Saravanan666/pypi-org huggingface dataset:
Package: image-processing-package-srmaia
image-processing-packageO pacote "image-processing-package" é usado para:Módulo "processing":Correspondência de histograma;Similaridade estrutural;Redimensionar imagem.Módulo "Utils":Ler imagem;Salvar imagem;Plotar imagem;Resultado do gráfico;Plotar histograma.Instalção do PacoteUse o gerenciador de pacotespippara instalar image-processing-packagepip install image-processing-package-srmaia
Package: image-processing-rbiegelmeyer
image_processingDescription.
The package image_processing is used to:Processing:Histogram MatchingStructural SimilarityResize ImageUtils:Read ImageSave ImagePlot ImagePlot Resultplot HistrogramInstallationUse the package managerpipto install image_processingpipinstallimage_processingUsagefromimage_processing_rbiegelmeyer.utilsimportio,plotfromimage_processing_rbiegelmeyer.processingimportcombination,transformationimage1=io.read_image('./data/image1.jpg')image2=io.read_image('./data/image2.jpg')# plot.plot_image(image1)# plot.plot_image(image2)result_image=combination.transfer_histrogram(image1,image2)plot.plot_result(image1,image2,result_image)AuthorRoberto Biegelmeyer
rbiegelmeyerLicenseMIT
Package: image-processing-soek
image_processingDescription.
The package image_processing_soek is used to:
Processing:
- Histrogram matching
- Structural similarity
- Resize image
Utils:
- Read image
- Save image
- Plot image
- Plot result
- Plot histogramInstallationUse the package managerpipto install package_namepipinstallimage_processing_soekAuthorDiego SoekLicenseMIT
Package: image-processing-teste
package_nameDescription.
The package package_name is used to:"Processing" module:-Histogram matching;
-Structural similarity;
-Resize image;Module "Utils":-read image;
-Save Image;
-Plot image;
-Plot result;
-Plot histogram;InstallationSetup walkthrough to host a Python package in the Test Pypi test environmentInstallation of the latest versions of "setuptools" and "wheel"py -m pip install --user --upgradesetuptools wheelMake sure the directory in the terminal is the same as the "setup.py" fileC:\User\https://github.com/ozeaseromina/package-templatepy setup.py sdist bdist_wheelAfter completing the installation, verify that the folders below have been added to the project:-build;
-dist;
-image_processing_test.egg-info.
-Just upload the files, using Twine, to Test Pypi:py -m twine upload --repository testpypi dist/*
After running the above command in the terminal, you will be asked to enter the username and password. Once this is done, the project will be hosted on Test Pypi. Host it on Pypi directly.
Here the goal is not to use Karina's project to post on my personal Pypi profile, since the project is hers. I still don't have any projects that can be used as a package.
However, keep in mind that Test Pypi, as its name implies, is just a testing environment. In order for the project to be available as a package to be used publicly, it needs to be hosted on the official Pypi website.
Local installation, after hosting on Test Pypi
installation of dependencies
pip install -r requirements.txt
Package Installation
Use package manager pip install -ihttps://test.pypi.org/simple/image-processing-test to install image_processing-testpip install image-processing-testUse the package managerpipto install package_namepipinstallpackage_nameUsagefrompackage_name.module1_nameimportfile1_namefile1_name.my_function()AuthorRomina BarrientosLicenseMIT
Package: image-processing-teste2
Projeto: Pacote de Processamento de ImagensAutora do Projeto: Karina Kato
Aula: Descomplicando a criaÃ§Ã£o de pacotes de processamento de imagens em Python - Digital Innovation OneTecnologia: Python
Data: 16/03/2022DescriÃ§Ã£oO pacote "image_processing-test" Ã© usado para:"MÃ³dulo "Processing":CorrespondÃªncia de histograma;
Similaridade estrutural;
Redimensionar imagem;"MÃ³dulo "Utils":Ler imagem;
Salvar imagem;
Plotar imagem;
Resultado do grÃ¡fico;
Plotar histograma;InstallationUse the package managerpipto install package_namepipinstallimage-processing-teste2Usagefromimage_processing_teste2.utilsimportio,plotfromimage_processing_teste2.processingimportcombination,transformationAutor (quem hospedou o projeto no Test Pypi)Gabriel andreLicenseMIT
Package: image-processing-test-hg
package_nameDescription.
The package package_name is used to:
Processing:
- Histogram matching
- Structural similarity
- Resize image
Utils:
- Read image
- Save image
- Plot image
- Plot HistogramInstallationUse the package managerpipto install package_namepipinstallpackage_nameUsagefrompackage_nameimportfile1_namefile1_name.my_function()AuthorhtonioniLicenseMIT
Package: image-processing-testing
image-processingDescription.
The package package_name is used to:
Processing:
- Histogram matching
- Structural similarity
- Resize imageUtils:
	- Read image
	- Save image
	- Plot image
	- Plot result
	- Plot histogramInstallationUse the package managerpipto install package_namepipinstallpackage_nameAuthorGabriel MonteiroLicenseMIT
Package: image-processing-testing-isabella
image-processingDescription.
The package package_name is used to:
Processing:
- Histogram matching
- Structural similarity
- Resize imageUtils:
	- Read image
	- Save image
	- Plot image
	- Plot result
	- Plot histogramInstallationUse the package managerpipto install package_namepipinstallpackage_nameAuthorIsabella M. RamosLicenseMIT
Package: image-processing-test-package
Desafio-002 : Pacote de Processamento de ImagensDescriçãoEsse projeto consiste na criação de um pacote para python, com base no curso ministrado por Karina Kato.É apenas um pacote de exemplo, baseado noscikit-imageAnotações das aulas podem ser vistasaqui.Passos para a hospedagem no PypiPrimeiro se realiza uma instalação ou upgrade dopip,twine,setuptoolsewheelremova a opção--userse não deseja instalar nouser.homeou esteja usando umvenv.python-mpipinstall--upgradepip
python-mpipinstall--usertwine
python-mpipinstall--usersetuptools
python-mpipinstall--userwheelCria-se as distribuiçõespythonsetup.pysdistbdist_wheelSerão criadas 3 pastas no projeto:builddistimage_processing_package.egg-infoO próximo passo é o upload no Test Pypi.python-mtwineupload--repository-urlhttps://test.pypi.org/legacy/dist/*O comando para upload no Pypi é:python-mtwineupload--repository-urlhttps://upload.pypi.org/legacy/dist/*InstalaçãoPara a instalação local, é necessário instalar os requerimentos primeiro.pipinstall-rrequirements.txtPara a instalação do pacote, basta usar opipdirecionando para o image-processing-test-packagepipinstallimage-processing-test-packageUsoBasta importar os módulos de acordo com o que desejafromimage-processing-test-package.processingimporttransformationtransformation.resize_image(image1,0.5)AutorAdriano RomeroLicençaMIT
Package: image-processing-test-project
Projeto - Pacote de Processamento de ImagensAutora do Projeto - Karina KatoBootcamp Cognizant Cloud Data Engineer - DIODescriÃ§Ã£o
O pacote "image-processing-test-project" Ã© usado para:MÃ³dulo "Processamento":CorrespondÃªncia de histograma;
Similaridade estrutural;
Redimensionar imagem;MÃ³dulo "Utils":Ler imagem;
Salvar imagem;
Plotar imagem;
Resultado do grÃ¡fico;
Plotar histograma;pipinstallimage-processing-test-projectUsagefrompackage_name.module1_nameimportfile1_namefile1_name.my_function()Author (Quem hospedou o projeto no Test Py)Fernando VenturaLicenseMIT
Package: image-processing-thiagor
image_processingDescription.
The package image-processing-thiagor 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-processing-thiagorAuthorThiago RegisLicenseMIT
Package: image-processing-to-cassiana
image_processingDescription.
The package image_processing is used to:
Processing:
- Histogram matching
- Structural similarity
- Resize image
Utils:
- Read image
- Save image
- Plot image
- Plor result
- Plot histogramInstallationUse the package managerpipto install image_processingpipinstallimage_processingAuthorCassianaLicenseMIT
Package: image-processing-vinicius
image_processingDescription.
The package image_processing 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 image-processingpipinstallimage_processingAuthorVinicius, slightly modified version from Karina KatoLicenseMIT
Package: image-processing-windlin
image_processingDescription.
The package image_processing_windlin 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_processing_windlinUsagefrompackage_name.module1_nameimportfile1_namefile1_name.my_function()AuthorKarinaLicenseMIT
Package: image-processor
About The ProjectThis repository contains the codebase for Monkey Music image processing library.Built WithThe list of all the major technologies used in the project.RustGetting StartedPlease setup the rust toolchain using instructions athttps://doc.rust-lang.org/book/ch01-01-installation.htmlClone this repo.Build codebase withcargo build --releaseContributingFollow the steps below to contribute to the project. Please ensure code is properly tested and the total lines of code
is not more than 20 lines for each pull requestFork the ProjectCreate your Feature BranchCommit your Changes.Push to the BranchOpen a Pull Request
Package: imageproxy
imageproxyis a small standalone WSGI application that dynamically
resizes images.It supports virtual hosting, so you can use the same instance to serve
assets for different domains.Example config file:[site:example.net]
root=/srv/example.net/web/media/images
prefix=/assets/media/images

[site:example.com]
root=/srv/example.com/web/media/images
prefix=/assets/media/imagesBy default only JPEG files can be resized, but if you’d like to make
GIFs and PNGs resizable, add the following:[type:image/gif]
resize=true

[type:image/png]
resize=trueYou can specify the configuration file location by giving its path in
theIMAGEPROXY_SETTINGSenvironment variable.If you want to use this with Paste, it comes with a sample config file.
Naturally, you’ll need Paste, PasteDeploy, and PasteScript to run it.
However, Paste isn’t required and theimageproxy.create_applicationcallable can be used with any WSGI server.
Package: image-puzzle-game
image-puzzle-gameA 3 x 3 grid semi-interactive image puzzle game built entirely using the Pillow Python library.Designed to be executed in an Interactive Python notebook environment.DemoAccess the demo notebookhereLog into your Google Account.Press the round play (run) button.Enjoy the game!How to PlayEnter the number of the tile you would like to move (displayed on the tiles from 1 to 8).Enter the position on the grid you would like to move the tile to.The 3 x 3 grid is labelled with positions from 1 to 9 starting from the upper left corner down to the lower right.Each tile can only be moved either vertically or horizontally to an adjacent empty position but not diagonally.Move the tiles until they have aligned to form the correct image.
Package: image-px-to-text
This library/package will give all the info (colors of the pixels) of any image you chooseIt has only one function called do()
syntax is like this do(r'Path\to\image',boolean) # the boolean is 'True' 'False' this is optional.
the boolean value determines weather color output is in rgb or hsv. True for rgb (default), False for hsvMy website:https://chaoticcoder.netlify.app
Package: image-pyconverter-cli
image_pyconverter_cliCLI providing simple image conversion functionality in python.New features will be added as needed.Install$pipinstallimage_pyconverter_cliUninstall$pipuninstallimage_pyconverter_cliRenameA text file of the record before and after the conversion of the image is automatically created.1$ic_renamedirectory-containing-images--is_all_replaced_with_new_name--new_namenew-namedirectry-containing-images
├──dir1
│├──dir1-image.png
│└──dir2
│└──dir2-image.png
└──image.png


directry-containing-imagesg-images
├──dir1
│├──new-name002.png
│└──dir2
│└──new-name003.png
└──new-name001.png2$ic_renamedirectory-containing-images--chars_before_replacementdir1dir2--chars_after_replacementnewdir1newdir2directry-containing-images
├──dir1
│├──dir1-image.png
│└──dir2
│└──dir2-image.png
└──image.png


directry-containing-images
├──dir1
│├──newdir1-image.png
│└──dir2
│└──newdir2-image.png
└──image.png3$ic_renamedirectory-containing-imagesdirectry-containing-images
├──dir1
│└──ＡＢＣ.png
└──image００１.png


directry-containing-images
├──dir1
│└──abc.png
└──image001.png4$ic_renamedirectory-containing-images--is_separator_and_delimiter_replaced--separator_directry-containing-images
├──dir1
│├──dir1-image.png
│└──dir2
│└──dir2-image.png
└──imageimage.png


directry-containing-images
├──dir1
│├──dir1_image.png
│└──dir2
│└──dir2_image.png
└──image_image.png5$ic_renamedirectory-containing-images--alternative_unavailable_char_in_windows-directry-containing-images
└──-_,!(:*?<>|¥)あabc.png


directry-containing-images
└──-_,!(--------)あabc.png6$ic_renamedirectory-containing-images--alternative_url_encoded_charXdirectry-containing-images
└──-_,!()abcあ*&^%.png


directry-containing-images
└──-_XXXXabcXXXXXX.png7$ic_renamedirectory-containing-images--prefixprefix--suffixsuffix--separator-directry-containing-images
└──image.png


directry-containing-images
└──prefix-image-suffix.png8$ic_renamedirectory-containing-images--prefixprefix--suffixsuffix--separator-directry-containing-images
└──image.png


directry-containing-images
└──prefix-image-suffix.png9$ic_renamedirectory-containing-images--is_serial_number_addeddirectry-containing-images
├──dir1
│├──dir1-image.png
│└──dir2
│└──dir2-image.png
└──image.png


directry-containing-images
├──dir1
│├──dir1-image002.png
│└──dir2
│└──dir2-image003.png
└──image001.png10$ic_renamedirectory-containing-images--is_output_to_same_dir--separator-directry-containing-images
├──dir1
│├──image.png
│└──dir2
│└──image.png
└──image.png


directry-containing-images
├──dir1-image.png
├──dir2-image.png
└──image.png
Package: imagepypelines-tools
This repository contains two docker images which provide a full development
environment for those doing image processing, computer vision, or machine
learning development in python.It includes:imagepypelines (obviously :p)Opencv (an optimized build)tensorflowkerasPillowsklearnthe usual suspects (scipy, numpy, etc)This repository is an accessory to the open source image and dataImagePypelinesnote that GPU usage requires separate installation of Nvidia-DockerThese images are built to work in tandem with the pip package imagepypelines-tools.
To enter this docker environment simply:pip install imagepypelines
imagepypelines shellimagepypelines shellStandardpip install imagepypelines
imagepypelines shellGPU Accelerated (limited to Linux hosts with Nvidia-Docker)pip install imagepypelines
imagepypelines shell --gpu
Package: image-pyqt
A PyQt5/PySide2 Image Widget for quickly displaying OpenCV Mat Image!Modified @ 2017.07.26 16:47:36 CST1. Dependency, Install and Uninstall1.1 Dependencynumpyopencv-python(oryoucancompilecv2fromtheOpenCVSource!)PyQt5/PySide21.2 Install$gitclonehttps://github.com/Image-Py/imagepyqt$cdimagepyqt$ls...imagepyqt/setup.py$python3setup.pyinstall...1.3 Uninstallpip3uninstallimagepyqt2. Usage2.1 Test the demo$python3-m"imagepyqt.demos"2.2 A simple demo""" [1] Read Image in cv2 """importcv2imagename="/home/auss/Pictures/test.png"## TODO: change to your image path!img=cv2.imread(imagename)""" [2] Display the OpenCV Mat in imagepyqt """importimagepyqtasipqipq.imshow(img,"Test ImagePyQt")ipq.runQApp()2.3  Other demosimportos,sysfromimagepyqt.widgetsimportimwidgetfromimagepyqt.myQtimportmkQApp,runQApp,QtWidgetsfromimagepyqtimportqimshow## TODO: change to your own imagepath!imagename="/home/auss/Pictures/test.png"deftest1():"""A Simple demo"""importcv2img=cv2.imread(imagename)qApp=mkQApp()qimshow(img,"Test MyImageWidget[2]")runQApp()deftest2():"""Another Simple demo"""importcv2img=cv2.imread(imagename)qApp=mkQApp()win=imwidget.MyImageWidget()win.setImage(img)win.setWindowTitle("Test MyImageWidget[1]")win.show()runQApp()defrun():test1()test2()if__name__=="__main__":run()
Package: image-quality
Image QualityDescriptionImage quality is an open source software library for Automatic Image
Quality Assessment (IQA).DependenciesPython 3.8(Development) DockerInstallationThe package is public and is hosted in PyPi repository. To install it in
your machine runpip install image-qualityExampleAfter installingimage-qualitypackage, you can test that it was
successfully installed running the following commands in a python
terminal.>>> import imquality.brisque as brisque
>>> import PIL.Image

>>> path = 'path/to/image'
>>> img = PIL.Image.open(path)
>>> brisque.score(img)
4.9541572815704455DevelopmentIn case of adding a new tensorflow dataset or modifying the location of a zip file, it is
necessary to update the url checksums. You can find the instructions in the followingtensorflow documentation.The steps to create the url checksums are the following:1. Take the file with the dataset configuration (e.g. live_iqa.py) an place it in thetensorflow_datasetsfolder. The folder is commonly placed in${HOME}/.local/lib/python3.8/site-packagesif you
install the python packages using theuserflag.2. Modify the__init__.pyof thetensorflow_datasetsto import your new dataset.
For examplefrom .image.live_iqa import LiveIQAat the top of the file.3. In your terminal run the commands:touch url_checksums/live_iqa.txt
python -m tensorflow_datasets.scripts.download_and_prepare  \
   --register_checksums  \
   --datasets=live_iqa4. The filelive_iqa.txtis going to contain the checksum. Now you can copy and paste it to your
project’surl_checksumsfolder.SponsorMaintainerRicardo Ocampo
Package: image-quantizer
Image QuantizerSimple Python package to convert an image into a quantized image using a customizable palette. Resulting image can be
displayed by ePaper displays such as Waveshare displays.InstallationIt can be installed as a PyPi packagepip install --user image-quantizerIt can also be installed manuallygit clone https://github.com/lobis/image-quantizer
cd image-quantizer
python3 setup.py install --userUsagefrom image_quantizer import quantize_image

with Image.open("tests/data/cliff.jpg") as image:
    quantized_image = quantize_image(image, palette=PALETTES["WAVESHARE-EPD-7COLOR"])
    quantized_image.save("cliffs-quantized.png")Custom palettefrom image_quantizer import quantize_image, PALETTES

# Existing palette names
print(PALETTES)

palette = [
    [0, 0, 0],  # white
    [255, 255, 255],  # black
    [0, 0, 255],  # blue
    [0, 255, 0],  # green
]

with Image.open("tests/data/cliff.jpg") as image:
    quantized_image_custom = quantize_image(image, palette=palette)
    quantized_image_custom.show()Split by PaletteIn some cases such as highlightedhere, it might be useful to split
an image into its colors. This is necessary to display the image in a waveshare RED-WHITE-BLACK display.from image_quantizer import quantize_image, split_image_by_color

with Image.open("tests/data/cliff.jpg") as image:
    quantized_image = quantize_image(image, palette=PALETTES["BLACK-WHITE-RED"])
    split_images = split_image_by_color(image)
    for color, image in split_images:
        image.show()Original image:Single palette color images:
Package: image-recognition-vladdemo
Python package with image recognition functionality by vladdemoThis package was developed for scientific purposes, the use of which is available to everyoneHow to installThe package will be installed using pipSet up a virtual environment for your new Python projectpython3 -m venv image_recognition_venvAfter that, go to your project and open the virtual environment directory, activate it.source <path_to_venv>/bin/activateInstalling the packagepip install image-recognition-vladdemoUsing functionality in a projectImportsfromimage_recognition_vladdemo.mainimportImageRecognitionThis import allows you to get the main classMain Variablesimage_path="new.png"language="eng"The path to the image can be specified direct or relative. Next we indicate the language.Creating an Objectimage=ImageRecognition(image_path,language)Getting text from an imagetext=image.get_text_from_photo()Congratulations. You got the text from the image.author="Vlad Demchenko"Additional instructions for creating your own Python package and uploading to PyPILinuxpython3 -m pip install --upgrade pipCreate a project with the following structureimage_recognition/
├── LICENSE
├── pyproject.toml
├── README.md
├── setup.cfg
├── src/
│   └── image_recognition_demo_test/
│       ├── __init__.py
│       └── main.py
└── tests/touch pyproject.toml
touch setup.cfg
mkdir src
mkdir src/image_recognition_demo_test
touch src/image_recognition_demo_test/__init__.py
touch src/image_recognition_demo_test/main.py
mkdir testspyproject.tomlThis file tells tools like pip and build how to create your project[build-system]
requires = [
    "setuptools>=42",
    "wheel"
]
build-backend = "setuptools.build_meta"build-system.requires gives a list of packages that are needed to build your package. Listing something here will only make it available during the build, not after it is installed.build-system.build-backend is the name of Python object that will be used to perform the build. If you were to use a different build system, such as flit or poetry, those would go here, and the configuration details would be completely different than the setuptools configuration described below.Setup.cfg setupUsing setup.cfg is a best practice, but you could have a dynamic setup file using setup.py[metadata]
name = example-pkg-YOUR-USERNAME-HERE
version = 0.0.1
author = Example Author
author_email = author@example.com
description = A small example package
long_description = file: README.md
long_description_content_type = text/markdown
url = https://github.com/pypa/sampleproject
project_urls =
    Bug Tracker = https://github.com/pypa/sampleproject/issues
classifiers =
    Programming Language :: Python :: 3
    License :: OSI Approved :: MIT License
    Operating System :: OS Independent

[options]
package_dir =
    = src
packages = find:
python_requires = >=3.6

[options.packages.find]
where = srcRunning the buildMake sure your build tool is up to dateLinuxpython3 -m pip install --upgrade buildCreate the buildpython -m buildUploading - preLinuxpython3 -m pip install --upgrade twineUploadLinuxpython3 -m twine upload --repository pypi dist/*