Saravanan666/pypi-org huggingface dataset:
Package: pixel-perfect
Pixel PerfectA versatile Python package leveraging TensorFlow's machine learning model for efficient image comparisons. Designed to seamlessly integrate with Selenium, it empowers developers with powerful tools for UI validations, making it a valuable asset for automated testing and visual verification in web applications.InstallationYou can install pixel_perfect using pip:pipinstallpixel_perfectUsage: Image ComparisonTheimage_similaritymethod allows you to compare two images and receive a boolean value indicating whether the images are similar or not. The comparison is performed with a default threshold of 0.1, providing a balance between strictness and leniency. You can customize the threshold by adjusting the value.frompixel_perfectimportimage_similarity# Provide paths to the images for comparisonimage_path1image_path2# Compare the images with default thresholdisImageSimilar=image_similarity(image_path1,image_path2)# Compare the images with custom thresholdisImageSimilar=image_similarity(image_path1,image_path2,1)You can utilize theimage_similarity_scoremethod to compare two images and obtain the similarity score. Here's a simple example:frompixel_perfectimportimage_similarity# Provide paths to the images for comparisonimage_path1image_path2# Compare the imagessimilarity_score=image_similarity(image_path1,image_path2)
Package: pixelpin-auth-core
# Python Social Auth - Core[![Build Status](https://travis-ci.org/python-social-auth/social-core.svg?branch=master)](https://travis-ci.org/python-social-auth/social-core)
[![Donate](https://img.shields.io/badge/Donate-PayPal-orange.svg)](https://www.paypal.com/cgi-bin/webscr?cmd=_donations&business=matiasaguirre%40gmail%2ecom&lc=US&item_name=Python%20Social%20Auth&no_note=0&currency_code=USD&bn=PP%2dDonationsBF%3abtn_donate_SM%2egif%3aNonHostedGuest)Python Social Auth is an easy to setup social authentication/registration
mechanism with support for several frameworks and auth providers.## DescriptionThis is the core component of the python-social-auth ecosystem, it
implements the common interface to define new authentication backends
to third parties services, implement integrations with web frameworks
and storage solutions.## DocumentationProject documentation is available athttp://python-social-auth.readthedocs.org/.## Setup`shell $ pip installsocial-auth-core`## ContributingSee the [CONTRIBUTING.md](CONTRIBUTING.md) document for details.## VersioningThis project follows [Semantic Versioning 2.0.0](http://semver.org/spec/v2.0.0.html).## LicenseThis project follows the BSD license. See the [LICENSE](LICENSE) for details.## DonationsThis project is maintened on my spare time, consider donating to keep
it improving.[![Donate](https://img.shields.io/badge/Donate-PayPal-orange.svg)](https://www.paypal.com/cgi-bin/webscr?cmd=_donations&business=matiasaguirre%40gmail%2ecom&lc=US&item_name=Python%20Social%20Auth&no_note=0&currency_code=USD&bn=PP%2dDonationsBF%3abtn_donate_SM%2egif%3aNonHostedGuest)
Package: pixelpin-auth-django
# Python Social Auth - Django[![Build Status](https://travis-ci.org/python-social-auth/social-app-django.svg?branch=master)](https://travis-ci.org/python-social-auth/social-app-django)
[![Donate](https://img.shields.io/badge/Donate-PayPal-orange.svg)](https://www.paypal.com/cgi-bin/webscr?cmd=_donations&business=matiasaguirre%40gmail%2ecom&lc=US&item_name=Python%20Social%20Auth&no_note=0&currency_code=USD&bn=PP%2dDonationsBF%3abtn_donate_SM%2egif%3aNonHostedGuest)Python Social Auth is an easy to setup social authentication/registration
mechanism with support for several frameworks and auth providers.## DescriptionThis is the [Django](https://www.djangoproject.com/) component of the
[python-social-auth ecosystem](https://github.com/python-social-auth/social-core),
it implements the needed functionality to integrate
[social-auth-core](https://github.com/python-social-auth/social-core)
in a Django based project.## Django versionThis project will focus on the currently supported Django releases as
stated on the [Django Project Supported Versions table](https://www.djangoproject.com/download/#supported-versions).Backward compatibility with unsupported versions won’t be enforce.## DocumentationProject documentation is available athttp://python-social-auth.readthedocs.org/.## Setup`shell $ pip installsocial-auth-app-django`## ContributingSee the [CONTRIBUTING.md](CONTRIBUTING.md) document for details.## VersioningThis project follows [Semantic Versioning 2.0.0](http://semver.org/spec/v2.0.0.html).## LicenseThis project follows the BSD license. See the [LICENSE](LICENSE) for details.## DonationsThis project is maintened on my spare time, consider donating to keep
it improving.[![Donate](https://img.shields.io/badge/Donate-PayPal-orange.svg)](https://www.paypal.com/cgi-bin/webscr?cmd=_donations&business=matiasaguirre%40gmail%2ecom&lc=US&item_name=Python%20Social%20Auth&no_note=0&currency_code=USD&bn=PP%2dDonationsBF%3abtn_donate_SM%2egif%3aNonHostedGuest)
Package: pixelpin-auth-storage-sqlalchemy
# Python Social Auth - SQLAlchemy[![Donate](https://img.shields.io/badge/Donate-PayPal-orange.svg)](https://www.paypal.com/cgi-bin/webscr?cmd=_donations&business=matiasaguirre%40gmail%2ecom&lc=US&item_name=Python%20Social%20Auth&no_note=0&currency_code=USD&bn=PP%2dDonationsBF%3abtn_donate_SM%2egif%3aNonHostedGuest)Python Social Auth is an easy to setup social authentication/registration
mechanism with support for several frameworks and auth providers.## DescriptionThis is the [SQLAlchemy](http://www.sqlalchemy.org/) component of the
[python-social-auth ecosystem](https://github.com/python-social-auth/social-core),
it implements the needed functionality to integrate
[social-auth-core](https://github.com/python-social-auth/social-core)
into a project using SQLAlchemy as the storage solution.## DocumentationProject documentation is available athttp://python-social-auth.readthedocs.org/.## Setup`shell $ pip installsocial-auth-storage-sqlalchemy`## ContributingSee the [CONTRIBUTING.md](CONTRIBUTING.md) document for details.## VersioningThis project follows [Semantic Versioning 2.0.0](http://semver.org/spec/v2.0.0.html).## LicenseThis project follows the BSD license. See the [LICENSE](LICENSE) for details.## DonationsThis project is maintened on my spare time, consider donating to keep
it improving.[![Donate](https://img.shields.io/badge/Donate-PayPal-orange.svg)](https://www.paypal.com/cgi-bin/webscr?cmd=_donations&business=matiasaguirre%40gmail%2ecom&lc=US&item_name=Python%20Social%20Auth&no_note=0&currency_code=USD&bn=PP%2dDonationsBF%3abtn_donate_SM%2egif%3aNonHostedGuest)
Package: pixelpotion
PixelPotionPixelPotion is a command line tool based on Pillow for easy processing
of PNG, JPG, and GIF images. It provides a simple and intuitive
interface for performing common image operations such as resizing,
cropping, and retrieving GIF frames.FeaturesSupports PNG, JPG, and GIF image formatsResizeimages to a specified width and heightCropimages to a specified size and positionRetrieveindividual frames from animated GIFsSave processed images to diskInstallationPixelPotion can be installed via pip:pipinstallpixelpotionUsagePixelPotion can be used via the command line interface. Here are some
examples:Original image:Resize to 100x100:# Resize an image to 400x400 pixelsppresizeinput.pngoutput.png--width100--height100100x100Crop to 200x100 JPEG:# Crop an image to 200x100 pixelsppconvert-finput.png-ooutpu.jpg-tjpg--width200--height100200x100Extract first frame of animated GIF:# Extract the first frame of an animated GIFppgifsplit-finput.gif-otmp-pframeFor a full list of available commands and options, please refer to the
Command Line Interface Documentation in the project wiki(TODO).APIPixelPotion is built on top of the popular Pillow library and extends
its functionality. For more information on the API, please refer to the
API Documentation in the project wiki(TODO).ContributingContributions to PixelPotion are always welcome! If you鈥檇 like to
contribute, please read the Contributing Guide and submit a pull
request(TODO).LicensePixelPotion is licensed under the MIT License.
Package: pixelripper
PixelripperPackage and CLI for downloading media from a webpage.Install with:pip install pixelripperPixelripper contains a class called PixelRipper and a subclass called PixelRipperSelenium.PixelRipper uses the requests library to fetch webpages and PixelRipperSelenium uses a selenium based engine to do the same.The selenium engine is slower and requires more resources, but is useful for webpages
that don't render their media content without a JavaScript engine.It can use either Firefox or Chrome browsers.Note: You must have the appropriate webdriver for your machine and browser
version installed in order to use PixelRipperSelenium.pixelripper can be used programmatically or from the command line.Programmatic usage:from pixelripper import PixelRipper
from pathlib import Path
ripper = PixelRipper()
# Scrape the page for image, video, and audio urls.
ripper.rip("https://somewebsite.com")
# Any content urls found will now be accessible as members of ripper.
print(ripper.image_urls)
print(ripper.video_urls)
print(ripper.audio_urls)
# All the urls found on a page can be accessed through the ripper.scraper member.
all_urls = ripper.scraper.get_links("all")
# The urls can also be filtered according to a list of extensions 
# with the filter_by_extensions function.
# The following will return only .jpg and .mp3 file urls.
urls = ripper.filter_by_extensions([".jpg", ".mp3"])
# The content can then be downloaded.
ripper.download_files(urls, Path.cwd()/"somewebsite")
# Alternatively, everything in ripper.image_urls, ripper.video_urls, and ripper.audio_urls
# can be downloaded with just a call to ripper.download_all()
ripper.download_all(Path.cwd()/"somewebsite")
# Separate subfolders named "images", "videos", and "audio"
# will be created inside the "somewebsite" folder when using this function.Command line usage:>pixelripper -h
usage: pixelripper [-h] [-s] [-nh] [-b BROWSER] [-o OUTPUT_PATH] [-eh [EXTRA_HEADERS ...]] url

positional arguments:
  url                   The url to scrape for media.

options:
  -h, --help            show this help message and exit
  -s, --selenium        Use selenium to get page content instead of requests.
  -nh, --no_headless    Don't use headless mode when using -s/--selenium.
  -b BROWSER, --browser BROWSER
                        The browser to use when using -s/--selenium. Can be 'firefox' or 'chrome'. You must have the appropriate webdriver installed for your machine and browser version in order to use the selenium engine.
  -o OUTPUT_PATH, --output_path OUTPUT_PATH
                        Output directory to save results to. If not specified, a folder with the name of the webpage will be created in the current working directory.
  -eh [EXTRA_HEADERS ...], --extra_headers [EXTRA_HEADERS ...]
                        Extra headers to use when requesting files as key, value pairs. Keys and values whould be colon separated and pairs should be space separated. e.g. -eh Referer:website.com/page Host:website.com
Package: pixelsort-cli
pixelsort cliA simple python command line tool for sort pixels in an image.
Based on the works ofKim Asendorf.The script blocks pixels into dark and light areas using a contrast mask.
Then it sorts the pixels in a given direction via their luminance.You can increase/decrease the contrast by setting the threshold.You can also invert the mask to sort the light pixels instead of the dark ones.UsageInstallpipinstallgit+https://github.com/Blotz/pixelsort-cliorpipinstallpixelsort-cliExamplespixelsort--helpusage:pixelsort[-h][--thresholdTHRESHOLD][--sort_brightestSORT_BRIGHTEST][--reverse_sortingREVERSE_SORTING][--outputOUTPUT]image_pathangle

Commandlinetoolforsortingpixelsinimages

positionalarguments:image_pathpathtoimageangleanglethattheimageissorted.0°isup.[0,360]options:-h,--helpshowthishelpmessageandexit--thresholdTHRESHOLDthresholdforcontrast.[-1.0,1.0]Default:1.0--sort_brightestSORT_BRIGHTESTSortthebrightestareaoftheimage.Default:True--reverse_sortingREVERSE_SORTINGSortsthepixelsfromlightesttodarkestinsteadofdarkesttolightest.Default:False--outputOUTPUTpathtooutputfilepixelsortdata/mountains.jpg90--threshold1.2LicenseMIT Ferdinand Theil
Package: pixelsparser
pixelsparserA Python library that allows users to import their Pixels JSON data and use it in their python scripts.InstallationInstall the library using pip:pipinstallpixelsparserUsageimportpixelsparserpixels=pixelsparser.load("location/to/data.json")# Access the mood of the first pixelprint(pixels[0].mood)# Access the notes of the second pixelprint(pixels[1].notes)CreditsThis library was created to parse data from the Pixels app by Teo Vogel, available on theGoogle Play Storeand on theApp Store
Package: pixeltable
PixeltablePixeltable presents a dataframe-like interface to image and video data.InstallationInstall PostgresOn MacOS,postgresapp.comis a convenient way to do that.pip install pixeltableInstall additional dependenciesInstall PyTorch (required for CLIP): seehereInstall CLIP fromhereSetupPixeltable requires a home directory and a Postgres database, both are created automatically the first time you create a Pixeltable client (see below).
The location of the home directory is~/.pixeltable(or the value of thePIXELTABLE_HOMEenvironment variable);
the name of the Postgres database ispixeltable(or the value of thePIXELTABLE_DBenvironment variable).OverviewImport convention:import pixeltable as ptCreate a clientcl = pt.Client()Create a databaseClient.create_db('db1')Create a table with video datac1 = Column('video', VideoType())
c2 = Column('frame_idx', IntType())
c3 = Column('frame', ImageType())
Db.create_table(
    'video_table', [c1, c2, c3],
    extract_frames_from='video',
    extracted_frame_col='frame',
    extracted_frame_idx_col='frame_idx',
    extracted_fps=1)Query tableH1H2Look at 10 rowsTable.show(10)Look at row for frame 15t[t.frame_idx == 15].show()Look at all frames after index 15t[t.frame_idx >= 15][t.frame].show(0)
Package: pixelti
Pixelti - Transform Your Pictures into Pixel ArtPixelti is a Python program designed to effortlessly convert any image into captivating pixel art. Follow these simple steps to get started with Pixelti on your local machine.PrerequisitesEnsure that you have the following installed on your system:Python 3.6 or laterpipmakeSetupClone the Pixelti repository to your local machine.gitclonehttps://github.com/your-username/pixelti.gitNavigate to the project directory.cdpixeltiRun the following command to initialize the required environment.makeinitInstallationAfter initialization, install Pixelti dependencies with:makeinstallWith this, your Pixelti environment is set up and ready to go.UsageExplore Pixelti's capabilities by running the program. Utilize the python --help command to view available options.Example Usage:pythoncli.pyhttp://image-url.dev/sampleimage.jpg--pixelsize10--save--filenamecool-pixelart.jpgAdjust the parameters according to your preferences--pixelsizeThis parameter determines how many original pixels will be combined into one pixel in the resulting pixel ar--saveSave pixel art into a file--filenameDefine output file name, default: random stringContributionIf you wish to contribute to Pixelti, please fork the repository, make your changes, and submit a pull request. Your contributions are highly appreciated!
Package: pixelyai-core
PixelyAI Core🧬IntroductionPixelyAI Core is the core component of PixelyAI, an AI assistant that helps businesses manage their customers and their
team more effectively. It provides a suite of tools for hosting and interacting with large language models (LLMs),
making it easy to integrate these powerful AI capabilities into your applications.Key FeaturesSupport for Multiple Backends:PixelyAI Core supports three popular backends for hosting LLMs:GGMLServe,TorchServe, andJaxServe. This flexibility allows you to choose the backend that best suits your needs and
infrastructure.Simplified API:PixelyAI Core provides an easy-to-use API for interacting with LLMs. This API makes it simple to
send queries to LLMs, receive responses, and handle errors.Gradio Integration:PixelyAI Core integrates seamlessly withGradio, a web framework for building interactive AI
applications. This integration allows you to create intuitive interfaces for interacting withLLMs, making it easier
for users to access their capabilities.BenefitsImproved Customer Support:Empower your customer support team with conversational AI capabilities, enabling them
to provide more personalized and efficient support.Enhanced Team Collaboration:Facilitate knowledge sharing and collaboration among team members through natural
language interactions.Automated Task Delegation:Automate routine tasks, such as report generation and data analysis, freeing up team
members to focus on more strategic initiatives.Getting StartedTo install PixelyAI Core, simply use the following command:pipinstallpixelyai-coreOnce installed, you can start using the PixelyAI Core API to interact with LLMs. For more information, please refer to
the official documentation.ConclusionPixelyAI Core is a powerful tool for businesses seeking to leverage the capabilities of LLMs to improve their customer
service, collaboration, and productivity. With its support for multiple backends, simplified API, PixelyAI Core provides
a versatile and user-friendly platform for integrating LLMs into your applications.
Package: pixel-zero
Welcome to the PixelZero repository!A zero boilerplate neopixel control library for the Raspberry PiInstallingPixelZero can be downloaded to your Raspberry Pi via PyPi. This will
install the library so you can use it with Python 3. We are also working
on a one line installer that will install the library and expamples, but
this is not ready yet. To install, fire up Terminal which you’ll find in
Menu > Accessories > Terminal on your Raspberry Pi desktop, which is
shown below:In the terminal window you have just opened, type the command below to
install the library (if you get any errors, check for spelling
mistakes):sudopip3installpixel-zeroContributing:If you want to contribute, you should first clone this repository,cdto the library directory on your Raspberry Pi, and then run:sudopython3setup.pyinstallDon’t forget to submit a pull request when contributing, this is the
best way for your code to get merged!0.0.1Initial Release0.0.2Bug Fixes0.0.3Added better way of doing set_item
Package: pix-framework
PIX FrameworkFramework for building process mining applications.InstallationThe package requiresPython 3.9+. You can install it from PyPI:pipinstallpix-frameworkReleasesYou can browse compiled releases in theReleasessection.DescriptionThepix_framework.discoverypackage besides root modules contains the following subpackages with additional information located in their README files:batch_processing_discoveryprioritization_discoverycase_attribute_discoveryThepix_framework.enhancementpackage besides root modules contains the following subpackages with additional information located in their README files:start_time_estimatorDevelopmentTestingTo run tests, use the following command:pytest-m"not benchmark"BenchmarkingTo run benchmarks, use the following command:pytest--benchmark-only
Package: pixhist
PixHistpip install pixhistPixHist - pixel histogram.Dependencies:Numba,NumPy, andMatplotlibto usepixhist.rendering.importmatplotlib.pyplotaspltfromnumbaimportnjitimportnumpyasnpimportpixhistimportpixhist.renderingExample 1: create a pixhist from a generatorThe generator should have no arguments, and return the valuesx, y:generator() -> x, yIt should be compiled with Numba'snjit/jit.@njitdefgen():"""A Clifford Attractor"""x,y=0,0whileTrue:yieldx,yx_=np.sin(2.27*y)+0.66*np.cos(2.27*x)y_=np.sin(1.13*x)+2.16*np.cos(1.13*y)x,y=x_,y_r=pixhist.estimate_range(gen,n_iter=100_000)r=pixhist.scale_range(r,1.2)N_ITER=1000_000W=500H=400hist=pixhist.from_gen(gen,N_ITER,W,H,range=r,make_xy_proportional=True,log=True)pixhist.rendering.plot(hist)plt.show()Example 2: using a generator factoryCreate a 'generator factory' to get around the fact that the generator should have no arguments.defget_clifford_generator(a,b,c,d,x_i=0,y_i=0):@njitdefgen():x,y=x_i,y_iwhileTrue:yieldx,yx_=np.sin(a*y)+c*np.cos(a*x)y_=np.sin(b*x)+d*np.cos(b*y)x,y=x_,y_returngenparams=[1.8,-1.4,-1.5,-0.71]gen=get_clifford_generator(*params)r=pixhist.estimate_range(gen,n_iter=100_000)N_ITER=1000_000W,H=500,500hist=pixhist.from_gen(gen,N_ITER,W,H,range=r,make_xy_proportional=False,log=True)pixhist.rendering.plot(hist,cmap='twilight')plt.show()Example 3: pixhist from arraysCreate a pixel histogram from two arrays of the same length.x_vals=np.random.random(100_000)y_vals=np.sin(x_vals)**2*np.random.random(100_000)W,H=200,300hist=pixhist.from_arrays(x_vals,y_vals,W,H,make_xy_proportional=True,log=True)pixhist.rendering.plot(hist,cmap='nipy_spectral')plt.show()Example 4: the advantage of using generatorsYou can have a large number of iterations, since you don't need to store the arraysx_vals, y_valsin memory. (Time becomes the limiting factor).frommagic_timerimportMagicTimerparams=[1.8,-1.4,-1.5,-0.71]gen=get_clifford_generator(*params)r=pixhist.estimate_range(gen,n_iter=100_000)N_ITER=100_000_000W,H=500,500t=MagicTimer()hist=pixhist.from_gen(gen,N_ITER,W,H,range=r,make_xy_proportional=False,log=True)print('Time elapsed:',t)pixhist.rendering.plot(hist,cmap='twilight')plt.show()Time elapsed: 8.4 seconds
Package: pixhostuploader
Unofficial Python 3.2+ upload client for pixhost.org image sharing
website.Usageimport pixhostuploader as pixhost

uploaded = pixhost.upload('image.jpg')

print(uploaded)Uploader returns 3 URLs for each image: thumbnail, full size image and a
its page on pixhost.org.{
    'thumb_image': '...',
    'full_size_image': '...',
    'page_url': '...',
}You can also upload multiple images at once.images = [
    'image.jpg',
    'another_image.jpg',
]
uploaded = pixhost.upload(images)Uploader then returns alistof URLs for each uploaded image.[
    {
        'thumb_image': '...',
        'full_size_image': '...',
        'page_url': '...',
    }, {
        'thumb_image': '...',
        'full_size_image': '...',
        'page_url': '...',
    }
]Maximum image size on pixhost.org is 10 MB so if you try to upload a
larger file the upload function throwsTooLargeImageFormatexception.Also in case the upload fails for some reason (upload page doesn’t
return200code)UploadFailedis thrown.
Package: pixian-ai
pixian-aiPython SDK forpixian.ai.What is it?Remove image backgrounds.Install$pipinstallpixian-aiUsageBasicfrompixian_aiimportPixianAIclient=PixianAI(api_id="PIXIAN-AI-API-ID",api_secret="PIXIAN-AI-API-SECRET",)img=client.remove_background("/path/to/input.jpeg")img.save("/path/to/output.jpeg")You can also use:client.remove_background(image_base64="base64encodedimage==")# orclient.remove_background(image_url="https://imageurl.com/test.jpeg")Advancedclient.remove_background(image_path="/path/to/image.jpeg",max_pixels=100,background_color="#0055FF"...)Reference:https://pixian.ai/apiAll parameters described in the API spec above replace period (.) with underscore (_). For example, if the parameter isbackground.color, the SDK will usebackground_color.ContributingFeel free to open a PR for any changes!Testing$python-munittestdiscover-stests-p'test_*.py'Made with ❤️ by@mitchbregs