Saravanan666/pypi-org huggingface dataset:
Package: videoflow-factory
videoflow-factoryvideoflow-factoryis a library for dynamically generatingVideoflowDAGs from YAML configuration files.videoflow-factoryInstallationUsageBenefitsContributingInstallationTo installvideoflow-factoryrunpip install videoflow-factory. It requires Python 3.6.0+ and Videoflow.UsageAfter installingvideoflow-factoryin your environment, there are two steps to creating DAGs. First, we need to create a YAML configuration file. For example:od_flow:description:"FyndTrak:MD&ODtoCacheFlow"owner:"KaushikB"tasks:reader:operator:videoflow.producers.VideoFileReadernode:Producerarguments:video_file:"./videos/sample.mp4"frame:operator:videoflow.processors.basic.FrameIndexSplitternode:Processordependencies:[reader]od_key:operator:videoflow.processors.KeyGeneratornode:Processorarguments:store_id:"abc"video_id:"abc"prefix:"od"dependencies:[reader]motion_detector:operator:videoflow.processors.detector.motion_detector.OpencvMotionDetectornode:Processordependencies:[frame]object_detector:operator:videoflow.processors.detector.AsyncObjectDetectornode:Processorarguments:url:"https://sample.url.com/api/v1/predict"nb_concurrent_tasks:500gradual_increase_task:Truedependencies:[frame]od_md_result_generator:operator:videoflow.processors.OdMdResultGeneratornode:Processordependencies:[motion_detector,object_detector]redis_cache:operator:videoflow.cache.RedisCachenode:Consumerdependencies:[od_key,od_md_result_generator]Then create a python script like this:fromvideoflow_factoryimportVideoflowFactoryimportosod_flow_config=os.path.abspath("./od_flow.yaml")od_flow=VideoflowFactory(od_flow_config)()od_flow.run()od_flow.join()And this DAG will be generated and the Flow will start running!BenefitsConstruct DAGs without knowing PythonConstruct DAGs without learning VideoFlow primitivesAvoid duplicative codeEveryone loves YAML! ;)ContributingContributions are welcome! Just submit a Pull Request or Github Issue.
Package: video-frame-processor
Python 3 library to make video frame processing easier.It allows processing video from webcams or video files,
with the user only having to supply a method that processes
the actual video frames. Everything else is handled by the
library.For more information and examples see:https://github.com/waikato-datamining/video-frame-processorChangelog0.0.1 (2021-01-05)initial release
Package: video-frame-selector
Meta-tool that presents frames from a video to image analysis frameworks and uses the predictions to determine
whether to use a frame or not.Frames can be presented as files (file-polling-based) with the predictions
then being read from files that the image analysis framework generated.Alternatively, a Redis (https://redis.io/) backend can be used (redis-based),
to broadcast the images as JPG bytes and then listening on another channel
for the predictions to come through. This approach avoids wearing out disks.Rather than just processing every n-th frame, a simple pruning mechanism can
be employed which discards frames that are too similar.Project page:https://github.com/waikato-datamining/video-frame-selectorChangelog0.0.9 (2022-01-27)added support for pruning frames that do not exhibit enough change over the previous one
(–prune,–bw_threshold,–change_threshold)0.0.8 (2021-11-02)process.pyandprocess_redis.pynow allow iterating through images (.jpg, .png) in a directoryprocess_redis.pynow handles predictions in bytes or str0.0.7 (2021-09-27)process.pynow adheres to the–output_metadataflagprocess_redis.pyallows processing of frames via Redis backend0.0.6 (2021-08-05)frames processedoutput is now always being outputadded logging output for frame file and metadata file inverbosemode0.0.5 (2021-08-05)added–output_metadataflag that stores information on predictions and cropping when outputting frames0.0.4 (2021-08-03)added–crop_to_contentflag that crops the frames to the bounding boxes
(only when not generating an output video)added–crop_marginoption to enforce a buffer around cropped regionadded–crop_min_widthand–crop_min_heightoptions to enforce a minimum width/height0.0.3 (2021-08-02)added–poll_intervaloption (https://github.com/waikato-datamining/video-frame-selector/issues/2)added logging output for when writing image to disk0.0.2 (2021-07-30)fixedreturnstatement inprocess_imagemethodadded more debugging outputadded–analysis_keep_filesoption for debugging purposes, which won’t delete the output
of the image analysis frameworkadded options for defining a frame window (–from_frame,–to_frame)0.0.1 (2021-07-21)initial release
Package: videofy
FeaturesTODORequirementsTODOInstallationYou can installVideofyviapipfromPyPI:$pipinstallvideofyUsagePlease see theCommand-line Referencefor details.ContributingContributions are very welcome.
To learn more, see theContributor Guide.LicenseDistributed under the terms of theMIT license,Videofyis free and open source software.IssuesIf you encounter any problems,
pleasefile an issuealong with a detailed description.CreditsThis project was generated from@cjolowicz’sHypermodern Python Cookiecuttertemplate.
Package: video-images-creator
Video Images CreatorThis package creates a video with animation for a set of Images urls(feature screens) along with there titles.Steps to generate your first videoStep 1:Install the package using pip:pip install video_images_creatorStep 2Create a python file Myfile.py with below codefrom video_images_creator import video_creator

feature_names = ["Splash Screen", "Search"] 
image_urls = ["https://buildernowassets.azureedge.net/builder-now-beta/uploads/staging/feature_figma/image/485/b478c7bd-84f8-48f2-81c7-3b9a5dbe7960.png", "https://buildernowassets.azureedge.net/builder-now-beta/uploads/staging/feature_figma/image/485/b478c7bd-84f8-48f2-81c7-3b9a5dbe7960.png"]

video_creator.build(image_urls, feature_names)#You can customize the images and feature namesStep 3Run your Python script to create the video inside the 'outputs' folder
Package: video-indexer
video_indexerThis library provides some common function for operating with Microsoft Video Indexer APIGetting startedpip install video_indexerCreate a VideoIndexer instancefrom video_indexer import VideoIndexer

CONFIG = {
    'SUBSCRIPTION_KEY': '',
    'LOCATION': '',
    'ACCOUNT_ID': ''
}

vi = VideoIndexer(
    vi_subscription_key=CONFIG['SUBSCRIPTION_KEY'],
    vi_location=CONFIG['LOCATION'],
    vi_account_id=CONFIG['ACCOUNT_ID']
)where
SUBSCRIPTION_KEY can be found athttps://api-portal.videoindexer.ai/developerLOCATION & ACCOUNT_ID can be found athttps://www.videoindexer.ai/settings/accountUpload a video for indexingvideo_id = vi.upload_to_video_indexer(
   input_filename='some-video.mp4',
   video_name='some-video-name',  # identifier for video in Video Indexer platform, must be unique during indexing time
   video_language='English'
)The library will retry with delay if it's being hit by throttling limit. Maximum 5 times of retrying.Get information for a videoinfo = vi.get_video_info(
    video_id,
    video_language='English'
)
Package: video-injection-pygame
PyGame Video InjectionYou are probably looking on how to make it so you can easily 
play videos inside of your pygame project without facing any huge troubles
and reinstalling old pygame versions. So here is a great solution for you!
only compatable with mp4 filesNow, you can easily create a 'video surface' and simply blit it onto your screenfrom video_pygame.video import VideoSurfacevs = VideoSurface(
    video_path='example.mp4',
    position=pygame.Vector2(0, 0,),
    size=(1000, 500)
)You can move it by changing it's position parameter - vs.position.x = 123You can check if it is playing or not by checking vs.playingand to get current frame, just call the object it self - vs()here are some function the library also hasVideoSurface().play() -> None: start playing video (audio included)
VideoSurface().stop() -> None: stop playing video and reset frame to zero (audio included)
VideoSurface().get_position() -> list: get current position of the video surfaceHere is some deeper explanation you dont really have to knowSo there is a data folder in the library, when you create a new video surface object
it should create a folder inside of this data called what your .mp4 file is named, if it already
exists we just leave it as it is. Next we add all of the frames of the video as .jpg files into this new
folder, if it was done before already we just leave it as it is again. And last but not least we check if 
the final result is corrupted, what that means is if all of the frames are in place. If the video has
730 frames, then you can only finish vs' initialization when there is a 'frame730.jpg' file in the folder, if there is not
then we clear all of the files currently being there and start initialization all over again and repeat the proccess
of creating .jpg files. So thats why it might take some time when creating a new vs object for the first time, but after
it has initialized for once, its going to be Way more faster next time you run your code. I am not going to explain how
video is being synced with its sound, which is stored as a .wav and converted to pygame.mixer.Sound object, and
everything i said is pretty much everything you have to know, though you can also go through the code - i left some notes there
but not much reallyThank you for choosing PyGame Video Injection :))
Package: videoio
videoio: save/load image sequence as H.264 videoA small Python module for saving and loading RGB and uint16 (depth) frames as H.264 encoded videoQuickstartSave/load RGB frames:importnumpyasnpfromvideoioimportvideosave,videoreadframes=np.random.random((20,200,400,3))#[framesNr, height, width, RGB]# Save to videovideosave("out.mp4",frames)# Load from videoframes=videoread("out.mp4")Read frames sequentially:fromvideoioimportVideoReaderforframeinVideoReader("in.mp4"):do_something_with(frame)Write frames sequentially:fromvideoioimportVideoWriterwriter=VideoWriter("out.mp4",resolution=(400,200))#[width, height]foriinrange(100):frame=get_frame()writer.write(frame)writer.close()orwithVideoWriter("out.mp4",resolution=(400,200))aswriter:foriinrange(100):frame=get_frame()writer.write(frame)Lossless write/read of uint16 3D arrays (useful for saving depth frames stored in mm, for example Kinect data):importnumpyasnpfromvideoioimportuint16save,uint16read# Generate 20 random depth framesdepth_frames=(np.random.random((20,200,400))*65535).astype(np.uint16)# Saveuint16save("out_depth.mp4",depth_frames)# Loaddepth_frames=uint16read("out_depth.mp4")Save RGB frames in lossless mode with different compression preset and different FPS:videosave("out.mp4",frames,lossless=True,preset="veryfast",fps=10.5)Read RGB frames and scale them to target resolution simultaneously:frames=videoread("in.mp4",output_resolution=(100,250))Read video/uint16-array starting from certain frame:(Works if the input video was created by videoio, other cases are not guaranteed)frames=videoread("in.mp4",start_frame=100)forframeinVideoReader("in.mp4",start_frame=100):do_something_with(frame)Prerequisitesffmpeg>=2.1with libx264 enabled andffprobe(usually comes with ffmpeg)numpyffmpeg-pythonInstallationFrom pip:pip install videoioFrom source:git clone https://github.com/vguzov/videoio.git
python setup.py install
Package: videojitter
videojitter - the video cadence measurement toolbox"You don't have to trust your eyes anymore"videojitter is a set of command line tools foraccurate measurement of frame
presentation timing in a video playback system. It can be used to detect and
quantify issues such as:Frames being displayed too early or too lateDropped framesRepeated framesPeriodic patternssuch as 3:2 "24p@60Hz"Sudden changesin presentation cadenceVideoclock jitterVideoclock skewetc.For more information and detailed documentation, see theproject homepage.
Package: videojoiner
VideoJoinerVideojoiner is now a Gooey program used to join video files together.
Documentation to come.The ffmpeg binaries are stored in%APPDATA%/videojoiner/ffmpegand will only be downloaded if missing or the '-d/--force-download' flag is passed.The output filename can be specified, or it will autogenerate a video file formattedmerged_video_YYMMDD_HHMMSS.EXTwhere the extension is copied from the first file in the input list.Installpip install videojoiner
Package: video-konverter
VideoKonverterVideoKonverter is a small python script for linux systems that allows you to convert video files to and from various formats. Since VideoKonverter works by interfacing with ffmpeg, most formats are accepted. So, why use VideoKonverter over ffmpeg directly? VideoKonverter supports converting entire directories of files to a given format!At some point, I may also get around to writing a qt front end.
Package: video-latency-test
video-latency-testThis project provides software for a simple video latency test,
utilizing the Linux framebuffer for video output and OpenCV for camera capture.UsageRunvideo-latency-testfrom the commandline.root@raspberrypi4-64:~# video-latency-test -h
usage: video-latency-test [-h] [--frames FRAMES] [--hue HUE] [--csv CSV]
                          output_fb cv2_cap

Run a video latency test

positional arguments:
  output_fb        The name of the framebuffer to use, e.g. fb0
  cv2_cap          Index of the cv2 capture device, e.g. 0

optional arguments:
  -h, --help       show this help message and exit
  --frames FRAMES  Number of frames to capture for the test
  --hue HUE        Hue threshold (uses hue values of 0-180)
  --csv CSV        Location to save a CSV log of captured dataImplementationThevideo-latency-testexecutable accepts a VideoOutputInterface object, and a VideoCapture object,
then measures the latency between setting a color on the VideoOutputInterface and detecting
that color on the VideoCaptureInterface.  The base implementation, using a Linux Framebuffer
for the output and a USB camera for the input, is shown in the diagram below.Video OutputInterfaceFramebuffer ImplementationVideo CaptureInterfaceFramebuffer ImplementationFrame TypesFrame types provide a method of generating frames written to the Video Output device,
along with a method of validating those frames from the Video Capture device.InterfaceSolid Colors
Package: videolog
Módulo Python para acesso à API do [Videolog](http://videolog.tv/“Videolog”).
A API do módulo ainda está incompleta e pode sofrer modificações até a versão
1.0 (que ainda deve demorar um bom tempo até aparecer)Pré-requisitosPython 2.6+Instalação$ pip install videologExemplos$ python
>>> from videolog.video import Video
>>> video = Video(“api-url”, “token”)
>>> video.search(“cool video”)
[]LicençaLicenciado sob os termos da [MIT License](http://www.opensource.org/licenses/mit-license.php).
Para detalhes, consulte o arquivo LICENSE-MIT
Package: videomap
Video Map ToolsTools to create,,  export and share video mapsFree software: GNU General Public License v3Documentation:https://videomap.readthedocs.io.FeaturesConvert a series of tiled maps to a tiled videovideomapconvert~/data/framesInterpolate a series of tiled map videosvideomapinterpolate~/data/framesWhere ~/data/frames contains frames in the structure~/data/frames/{frame}/{z}/{x}/{y}.pngframe:  the frame number
z: zoom level
x: tile column
y: tile rowPng’s are converted to transparent webm contained vp8 with alpha channel.CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2019-11-12)First release on PyPI.
Package: video-marker
Video MarkerVideo Marker is a python application based on OpenCV that can automate the following tasks:video recording from a webcam or any other OpenVC VideoCapture sourceprepend a video before your video record startsappend a video after your video record endsadd a watermark imagesave to a fileSetuppip install video-markerDocumentationvideo_marker -hUsage examplesMonitor your webcam, pressqkey on the keyboard orCTRL+cvideo_marker --video-cap 0 --monitorAdd watermark to your webcamvideo_marker --watermark-fpath 'assets/logo.png' --monitorA quite complete examplevideo_marker --watermark-fpath 'assets/logo.png' --monitor --pre-media assets/intro.mp4  --post-media assets/intro.mp4  --watermark-size 50You can stop the video recording gracefully, withSIGTERMsignalkill -SIGTERM $(ps a | grep video_marker | grep python | awk -F' ' {'print $1'} | xargs kill -SIGTERM).LicensesesLICENSEfile.AuthorGiuseppe De Marco
Package: videomass
VideomassIt is a FLOSS, powerful, multitasking and cross-platform graphical user interface (GUI) forFFmpegandyt-dlp. Designed for advanced and beginner users, it offers a wide range of features and functions, making it a comprehensive software solution.Videomass isFree (libre) Software,
written inPython3using thewxPython Phoenixtoolkit; it works on Linux, MacOs, Windows and FreeBSD.ChangelogFeaturesScreenshotsInstalling and DependenciesFor regular users (non-developers)If you are not a programmer or if you are not familiar with the command line
you can skip the whole part below and visit theDownload and installationweb page, which provides the information required to install Videomass on
each operating system.RequirementsPython >= 3.7.0 < 3.12.0wxPython-Phoenix >= 4.0.7PyPubSub >= 4.0.3requests >= 2.26.0ffmpeg >=5.1ffprobe >=5.1(usually bundled with ffmpeg)ffplay >=5.1(usually bundled with ffmpeg)Optionalsyt-dlpatomicparsleyInstall basic dependencies for your OSOSBasic DependenciesLinux/FreeBSDpython3, wxpython-phoenix, pip for python3, ffmpegMS Windowspython3, ffmpegMacOspython3, pip for python3, ffmpegInstall Videomass using pippython3 -m pip install videomassThis should also automatically install the remaining required dependencies
such as wxPython (only for Mac-Os and Windows), PyPubSub, yt-dlp and requests.On Linux and FreeBSD a launcher should be even created in the application
launcher of your desktop environment.To start Videomass on Mac-Os and MS-Windows open a console and typevideomasscommand.VisitInstalling dependencieswiki page for more explanations.Start Videomass manually from source codeVideomass can be run without installing it, just download and unzip thesource codearchive and
executing the "launcher" script inside the directory:python3 launcherFirst, make sure you have installed at least all the above required
dependencies.VisitInstalling dependencieswiki page for more explanations.Videomass can also be run in interactive mode with the Python interpreter,
always within the same unpacked directory:>>>fromvideomassimportgui_app>>>gui_app.main()ResourcesSupport Page and DocumentationWiki pageVideomass on PyPiDevelopmentOfficial download page
Package: video-ocr
video-ocrvideo-ocr is a command line tool and a python library that performs OCR on video frames, reducing the computational effort by choosing only frames that are different from their adjacent frames.Installationvideo-ocr usestesserocr, which in turn usestesseractas the OCR engine. So, please follow the tesserocr installation instructions.Install using pip:pip install video-ocrGetting startedCommand line usageRunvideo-ocr --helpto show the help text. Example usage isvideo-ocr/path/to/video.mp4--sample_rate=1--debug_dir="path/to/debug/dir"Python usageimportvideo_ocrvideo_ocr.perform_video_ocr("/Users/veneetreddy/Downloads/texts.mp4",sample_rate=1)
Package: video-pipeline
Video PipelineSimplify the video streaming pipeline to provide frame by frame image manipulation in near real-time.AbstractVideo streaming and image processing are really interesting!This package aims to simplify the video streaming pipeline so users can focus on the more interesting parts of image processing.
To learn more about how this is accomplished and the details that make up the pipeline see thedocs.Getting StartedThevideo-pipelinecomes with a command line interface (CLI) that you can utilize to preview, transport, and/or modify video streams!First you need to install thevideo-pipelinemodule from PyPI by running:pipinstallvideo-pipelineOnce installedvideo-pipelineshould be on yourPATH.Make sure you havevlcinstalled and on yourPATH.Run the following command to start streaming video from your webcam:video-pipelinestart--sourceos--transporttcp-servertransport-host=0.0.0.0transport-port=8000On the same computer (or another computer on your LAN) run the following command replacingHOSTNAMEwith the hostname of the computer runningvideo-pipeline.Note: If you're running on a linux machine you can runhostnameto get yourHOSTNAME.vlc"tcp/mjpeg://@HOSTNAME:8000/"You should now see a stream of your webcam!To learn more about thevideo-pipelinecommand line interface runvideo-pipeline --help.If you have any issues questions, comments, or concerns please feel free to submit an issue to theissue tracker.
Package: videoplayer
VideoPlayerVideoPlayer is a C-extension in Python to read OGG video files.SetupDependenciesYou'll need those packages:gliblibogglibtheoralibswscale(part offfmpeg).Native modulesBuild the extension:python setup.py build_ext --inplace --forceTestsTo test this python package, we are usingBig Buck Bunny trailers:OGG trailer(4.3MiB)IPhone trailer(3.8MiB)
Package: videoprocessor
基于 ffmpeg-python 的音视频处理工具依赖：ffmpegffmpeg-python (python module)项目初衷：该项目主要是针对日常对实验视频处理存在如下情况而提出：制作对比实验制作实验连环图为了提高实验视频的处理效率，进行了该项目的开发目前进度：目前该项目已封装成了Func APIvideo_info(in_filename: str)函数功能：获取输入视频的参数信息，在终端打印输出如下信息文件名称视频宽度视频高度视频总帧数输入参数：in_filename 输入视频文件路径addText(in_filename: str, out_filename:str, text: str)函数功能：在输入视频文件中添加文字水印用于视频说明输入参数：in_filename 输入视频文件路径out_filename 输出视频文件路径text 添加的文字内容getVideoPng(in_filename: str, out_picname):函数功能：处理输入视频文件，获取所有帧的图片数据输入参数：in_filename 输入视频文件路径out_picnamevideoCrop(in_filename: str, out_filename: str,whxy: list)函数功能：对输入视频文件进行裁剪，并将裁剪结果输出保存输入参数：in_filename 输入视频文件路径out_filename 输出视频文件路径whxy 列表，[w,h,x,y]w 裁剪目标视频宽度h 裁剪目标视频高度x 裁剪起始点 x 坐标y 裁剪起始点 y 坐标getOneFrame(in_filename: str, out_picname: str)函数功能：获取输入视频文件的单帧图片输入参数：in_filename 输入视频文件路径out_picname 输出图片路径drawBoxInPic(in_picname: str, out_picname: str, whxy: list)函数功能：在输入图片中绘制目标矩形框输入参数：in_picname 输入图片路径out_picname 输出图片路径whxywhxyvideoMerge2by2(in_filenames:list,out_filename)函数功能：输入 4 个视频将其合并为一个视频，布局为 2*2输入参数：in_filenamesout_filenamevideoMerge2by3(in_filenames: list, out_filename)函数功能：输入 6 个视频将其合并为一个视频，布局为 2*3输入参数：in_filenamesout_filenamevideoMerge(in_filenames: list, out_filename, mergesize: list)函数功能：输入 n*m 个视频合并输出为一个视频，合并布局为 n*m 的形式输入参数：in_filenames 输入视频文件路径列表out_filename 输出视频文件路径mergesize 布局列表 [n, m]n 行数m 列数picScale(in_picname: str, out_picname: str, scale: int)函数功能：输入图片将其按 scale 比例进行缩放并输出为新的图片输入参数：in_picname 输入图片路径out_picname 输出图片路径scale 缩放系数addTimeLabel(in_filename: str,out_filename,text: str)函数功能：输入图片，在图片中添加时间戳信息，用于连环图出图输入参数：in_filename 输入图片路径out_filename 输出图片路径text 时间戳文本内容addLabLogo(in_filename: str, out_filename: str, in_image: str, scale: int)函数功能：输入视频文件，在视频指定位置添加图片水印（实验室 logo）输入参数：in_filename 输入视频文件路径out_filename 输出视频文件路径in_image 水印图片文件路径scale 水印图片缩放系数