Saravanan666/pypi-org huggingface dataset:
Package: fancy-descriptor
fancy-descriptorsThis package adds a callable descriptor called method descriptor which can apply to methods.Usagea simplest example:importfancy.descriptorasfdclassMyDescriptor(fd.MethodDescriptor):passclassMyClass:@MyDescriptordefmethod_a(self):pass# or@MyDescriptor.bind()defmethod_b(self):pass# after a MyClass object is created.my_obj=MyClass()assertisinstance(my_obj.method_a,MyDescriptor)# returned {"method_a": <MyDescriptor object>, "method_b": <MyDescriptor object>}MyDescriptor.get_marked_method(my_obj)the statement MyDescriptor.get_marked_method(my_obj) will get all marked methods' descriptorswith metadataimportfancy.descriptorasfdclassMyDescriptor(fd.MethodDescriptor):def__init__(self,method,value:int,factory=None):"""method must at first place of argumentfactory is a method descriptor factory for underlying descriptor"""super().__init__(method,factory)self._value=valuedefget_value(self):returnself._valueclassMyClass:# you cannot directly use MyDescriptor as decorator#  if the constructor of the descriptor has over one required argument# you must use .bind() to instead.@MyDescriptor.bind(value=1)defmethod_annotated(self):passmy_obj=MyClass()my_obj.method_annotated.get_value()# returned 1Inheritanceimportfancy.descriptorasfdclassMyBaseDescriptor(fd.MethodDescriptor):passclassMyDescriptor(MyBaseDescriptor):passclassMyClass:@MyBaseDescriptordefmethod_base(self):pass@MyDescriptordefmethod_sub(self):passmy_obj=MyClass()MyBaseDescriptor.get_marked_method(my_obj)# returned both method_base and method_subMyDescriptor.get_marked_method(my_obj)# returned only method_sub
Package: fancy-dick
Testnet_001regnerischerbuerger's projectПроект тестовый, но уже предлагает бесполезную функцию!Ну, например, используя функциюupdate_a_setвы можете обновить множество Python.
Будто бы нам обычного метода не хватало... Ну, зато множество ошибок может быть исключено...
Package: fancy-einsum
Fancy EinsumThis is a simple wrapper aroundnp.einsumandtorch.einsumthat allows the use of self-documenting variable names instead of just single letters in the equations. Inspired by the syntax ineinops.For example, instead of writing:importtorchtorch.einsum('bct,bcs->bcts',a,b)orimportnumpyasnpnp.einsum('bct,bcs->bcts',a,b)With this library you can write:fromfancy_einsumimporteinsumeinsum('batch channels time1, batch channels time2 -> batch channels time1 time2',a,b)
Package: fancy-eventbus
fancy-eventUsageimportfancy.eventbusasfeclassMyEvent:value:intdef__init__(self,value):self.value=valueclassMyEvent2:passclassTarget:def__init__(self):fe.register(self)@fe.SubscribeEvent()defon_start(self,event:fe.StartEvent):print("start!")fe.post(MyEvent(1))@fe.SubscribeEvent()defmy_event(self,event:MyEvent):print("my_event",event.value)fe.post(MyEvent2())fe.post(self)@fe.SubscribeEvent()defmy_event2(self,event:MyEvent2):print("my_event2")raiseRuntimeError("an error")@fe.SubscribeEvent(priority=fe.EventPriority.HIGHEST)# execute before my_event2defself_as_event(self,event:"Target"):# forwarding refprint("self_as_event",eventisself)@fe.SubscribeEvent()deferror_handler(self,e:RuntimeError):print("handle by runtime error",e)@fe.SubscribeEvent(priority=fe.EventPriority.LOW)# method name should differentdeferror_handler2(self,e:Exception):print("handle by exception",e)returnFalse# returned false will cancel the event@fe.SubscribeEvent(priority=fe.EventPriority.LOWEST)deferror_handler3(self,e:BaseException):print("this should be canceled.",e)loop=fe.EventLoop()# registersTarget()loop.start()start!my_event 1self_as_event Truemy_event2handle by runtime error an errorhandle by exception an error
Package: fancy-jira
![PyPI - Downloads](https://img.shields.io/pypi/dm/fancy-jira)
# fancy-jira
Just a fancy JIRA command line tool for people that do not like GUIs# Install
For now you can just install this CLI using pip:`shell pip installfancy-jira`# Getting started
To start using this CLI you’ll need to first login:jira loginThe endpoint that it is waiting is the base url for your JIRA endpoint:https://jira.yourcompany.com
Package: fancylit
FancylitFancylit is a python module that contains pre-packaged Streamlit code to render fancy visualizations, run modeling tasks, and data explorationInstallationpip install fancylitQuick StartFancylit makes it incredibly easy to build fancy interactive apps:importstreamlitasstimportfancylitdf=pd.read_csv("datasets/iris.csv")st.write("Bar Chart Example")fancylit.viz.charts.bar_chart(df)See more examples here:https://share.streamlit.io/banjtheman/fancylit/main/example_app.pyHacktoberfest 2021There are plenty of modules to create, or update all detailed in theissues page. Complete 4 PRs during October to win a free t-shirt.To learn more, check out theirFAQIf you want to build right away you can useGitpodwhich provides a developer environment ready to begin coding. Simply click the button below to begin building.
Package: fancylogging
IntroductionThis Python module provides an advanced logging setup usingrichfor
console logging andpython-json-loggerfor file logging. It allows for
detailed and formatted logging, ideal for applications requiring high-level
logging capabilities.InstallationThis module requires the following dependencies:richpython-json-loggerUsageImportsetup_fancy_loggingfrom the module and configure your logging setup
by specifying parameters likebase_logger_name,console_log_level,file_log_level,log_file_path, and others.Example:importloggingfromfancyloggingimportsetup_fancy_logginglog=logging.getLogger("test")if__name__=="__main__":setup_fancy_logging("test",console_log_level=logging.INFO,file_log_level=logging.DEBUG,file_log_path="logs/test.json",file_mode="w",)log.info("Info message")log.debug("Debug message")log.warning("Warning message")log.error("Error message")log.critical("Critical message")try:raiseException("Raising a test exception")exceptException:log.exception("Exception message")
Package: fancymath
# fancymathWrite fancy math symbols in your email!Too many engineers lost their lives to come up with Unicode,we might just as well use it.This is a simple LaTeX sequences to Unicode translation for math symbols.Example:$ cat spivak.txtWhen these symbols, \otimes and \sqcup, are used to denotemorphisms, they indicate a monoidal product. So, you shouldn'tuse it to denote the universal arrow itself.In other words, given f:A-->X and g: B-->Y, you can writef \sqcup g: A \sqcup B \to X \sqcup Yorf \otimes g: A\otimes B \to X \otimes YBut given f: A-->X and g: B-->X, you shouldn't name theuniversal morphism  A \sqcup B --> X by f\sqcup g ..$ fancymath < spivak.txtWhen these symbols, ⊗ and ⊔, are used to denotemorphisms, they indicate a monoidal product. So, you shouldn'tuse it to denote the universal arrow itself.In other words, given f:A⟶X and g: B⟶Y, you can writef ⊔ g: A ⊔ B ⟶ X ⊔ Yorf ⊗ g: A⊗ B ⟶ X ⊗ YBut given f: A⟶X and g: B⟶X, you shouldn't name theuniversal morphism  A ⊔ B ⟶ X by f⊔ g ..### InstallationSimply this:$ pip install fancymath### Installation from source if you want to change the symbols1. download this repo2. use this:$ python setup.py develop
Package: fancy-source-query
Nonebot plugin fancy source query这个插件的目的是将 Source Server Query 的功能集成进 Nonebot 框架中，
以便使用者方便地实现查询 Valve Source 服务器状态的查询。
并且默认实现了将较长的查询结果转换成图片输出的功能，以免刷屏
（此功能仅在 QQ 上测试）。功能介绍FancySourceQuery(以下简称FSQ) 插件可以查询 Source 服务器的名称、人数、正在运行的地图和服务器内玩家的详细状态。
提供以下指令：查询：查询当前服务器组的概况（所有服务器名称、当前人数、最大玩家数、地图名称）并统计总人数查询人数：同上查询（服务器名）：当输入的参数不为空或“人数”时，机器人优先将其认作服务器的名称，将会从当前服务器中寻找对应的服务器，
查询服务器的状态和详细的玩家状态查询（玩家名）：当输入的参数不为空或“人数”或已知的服务器名时，机器人会将其认作玩家的名称片段，将会从当前服务器组里的所有服务器中搜索玩家名匹配的玩家信息（输入参数被当作正则表达式处理，并且匹配标准是re.search）刷新配置：此功能仅 SUPERUSER 可用，可让机器人在不停机的情况下重新加载配置文件刷新地图数据：此功能仅 SUPERUSER 可用，可让机器人在不停机的情况下重新加载地图数据该插件的所有功能都提供 Python 接口或命令行接口，可以在不启动 Nonebot 的情况下执行，以便调试。Python 接口为fancy_source_query.interfaces:FancySourceQuery此对象的所有方法都返回适合 Python 处理的对象Cli 接口在fancy_source_query.interfaces.cli:cli_main此方法提供了命令行的程序调用nonebot 接口在fancy_source_query.interfaces.nonebot此模块中定义了 Nonebot 响应函数，只支持 Onebot v11 程序相关文件运行时，你的项目文件夹下必须有这两个文件：fancy_source_query.toml： 默认的配置文件mapnames.toml： 默认的地图数据文件，其中储存了地图的原名、中文名、地图代码，以便插件生成对应的反查表文件内容可以查看仓库中的示例，其中mapnames.toml文件在另一地址有随时更新的版本 （TODO）安装将此插件添加到 Nonebot 项目的依赖中，可以使用 nb-cli 或者 pdm, poetry, pip 等
包管理工具安装。例如：pdmaddfancy_source_query然后在pyproject.toml中配置：[tool.nonebot]plugins=[# ..."fancy_source_query.interfaces.nonebot",# ...]配置此插件的配置分为两个部分，一个是 NoneBot 的 Env 配置文件，另一个（主要的）是 toml 格式的配置。FANCY_SOURCE_QUERY_CONFIG="fancy_source_query.toml"env 配置中只需要指定插件配置文件的路径，默认为 nonebot 进程工作目录下的fancy_source_query.toml文件。
以下为默认的配置模板与解释：[fancy_source_query]# 默认超时等待 5stimeout=5# 默认查询池缓存 20scache_delay=20# 默认限制文本输出 5 行，超过 5 行的转成图片输出output_max_lines=5# Fancy Source Query 可以配置地图数据库，方便将地图代码转换成人类可读的地图名# 该路径相对于 nonebot 进程工作目录mapnames_db="mapnames.toml"# 默认的服务器组，在不传入组名时使用此组default_server_group="A"# 转图片时的字号，pxfontsize=16[fancy_source_query.impaper]# 建议留空，加载默认的更纱黑体，# 或者指定一个 ttf 文件的路径。# font.path =[fancy_source_query.impaper.layout]# 外边距，按上右下左的顺序（和 CSS 里的习惯一致），px# 右边距建议拉大一点，防止手机上看时像素被遮住margin=[6,6,18,6]# 内边距，按上右下左的顺序（和 CSS 里的习惯一致），pxpadding=[2,2,2,2]# 行间距，pxspacing=2[fancy_source_query.impaper.typesetting]# 行宽，英文1，汉字2line_width=52# 折行缩进indentation="  "# 格式化查询数据的模板[fancy_source_query.fmt]server_info="服务器：{name}\n概况：({players:>2d}/{max_players:>2d})[{mapname}]"player_info="[{score}]({minutes:.1f}min){name}"rule_info="({key} = {value})"players_count="总人数：{players}"query_time="查询时间：{time}"# strftime 格式符time="%Y-%m-%d %H:%M:%S"# Fancy Source Query 可以为不同的 QQ 群设置不同的服务器组# 为不同的群分别提供查询服务，例如为 A 群配置服务器组 AG, 其中包含服务器 A1, A2, A3；# 为 B 群配置服务器组 BG，其中包含服务器 B1, B2, B3；# 为 开发者测试群 配置服务器组 DEVG，其中包含所有服务器；# 那么机器人在 A 群中查询时只会考虑 A1, A2, A3 服务器，以此类推。[[fancy_source_query.server_groups]]name="A"related_sessions=["<QQ群号A>","<开发者测试群>"][[fancy_source_query.server_groups]]name="B"related_sessions=["<QQ群号B>","<开发者测试群>"][[fancy_source_query.servers]]# 此处的 A 需要与 server_group.name 相同group="A"name="A1"host="127.0.0.1"port=65501[[fancy_source_query.servers]]group="A"name="A2"host="127.0.0.1"port=65502[[fancy_source_query.servers]]group="B"name="B1"host="127.0.0.1"port=64501在修改完配置文件后，可以通过 SUPERUSER 账号向机器人发送 "刷新" 指令，以热重载配置和数据。
Package: fancySVD
A fork ofhttps://github.com/iskandr/fancyimputewhich only includes its IterativeSVD algorithm.
The original fancyimpute project had many more algorithms which required installing Tensorflow, which was difficult to do because of dependency issues.
This minimal project is much simpler to install.To install:pip install fancySVDImportant Caveats(1) This project is in "bare maintenance" mode. That means we are not planning on adding more imputation algorithms or features (but might if we get inspired). Please do report bugs, and we'll try to fix them. Also, we are happy to take pull requests for more algorithms and/or features.UsagefromfancySVDimportIterativeSVDimputed_matrix=IterativeSVD().fit_transform(matrix)AlgorithmsIterativeSVD: Matrix completion by iterative low-rank SVD decomposition. Should be similar to SVDimpute fromMissing value estimation methods for DNA microarraysby Troyanskaya et. al.CitationAs this project was forked from work done inhttps://github.com/iskandr/fancyimpute, if you usefancySVDin your academic publication, please cite the original authors as follows:@software{fancyimpute,author={Alex Rubinsteyn and Sergey Feldman},title={fancyimpute: An Imputation Library for Python},url={https://github.com/iskandr/fancyimpute},version={0.5.4},date={2016},}
Package: fancy_tag
Overviewfancy_tagis a template tag decorator designed to replace Django’s built insimple_tagdecorator. It’s backwards compatible withsimple_tagand adds
new calling options like named arguments.FeaturesKeyword arguments - arguments can be explicitly assigned to parameter
specific parameters in the template tag functionVariable length arguments - The “*args” and “**kwargs” notationThe trailing “as <varname>” to assign the output of the template tag to
a variable in the template’s context.InstallationAdd the fancy_tag package to your Python pathInstead of:@register.simple_tag
def some_tag(arg1, arg2):
    return '%s %s' % (arg1, arg2)Use:@fancy_tag(register)
def some_tag(arg1, arg2):
    return '%s %s' % (arg1, arg2)ExamplesKeyword ArgumentsPython Code:@fancy_tag(register)
def say_cheese(name, thing_to_say='cheese'):
    return 'Hey, %s! Say %s!' % (name, thing_to_say)Template Code:{% say_cheese "Jacob" %} -> "Hey, Jacob! Say Cheese!"
{% say_cheese "Malcolm" thing_to_say="Vegemite" %} -> "Hey Malcolm! Say Vegemite!"Variable Length ArgumentsPython Code:@fancy_tag(register)
def greet_people(*args):
    return 'Hello, %s' % ', '.join(args)Template Code:{% greet_people "Larry" "Darryl" "Darryl" %}Produces:Hello, Larry, Darryl, DarrylVariable Length Keyword ArgumentsPython Code:@fancy_tag(register)
def watch_your_mouth(s, **kwargs):
    for key, value in kwargs.items():
        s = s.replace(key, value)
    return sTemplate Code:{% watch_your_mouth "You damn dirty ape!" "damn"="doggone" "dirty"="handsome" %}Produces:You doggone handsome ape!”Assigning Output To A VariablePython Code:@fancy_tag(register)
def now(format_string):
    df = DateFormat(datetime.now())
    return df.format(format_string)Template Code:{% now as just_now %}
Oh no, it's already {{ just_now }}!Produces:Oh no, it’s already February 20th, 2010!Accessing the Template ContextPython Code:@fancy_tag(register, takes_context)
def say_hello_to_user(context, phrase):
    return u'%s, %s!' % (phrase, context['user'])Template Context:{'user': 'Tobias'}  # Provided by a template context processor, for exampleTemplate Code:{% say_hello_to_user "Hallo" %}Produces:Hallo, Tobias!TestingWith Django in your python path, runtests/run_tests.pyor usetoxto run the tests using multiple
Python and Django versions.Sourcehttp://github.com/trapeze/fancy_tagLicensefancy_tag is Copyright (c) 2010-2012 Sam Bull, Trapeze. It is free software, and
may be redistributed under the terms specified in the LICENSE file.Creditsfancy_tag is maintained bySam Bull, with support fromTrapeze.
Package: fancytools
Browse theAPI DocumentationFork the code ongithubInstallationfancytoolsis listed in the Python Package Index. You can install it typing:pip install fancytoolsTestsfancyToolsuses mostly the ‘one class/function per file’ rule. Running each module as program, like:python -m fancytools.render.GridRenderwill execute the test procedure of this module.To run all tests type:python -m fancytools.testsv0.1, <12/05/2014> – Initial release.v0.2, <20/12/2014> – major updates and new modules.V0.3, <27/05/2016> – major update - new modulesKarl Bedrich 2013 - 2016
Package: fancywidgets
Based onpyQt4andpyqtgraphBrowse theAPI DocumentationFork the code ongithubInstallationfancywidgetsis listed in the Python Package Index. You can install it typing:pip install fancywidgetsTestsfancyWidgetsuses mostly the ‘one class/function per file’ rule. Running each module as program, like:python -m fancywidgets.pyQtBased.Tablewill execute the test procedure of this module.To run all tests type:python -m fancywidgets.testsv0.1, <22/12/2014> – Initial release.Karl Bedrich 2013 -
Package: fand
Simple daemon to control fan speed.AboutThe main executable of this program is thefand-serverdaemon.
There are 3 main modules: server, clientrpi and fanctl.
They can be accessed through their respective entry points:fand-server,fand-clientrpiandfanctl.
They can also be accessed withfand<module-name>.A server monitor the hardware and clients connect to it to get data (e.g.
fan speed or override a fan speed).$fanctlget-rpmshelf11500$fanctlget-pwmshelf150$fanctlset-pwm-overrideshelf1100ok$fanctlget-pwmshelf1100$fanctlget-rpmshelf13000ServerTheservermodule provide a daemon which monitor devices
temperatures and find a corresponding fan speed.
It listens for connections from clients, and answers to requests.Fan clientsA client is assigned a shelf and will regularly request the server for the
fan speed (percentage).  It will then ajust the fan to use this speed.Clients also send the actual fan speed in RPM to the server. This will allow
other client to have access to the data from the server.Raspberry Pi clientTheclientrpimodule will connect to a server and
get a fan speed from it.
It will then set the fan speed with a PWM signal through the GPIO interface
of the Pi.
It will also tell the server the current real speed of the fans in rpm.Command-line interfaceThefanctlmodule is a command line interface to interact
with the server.
It provides commands to get the fan speed and rpm, and also allow to override
the fans speed.DocumentationThe fand documentation is available athttps://fand.readthedocs.io/.
Theinstallationchapter provides install instructions and compatibility
informations.
Package: fandak
Fandak: فندکComing soon...Will help you train your models for research.Installation:exclamation: Requires Python 3.7 :snake:.pip install fandakRelease NotesRelease NotesExamplesSeeexamplesdirectory.Visualizing the effects of hyper-parametersSample usage:python-mfandak.hyper/path/to/rootmetric1[metric2][--exp-namebaseline-*][--params-listpath/to/params/list.txt]If no exp-name is provided, then all are going to be considered.
exp-name can be something usable from glob.We also have to specify the params list. What to have in the figure? Otherwise, we look
at the experiments and find the params that are not the same among them.
If a param is missing from a config file, then it is replaces with "?".
Package: fandomanime
OverviewWritten to scrape clean anime summaries fromhttps://www.fandom.com/Getting itTo download animefandom, either fork this github repo or simply use Pypi via pip.$pipinstallfandomanimeUsing itFirst,importfandomanimeasfaCreate an fandomanime objectfaObject=fa.AnimeFandom("https://naruto.fandom.com/wiki/Konohamaru!!")Now get the summary,print(faObject.getSummary())LicenseMIT LicenseMIT LicenseCopyright (c) 2020 Matthew MurrayPermission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Package: fandom-py
fandom-pyis a Python library that makes it easy to access and parse
data from anyFandom website.Search a Fandom, get article summaries, get data like links and images
from a page, and more.fandom-pywraps the Fandom API so you can focus on using
Fandom data, not getting it.>>>importfandom>>>fandom.summary("Banshee","Runescape")# Banshees are Slayer monsters that require level 15 Slayer to kill. They frequently drop 13 noted pure essence, making them an alternative source of essence. Additionally, banshees tend to frequently drop many different types of herbs. Mighty banshees are a higher-levelled alternative, if this is given as your Slayer assignment.>>>fandom.search("Forest","Runescape")# [('Forest', 158584), ("Forester's Arms", 13771), ('Forester (Burgh de Rott Ramble)', 37816), ('Forester', 37518), ('Forest Beyond', 498451), ('Nemi Forest', 538558), ('Jungle forester', 68434), ('Freaky Forester', 6805), ("Bartender (Forester's Arms)", 543117), ('Dense forest', 83395)]>>>fandom.set_wiki("Runescape")>>>drakan=fandom.page("Castle Drakan")>>>drakan.title# u'Castle Drakan'>>>drakan.url# u'http://runescape.fandom.com/wiki/Castle_Drakan'>>>drakan.plain_text# u'Castle Drakan is the home of Lord Drakan, the vampyre lord of Morytania. Found just north of Meiyerditch, it looms over the Sanguinesti region'...>>>fandom.set_lang("nl")# Dutch>>>fandom.summary("Runes","Runescape",sentences=1)# Runes, of Magische runes zijn kleine gewichtloze steentjes waarmee spelers een spreuk kunnen uitvoeren.Note: this library was designed for ease of use and simplicity, not for advanced use.InstallationTo install fandom-py, simply run:$ pip install fandom-pyfandom-py is compatible with Python 3.9+.DocumentationYou can find the documentation for fandom-pyhere.TestsTo run tests, clone therespository on GitHub, then run:$ pip install -r requirements.txt
$ bash runtests.bat  # will run tests for python
$ runtests.bat # will run tests for python (windows)
$ python3 -m unittest discover -s fandom/tests -p '*test.py'  # manual stylein the root project directory.LicenseMIT licensed. See theLICENSE
filefor
full details.Creditswiki-apiby
@richardasaurus for inspiration@nmoroze and @themichaelyang for feedback and suggestionsTheWikimedia
Foundationfor giving
the world free access to data@goldsmith for making such a fantastic library to fork/u/captainmeta4 for giving the idea for a reddit bot to post game wiki info
like auto-wiki bot@timidger for writing the wikia code this is based on
Package: fanesis
Facial Network AnalysisFanesis is a Facial Network Analysis tool that analyzes the faces and behaviors of individuals in a group and creates a visual representation of their relationships. Fanesis uses computer vision and machine learning techniques to detect the emotions and interactions of each individual. It then creates two types of associations: group-based and emotion-based. Group-based associations show how individuals are connected within the group, such as who knows whom, who is close to whom, and who is influential to whom. Emotion-based associations show how individuals feel about each other, such as who likes whom, who dislikes whom, and who is neutral to whom. Fanesis provides insights into the dynamics and characteristics of the group, which can be useful for various applications such as social network analysis, group psychology, and team building.Here is an example output from a very small dataset of images. We are presenting the results from a different embedding model. This allows us to analyze which person is more popular in the known dataset.[!WARNING]
The quality of the generated network depends on the quality of the embedding model.InstallationUsageUsing the individual classesfromfanesisimportIndividualize,Grouping,Visualizeimgs_path="./data/"base_path="./output/"output_path="./output/output/"i=Individualize(imgs_path,base_path)i.run()g=Grouping(output_path)df=g.run()v=Visualize(output_path)v.visualize(df)UsingFanesisPipelinefromfanesisimportFanesisPipelineimgs_path="./data/"base_path="./output/"pipeline=FanesisPipeline()pipeline(imgs_path,base_path)