Saravanan666/pypi-org huggingface dataset:
Package: evaluate
🤗 Evaluate is a library that makes evaluating and comparing models and reporting their performance easier and more standardized.It currently contains:implementations of dozens of popular metrics: the existing metrics cover a variety of tasks spanning from NLP to Computer Vision, and include dataset-specific metrics for datasets. With a simple command likeaccuracy = load("accuracy"), get any of these metrics ready to use for evaluating a ML model in any framework (Numpy/Pandas/PyTorch/TensorFlow/JAX).comparisons and measurements: comparisons are used to measure the difference between models and measurements are tools to evaluate datasets.an easy way of adding new evaluation modules to the 🤗 Hub: you can create new evaluation modules and push them to a dedicated Space in the 🤗 Hub withevaluate-cli create [metric name], which allows you to see easily compare different metrics and their outputs for the same sets of references and predictions.🎓Documentation🔎Find ametric,comparison,measurementon the Hub🌟Add a new evaluation module🤗 Evaluate also has lots of useful features like:Type checking: the input types are checked to make sure that you are using the right input formats for each metricMetric cards: each metrics comes with a card that describes the values, limitations and their ranges, as well as providing examples of their usage and usefulness.Community metrics:Metrics live on the Hugging Face Hub and you can easily add your own metrics for your project or to collaborate with others.InstallationWith pip🤗 Evaluate can be installed from PyPi and has to be installed in a virtual environment (venv or conda for instance)pipinstallevaluateUsage🤗 Evaluate's main methods are:evaluate.list_evaluation_modules()to list the available metrics, comparisons and measurementsevaluate.load(module_name, **kwargs)to instantiate an evaluation moduleresults = module.compute(*kwargs)to compute the result of an evaluation moduleAdding a new evaluation moduleFirst install the necessary dependencies to create a new metric with the following command:pipinstallevaluate[template]Then you can get started with the following command which will create a new folder for your metric and display the necessary steps:evaluate-clicreate"Awesome Metric"See thisstep-by-step guidein the documentation for detailed instructions.CreditsThanks to@marellafor letting us use theevaluatenamespace on PyPi previously used by hislibrary.
Package: evaluateqa
EvaluateQAPackage for evaluate QA datasets and Leaderboard with SOTA approachesInstallpipinstallevaluateqaSupported datasetsMintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answeringfromevaluateqa.mintakaimportevaluatepredictions={'9ace9041':'Q90','9ace9042':3,...}results=evaluate(predictions,split='test',mode='kg',lang='en',)
Package: evaluate-service
Evaluate Service ver1.8.5 released:IntroductionThe evaluation service is a tool used to evaluate the performance of a
model on specific hardware  developed by Noah's Ark Laboratory, the main features are as follows:Multi-Backend: PyTorch, TensorFlow, MindSpore and Caffe. The input model can come form Pytorch, Tensorflow,
Mindspore and caffe.Multi-hardware: Mobile Phone, Ascend 310, Kirinri 990 and etc. The model can be evaluated on multiple types of hardware.Online real-time evaluation and offline evaluation. The evaluate service can combine withVegato implement network architecture search with hardware in the ring. One can also use the evaluate service independently.Supports secure communication encryption. In security mode, communications are encrypted to secure the model and data.InstallationInstall evaluate service and the open source softwares that evaluate service depends on:pip3 install --user --upgrade evaluate-serviceCooperation and ContributionWelcome to use evaluate-service. If you have any questions or suggestions, need help, fix bugs, contribute new algorithms,
or improve the documentation, submit an issue in the community. We will reply to and communicate with you in a timely manner.
Package: evaluation-function-utils
Evaluation Function UtilitiesPython package containing a range of utilities that might be used by some (but not all) evaluation functions on the LambdaFeedback platform. This package is pre-installed on theBaseEvaluationFunctionLayer, to be utilised by individual functions to carry a range of common tasks:Better error reportingSchema checkingInput symbols (multiple ways of inputing the same answer)TestingRun tests from the root dir with:pytestUseful flags:-vv: verbose output-rP: show captured output of passed tests-rx: show captured output of failed tests
Package: evaluation-metrics
A package to compute the KS Score, AUC & Gini Coefficient of the model for the given predictionsMethodsplot_roc_curve(): Plots the ROC Curvecompute_auc_gini(): Returns the AUC and Gini coefficientcompute_gains_table_ks(): Computes the gains table from the provided predictions DataFrame. Returns the gainstable & KS value from the gains table.
Package: evaluationRecall
Installationpip install evaluationRecallUsageSee the example indemo.ReferencesJégou, Hervé, Matthijs Douze, and Cordelia Schmid. "Product quantization for nearest neighbor search." (2010).Babenko, Artem, and Victor Lempitsky. "Additive quantization for extreme vector compression." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2014.
Package: evaluations
EvaluationsThe library implements various metrics for evaluating machine learning algorithmsTable of contentsHow to useInstallationPyPIDocumentationAuthorsHow to use>>> from evaluations.classification import confusion_matrix_binary
>>> confusion_matrix_binary([1, 1, 0, 0], [1, 0, 0, 1])
{'tp': 1, 'tn': 1, 'fp': 1, 'fn': 1}InstallationPyPIYou can use pip to install evaluations:pip install evaluationsYou can clone and install the latest version of the library from GitHub:pip install -U git+https://github.com/yisaienkov/evaluationsDocumentationThe full documentation is available athttps://evaluations.readthedocs.io/.AuthorsYaroslav Isaienkov
Package: evalutils
evalutilsevalutils helps challenge administrators easily create evaluation
containers for grand-challenge.org.Free software: MIT licenseDocumentation:https://comic.github.io/evalutils/.FeaturesGeneration your challenge evaluation project boilerplate usingCookiecutterScripts to build, test and export your generated docker container
for grand-challenge.orgLoading of CSV, ITK and Pillow compatible prediction filesValidation of submitted predictionsInterface to SciKit-Learn metrics and Pandas aggregationsBounding box annotations with Jaccard Index calculationsGetting Startedevalutilsrequires Python 3.8 or
above, and can be installed frompip.
Please see theGetting Starteddocumentation for more details.
Package: evalys
“Infrastructure Performance Evaluation Toolkit”It is a data analytics library made to load, compute, and plot data from
job scheduling and resource management traces. It allows scientists and
engineers to extract useful data and visualize it interactively or in an
exported file.Free software: BSD licenseDocumentation:https://evalys.readthedocs.org.FeaturesLoad and allBatsimoutputs filesCompute and plot free slotsSimple Gantt visualisationCompute utilisation / queueCompute fragmentationPlot energy and machine stateLoad SWF workload files fromParallel Workloads ArchiveCompute standard scheduling metricsShow job detailsExtract periods with a given mean utilisationExamplesYou can get a simple example directly by running ipython and discover the
evalys interface. For example:from evalys.jobset import JobSet
import matplotlib.pyplot as plt

js = JobSet.from_csv("evalys/examples/jobs.csv")
js.plot(with_details=True)
plt.show()This also works for SWF files but the Gantt chart is not provided because
job placement information is not provided in this format.You can find a lot of examples in the./examplesdirectory.Gallery4.0.0 changelogVersion 4.0.0Fits with the new trace format of Batsim 3.0
Package: evanduke
Evan Duke EnterprisesEvan Duke Enterprises is the music business owned and operated by Evan Duke, DMA. Offerings include
trumpet performances, brass lessons, business and non-profit administration, and consulting.AboutEvan Duke Enterprises created a business site in 2008 using Joomla.The site has been ported to a modern stack, the user interface overhauled, and
is now hosted in AWS.MVPBasic Django site with FAQ managementRoadmapPost-launch Phase IAdd Case Studies (Resources)Design modelsDesign UIDeployedMVP
Package: evaporation
evaporationCalculation of evaporation and transpirationFree software: GNU General Public License v3Documentation:https://evaporation.readthedocs.io.History1.0.1 (2021-09-01)Updated some dependencies, notably htimeseries 3. Python 3.7, 3.8 and
3.9 are now supported.1.0.0 (2020-01-05)Now uses version 5 of hts file (i.e. different time step notation).0.1.2 (2019-10-24)Fixed a bug where hts files were opened in the wrong mode, with
inconsistent results.0.1.1 (2019-07-18)Fixed a spurious RuntimeWarning.Improved error message if the altitude or location is missing in an
input file.0.1.0 (2019-06-21)Initial release
Package: evar
EVAR – Einfach vorlesen auf'm ReaderEvar erlaubt es die Geschichten vonhttps://www.einfachvorlesen.de/ins Epub-Format zu wandeln um sie anschließen auf einem Ebook Reader vorlesen zu können.NutzungEinfachevaroderpython3 -m evarausführen. Die aktuellen Geschichten werden als PDF und Epub im aktuellen Verzeichnis gespeichert und können dann auf den Reader kopiert werden.SystemvorraussetzungenDas Skript benötigtPython3undPandoc.
Alle benötigten Python-Biblotheken sind in den Metadaten deklariert und werden bei der Installation automatisch mitinstalliert.Installationpip3 install evarLizensEvar ist freie Software und darf unter den Bedingungen derGPL3genutzt, verändert und weitergegeben werden.
Package: evarequests
EvaRequestsEvaRequestsis Asynchronous HTTP Client for Python.Example Usagefromevarequestsimportr,EvaRequestsevaRequests=EvaRequests()defcallback(future):res=future.result()print(res)r.get(url='http://www.baidu.com')evaRequests.get(callback,url='http://www.baidu.com')Installing EvaRequestsEvaRequests is available on PyPI:$python-mpipinstallevarequestsAPI ReferenceEvaRequests is developed based on Requests, Requests API Reference and User Guide available onRequests Docs
Package: evariste
On s’empressera de publier ses moindres observations pour peu qu’elles
soient nouvelles et on ajoutera : « Je ne sais pas le reste. »—Évariste Galois, 1831ExampleI use this program to convertthis(a repository of several hundreds of .tex files, with a few LibreOffice documents) tothat(a web page representing the same directory structures, with the same files, along with their compiled (pdf) version, and some comments).What’s new?Seechangelog.Download and installSeehttps://evariste.readthedocs.io/en/latest/install/DocumentationThe compiled documentation is available onreadthedocsTo compile it from source, download and run:cd doc && make html
Package: evas-docs
这个项目根据esp-docs更改而来，将依赖的pip包更新到了最新版本
支持Sphinx7.2.6，原来evas-docs只支持Sphinx4.5.0
主题由sphinx-idf-theme更换成了原版的sphinx-rtd-theme参考项目链接：
evas-docs:https://github.com/espressif/esp-docssphinx-idf-theme:https://github.com/espressif/sphinx_idf_theme环境准备 Windows和Linux都可以Windows下生成pdf需要安装Latex和Perl环境，Latex建议Miktex，Miktex需要设置国内宏包源，并且设置根据需要自动下载宏包
Miktex:https://miktex.org/downloadPerl:https://strawberryperl.com/启用sphinxcontrib.wavedrom扩展 在Windows环境下需要下载GTK+ for Windows Runtime Environment 64-bithttps://github.com/tschoonj/GTK-for-Windows-Runtime-Environment-Installer/releases记得一定要加上--no-dependencies参数不安装依赖，否则会额外安装一个xcffib包，导致生成报libxcb找不到的错误
pip install --no-dependencies -r requirements.txt如果xcffib不小心被安装，可以使用如下命令卸载
pip uninstall xcffib -y构建evas-docs pip包pip install build twine
python -m build
twine upload dist/*使用方法切换到docs文件夹
cd docs生成html
build-docs build 或 build-docs -l en生成pdf
build-docs -bs latex -l en
Package: evasion-common
ContentsEvasionProject code documentationEvasionProject WikiIntroductionevasion.common.netget_free_portwait_for_readywait_for_serviceEvasionProject code documentationhttp://www.evasionproject.com/apidocs/EvasionProject Wikihttp://www.evasionproject.com/IntroductionThis package provides “evasion.common”. This is a collection of useful functions
and other utilities.evasion.common.netget_free_portFind a TCP port locally that is not in use and return it. This finds a random
port in the range 2000 - 10000. It tests if it is available by binding to it. It
the closed the socket and return the port.This is quite handy for getting a free port to run a service on while acceptance
testing.Example usage:from evasion.common import net

# Get a free port:
port1 = net.get_free_port()

# Get another free port excluding the first port from the list
port1 = net.get_free_port(exclude_ports=[port1])wait_for_readyCalled to wait for a web application to respond to normal requests. This is
useful when you want to know a web app is not just bound to a socket, but is
actually responding 200 OK to root page downloads.Example usage from unit tests:from evasion.common import net
from evasion.common import webhelpers

port1 = net.get_free_port()

# Run the web app and wait for ready should connect:
web = webhelpers.BasicWeb(port=port1)
web.start()

result = net.wait_for_ready(web.uri)
assert result

web.stop()wait_for_serviceCalled to wait until a socket connection can be made to a remote service.Example usage from unit tests:from evasion.common import net
from evasion.common import webhelpers

port1 = net.get_free_port()

# Run the web app and wait for ready should connect:
web = webhelpers.BasicWeb(port=port1)
web.start()

result = net.wait_for_service('localhost', port1)
assert result

web.stop()
Package: evasion-web
Pylons based web application framework on which the director admin is based.The evasion.web framework is 99% Pylons. I don’t like calling it a framework,
but I cannot think of a better description. It differs from Pylons in
that is allows the loading of python packages with multiple controllers,
templates, static files. Each python package can be the complete customer
specific web application or it could be part of the overall application.This easily allows the componentisation or easy mashup of differing
applications.
Package: evatestdb
EVA (Exploratory Video Analytics)What is EVA?EVA is a visual data management system (think MySQL for videos). It supports a declarative language similar to SQL and a wide range of commonly used  computer vision models.What does EVA do?EVAenables querying of visual datain user facing applications by providing a simple SQL-like interface for a wide range of commonly used computer vision models.EVAimproves throughputby introducing sampling, filtering, and caching techniques.EVAimproves accuracyby introducing state-of-the-art model specialization and selection algorithms.Quick LinksDemoWebsiteDocumentationTutorialsForumInstallationDependencyEVA requires Python 3.8 or later and JAVA 8. On Ubuntu, you can install the JAVA bysudo -E apt install -y openjdk-8-jdk openjdk-8-jre.RecommendedTo install EVA, we recommend using virtual environment and pip:python3-mvenvenv38
.env38/bin/activate
pipinstall--upgradepip
pipinstallevatestdbInstall from sourcegitclonehttps://github.com/georgia-tech-db/eva.git&&cdeva
python3-mvenvenv38
.env38/bin/activate
pipinstall--upgradepip
shscript/antlr4/generate_parser.sh
pipinstall.QuickStart1. Set up the server and client
- Activate the virtual environment: `. env37/bin/activate`Launch EVA database Server:eva_serverLaunch CLI:eva_clientRun theUPLOADcommand in the client terminal (use theua_detrac.mp4as an example):UPLOADINFILE'data/ua_detrac/ua_detrac.mp4'PATH'test_video.mp4';Run theLOADcommand in the client terminal:LOADDATAINFILE'test_video.mp4'INTOMyVideo;Below is a basic query that should work on the clientSELECTid,dataFROMMyVideoWHEREid<5;Example QueriesSearch frames with a carSELECTid,frameFROMMyVideoWHERE['car']<@FastRCNNObjectDetector(frame).labels;Search frames with a pedestrian and a carSELECTid,frameFROMMyVideoWHERE['pedestrian','car']<@FastRCNNObjectDetector(frame).labels;Search frames containing greater than 3 carsSELECTid,frameFROMDETRACWHEREarray_count(FastRCNNObjectDetector(frame).labels,'car')>3;DocumentationYou can find documentation for EVAhere.ContributingTo file a bug or request a feature, please file a GitHub issue. Pull requests are welcome.For information on installing from source and contributing to EVA, see ourcontributing guidelines.ContributorsSee thepeople pagefor the full listing of contributors.LicenseCopyright (c) 2018-2022Georgia Tech Database GroupLicensed underApache License.
Package: evatidevice
EvaTideviceEvaTideviceis Add push folder function for tidevice.Example UsagefromevatideviceimportEvaTideviceevaTidevice=EvaTidevice(udid,bundle_id)evaTidevice.pushtree(src,dst)# push file/folderevaTidevice.pulltree(src,dst)# pull file/folderInstalling EvaTideviceEvaTidevice is available on PyPI:$python-mpipinstallevatidevice
Package: eva-tools
The eva_tools package is set of tools used for research on stratospheric aerosol data sets. In particular, the package
was created to aid in the development of the Easy Volcanic Aerosol model (EVA).This package was created by C.J. Ogilvie under the supervision of Dr. Matthew Toohey, for the Institute of Space and
Atmospheric Studies at the University of Saskatchewan.For questions, contact:
- C.J. Ogilvie:cfo188@usask.ca- Dr. Matthew Toohey:matthew.toohey@usask.caThe package contains four tools. These are:
- read_eva: Reads stratospheric aerosol files into python-usable data.
- write_eva: Writes stratospheric aerosol data into files (netCDF4 and Excel files currently supported).
- plot_eva: Quickly generate data plots from stratospheric aerosol files.
- merge_eva: Concatenates two or more stratospheric aerosol files to cover a larger time period.Last updated April 28th, 2022.
Package: ev-audio-streaming-transcription-py
Engage Voice Audio Streaming Quick Test PackageThis package is to test basic functionality of Engage Voice Audio Streaming feature by usingGoogle Cloud Speech-To-Text ServiceGetting Started1. Enable Google Cloud Speech-To-Text ServiceGoogle Cloud AccountEnable Google Speech To Text ServiceGoogle Service AccountAfter above steps, you will get a JSON key file in your local drive. Create a new environment variable with name as 'GOOGLE_APPLICATION_CREDENTIALS' and value as your file path(including file name).2. Install This PackageCreate a new folder and do:pip install ev_audio_streaming_transcription_pyCreate a new fileserver.pywith code below in it:from ev_audio_streaming_transcription_py import server
import asyncio

port=3333
if __name__ == "__main__":  
    asyncio.run(server.main(port))Run the scriptInstallngrokor other similar web tunneling tool, and run:ngrok http 3333You'll get a HTTPS address. Replace 'HTTPS' with 'WSS' and that is the address to be uploaded to your streaming profile.
Package: evautils
EvaUtilsEvaUtilsis Utils for Python.Example Usagefromevautils.requestsimportdownload_filefromevautils.futuresimportmulti_thread_executorprint(download_file('./','https://demo.com/demo.jpg'))defdemo(items,update,name):foriteminitems:print(name,item)ifupdate:update()multi_thread_executor(2,[1,2],demo,None,'thread')Installing EvaUtilsEvaUtils is available on PyPI:$python-mpipinstallevautils
Package: evax.bitten.tools
evax.bitten.toolsevax.bitten.tools is aBittenplugin adding support forcheckandlcovevax.bitten.tools is provided under a BSD-style license.Installationeasy_install evax.bitten.toolsUsageIn order to use the plugin in a build configuration, you must define the plugin namespace as follows:<build
    (...)
    xmlns:evax="http://www.evax.fr/bitten/tools"
    (...)>then use it like this:<step id="tests" description="Automated tests">
    <c:make file="Makefile" target="check" />
    <evax:check reports="tests/*_check.xml" />
    <evax:lcov directory="src" />
</step>Please note that the plugin expects check’s xml output format.Changelog1.0Initial release
Package: evb.py
evb.pyAsynchronous wrapper for the EditVideoBot APIhttps://pigeonburger.xyz/api/docs/ExampleimportasynciofromevbimportAsyncEditVideoBotSession,EditResponseasyncdefmain():withopen("input.mp4","rb")asinput_file:input_bytes=input_file.read()asyncwithAsyncEditVideoBotSession.from_api_key("your_api_key")asevb_session:output_bytes:EditResponse=awaitevb_session.edit(input_bytes,"tt=smell")withopen("output.mp4","xb")asoutput_media:output_media.write(awaitoutput_bytes.download())asyncio.run(main())
Package: evbunpack
evbunpackEnigma Virtual BoxunpackerFeaturesRestores PEsPEs with overlays can be recovered as well (EVB sometimes break them).TLS, Exceptions, and Import Tables are recovered in a way that resembles the original PE most closely.Produces nearly byte-perfect packages. You should be able to run like they were intended to!Unpacks EVB's virtual file system w/wo compression (aplib)This applies to both built-in content and external packagesSupport for older/6.X and newest/9.X EVB packagesInstallationFor Windows Users: Builds are availablehereOr get the latest version from PyPi:pip install evbunpackUsageusage: evbunpack [-h] [--ignore-fs] [--ignore-pe IGNORE_PE] [--legacy] [--list] file output

Enigma Virtual Box Unpacker

positional arguments:
  file                  File to be unpacked
  output                Extract destination directory

options:
  -h, --help            show this help message and exit
  --ignore-fs           Don't extract virtual filesystem. Useful if you want the PE only
  --ignore-pe IGNORE_PE
                        Treat PE files like external packages and thereby does not recover the original executable (for usage without pefile)
  --legacy              Enable compatibility mode to work with older (6.x) EVB packages
  --list                Don't extract the files and print the TOC only (surpresses other output)Examplesevbunpack Lycoris_radiata.mys ../biman5_chs_moe
evbunpack biman2.exe ./extract --legacyTODORestore original PEsRegistery configuration extractionCreditsevb-extractoraplibLicenseApache 2.0 License