Saravanan666/pypi-org huggingface dataset:
Package: pyimgaug3d
Pyimgaug3dA 3DGPUaugmentation library. This library is work-in-progress and will be constantly updated with more augmentation methods. The current supported ones are grid warp 3D, flip  3D and identity. As all the augmentation methods are implemented in TensorFlow, a Cuda compatible GPU is required to take advantage of increases speeds.Installationpip install pyimgaug3dExample Usagefrom pyimgaug3d.augmentation import GridWarp, Flip, Identity
from pyimgaug3d.augmenters import ImageSegmentationAugmenter

img = load_img... # shape=(H,W,D,C)
seg = load_seg... # shape=(H,W,D,C)(one hot encoded)

# This augmenter automatically rounds the segmentation mask
aug = ImageSegmentationAugmenter()
aug.add_augmentation(GridWarp(grid=(4, 5, 5), max_shift=10))
aug.add_augmentation(Flip(0))
aug.add_augmentation(Identity())

aug_img, aug_seg = aug([img, seg]) # call to perform augmentation, each time an augmentation method is sampled at random.CitationThis library is published along with the following paperS.  Liu,  W.  Dai,  C.  Engstrom,  J.  Fripp,  P.  B.  Greer,  S.  Crozier,J. A. Dowling, 
and S. S. Chandra, “Fabric Image Representation Encoding Networks for Large-scale 3D Medical 
Image Analysis,”arXiv e-prints, p. arXiv:2006.15578, Jun. 2020.
Package: pyimgbb
Imgbb Python Client LibraryFeaturesEasy image uploading to Imgbb's servers.Supports JPG, PNG, GIF, base64, and URL image sources.Automatic retry with configurable retry intervals for robustness.Clear and intuitive API for quick integration.Installationits recommended to use a virtual environment to install the packagepipinstallimgbb-clientUsagefromimgbb_clientimportImgbbClientclient=ImgbbClient("your-api-key")# Upload image from URLresult=client.upload("https://example.com/image.jpg",name="My Image",expiration=3600)ChangelogFor a list of changes and release notes, see theCHANGELOGfile.LicenseFor license information, please seeLICENSEContributingContributions are welcome! If you encounter any issues or have suggestions for improvements, feel free to open an issue or submit a pull request.Built with ❤️ byAdivhaho Mavhungu
Package: pyimgbox
Python 3.6+ library for uploading images tohttps://imgbox.com/.imgbox-cliis a command line tool that uses pyimgbox.Installationpyimgbox is onPyPI.$pipinstallpyimgboxUsageasyncwithpyimgbox.Gallery(title="Hello, World!")asgallery:asyncforsubmissioningallery.add(files):pprint.pprint(submission)Seeexamples.pyfor more examples.
Package: pyimgconvert
Quick OverviewPython wrapper around Linux CLI “convert” which works as an entrypoint around the Linux image processing ‘ImageMagick’.Overviewpyimgconvertis a Python utility which acts as a wrapper around themagick convertLinux CLI program that is useful for convert input images to the desired format and saves them in an output directory specified by the user.This utility requires you to pass aninputDir,inputFile,outputDir,outputFile, and all the other optional CLI arguments that theconvertaccepts as a string to theargsargument ofpyimgconvert.AssumptionsThis document assumes UNIX conventions and abashshell. The script should work fine under Windows, but we have not actively tested on that platform – our dev envs are Linux Ubuntu and macOS.InstallationPython moduleOne method of installing this script and all of its dependencies is by fetching it fromPyPI.pip3installpyimgconvertDocker containerWe also offer a docker container ofpyimgconvertas a ChRIS-conformant platform plugin herehttps://github.com/FNNDSC/pl-imageconvert– please consult that page for information on running the dockerized container. The containerized version exposes a similar CLI and functionality as this module.How to Usemgz2imgslicesneeds at a minimum the following required command line arguments:-I|--inputDir<inputDir>: The input directory which contains the input image that is to be converted-i|--inputFile<inputFile>: The input image file to convert.-O|--outputDir<outputDir>: The output directory which will store the output image-o|--outputFile<outputFile>: The output file name (with extension) to save the output imageOptional:-a|--args"ARGS: <otherArgs>": Pass all the other arguments thatconvertaccepts to this argument using the double quotes.ExamplesFirst, let’s create a directory, saydevelwherever you feel like it. We will place some test data in this directory to process with this plugin.cd~/mkdirdevelcddevelexportDEVEL=$(pwd)Make sure your current working directory isdevel. At this juncture it should contain the image file that you want to convert.Create an output directory namedresultsindevel.mkdirresults&&chmod777resultsExample-1pyimgconvert--inputDir${DEVEL}/\--inputFileimage.jpg\--outputDir${DEVEL}/results/\--outputFileimage.png\Example-2pyimgconvert--inputDir${DEVEL}/\--inputFileimage.jpg\--outputDir${DEVEL}/results/\--outputFileimage.png\--args"ARGS: -colorspace RGB    -resize 40% "The output image will be stored in theresultsdirectory.
Package: pyimgdown
pyimgdown is a python module for downloading image using url and resizing.Installationpip install pyimgdownFeaturesdownload image from url.resize and attach thumbnail file suffix.single url mode and file (url list file) mode.specify download directory.Usageurl>>> import pyimgdown
>>> url = "https://localhost/test.jpeg"
>>> pyimgdown.download(url=url)
    ...
    => {'image': './PyImgDown/test.jpeg'}file>>> import pyimgdown
>>> pyimgdown.download(file="./url_list.txt")
...
    [
    {'image': u'./PyImgDown/test1.jpg'},
    {'image': u'./PyImgDown/test2.jpg'},
    {'image': u'./PyImgDown/test3.jpg'},
    {'image': u'./PyImgDown/test4.jpg'},
    {'image': u'./PyImgDown/test5.jpg'},
    {'image': u'./PyImgDown/test6.jpg'},
    {'image': u'./PyImgDown/test7.jpg'},
    {'image': u'./PyImgDown/test8.jpg'},
    {'image': u'./PyImgDown/test9.jpg'},
    {'image': u'.PyImgDown/test10.jpg'}
    ]url+thumbnail>>> pyimgdown.download(url="https://localhost/test.jpeg", thumbnail_size=(64,64))
    {
    'image': './PyImgDown/test.jpeg',
    'thumbnail': './PyImgDown/test_thumbnail.jpeg'
    }url+thumbnail+download directory>>> pyimgdown.download(url="https://localhost/test.jpeg", thumbnail_size=(64,64), download_dir="./download")
    {
    'image': './download/test.jpeg',
    'thumbnail': './download/test_thumbnail.jpeg'
    }url+thumbnail+download directory+thumbnail_file_suffix>>> pyimgdown.download(url="https://localhost/test.jpeg", thumbnail_size=(64,64), download_dir="./download", thumbnail_file_suffix="_thumb")
    {
    'image': './download/test.jpeg',
    'thumbnail': './download/test_thumb.jpeg'
    }
Package: py-img-editor
py-img-editor: image Editor in the browser written in pythonInstallationpip install py-img-editorUsageTo start the image editor up, runpy-img-editor --startGo tohttp://127.0.0.1:8000/to use itTo stop it, runpy-img-editor --stopDisclaimerThis is definitely a WIP. And there are probably a lot of ways I'm not following "best practices".
Package: pyimg-process
pyimg-processThepyimg-processpackage is a Python library that provides simple and expressive manual image processing techniques. It aims to provide an easy toolkit for begginer users in order to develop their image treatment projects. It is already well on its way towards this goal.Main FeaturesHere are some of the implemented features:Easy way to read, write and display imagesImage resizing to any dimensionRGB to grayscale conversionImage blurring and sharpening methodsImage filtering by thresholdingVisualization of the histogram of the imageInverse image obtentionInstallationUse the package managerpipto install pyimage.pipinstallpyimg-processUsageimportpyimg_process# loads 'image' from 'path'img=pyimg_process.Methods.read_image('path','image')# converts img to grayscalegray=pyimg_process.Methods.grayscale(img)# sharpen img with a 100x100 kernelsharp=pyimg_process.Methods.sharpen(img,100)# displays both imagespyimg_process.Methods.show_image(img)pyimg_process.Methods.show_image(gray)pyimg_process.Methods.show_image(sharp)DependenciesNumPy- Adds support for large, multi-dimensional arrays, matrices and high-level mathematical functions to operate on these arraysMatplotlib- Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible.OpenCV- OpenCV provides a real-time optimized Computer Vision library, tools, and hardware.ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.LicenseMIT
Package: pyimgtool
pyimgtoolImage compression/watermarking using pillow. Useful for photographers to prep files for web sharing.FeaturesResize/thumbnail images to maximum or minimum dimensionsImage watermarkingText watermarkingJPEG compressionInstallSimply runpip install pyimgtoolTodoAutomatically find best region for watermarkingSet text watermark color based on target regionCreate specific print sizes at 300 dpiAdd padding if image is smaller than print size
Package: pyimgurapi
PyImgurAPIA Python SDK for the Imgur API.OverviewThe package is supposed to be in strict accordance with theImgur's documentation, i.e. description for any endpoint implemented in the SDK can also be found there.The package does not have any third-party dependencies; it requires only Python 3.7+.Alternatives:PyImgurwas originally an official client for Imgur, but it seems to be deprecated now.imgur-pythona relevant unofficial SDK for Imgur.InstallationUsing pip:$pipinstallpyimgurapiFirst authenticationRegister your applicationto getclient_idandclient_secret.Open the next URL in a browser:https://api.imgur.com/oauth2/authorize?client_id=<your_client_id>&response_type=token(replace<your_client_id>with the actual ID)Allow authentication for a client.Copy therefresh_tokenvalue from the URL field.Then you can authenticate your client:frompyimgurapiimportImgurAPIapi=ImgurAPI(refresh_token="<refresh_token>",client_id="<client_id>",client_secret="<client_secret>",)api.auth()Basic usageGetting info about an image:frompyimgurapiimportImgurAPIapi=ImgurAPI(refresh_token="<refresh_token>",client_id="<client_id>",client_secret="<client_secret>",)api.auth()meme_image=api.image.get_image("6yHmlwT")Then you can access attributes of the response using a dot-notation:print(meme_image.data.link)or using a subscript-notation:print(meme_image["data"]["link"])Uploading a new image:frompyimgurapiimportImgurAPIapi=ImgurAPI(refresh_token="<refresh_token>",client_id="<client_id>",client_secret="<client_secret>",)api.auth()filename="cat1.jpg"withopen(filename,'rb')asf:new_image=api.image.upload(f,filename,title="New image",# optionaldescription="Absolutely new image"# optional)Then you can access attributes of the new image as well:print(new_image.data.link)ContributingSee thecontributing guidelines.LicenseMIT
Package: pyimgutil
Python Image Utility (pyimgutil)AboutThis is a simple command-line utility, written in Python, for individual or
batch image processing.There are a number of excellent programs out there that already do what this
program does, but sometimes a quick, lightweight, solution is nice to have
handy, too.Features:convertcropresizerotatetransposechange qualityIf you find this program useful and there is a feature you would like to
suggest, seeCONTRIBUTING.How to Get StartedCompatibilityIf you're running Python 3.7+ on any operating system, you're most likely
good-to-go.For more details, view thecompatiblity docs.InstallationThis program is available through pip. Runningpip install pyimgutilwill
install it.For more details, view theinstallation docs.UsageAfter installing,pyimgutil -hwill help you get started.For command explanations and examples, view theusage docs.ContributingPlease report any bugs to theGitLab issue tracker.
SeeCONTRIBUTINGfor more details.CreditsBig thanks to the Pillow team for providing such a powerful and user-friendly
image processing library.LicenseThis program is free software and is licensed under the GNU General
Public License. For the full license text, view theLICENSEfile.Copyright © 2021 emerac
Package: pyimmutable
pyimmutableAPI documentationis hosted on GitHub pages.Introductionpyimmutable offers two immutable data types for Python3.6+: a mapping (similar todict, but, obviously immutable) and a sequence (likelist). It is implemented in C++, using the faboulous “immer” library for efficiently implementing the immutable data structures.When your Python code passes anImmutableDictor anImmutableListto some function, you do not have to worry that function may alter the contents of that object. A reference to such an immutable data structure is guaranteed to forever point to the same data. If you do want to change the contents of your data, you have to update the reference. So instead ofdata["foo"]= "bar"you will have to writedata =data.set("foo","bar"). As a result, yourdatavariable will be updated, but any other variable that referenceddatabefore the change will keep referencing the olddata—the one before the update.Immutable data structures like this allow for some interesting optimization features. For example, twoImmutableDictobjects with identical content are not actually two objects but one and the same object, and the same is true forImmutableList. If any operation returns anImmutableDictor anImmutableListthat is identical to one that has been constructed earlier, the existing one is returned instead of a new one being constructed. This entails that e.g. twoImmutableDictobjects, even if they represent big trees of data, can be compared using the Pythonisoperation.pyimmutable has a stricter requirement for equality than the usual Python convention. In a nutshell, for pyimmutable, the integer3and the float3.0are not equal. AnImmutableDictcan store different values for the keys3and3.0, whereas a normal Pythondictcannot. You can use objects ofanytype as keys and values, but only identical objects are considered equal. There is an exception to this rule for a small set of built-in types (int,float,str,bytes,tuple—all of which are immutable themselves), which are considered equal when they contain the same data.Example>>> from pyimmutable import ImmutableDict
>>> d1 = ImmutableDict()d1is an empty immutable dictionary.>>> d2 = d1.set("foo", "bar")d2contains one key (“foo”) whose value is “bar”.d1is remains an empty immutable dictionary.>>> d3 = d2.set("fox", "baz")d3now contains two keys (“foo”, “fox”) with values “bar” and “baz”, respectively.d1andd2remain unchanged.>>> d4 = ImmutableDict(foo="bar", fox="baz")d4is a newly constructedImmutableDict, initialized with valuesfooandfoxthat happen to be the same as ind3. In such a case, pyimmutable does not actually construct anewImmutableDictfor us, but returns thed3object from earlier.>>> d3 is d4
TrueThis is fine, becauseImmutableDictobjects are immutable, and since the objects referred to byd3andd4can never be mutated and therefore will always have the same contents,d3andd4might as well refer to the same object.
Package: pyimpact
Python ImpactJS Development Webserver
This egg is heavily based on amadeus’ server.py for which none of this would be possible.Thanks amadeushttps://github.com/amadeus/python-impactDisclaimerUse this in a production environment at your own risk. In fact it is heavily discouraged to deploy your ImpactJS game being served by this webserver.UsageTo get up and running with the python impactjs webserver all you will need to do is:pip install pyimpactAfter you’ve installed pyimpact, from the command line, typestartimpact –host=<HOSTNAME> –port<PORT>The command line arguments are strictly optional and will default to:host: ‘localhost’
port: ‘8080’
TipChange the –host=0.0.0.0 if you’d like to access your game across a local network.
Package: pyimpfuzzy
pyimpfuzzyPython module for comparing the impfuzzypyimpfuzzy is python module which calculate and compare the impfuzzy(import fuzzy hashing)More details are described in the following documents:https://www.jpcert.or.jp/magazine/acreport-impfuzzy.html(Japanese)http://blog.jpcert.or.jp/2016/05/classifying-mal-a988.html(English)Requirementspyimpfuzzy requires the following modules:pefile 1.2.10-139 or laterssdeephttp://ssdeep.sourceforge.netInstallation$pipinstallpyimpfuzzyor$sudopythonsetup.pyinstallUsageget_impfuzzy - return the impfuzzy hash for a given fileget_impfuzzy_data - return the impfuzzy hash for a bufferhash_compare - return the match between 2 hashesExample Usageimportpyimpfuzzyimportsyshash1=pyimpfuzzy.get_impfuzzy(sys.argv[1])hash2=pyimpfuzzy.get_impfuzzy(sys.argv[2])print("ImpFuzzy1:%s"%hash1)print("ImpFuzzy2:%s"%hash2)print("Compare:%i"%pyimpfuzzy.hash_compare(hash1,hash2))
Package: pyimpfuzzy-windows
pyimpfuzzy-windowsPython module comparing the impfuzzy for Windowspyimpfuzzy-windows is python module which calculate and compare the impfuzzy(import fuzzy hashing)This module is pyimpfuzzy for Windows version. For Linux and Mac OS users, please usepyimpfuzzy.More details are described in the following documents:https://www.jpcert.or.jp/magazine/acreport-impfuzzy.html(Japanese)http://blog.jpcert.or.jp/2016/05/classifying-mal-a988.html(English)Requirementspyimpfuzzy-windows requires the following modules:pefile 1.2.10-139 or laterInstallation$pipinstallpyimpfuzzy-windowsor$pythonsetup.pyinstallUsageget_impfuzzy - return the impfuzzy hash for a given fileget_impfuzzy_data - return the impfuzzy hash for a bufferhash_compare - return the match between 2 hashesExample Usageimportpyimpfuzzyimportsyshash1=pyimpfuzzy.get_impfuzzy(sys.argv[1])hash2=pyimpfuzzy.get_impfuzzy(sys.argv[2])print("ImpFuzzy1:%s"%hash1)print("ImpFuzzy2:%s"%hash2)print("Compare:%i"%pyimpfuzzy.hash_compare(hash1,hash2))NotesThis module includesfuzzy.dll version 2.14.1.
Package: pyImpinj
pyImpinj is a protocol library for R2000 reader.InstallationCompile and install the library:pip3 install pyImpinjUsageIn Python 3from pyImpinj import ImpinjR2KReaderExamplefrom pyImpinj import ImpinjR2KReaderTAG_QUEUE = queue.Queue( 1024 )R2000 = ImpinjR2KReader( TAG_QUEUE, address=1 )R2000.connect( ‘COM9’ )R2000.worker_start()R2000.rt_inventory( repeat=100 )print( TAG_QUEUE.get( ) )V1.2 (2020-02-27)Release ver1.2New add get(set)_frequency_regionNew add set_frequency_region_userNew add test/auto_config.pyV1.1 (2020-02-20)Release ver1.1
Package: py-import-cycles
py-import-cyclesDetect import cycles in Python projectsInstallationThe py-import-cycles package is available on PyPI:python3 -m pip install --user py-import-cyclesUsagepython3 -m py_import_cycles --versionpython3 -m py_import_cycles --helppython3 -m py_import_cycles --project-path /path/to/project
Package: pyimporter
pyimporterPython import lib extensions with implementation to import from url.InstallationThe easiest way to install the package is to usepipand install directly frompypi:$pipinstallpyimporterBuildingInstall dependencies:$pipinstall--upgradesetuptoolswheel
$pipinstall--upgradetwineBuild the distribution package:$pythonsetup.pysdistbdist_wheelUpload the package to pypi:$python-mtwineuploaddist/*TestingThe tests are implemented using pytest. You need to install pytest first:$pipinstallpytestFor functional tests, internally a live server is used. By default the functional tests are deselected. To run the functional tests, add the--functionaloption flag to pytest command line:$pytest--functionalIf you prefer verbose output, add-vor-vvoption to the pytest command line:$pytest--functional-vvReferenceThe import system:https://docs.python.org/3/reference/import.htmlSample implementations:https://blog.quiltdata.com/import-almost-anything-in-python-an-intro-to-module-loaders-and-finders-f5e7b15cda47https://github.com/polinom/knockout
Package: pyimporters-dummy
RequirementsPython 3.8+Flit to put Python packages and modules on PyPIPydantic for the data parts.Installationpip install flit
pip install pyimporters-dummyPublish the Python Package to PyPIIncrement the version of your package in the__init__.pyfile:"""An amazing package!"""

__version__ = 'x.y.z'Publishflit publishWrite your own pyimporters pluginGit clone the pyimporters_dummy projectgit clone git@bitbucket.org:kairntech/pyimporters_dummy.gitRename the project with your own format name <new_format>mv pyimporters_dummy pyimporters_<new_format>Delete the .git directoryrm -r -f pyimporters_<new_format>/.gitChange to the new pyimporters_<new_format> directorycd pyimporters_<new_format>Rename the package directory projectmv pyimporters_dummy pyimporters_<new_format>Rename the python file implementationmv pyimporters_<new_format>/dummy.py pyimporters_<new_format>/<new_format>.pyRename the python tests file implementationmv tests/test_dummy.py tests/test_<new_format>.pyEdit the pyproject.toml file to change a few lines and add your additional requirements[tool.flit.metadata]
module = "pyimporters_<new_format>"
...
requires = [
    "pyimporters_plugins>=0.1.61",
    "additional_requirement1",
    "additional_requirement2",
    ...
    "additional_requirementN",
]
dist-name = "pyimporters-<new_format>"
...
[tool.flit.entrypoints."pyimporters.plugins"]
<new_format> = "pyimporters_<new_format>.<new_format>:NewFormatKnowledgeParser"Write the implementation and test of your new format in python using your favorite IDE@dataclass
class NewFormatOptions(KnowledgeParserOptions):
    """
    Options for the new format knowledge import
    """
    foo : str = Query("bar", description="Dummy parameter")

NewFormatOptionsModel = NewFormatOptions.__pydantic_model__

class NewFormatKnowledgeParser(KnowledgeParserBase):
    def parse(self, source : Path, options: Union[KnowledgeParserOptions, Dict[str, Any]], bar : Bar) -> Generator[Term, None, None]:
        options = NewFormatOptions(**options) if isinstance(options, dict) else options
        # Initialize the progress indicator number of terms to read so that the progress indicator can send feedback to the end user
        bar.max = 100 
        bar.start()
        # yield as many terms as you want, advancing the progress indicator each time
        bar.next()
        yield Term(identifier=options.foo, preferredForm=options.foo)
        # Terminate the progress indicator
        bar.finish()

    @classmethod
    def get_schema(cls) -> KnowledgeParserOptions:
        return NewFormatOptions

    @classmethod
    def get_model(cls) -> Type[BaseModel]:
        return NewFormatOptionsModel
Package: pyimporters-plugins
RequirementsPython 3.8+Flit to put Python packages and modules on PyPIPydantic for the data parts.Installationpip install flit
pip install pyimporters-pluginsPublish the Python Package to PyPIIncrement the version of your package in the__init__.pyfile:"""An amazing package!"""

__version__ = 'x.y.z'Publishflit publish