also use imagefacts from the command line:$ python -m imagefacts http://example.com/image
('image/png', 400, 476)
$ContributorsPortions of imagefacts are from the feedparser project by Mark Pilgrim and
bfg-pages by zutesmog. Thanks!
Package: image-features-extract
Product NameToolbox to extract features from an image.InstallationRun the following to install:pipinstallimage_features_extractUsage examplerefer toimage_features_extract-examples.Release History0.O.3 add read_plu_topography to read a binary .plu image,
add fill_gap to replace missing values in .plu image by interpolated onesMeta- François Bertin– francois.bertin7@wanadoo.fr 
- Amal ChabliDistributed under theMIT licenseAbout the authors- François Bertin now retired was an expert senior in nanocharacterization at CEA-LETI
- Amal Chabli now retired was a Director of Research in nanocharacterization at CEA-LITEN
Package: image-fetcher
Python Image FetcherA simple lightweight library to download images (and other files)InstallWithPython 3.5+run:pip install image-fetcherKey featuresSpeed:By using multi-threading, more images can be downloaded per secondNo download duplication:To avoid unnecessary downloadsProgress bar:To track how your download is getting onUsageThe simplest usage involves passing a list of URL's and the folder you want the images to be saved to:from image_fetcher import multi_thread_image_download

multi_thread_image_download(
    ["https://benaandrew.github.io/images/sentiment.jpg","https://benaandrew.github.io/images/dog.jpg"],
    "images",
)If you have your URL's saved in a text file you can instead give the path to that filemulti_thread_image_download(
    "urls.txt",
    "images",
)Additional argumentsmax_fetching_threads(int): Sets the maximum number of concurrent image downloadsIncreasing this increases download throughput but also uses more processing power and can cause errors when set too highBy default is set the number of cpu cores x 5download_timeout(int): Seconds before a download is abandonedIncreasing this means more time will be allowed per download. If every download is important you should set this highIf set to None, download will only timeout if the connection does soThe default is 5 secondsverbose(bool): Whether to show progress barOn by defaultYou can pass these like so:multi_thread_image_download(
    "urls.txt",
    "images",
    max_fetching_threads=5,
    download_timeout=10,
    verbose=False
)
Package: image-file-validator
This is a simple pluggable python library that validate image file and size useful for all
type of python applications.####How to use the packagesfrom image_file_validator.image_file_validator import check_file_typecheck_for_image_size = check_file_type("./hello.png")#FOR USAGE
if check_for_image_size == True:
print("valid image file")
else:
print("invalid image file)PIP PACKAGE DEPENDECIESpip install filetype (pick your desired os)KINDLY MAKE PR for UPGRADE....Change Log====================0.0.1   (22/04/2023)First Release
Package: imageflowpy
Imageflow is a library that generates images of basically anything. For example:Generating a random picture of Billie Eilish.More will be added soon.How to use:Generate a random picture of Billie Eilish.import imageflow-py as imageflow

imageflow.billie_eilish()Authors of Imageflow:bqahellrisenAuthor of the Python Wrapper for Imageflow:skrvtChange Log for Imageflow0.0.1 (07.06.2023)[ADDED]Generate a random image of Billie Eilish[FIXED]
Package: image-format-converter
Image Format ConverterA lightweight Python package that converts images in a directory from one format to another while preserving their dimensions.Features:Convert images from one format (e.g., JPEG) to another (e.g., PNG).Option to save the converted images in a different directory.Option for recursive conversion in subdirectories.Option to overwrite the original images with the converted ones.InstallationTo install the Image Format Converter, use pip:pip install image-format-converterUsageAfter installing the package, you can use it from the command line:image-format-converter -d DIRECTORY -i INPUT_FORMAT -o OUTPUT_FORMAT [OPTIONS]Parameters-d, --directory: Path of the directory containing images to be converted.
-i, --input_format: Input image format (e.g., jpeg, png).
-o, --output_format: Output image format (e.g., png, bmp).
-od, --output_directory: Directory to save the converted images. If not specified, images will be saved in the input directory.
-r, --recursive: Use this flag to process files in subdirectories too.
--overwrite: Use this flag to overwrite the original image with the converted one.ExamplesBasic Conversion:Convert all JPEG images in theimages/directory to PNG.image-format-converter -d images/ -i jpeg -o pngSaving to a Different Directory:Convert all JPEG images in theimages/directory to PNG and save them inconverted/directory.image-format-converter -d images/ -i jpeg -o png -od converted/Recursive Conversion:Convert all JPEG images in theimages/directory and its subdirectories to PNG.image-format-converter -d images/ -i jpeg -o png -rOverwriting Original Images:Convert all JPEG images in theimages/directory to PNG and replace the original JPEGs.image-format-converter -d images/ -i jpeg -o png --overwriteLicenseThis project is open-source and available under the MIT License.
Package: image-fragment
FragmentAny extent is a set of smaller fragment extent , which can be as small as1 x 1to thesizeof the extent given.
This library will section the given extent in to specified smaller fragment extentInstallationpip install image-fragmentImage FragmentsAn image extent can be sectioned into many fragments, these fragments holds positional information to where it is located
to the original extentNow this information can be used to extract selected fragments from the Image, perform operation, and transfer the new
data to selected position.importnumpyasnpfromimage_fragment.fragmentimportImageFragmentimage=np.zeros((1,1024,1024,3))new_image=np.zeros((1,1024,1024,3))image_fragment=ImageFragment.image_fragment_4d(fragment_size=(1,512,512,3),org_size=(1,1024,1024,3))forfragmentinimage_fragment:# GET DATA THAT BELONGS TO THE FRAGMENTfragmented_image=fragment.get_fragment_data(image)# DO SOME OPERATION ON THE FRAGMENTED DATAoperation_done_on_fragmented_data=np.rot(fragmented_image)# TRANSFER OPERATED IMAGE ON NEW IMAGE ON THE FRAGMENT POSITIONnew_image=fragment.transfer_fragment(transfer_from=operation_done_on_fragmented_data,transfer_to=new_image)If image is 3 Dimensional then switch toimage_fragment = ImageFragment.image_fragment_3d(fragment_size=(512, 512, 3), org_size=(1024, 1024, 3)),
this will provide fragments for 3 dimensional image
Package: image_frequency_analysis
Image Frequency AnalysisThis package is built to combine all the steps that are done as part of the
frequency analysis using the Fourier transform approach.Install the PackageYou can install the package using the pip command!pip install image_frequency_analysis- when installing through jupyter notebookpip install image_frequency_analysis- when installing through a command promptUsing the packageOnce you have installed you can use the package by importing the image_frequency_analysis method from the packageimport image_frequency_analysis as ifaYou can then pass the image path to the function which is a required argument, to get the plot
of comparison between the original image and the filtered imageExample:obj = ifa.FrequencyAnalysis('car_image.jpg')output = obj.perform_image_frequency_analysis()By default the package uses the high pass filter to perform the filtering of the image. This option can be overridden using
the optional parameters that can be sent to the function.You can find the various optional parameters and their usage in the package using the help command.help(ifa.FrequencyAnalysis)or looking through the docstring directly in the IDESample OutputOutput with default parametersOutput with Modified Parameters
Package: imageGenie
ImageGenieTraining a model to classify images between different classes .This single package lets us harness the power of the state of the art models without any hassle of
coding them ourselves.Just 3 lines of code and we're done.Installationpip install imageGenieCOLAB Notebook Demohttps://colab.research.google.com/drive/1DGgrENv-XTVeRz7PsOm0tpofJFZWn6PU?usp=sharingUsageFully Automated ModeFolder Structuremain folderfrom imageGenie.classify import Classifier # import the Classifier Class

cl = Classifier("/root", "/models") # arg1 -> base directory containing train & test ; arg2 -> saving directory

cl.run() # this trains the model by automatically finding out number of classes, types of images and optimum training epochs.Controlled mode (Work in progress)TODOHandle all image formatsParse the specifications provided by the uer from a config file. That may include the priority
of speed, accuracy, emphasis on False Positives or negatives, time available to experiment and train.Include all other model architectures like EfficientNet, MobileNet, Inception, VGG.Algorithm to figure out what architecture and hyper-params would be the best (in the fully automated mode) as per hardware.Save all other artefacts like pipeline, metrics, plots, etcAllow user to construct a model by themselvesAllow to either have a proper folder structure or a json with labels.
Package: image-go-nord
ImageGoNord - RGB image to Nordtheme paletteA tool that can convert your rgb images to nordtheme palette.This repository is a python package that can convert any sort of image into anordthemepalette image.You can find a demo onthe websitefor testing out the package.We build also a little API hosted on Heroku to give to anyone the change to test it out by theirself. You can find the documentation on the website too.The main repository of this whole project isImageGoNord.DocumentationYou can find thedocumentation into this repositoryand also on the website.InspirationWe are in love with Nordtheme, that is why we created this repository.Our goal is to make a shortcut to convert anything into this theme, by starting from the images.An example could be an awesome wallpaper converted into the Nordtheme palette.We checked the commnunity and we did not find anything similar or any project that can accomplish this task. So, here we are.What you can do with this packageYou can convert any image into the nord palette (or others). Here are some examples:OriginalProcessed with avg algorithmOriginalProcessed with avg algorithmYou can also convert videos into the nord palette (or others). Here is an example:Originalhttps://github.com/05Alston/ImageGoNord-pip/assets/89850018/76d4c4a6-9660-4a02-9f46-e5f3f6d0147aProcessed with algorithmhttps://github.com/05Alston/ImageGoNord-pip/assets/89850018/13822280-c019-49b1-92f7-7c658b33a01dCore Technical ConceptsWe are using the PIL because it is the most simple library and it is very useful when you need to manipulate some images.Our goal is also to make this project open source and maintainable by the community. We would love to.We believe in the open source community.Getting StartedGetting it from PIPpip install image-go-nordThen you can usesome exampleto getting started properly!ContributingFollow the contributor guidelinesFollow the code style / requirementsFormat for commit messagesTODOTestingImprovements on image quality and supporting any image formatMake contributing guidelinesAuthorsTheJoin95&WabriNOTE: we are not (yet) affiliated with the Nordtheme orArcticicestudio.CreditsNordthemeLicenseMIT license
Package: image-grid
image-gridpython module to make image gridsinstall$ pip install image-gridInstalling the module registers a scriptimage-gridwhich can be run from any folder.usage$ image-grid --folder ./images --n 4 --rows 1 --width 1000 --fill
saved image-grid.jpg, (166, 998, 3), 27.1KiB$ image-grid -f images -n 14 -r 2 -w 1000 --aspect-ratio 1 --out image-grid.png
saved image-grid.png, (284, 999, 4), 338.7KiB$ image-grid -f images -n 16 --fill -a 1 -w 400 -bs 0 -o square.png
saved square.png, (400, 400, 4), 263.1KiB$ image-grid -h
usage: image-grid [-h] (-f FOLDER | -i IMAGES [IMAGES ...]) [-o OUT] [-y]
                  [-q JPEG_QUALITY] [-t FILE_TYPES] [-a ASPECT_RATIO] [--fill]
                  [--interpolation {auto,nearest,bilinear,bicubic,lanczos}]
                  [-n N] [--no-sort] [--shuffle] [-w WIDTH | -H HEIGHT]
                  [-r ROWS] [-c COLUMNS] [-bs BORDER_SIZE]
                  [-bsa BORDER_SIZE_AROUND]
                  [-bc BORDER_COLOR [BORDER_COLOR ...]]

optional arguments:
  -h, --help            show this help message and exit
  -f FOLDER, --folder FOLDER
                        path to folder with images
  -i IMAGES [IMAGES ...], --images IMAGES [IMAGES ...]
                        image file paths
  -o OUT, --out OUT     output file path
  -y, --override        if set, it will override the output file
  -q JPEG_QUALITY, --jpeg-quality JPEG_QUALITY
                        jpeg quality [1-100]
  -t FILE_TYPES, --file-types FILE_TYPES
  -a ASPECT_RATIO, --aspect-ratio ASPECT_RATIO
                        aspect ratio of grid cells (width/height). if not
                        defined, it will be chosen from the first image
  --fill                fill the grid cell instead of fitting the whole image
                        in the cell
  --interpolation {auto,nearest,bilinear,bicubic,lanczos}
  -n N, --n N           limit the amount of pictures to include
  --no-sort             don't sort images by path
  --shuffle             shuffle image order
  -w WIDTH, --width WIDTH
                        approx width of image grid in px
  -H HEIGHT, --height HEIGHT
                        approx height of image grid in px
  -r ROWS, --rows ROWS  number of rows in image grid
  -c COLUMNS, --columns COLUMNS
                        number of columns in image grid
  -bs BORDER_SIZE, --border-size BORDER_SIZE
                        border size in px
  -bsa BORDER_SIZE_AROUND, --border-size-around BORDER_SIZE_AROUND
                        border around image grid in px
  -bc BORDER_COLOR [BORDER_COLOR ...], --border-color BORDER_COLOR [BORDER_COLOR ...]
                        rgba color [0-255]
Package: imagehat
Image HATInstallationInstall dependenciesThe python3-smbus package$sudoaptinstallpython3-smbusInstall using pip$sudopip3install-UimagehatListing attributes and methods#!/usr/bin/env python3fromimagehatimportImageHathat=ImageHat(0x20)# 0x20 is the I2C bus addresshat.host# get selected hosthat.host=0# unplug USB devicehat.host=1# assign USB device to host 1hat.host=2# assign USB device to host 2hat.host2_power# get power state of host 2hat.ext_in# get state of external inputhat.ext_out# get state of external outputhat.ext_out=0# turn off external outputhat.ext_out=1# turn on external output
Package: imagehide
ï»¿# IMGHIDEHide secret texts/messages inside an image. You can optionally encrypt your texts with a password using AES-256 before encoding into the image.Inspired from thisMedium postWatchexplanation videoInstallationpip install imagehideUsageimport imagehideEncodeChooseEncodein the options menuEnter the image path (with extension)Enter the message to be hiddenChoose a password to encrypt with AES-256 (optional)The image is encoded and saved as aPNGfile.DecodeChooseDecodefrom the menuEnter the path of the encoded image (with extension) and type in the password to decrypt (leave empty if no password was used)The decoded text will be displayed on the terminal.
Package: image-inspector
===============Image Inspector===============.. image:: https://img.shields.io/pypi/v/image_inspector.svg:target: https://pypi.python.org/pypi/image_inspector.. image:: https://img.shields.io/travis/TNRIS/image_inspector.svg:target: https://travis-ci.org/TNRIS/image_inspector.. image:: https://readthedocs.org/projects/image-inspector/badge/?version=latest:target: http://image-inspector.readthedocs.io/en/latest/?badge=latest:alt: Documentation Status.. image:: https://pyup.io/repos/github/TNRIS/image_inspector/shield.svg:target: https://pyup.io/repos/github/TNRIS/image_inspector/:alt: UpdatesCommand line utility to export exif data to a csv.* Free software: MIT license* Documentation: https://image-inspector.readthedocs.io.Features========* Iterates through a base directory to find .tif files.* Outputs a CSV of EXIF tags for each .tif file.* User can specify only a set list of tags to capture.Usage=====Basic Usage:.. code-block:: console$ image-inspector .Specifying a Directory:.. code-block:: console$ image-inspector /test/sample_imagesFiltering Exported Fields:.. code-block:: console$ image-inspector . "Image XResolution" "Image YResolution"User-defined Output File:.. code-block:: console$ image-inspector . --inventory-file-name "images_2016"Overwrite Existing Inventory Files:.. code-block:: console$ image-inspector . --overwriteCredits=======This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template... _Cookiecutter: https://github.com/audreyr/cookiecutter.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage=======History=======0.1.0 (2017-05-03)------------------* First release on PyPI.
Package: imageInterfusion
package_nameDescription.
The package imageInterfusion is used to:
* Interfusion:
- Find difference;
- Transfer histogram;
- Resize image.
* Useful:
- Read image;
- Save image;
- Plot image;
- Plot Result;
- Plot histogram.InstallationUse the package managerpipto install imageInterfusionpipinstallimageInterfusionUsagefromimageInterfusion.interfusionimportimageFitimageFit.resizeImage()fromimageInterfusion.interfusionimportimageMergeimageMerge.findDifference()imageMerge.transferHistogram()fromimageInterfusion.usefulimportioio.readImage()io.saveImage()fromimageInterfusion.usefulimportplotplot.plotImage()plot.plotResult()plot.plotHistogram()AuthorAluizio NetoLicenseMIT
Package: image-in-terminal
Image In TerminalSimple Python package to display an image in the terminal by converting it into text. For the desired behavior to be achieved, the terminal must support colors, unicode characters and there should be no spacing between lines (0 line-spacing).Installationpip install image-in-terminalHow to useYou can use the package either from the terminal or from a script.imageinterminal -h

Usage:
  imageinterminal image_uris [options]

                                                  Image In Terminal
                                                        v1.2.5
                                                       by Odell
                                                      2023-2024
Positional Arguments:
  image_uris            File path(s) or HTTP/HTTPS link(s) of the image(s) to be displayed. A directory can also be
                        passed in which case all supported images in the directory will be displayed.

Options:
  -w, --width WIDTH     Destination width of the image(s).
  -wt, --whiteness-threshold WHITENESS_THRESHOLD
                        (float [0 - 1]). Pixels with a whiteness higher than this value will be inverted.
  -dt, --darkness-threshold DARKNESS_THRESHOLD
                        (float [0 - 1]). Pixels with a whiteness lower than this value will be inverted.
  -r, --recursive       If a directory is passed as image_uri the image search will be recursively performed within
                        the directory passed and all its subdirectories.
  -pp, --procedural-printing
                        The image(s) pixels will be printed one by one procedurally instead of printing/displaying the
                        entire image at once. Useful when printing/displaying high resolution images.
  -nc, --no-center      Do not center image(s).
  -nf, --no-fit         Do not automatically fit image(s) width to terminal width when -w/--width is not specified.

Miscellaneous:
  -h, --help            Show this help message and exit.
  -v, --version         Show version number and exit.

Simple Python package to display a single or multiple images in the terminal by converting it into text. For the
desired behavior to be achieved, the terminal must support colors, unicode characters and there should be no spacing
between lines (0 line-spacing).From the terminal:imageinterminal "myImage.jpg"
iit "https://images/exampleImage.jpg" "myOtherImage.png" -w 128
iit "myImagesOnWhiteBackgrounds" --width 256 -wt 0.97 
iit myImage2.png --no-fit --no-centerFrom a python script:from imageinterminal import display_image
display_image("myImage.jpg")ScreenshotsJPG 1440x1800JPG 256x256PNG 256x256Procedural Printing