Saravanan666/pypi-org huggingface dataset:
Package: cvbot
CVBot for desktop automationCVBotis a python package developed to make using computer vision techniques easier and simple to use.
Its main focus is toaid in automating visual desktop related tasksfor repetitive work, games and others. Working "like a human".FeaturesMouse & keyboard control.Control windows and get their position.OpenCV image wrapperImage classto easily crop, resize, show, and convert images.Flexible digits & numbers recognition/matching.Powerful image search on screen or a local file.Implements sophisticated image search techniques like SIFT.Color based object detection.Very fast screenshot grab.Accurate OCR integrated withImage class.Artificial Intelligence based object detection support using Yolov7.UpcomingBetter documentation.More QOL functions and classes.More detection options.Simple exampleDetect an object on the screenfromcvbot.captureimportscreenshotfromcvbot.ioimportread_imgfromcvbot.matchimportlook_forobj=read_img("object.png")# Read 'object.png' file, (an object currently visible on screen)scimg=screenshot()# Take a screenshotpos=look_for(obj,scimg,0.6)# Image search function, parameters: (needle, haystack, search confidence 1 = 100%)print(pos)# PRINTS: (188, 538) # None if not foundLinksFull DocumentationGithub
Package: cvbuilder
OpenCV Hands-FreeUnofficialOpenCV builder for Python.This package aims at building OpenCV 4.5.4 with Python bindings from the official sources.
It provides a simple command line interface for starting the process of downloading the
official sources, configuring the build dependencies, compiling and installing the resulting
CV2 shared object within a virtual environment.In contrast toopencv-pythonit will not provide any
wheels and therefore the installation / build process will be by far slower (depending on the
actual system performance).IMPORTANT NOTEDepending on the usage and system dependencies, the on-the-fly build output can
contain video and GUI functionality and the contrib package.Featuresbuilds against Python >= 3.6runs and builds inside virtual environmentincludes video supportsupports OpenCV check (import, build information)compiles with many flags enabled (which???)Supported OSDebian Jessie, StretchUbuntu 18.04LinuxMint 18.2ManjaroArchRaspbian 9 (Stretch)Supported Python runtimesCPython 3.6, 3.7, 3.8, 3.9PyPy (not yet)Note:PyPy (7.3.0) is not supported yet due to missing path variables in modulesysconfig.InstallationUse a Python'svirtual environmentor even better add the package viapoetry:poetry add cvbuilderFollow instructions belowUsageAfter installing the package viapip/pipenv/poetry, you can manually invokecvbuildercommands.Install system dependenciescvbuildersystem--enable-gui--enable-videoDownload, configure, build, installThedo-it-allcommand is:cvbuilderbuildor if you already downloaded the source zip files in the default temporary
directory or need to rerun the process in a clean way:cvbuilderbuild--cleanCustomIf you need to run the individual steps (i.e. for debugging) the following
commands are provided.Download sourcescvbuilderdownloadGenerate make configcvbuilderconfigure[--tmpdirXYZ]CompilecvbuildermakeInstallcvbuilderinstallDumpcvbuilderdumpCheckYou can run the check command:cvbuildercheckin order to check whether the build process and installation worked.Running OpenCVNow everything should be up and running and you should be able to work with OpenCV:Start a python REPL:poetry run pythonImport the CV package:import cv2ReadOpenCV documentation
Package: cvc
CVCConvert video to character art animation.中文说明InstallInstall cvc:pip install cvcThis tool relies onimageio-ffmpeg, but only the binary version ofimageio-ffmpegcontains theffmpegbinary.
if pip choose the source version, problem will occurs.Usagecvc --chars_width 120 --t_end 10 path/of/video_fileThe command shows that the specified video will be converted to an ascii art animation with the width of 120, and only convert the first 10 seconds.
you'll see a file namedoutput.mp4in your current directory when completes, have fun ~p.s. it's a bit slow, turn down the width and fps, to speed up the conversion.Checkcvc --helpfor more information.
Package: cvdast
cv-dastCV-DAST is a Python library for regenerating the pytest fixtures and test cases dynamically from Open API Spec and Cloudvector APIShark eventsVisithttps://www.cloudvector.com/api-shark-free-observability-security-monitoring-tool/#apisharkInstallationUse the package managerpipto install foobar.pipinstallcv-dastUsage****************************************************************************************************CloudVectorCommunityEdition-Coverageanalysisplugin****************************************************************************************************EnterCommunityEdition(CE)hostinformat<host>:<port>:x.x.x.x:yEnteryourCommunityEdition(CE)username:sandeepCommunityEdition(CE)password:EnterabsolutepathtoOldAPISPEC:../input.jsonEnterabsolutepathtonewAPISPEC:../input1.jsonDoyouwanttoprocessonlydiff?(Y/N):Enterabsolutepathtoinputparameteresjson(pressEnterforNone):instead of giving inputs every single time you can also alternatively create a file called my_cesetup.yaml in the path from where you are running the toolce_host:ce_username:you can have multiple such my_cesetup.yaml for different CE setup or different recordings and run them from specific paths for its corresponding reportsLicenseMIT
Package: cv-dice-detection
Welcome to the documentation for our Computer Vision class project.
This Python library has been developed to detect live-streamed dice numbers.
The objective is to provide a straightforward tool for identifying and analyzing
dice numbers in real-time. This documentation offers detailed information on
the library’s functionalities, installation procedures, and practical examples
to facilitate the utilization of our solution. The project is a reflection of our
exploration into the world of Computer Vision, born out of the requirements
of our class assignment. We invite you to navigate through this documentation as
we delve into the intricacies of dice detection using Python
Package: cvd-risk-scores
CVD-risk-scoresA Python package for computing cardiovascular disease risk using clinically validated models.Note:This is a work in progressInstallThis package is available on PyPIpipinstallcvd-risk-scoresGetting startedCVD-risk-scoresis based upon thetorchphilosophy of callable objects. EachRiskModelsubclass is a callable upon
initialisation, taking an array-like of subjects, each defined by some variables of interest, and returning an array-like offloatvalues corresponding to cardiovascular risk scores.importcvd_risk_scores# Instantiate the risk model we are interested inrisk_model=cvd_risk_scores.FraminghamRiskScore()# Define our subject, in this case using a dictionarysubject={"gender":"female","age":61,"SBP_nt":124,"SBP_t":0,"TotalChol":180,"HDL":47,"smoker":True,"diabetes":False}# Create a numpy array from features valuesdata=np.array([list(subject.values())])# Alternatively:#data = np.array([#  ["female", 61, 124, 0, 180, 47, True, False]#])# define a dictionary mapping our own column names to the names# expected by the risk score model.# if data is either a numpy array or a list of lists,# the `columns_map` mapping must present the columns# in the correct order so that data can be cast to a pandas DataFrame.columns_map={"gender":"sex","age":"age","SBP_nt":"SBP_nt","SBP_t":"SBP_t","TotalChol":"tch","HDL":"HDL","smoker":"smoking","diabetes":"diabetes"}# Compute the risk scorerisk_score=risk_model(data=data,columns_map=columns_map)AboutCVD-risk-scoresis a Python package for computing cardiovascular disease risk using clinically validated models. It exposes an object-based API for interacting with risk models that is inspired by thetorchparadigm of callable objects.Available risk models:Framingham Risk ScoreReferences[1] D'Agostino, Ralph B Sr et al. “General cardiovascular risk profile for use in primary care:
the Framingham Heart Study.” Circulation vol. 117,6 (2008): 743-53. doi:10.1161/CIRCULATIONAHA.107.699579
Package: cvds
datastateDataset statistical calculation.How to usefromcvdsimportcalc_mean_std,SegLabel# calculate mean and std from image datasetmsd=calc_mean_std("dataset/image")print(msd)"""output:{'mean': array([[0.4923597 , 0.4912278 , 0.44912583]], dtype=float32), 'std': array([[0.2124527 , 0.20088832, 0.22155836]], dtype=float32)}"""# check label's informationlab_infor=SegLabel("dataset/label",num_classes=4)print(lab.area)# area of each categoryprint(lab.sample)# number of samples per categoryprint(lab.index([0,1,2,3]))# list of path with index category"""output:{'0': 18.079630533854164, '1': 42.78903537326389, '2': 18.866475423177086, '3': 20.26485866970486}{'0': 5, '1': 8, '2': 4, '3': 6}['dataset\\label\\45.png', 'dataset\\label\\47.png']"""TODOcalc neam and std (population).calc area of each category in segmentation task.calc number of samples per category in classification task.calc anchor size and etc in detection task.add other state calc about dataset.
Package: cve-analyzer
CVE analyzerThis project aims to extract from a collection of vulnerabilities report expressed in common English language various semantic information.
These semantic information are encoded and retrieved using Name Entity recognition (NER) on the description and currently the available labels are the following:FUNCTION: Vulnerable function name.VERSION: Vulnerable version of the target program.SOURCECE: Path to the source code that contains the vulnerable function/functions.DRIVER: Driver that we the attacker needs to interact with to trigger the exploit.STRUCT: Malformed struct that contains the bug.VULNERABILITY: Type of the vulnerability (e.g. buffer overflow, etc...).CAPABILITY: Capability that the attacker gains after a successful exploitation of the vulnerability (e.g. remote code execution, etc...).DatasetThe dataset on which the initial state of the project has been developed and tested on is the list of Common Vulnerability Exposure (CVE) regarding the Linux kernel for the years 2017 and 2018 (for this first implementation). The dataset can be found on the websiteCVE detailThe dataset is formatted as a Comma Separated Values (CSV) but it has been simplified from it's original version and only the description fields has been taken into account.InstallationInstall the project and al its dependencies with:pip install cve_analyzer
Package: cvebase-wiki
cvebase-wikicvebase's command line tool for interacting with cvebase.com wiki data.Visit cvebase.com web appView wiki repo on GitHub (cvebase/cvebase.com)Installationpython3 -m pip install cvebase-wiki --upgradeUsageLint all CVE & Researcher markdown files.cvebase-wiki lint -r <path to cvebase.com repo>Edit CVE file. Looks for ${EDITOR} env variable, then system editor in order: vim, emacs, nano.cvebase-wiki edit -t <path to cvebase.com repo> -t cve CVE-2020-14882
Package: cve-bot
CVE Bot: Telegram bot that notifies about package update linked with CVETry it out!Key FeaturesFrequent DB updateGet actual info based on CVE number or Package nameSubscribe to update at any number of CVEsTechnical Requirements/InstallationPre-requirementsInstall Python 3.9, and pip package management tool.Development StatusCVE Bot is in active development and accepts contributions. See ourContributingsection below for more details.We report new releases informationhere.How to contributeFork, clone, setup development environment.No third-party build or test toolsneed to be installed at your system.python3-mvenv.venv
../.venv/bin/activate
pipinstallsetuptoolswheel
pipinstall-e'.[dev]'After that you'll have cve_bot and all development tools installed into virtualenv. Refer toconfigto set proper env vars for development. Actually the minimum required isCVE_BOT_TOKENwith your token
Hack, then make PR. Don't forget to write unit tests, and check your code:flake8cve_bot
isort-ccve_bot
black--checkcve_bot
pytest--covOr you can just install git-hooksGit hooksln-s-r-t./.git/hooks/./hooks/*LicenseMIT, seeLICENSE.
Package: cvectors
CvectorsCvectors is a Python package for 2D vectors. It provides a class,Vector, which usescomplexinternally.Usage is as follows:>>>fromcvectorsimportVector>>>foo=Vector(4,3)>>>fooVector(4.0,3.0)>>>foo.x4.0>>>foo.y3.0>>>foo.r5.0>>>bar=Vector(4,5)>>>foo+barVector(8.0,8.0)>>>foo.dot(bar)31.0>>>importmath>>>foo.rotate(math.pi/2)Vector(-2.9999999999999996,4.0)>>>Vector.from_polar(r=3,theta=5)-Vector.from_polar(r=5,theta=2)Vector(2.9317207391253906,-7.423259958117824)>>>Vector(5,6).perp_dot(Vector(-6,1))41.0>>>abs(foo)5.0>>>Vector(1,-9).rec()(1.0,-9.0)>>>Vector(1,-9).pol()(9.055385138137417,-1.460139105621001)>>>Vector(3,2).perp()Vector(-2.0,3.0)>>>Vector(3.142,2.718).round()(3,3)>>>Vector(3.142,2.718).round(1)(3.1,2.7)
Package: cvedb
CVEdbCVEdb is yet another Python CVE database library and utility. There are lots already available. Why create another?
Most existing libraries rely on a third party API likecve.circl.lu, which can and do
throttle usage, require registration, and/or demand an internet connection. Some libraries are bloated, including web
interfaces for search.CVEdb Features:Can be used either as a library or a command line utilitySimple APIDownload directly from theNational Vulnerability DatabaseAutomatically, incrementally update at any timeCVEdb Anti-Features:Does not require many dependenciesDoes not have a web serverDoes not require Internet connectivity other than to download new CVEsInstallation$pip3installcvedbCommand Line Usage$cvedb--helpPython Examplesfromcvedb.dbimportCVEdbwithCVEdb.open()asdb:forcveindb:print(cve)By default, the CVEs downloaded from NIST are saved to a sqlite database stored incvedb.db.DEFAULT_DB_PATH, which is
set to~/.config/cvedb/cvedb.sqlite. This can be customized by passing thedb_pathargument toCVEdb.open.Thedb.data()function returns an instance of acvedb.feed.Dataobject, which hasnumerous methods to query CVEs.
For example:withCVEdb.open()asdb:forcveindb.data().search("search term"):print(cve)In addition to accepting strings, thedata().search(...)function will accept anycvedb.search.SearchQueryobject.Known IssuesThe NIST National Vulnerability Database is in the process of transitioning to a new REST API. The datasets on which
CVEdb is built are still available, but it is unclear whether they may become deprecated. Also, NIST has started rate
limiting downloads, which may affect CVEdb syncing. Therefore, CVEdb shipspre-seeded with a database. Therefore, CVEdb does not
require any Internet connectivity after it is installed, other than to download new CVE definitions. Also, the behavior
of CVEdb was changed from automatically checking for updates as necessary to now requiring the user explicitly request
an update with the new--updateargument. Support for the new REST API is being tracked inthis GitHub issue.License and AcknowledgementsCVEdb was created byTrail of Bits.
It is licensed under theGNU Lesser General Public License v3.0.Contact usif you're looking for an exception to the terms.
© 2021, Trail of Bits.TheCVE database shipped with CVEdbis created and
maintained by NIST and is released in the public domain.
Package: cvee
cveeA set of tools for CV researchers.InstallationWe aim to limit our dependencies to the following libraries (which should be quite common):torch
numpy
opencv2
matplotlib
pyyaml
richAnd following libraries should be optional:trimesh (for geometry process)
open3d  (for 3d visualization)Install locallypipinstall-e.AcknowledgementSome code is adapted frommmcvanddetectron2.
Package: cvehunter
CVEHunter - Async python wrapper for CVE/CPE dataCVEHunter is a Python asynchronous library designed to simplify the retrieval of CVE (Common Vulnerabilities and Exposures) and CPE (Common Platform Enumeration) information using the NVD API. It streamlines the process of searching for and accessing valuable security data for vulnerability assessment and management.Installationpip3 install cvehunterExampleCode:importasynciofromcvehunterimportCveHunterasyncdeftest()->None:ch=CveHunter()cve=awaitch.search_by_cve("CVE-2023-41991")print(cve.cve_id)print(cve.cwe_id)print(cve.description)print(cve.cvss_v3)print(cve.references)asyncio.run(test())Output:CVE-2023-41991
CWE-295
A certificate validation issue was addressed. This issue is fixed in macOS Ventura 13.6, iOS 16.7 and iPadOS 16.7. A malicious app [...]
{'score': 5.5, 'vector': 'CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:H/A:N', 'severity': 'MEDIUM', 'version': 3.1, 'exploitability': 1.8, 'impact': 3.6}
['http://seclists.org/fulldisclosure/2023/Oct/5', 'https://support.apple.com/en-us/HT213927', 'https://support.apple.com/en-us/HT213931']DocumentationThe documentation is hosted on readthedocs, check ithereTODOChange historyBetter filtersContributingContributions are welcome! If you'd like to contribute to CVEHunter, please follow the guidelines outlined in the Contributing Guide.LicenseThis project is licensed under the MIT License.
Package: cve-lookup
CVE LookupLook up Common Vulnerabilities and Exposures (CVE for short) and get details about them.How to useAs a program$cve_lookupCVE-2017-5754
CVE-2017-5754
CVSS:3.0/AV:L/AC:H/PR:L/UI:N/S:C/C:H/I:N/A:N(AV:L/AC:M/Au:N/C:C/I:N/A:N)4.7"Medium"As a libraryimportcve_lookupmy_cve=cve_lookup.cve("CVE-2017-5754")print(my_cve.id)print(my_cve.cvss3v)print(my_cve.cvss2v)print(round(my_cve.cvss2.score_overall,1),'\"{}\"'.format(my_cve.cvss2.score_name))InstallFrom PyPi$pip3installcve_lookupFrom GitHub$gitclonehttps://github.com/machinething/cve-lookup
$cdcve-lookup
$gitcheckoutproduction# Skip if you want a development build$pip3install-rrequirements.txt
$python3setup.pyinstallRequirements/DependenciesPython3 and Pip3An internet connection (You probably have one)
Package: cve-maker
CVE-MAKERUse this softwareonly for legal purposes.I am in no way responsible for your actions.Use python 3.11.2Made by msd0peDESCRIPTIONcve-maker is a hub for finding CVEs and exploits. It is based on the official NIST, ExploitDB and Github databases. The tool makes it quick and easy to search for CVEs and their associated exploits. It is able to detect exploit compilation options. It can also be used to list the latest critical vulnerabilities.USAGEINSTALLATIONFrom PIP:apt-get install python3 python3-pip python3-dev git libssl-dev libffi-dev build-essential curl
pip3 install --upgrade pip
pip3 install cve-makerOr download the project:apt-get install python3 python3-pip python3-dev git libssl-dev libffi-dev build-essential virtualenv curl
git clone https://github.com/msd0pe-1/cve-maker/
cd cve-maker
virtualenv -p python3 venv
source venv/bin/activate
pip3 install --upgrade pip
pip3 install .# Launch:
python3 -m cve-makerCONTRIBUTINGThis project is in active development. Feel free to suggest a new feature or open a pull request !
Package: cvemanager
cve_managerA python script that:a) parses NIST NVD CVEs,
b) prcoesses and exports them to CSV files,
c) creates a postgres database and imports all the data in it, and
d) provides query capabilities for this CVEs database.It required Python 2.7.x (soon to be migrated to Python 3)Usage examples:Download, parse and save in CSV files all CVEs from NIST NVD:
./cve_manager.py -d -p -csvCreate a postgresql database to host the downloaded CVEs:
./cve_manager.py -u  -ps  -host  -db <database_name> -ow <new_owner of database> -cdCreate the tables and views at the database:
./cve_manager.py -u  -ps  -host  -db <database_name> -ctImport all data into the created database (requires the download, parse and sdtore as CSV files first, as explained above):
./cve_manager.py -u  -ps  -host  -db <database_name> -idb -pQuery for a specific CVE:
./cve_manager.py -u  -ps  -host  -db <database_name> -cve 2019-2434Query for all CVEs related with a product (e.g. windows), with a base metric score greater than a value (e.g. 9, that is critcal), and a publication date equal or newer than a specific year (e.g. 2018):
./cve_manager.py -u  -ps  -host  -db <database_name> -pr radar -sc 9 -dt 2018Query for all CVEs with a base metric score greater than a value (e.g. 9, that is critcal), and a publication date equal or newer than a specific year (e.g. 2019):
./cve_manager.py -u  -ps  -host  -db <database_name> -sc 9 -dt 2019Truncate the contents of all tables (required if you want to repeat the import process so as to update the data):
./cve_manager.py -u  -ps  -host  -db <database_name> -trDelete the database (remove it completely):
./cve_manager.py -u  -ps  -host  -db <database_name> -ddComplete list of supported arguments:-h, --help            show this help message and exit-v, --version         show program's version number and exit-p, --parse           Process downloaded CVEs.-d, --download        Download CVEs.-y YEAR, --year YEAR  The year for which CVEs shall be downloaded (e.g. 2019)-csv, --cvs_files     Create CSVs files.-idb, --import_to_db  Import CVEs into a database.-i INPUT, --input INPUT
The directory where NVD json files will been downloaded, and the one from where they will be parsed
(default: nvd/)-o RESULTS, --output RESULTS
The directory where the csv files will be stored (default: results/)-u USER, --user USER  The user to connect to the database.-ow OWNER, --owner OWNER
The owner of the database (if different from the connected user).-ps PASSWORD, --password PASSWORD
The password to connect to the database.-host HOST, --host HOST
The host or IP of the database server.-db DATABASE, --database DATABASE
The name of the database.-cd, --create_database
Create the database-dd, --drop_database  Drop the database-ct, --create_tables  Create the tables of the database-tr, --truncate_cves_tables
Truncate the CVEs-related tables-cve CVE, --cvs_number CVE
Print info for a CVE (CVSS score and other)-sc SCORE, --score SCORE
Use base score as a selection criterion-dt DATE, --date DATE
Use publication date as a selection criterion
Package: cve-py
cve-pycve-py is a Python library that allows users to track Common Vulnerabilities and Exposures (CVEs) from the National Vulnerability Database (NVD). The project fetches data from the NVD and stores it in a database for easy access and analysis.InstallationInstall package from PyPI:pipinstallcve-pyContributingIf you'd like to contribute to the project, please follow these steps:Fork the repository.Create a new branch for your changes:git checkout -b my-new-feature.Make your changes and commit them:git commit -am 'Add some feature'.Push to the branch:git push origin my-new-feature.Submit a pull request.LicenseCVE Tracker is licensed under theMIT License. Feel free to use it for personal or commercial use.
Package: cver
CVERA simple commandline app for searching and looking up opensource vulnerabilitiesInstallationUsing Pip$pipinstallcverManual$gitclonehttps://github.com/citguru/cevr
$cdcver
$pythonsetup.pyinstallUsage$cverSearchsearch <keyword>$cversearchpythonLookupsearch <name>$cverlook-upCVE-2020-2121
Package: cvertools
当前版本1.0.3说明这是一些CV工作人员常用的函数组成的包，可以简化一些读写操作，使代码更加可读。主要包括两个部分：基本的读写工具和机器学习/深度学习工作中常用的数据处理函数。baseio基本的读写工具。包括了文件读写、文件夹读写、数据读写等功能。baseml机器学习/深度学习工作中常用的数据处理函数。包括划分十折交叉数据、常见json格式数据读取等功能。Emamplepass
Package: cvesearch
CVESearchis a tool to simplify searching for exploits, references and proof-of-concept codes fairly simple from sources like Metasploit, Exploit-DB etc. All you need is a Linux/Windows box with*Python3*installed. Internally, this tool works as a thin wrapper around:https://cve.circl.lu/without which, this project might have not been possible!## RequirementsPython 3.xrequeststermcolorujson (optional, but good to have!)## Install` * pip3 install cvesearch `## Usage` * cvesearch-h# Show help and exit * cvesearch-s2017-0145# Show all found matches `## FeedbackShould you have any feedback or suggestion, kindly drop an email to the author (Sujit Ghosal,thesujit[@]gmail[.]com) mentionining your inputs.## DisclaimerPlease, use this tool at your own risk. The author shall not be responsible for any misuse done through usage of this tool. Any actions and or activities related to this tool is solely your responsibility. The misuse of this tool might result in criminal charges brought against the persons in question. Please pay respect to the third-party website owners and bandwidth, who makes these type of structured information available easily to the public.