Saravanan666/pypi-org huggingface dataset:
Package: mctthermalface
Face Detection on Thermal ImageInstallationBefore installing, make sure the following packages are available:NumpyPyTorch (I recommend to install your PyTorch fromfollowing website)PILOpenCVTo Install, run the following command:pipinstallmctthermalfaceOnly available in PIP, not in CondaUsageFor 3 channels image (8-bit)importmctthermalfacefromPILimportImagedetector=mctthermalface.Detector('thermal_face_detection.pt')img=Image.open("img_path.png")bbox=detector.detect(img)Fpr 1 channels image (16-bit) stored in csvimportmctthermalfaceimportcv2importnumpyasnpdetector=mctthermalface.Detector('thermal_face_detection.pt')img_1channel=np.loadtxt("img_path.csv",delimiter=",")img_1channel=cv2.normalize(img_1channel,None,0,255,cv2.NORM_MINMAX,cv2.CV_8U)bbox=detector.detect(img_1channel)Bounding Box Formatbbox = [xmax, xmin, ymax, ymin]Model DownloadClick Here To Downloadthermal_face_detection.ptSample UsageCheck thisnotebookCreditsOriginal Works by: Diza Febriyan Hasal on his Bachelor Thesis about Detecting Face in Thermal Image. Reworked by Martin Clinton Manullang to adjust the performance, adaptability, and compatibility (2023).
Package: mc-uncertainty
MC UncertaintyUncertainty estimation functions for use with Monte Carlo sampled model outputs.Installationpip install mc-uncertaintyUsageimportmc_uncertaintyasmcu# All functions accept data with shape (mc_samples, n, classes)data=np.array(...# Varianceprint(mcu.variance(data).shape)# [n, classes]# Entropyprint(mcu.entropy(data).shape)# [mc_samples, n]# Predicted entropyprint(mcu.predicted_entropy(data).shape)# [n,]# Mutual informationprint(mcu.mutual_information(data).shape)# [n,]
Package: mcunet
MCUNet: Tiny Deep Learning on IoT Deviceswebsite|paper|demoNews(2022/06)We refactor the MCUNet repo as a standalone repo (previous repo:https://github.com/mit-han-lab/tinyml)(2021/10)Checkout our new paperMCUNetV2:https://arxiv.org/abs/2110.15352!Our projects are covered by:MIT News,WIRED,Morning Brew,Stacey on IoT,Analytics Insight,Techable, etc.
Package: mcup
MCUPMCUP (Monte Carlo Uncertainity Propagation) is a Python library that estimates the uncertainty of least squares fit parameters with Monte Carlo.StatusScopeThe aim of this package is to estimate the error of regression parameters based on error intervals of the input data.PEE – Parameter Error Estimator, a bootstraping method which, takes input data for lsq (x, y, x_err, y_err), generates datapoints within given errors and calculate mean and std of parameters from lsq fit.Installing MCUPPyPITo install mlxtend, just executepython3-mpipinstallmcupDev VersionThe MCUP version on PyPI may always be one step behind. You can install the latest development version from the GitHub repository by executingpython3-mpipinstallgit+https://github.com/detrin/MCUP.git#egg=mcupExampleimportnumpyasnpfrommcupimportMeasurementx_data=np.array([0.0,1.0,2.0,3.0,4.0,5.0])y_data=np.array([0.1,0.9,2.2,2.8,3.9,5.1])y_sigma=np.array([0.0,0.1,0.1,0.1,0.1,0.1])deffun(x,c):returnc[0]*x+c[1]c_initial_guess=[0.0,0.0]measurement=Measurement(x=x_data,y=y_data,y_err=y_sigma)measurement.set_function(fun,c_initial_guess)params_mean,params_std=measurement.evaluate_params(iter_num=1000)print(params_mean)# [0.9901532  0.02477131]print(params_std)# [0.01881003 0.04965347]params_mean,params_std=measurement.evaluate_params(atol=1e-4,rtol=1e-4)print(params_mean)# [0.98854127 0.02771339]print(params_std)# [0.0172098  0.04729087]ContributingWhen contributing to this repository, please first discuss the change you wish to make via issue, email, or any other method with the owners of this repository before making a change.
Package: mcuser
mcuserModule for parsing Minecraft playerdb.cotesting python version 3.8SynchronousfrommcuserimportMCuserdefmain():Main=MCuser.lookup("username or user uuid of id")Text=Main.user_check()#return dictUser=Main.user_name()#return strUsers=Main.user_names()#return jsonUserid=Main.user_id()#return strUserrawid=Main.user_rawid()#retrun strUseravatar=Main.user_avatar()#return str urlmain()#return"""Text = {'code': 'player.found', 'message': 'Successfully found player by given ID.', 'success': True}User = NameUsers = [{'name': '_Siu'}, {'name': 'Name', 'changedToAt': 1423044715000}, {'name': 'name', 'changedToAt': 1430030146000}, {'name': 'Name', 'changedToAt': 1482572974000}]Userid = fa90ba90-9446-4141-83c5-6b31487112c3Userrawid = fa90ba909446414183c56b31487112c3Useravatar = https://crafatar.com/avatars/fa90ba909446414183c56b31487112c3"""AsynchronousimportasynciofrommcuserimportasyncMCuserasyncdefmain():Main=awaitasyncMCuser.lookup("username or user uuid of id")Text=awaitMain.user_check()#return jsonUser=awaitMain.user_name()#return strUsers=awaitMain.user_names()#return jsonUserid=awaitMain.user_id()#return strUserrawid=awaitMain.user_rawid()#retrun strUseravatar=awaitMain.user_avatar()#return str urlasyncio.run(main())#return"""Text = {'code': 'player.found', 'message': 'Successfully found player by given ID.', 'success': True}User = NameUsers = [{'name': '_Siu'}, {'name': 'Name', 'changedToAt': 1423044715000}, {'name': 'name', 'changedToAt': 1430030146000}, {'name': 'Name', 'changedToAt': 1482572974000}]Userid = fa90ba90-9446-4141-83c5-6b31487112c3Userrawid = fa90ba909446414183c56b31487112c3Useravatar = https://crafatar.com/avatars/fa90ba909446414183c56b31487112c3"""
Package: mcush
DESCRIPTIONThe python core module and test suites/framework for MCUSH project.
It eases the test work and create CLI/GUI applications.
Code is hosted on github:https://github.com/pengshulin/mcush/For commerical support:http://www.linkongsoft.com/LICENSEFree only for non-commercial purpose.Commercial use NEED TO BE AUTHORIZED!!!Contact Shanghai Linkong Software Technologies Co., Ltd for commerical support.AUTHORPeng Shulin <trees_peng@163.com>
Shanghai, China 2022
Package: mcutils
mcutils open-sourceFree software: GNU General Public License v3Documentation:https://mcutils.readthedocs.io.FeaturesCreate easy and simple Menu cycles.Title, Subtitle, TextOptions (list the different alternatives to choose from)Submenus (Menu instance)Functions (MenuFunction instance)Retrieve MenuFunction returned valueEach menu is an instance from the Menu ClassAllows to return to previous menus (parent menu)Controlled user inputError handler with input validationDirectory ManagerList files in directoryFilter through different file extensionsOpen files with default application (cross-platform support)Select FilesDelete FilesJSON ManagerPrint ManagerColor printingSupported VersionsPython 3.xCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.
Package: mcuuid
MCUUIDGetting Minecraft Player Information from Mojang API.Usagepip install mcuuidUse the module like this:API> from mcuuid import MCUUID
> player = MCUUID(name="gronkh")
> player.name
'Gronkh'
> player.names
{0: 'Gronkh'}
> player.uuid
'a2080281c2784181b961d99ed2f3347c'You can also use an existing uuid to start from:> player = MCUUID(uuid="a2080281c2784181b961d99ed2f3347c")
> player.name
'Gronkh'ToolsCheck syntax of an username:>from mcuuid.tools import is_valid_minecraft_username
> is_valid_minecraft_username('gronkh'):
TrueCheck syntax of an UUID:> from mcuuid.tools import is_valid_mojang_uuid
> is_valid_mojang_uuid('a2080281c2784181b961d99ed2f3347c'):
TrueVersion informationThere is a wrapper around the new MCUUID class to still be usable using former api versions.
They are deprecated and not recommended for future use.LicenseThis software is licensed under the MIT license. Feel free to use it however you like.
Package: mcuuidButWorks
MCUUIDGetting Minecraft Player Information from Mojang API.Usagepip install mcuuidUse the module like this:APIfrom mcuuid.api import GetPlayerData

player = GetPlayerData(identifier)

if player.valid is True:
    uuid = player.uuid
    name = player.usernameIdentifier can be a username or a UUID.Whenidentifier = "gronkh":uuidwill be"a2080281c2784181b961d99ed2f3347c"andnamewill be"Gronkh"player = GetPlayerData(identifier, timestamp)Some names are time-sensitive. (When they are changed)
So you can choose a special time.It even works with UUIDs. They respond the username at the given time.ToolsSyntax check of usernamefrom mcuuid.tools import is_valid_minecraft_username

if is_valid_minecraft_username('gronkh'):
  print('Valid')Syntaxcheck of UUIDfrom mcuuid.tools import is_valid_mojang_uuid

if is_valid_mojang_uuid('a2080281c2784181b961d99ed2f3347c'):
  print('Valid')Test fileUsage$ python test.py gronkhor$ python test.py a2080281c2784181b961d99ed2f3347cor$ python test.py
Please enter a username or UUID:
gronkhor$ python test.py
Please enter a username or UUID:
a2080281c2784181b961d99ed2f3347cResponse:UUID: a2080281c2784181b961d99ed2f3347c
correct name: GronkhLicenseThis software is licensed under the MIT license. Feel free to use it however you like.
Package: mcv-api-python-unofficial
Mycoursevile API Python UnofficialReverse engineering of the Mycourseville API to create a Python API wrapper.
Developed by CEDTPurposeInteract with the Mycourseville Website in a programmatic way.
As we're a GigaChad Computer Engineering Student, we need to automate everything.Installationpipinstallmcv-api-python-unofficialDisclaimerThis is an unofficial API wrapper and is not affiliated with Mycourseville in any way.
The use of this API wrapper is at your own risk.
We do not take responsibility for any misuse of this API.
Package: mcvariable
MonteCarlo Variable objectThis python object is a Monte Carlo variable.It is initialized with a central value, uncertainty and (optionnaly)
distribution lawIt stores a value according to this probability distirbutionThe value is returned when converted tofloatorintThe MC value is renewed only when callingmcvariable.refresh()The module also includes a generator function to geneate multiple
outcome of the random variable.MCVariableusage:The object is initialized withMCVariable(parameters:Sequence[Number],law:Callable[...,Number],keep_positive:bool=True,non_zero:bool=True,replace_zero_with:float=1e-20)With the parameters:parameters: parameters of the probability law.As a tuple or list of numbers/law: Distribution law of the random variableAs a callable taking*parametersas argumentsand returning a number/keep_positive(bool) = True : keep the value >=0non_zero(bool) = True    : prevent the value to be exactly 0.0000replace_zero_with(float) = 1e-20 : if the previous parameters is True,replace all 0 by this value.To be used, it is recommended to convert explicitely the variable
asintorfloat:mcv=mcvariable.MCVariable((0.,1.))print(f"{int(mcv)}")Default probability lawsThe module includes two probability law by default:mcvariable.law_gaussianwhich takes two parameters:(mean,stddev)mcvariable.law_flatwhic takes to parameters:(central,delta)(and retruns a value within the (central - delta, central + delta) range.GeneratorTo obtain a series of realization of the random variable,
use themcvariable.MCGeneratorfunction that returns a generator.mcvariable.MCGenerator(mcv:MCVariable,nmax:Number=math.inf,variable_type:type=float)The parameters are :mcvthe MCVariable instance to use to generate the valuesnmaxnumber of elements to return (by defaultl infinite)variable_type: the type of value to return (floatby default,
can be changed toint).TestingThe module comes with a test scripttest_mcvariable.py.AuthorsGreg Henning- ghenning​.at.​iphc․cnrs․frLicenseThis project is licensed under the CeCILL FREE SOFTWARE LICENSE AGREEMENT.SeeLICENSEfor more.
Package: mcvine
MCViNE is a Monte Carlo simulation framework useful for simulating neutron experiments.MCViNE is a framework to construct simulated neutron instruments, and manage the flow of neutrons through them from moderator to detector.It also provides a mechanism to allow users to assemble a complex sample component (including sample and also the sample environment, eg. sample holder). This mechanism is extensible to handle arbitrary complex geometeric shapes of neutron scatterer, and arbitrary complex physics of neutron scattering.
Package: mcvoronoi
mcvoronoiComputingvoronoiareas using monte carlo simulationPrerequisites (required modules)python_requires='>=3.6'$python3--versionIf not installed, visit official site for pythonhereand download the latest version of Python.numpy$pip3installnumpysklearn$pip3installsklearnmatplotlib$pip3installmatplotlibInstallation$pip3installmcvoronoiin main.py fileexample code to use the module:importnumpyasnp
importmcvoronoipoints=np.random.rand(10,2)# a numpy array of 10 input co-ordinateslat_lon_area,mean_percentage_error=mcvoronoi.voronoi_area(points,voronoi_plot_enabled=True,NUM_COLORS=5)Parameters to the functionInput TypeInputDefault_Valuenumpy arrayinput_coordinatesNo default valueintegernumber_of_iterations50integernumber_of_trials_per_iteration10000booleanerror_plot_enabledTruebooleanvoronoi_plot_enabledFalsefloatsizeOfMarker0.5integerNUM_COLORS20Returned valuesReturn TypeOutputpython dictkey = (x,y), value = % of area of the smallest rectangle enclosing all input_coordinates, len(lat_lon_area) is same as number of input_coordinatesplotline graph of % error vs trial number (saved as .png)plotvoronoi Diagram with pts & random pts closest to points marked in NUM_COLORS(saved as .png)floatmean % error at the last trialCreditsAuthorContributionEmailKusum Kumaricode standardization; code extension to include useful functionalities; creation and maintenance of mcvoronoi python librarykusum.kumarisjce@gmail.comNishant Kumarinitial working solution usingMCsimulation for voronoi areasabc.nishant007@gmail.comContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to add/change.LicenseMITOutput plotsmean_errors_plotvornoi_colored_areas
Package: mcvqoe
SummaryThe purpose of this software is to make quality of expirence (QoE) measurements
for push-to-talk (PTT) communications systems. This Python package develoved by NIST’s PSCR division contains a
GUI for making these measurements. This GUI is the recommended way to run the
following QoE measurements:mouth 2 ear latencyAccess TimeProbability of Successful DeliveryIntelligibilityTransmit Volume OptomizationMCV-QoE-GUI Python PackageThemcvqoeGUI package depends on the following other PSCR published packages:https://github.com/usnistgov/mcvqoe-basehttps://github.com/usnistgov/abcmrt16https://github.com/usnistgov/mouth2earhttps://github.com/usnistgov/accessTimehttps://github.com/usnistgov/psudhttps://github.com/usnistgov/intelligibilityhttps://github.com/usnistgov/MCV-QOE-TVOIn addition the following dependencies can be found in the Python Package index (PyPI) and will
be downloaded automatically, if needed, whenmcvqoeis installed:numpypandasdashflaskplotlyrequestspillowTo install the package run the following:pip install mcvqoeThis is the easiest way to install all MCV QoE measurement software, as all the above packages are dependencies, and will be installed via PyPI.Alternatively, one could clone this repository and run the following from the
root of the git repository:pip install .Running with terminal outputOn windows, the GUI entry point,mcvqoecauses all console output from the GUI
to be lost (on windows). If the input is desired on windows the GUI can also be
run with the following:python -m mcvqoe.hubEvaluation GUIData can be evaluated by using the Process Data menu from the GUI. Here users can select data they wish to process and a separate, browser-based interface will initialize.LicenseThis software was developed by employees of the National Institute of Standards
and Technology (NIST), an agency of the Federal Government. Pursuant to title 17
United States Code Section 105, works of NIST employees are not subject to
copyright protection in the United States and are considered to be in the public
domain. Permission to freely use, copy, modify, and distribute this software and
its documentation without fee is hereby granted, provided that this notice and
disclaimer of warranty appears in all copies.THE SOFTWARE IS PROVIDED 'AS IS' WITHOUT ANY WARRANTY OF ANY KIND, EITHER
EXPRESSED, IMPLIED, OR STATUTORY, INCLUDING, BUT NOT LIMITED TO, ANY WARRANTY
THAT THE SOFTWARE WILL CONFORM TO SPECIFICATIONS, ANY IMPLIED WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, AND FREEDOM FROM INFRINGEMENT,
AND ANY WARRANTY THAT THE DOCUMENTATION WILL CONFORM TO THE SOFTWARE, OR ANY
WARRANTY THAT THE SOFTWARE WILL BE ERROR FREE. IN NO EVENT SHALL NIST BE LIABLE
FOR ANY DAMAGES, INCLUDING, BUT NOT LIMITED TO, DIRECT, INDIRECT, SPECIAL OR
CONSEQUENTIAL DAMAGES, ARISING OUT OF, RESULTING FROM, OR IN ANY WAY CONNECTED
WITH THIS SOFTWARE, WHETHER OR NOT BASED UPON WARRANTY, CONTRACT, TORT, OR
OTHERWISE, WHETHER OR NOT INJURY WAS SUSTAINED BY PERSONS OR PROPERTY OR
OTHERWISE, AND WHETHER OR NOT LOSS WAS SUSTAINED FROM, OR AROSE OUT OF THE
RESULTS OF, OR USE OF, THE SOFTWARE OR SERVICES PROVIDED HEREUNDER.
Package: mcvqoe-base
mcvqoe Python PackageCommon code for MCV QoE Measurement Methods. This package contains core code for
QoE measurements used in the following packages:https://github.com/usnistgov/mcvqoehttps://github.com/usnistgov/mouth2earhttps://github.com/usnistgov/accessTimehttps://github.com/usnistgov/psudhttps://github.com/usnistgov/intelligibilityhttps://github.com/usnistgov/MCV-QOE-TVOThemcvqoe-basepackage includes libraries to play audio through a Push To
Talk (PTT) communication system. Also included are equivalent libraries to
simulate sending audio through a PTT communication system.Installing the PackageTo install the package runpip install mcvqoe-baseAlternatively, to build and install the package, clone this repository and run the following
from the root of the git repository :pip install .Radio Interface FirmwareThe firmware for the RadioInterface board can be found at:https://github.com/usnistgov/MCV-QoE-firmwareMeasurement Data StructureFor more information about how measurement data gets stored see theData Structure Readme.LicenseThis software was developed by employees of the National Institute of Standards
and Technology (NIST), an agency of the Federal Government. Pursuant to title 17
United States Code Section 105, works of NIST employees are not subject to
copyright protection in the United States and are considered to be in the public
domain. Permission to freely use, copy, modify, and distribute this software and
its documentation without fee is hereby granted, provided that this notice and
disclaimer of warranty appears in all copies.THE SOFTWARE IS PROVIDED 'AS IS' WITHOUT ANY WARRANTY OF ANY KIND, EITHER
EXPRESSED, IMPLIED, OR STATUTORY, INCLUDING, BUT NOT LIMITED TO, ANY WARRANTY
THAT THE SOFTWARE WILL CONFORM TO SPECIFICATIONS, ANY IMPLIED WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, AND FREEDOM FROM INFRINGEMENT,
AND ANY WARRANTY THAT THE DOCUMENTATION WILL CONFORM TO THE SOFTWARE, OR ANY
WARRANTY THAT THE SOFTWARE WILL BE ERROR FREE. IN NO EVENT SHALL NIST BE LIABLE
FOR ANY DAMAGES, INCLUDING, BUT NOT LIMITED TO, DIRECT, INDIRECT, SPECIAL OR
CONSEQUENTIAL DAMAGES, ARISING OUT OF, RESULTING FROM, OR IN ANY WAY CONNECTED
WITH THIS SOFTWARE, WHETHER OR NOT BASED UPON WARRANTY, CONTRACT, TORT, OR
OTHERWISE, WHETHER OR NOT INJURY WAS SUSTAINED BY PERSONS OR PROPERTY OR
OTHERWISE, AND WHETHER OR NOT LOSS WAS SUSTAINED FROM, OR AROSE OUT OF THE
RESULTS OF, OR USE OF, THE SOFTWARE OR SERVICES PROVIDED HEREUNDER.
Package: mcwb
mcwbA Minecraft world builder library.Requirementsmcwbrequires Python 3.9 or higher. It also depends onmcipc.
If you installmcwbviapip, it will automatically be installed as a dependency.DocumentationDocumentation is available onreadthedocs.Quick startInstall mcwb from theAURor via:pip install mcwbCreditsMany thanks to all contributors to theMinecraft Wikiand theWiki.vg.LicenseCopyright (C) 2018-2021 Richard Neumannmcwb is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.mcwb is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.You should have received a copy of the GNU General Public License
along with mcwb.  If not, seehttp://www.gnu.org/licenses/.LegalMinecraft content and materials are trademarks and copyrights of
Mojang and its licensors. All rights reserved.
This program is free software and is not affiliated with Mojang.
Package: mcworldmanager
Minecraft World CheckerInsperated byFenixin/Minecraft-Region-Fixer, but a optimized commandline usage, and integration to your backup Process.For more informations take a look to theDocumentation.FeaturesScanning a single Region FileScanning a list of given WorldsScanning all World Folders from a Minecraft Server StructureSaving the Report as yaml FileSupported SystemsFor executing you need Python 3.5 or later, or you use the Preconfigured Docker Container fromDockerHub.Example Callsmcworldmanagerserver~/repos-ansible/minecraft-server-project-repos/docker_compose-world-maps/worldfolder/worldmcworldmanagerworlds~/repos-ansible/minecraft-server-project-repos/docker_compose-world-maps/worldfolder/worldmcworldmanagerregion~/repos-ansible/minecraft-server-project-repos/docker_compose-world-maps/worldfolder/world_flat/region/r.1.1.mca
Package: mcwrapper
Minecraft APIThis a simple package to wrap many APIs, including the Mojang and Hypixel onesRequires Python 3.7+Usage guide for PackageImport the package withimportmcwrapperOr the preferred wayfrommcwrapperimporthypixelThe second way allows you to save some lines writing the actual code. To actually use this, create a Bedwars, Skywars, or Hypixel object. You must pass in a username and api key for the hypixel-related objects**Example**frommcwrapperimporthypixelobject=hypixel.Bedwars("ThePotatoPowers","yourapikeyhere")To get information from this object, use thestats()method. Then, the object's attributes will be setfrommcwrapperimporthypixelobject=hypixel.Bedwars("ThePotatoPowers","yourapikeyhere")object.stats()print(object.wins)#prints bedwars wins for ThePotatoPowersSkinsCreate askin objectby first importing the skin file from the packagefrom mcapiwrapper import skinThe class takes a username argumentTheskingrabmethod will return a link with the user's skin. You can access this with the skin attributeThebodymethod will return a link with the user's body. You can access this with the body attributeTheheadmethod will return a link with the user's head. You can access this with the head attributeTheavatarmethod will return a link with the user's head in 2D. You can access this with the avatar attributeBedwarsAs shown above, import hypixel from mcapiwrapper. Then, create aBedwarsobject which takes a username and apikey parameter (in that order)After thestatsmethod is run, you can access all attributes of the Bedwars object. This includes:display (displayname)winslossesdeathskillscoinsfinal_killsfinal_deathsbeds_destroyedbeds_lostwinstreaklevelSkywarsAs shown above, import hypixel from mcapiwrapper. Then, create aSkywarsobject which takes a username and apikey parameter (in that order)After thestatsmethod is run, you can access all attributes of the Skywars object. This includes:winslossesdeathskillscoinssoulsheadswinstreakdisplayHypixelAs shown above, import hypixel from mcapiwrapper. Then, create aHypixelobject which takes a username and apikey parameter (in that order)After thestatsmethod is run, you can access all attributes of the Hypixel object. This includes:firstLoginlastLoginnameHistorydisplayContributeSource Code:https://github.com/ThePotatoPowers/mcapiwrapper/Issue Tracker:https://github.com/ThePotatoPowers/mcapiwrapper/issuesSupportIf you are having issues, please let me know @zkarim7676@gmail.comLicenseThe project is licensed under the MIT license.