黑马程序员&传智播客Python入门教程完整版（懂中文就能学会）免费视频课程配套讲义及代码课程官网:http://yun.itheima.com/course/273.htmlbilibili:https://www.bilibili.com/video/av14184325/

--------------------------------------------------------------------------------------TheExtendedCohn-Kanade(CK+)databasedistribution:PHASE1Initial:1stJuly2010Revised:28thSept2010---------------------------------------------------------------------------------------InthisPhasethereare4zippedupfiles.Theyrelateto:1)TheImages(cohn-kanade-images.zip)-thereare593sequencesacross123subjectswhichareFACScodedatthepeakframe.Allsequencesarefromtheneutralfacetothepeakexpression.2)TheLandmarks(Landmarks.zip)-AllsequencesareAAMtrackedwith68pointslandmarksforeachimage.3)TheFACScodedfiles(FACS_labels.zip)-foreachsequence(593)thereisonly1FACSfile,whichisthelastframe(thepeakframe).EachlineofthefilecorrespondstoaspecificAUandthentheintensity.Anexampleisgivenbelow.4)TheEmotioncodedfiles(Emotion_labels.zip)-ONLY327ofthe593sequenceshaveemotionsequences.Thisisbecausethesearetheonlyonesthefittheprototypicdefinition.LiketheFACSfiles,thereisonly1Emotionfileforeachsequencewhichisthelastframe(thepeakframe).Thereshouldbeonlyoneentryandthenumberwillrangefrom0-7(i.e.0=neutral,1=anger,2=contempt,3=disgust,4=fear,5=happy,6=sadness,7=surprise).N.Bthereisonly327files-IFTHEREISNOFILEITMEANSTHATTHEREISNOEMOTIONLABEL(sorrytobeexplicitbutthiswillavoidconfusion).Examples:-----------------------------------------------------------------------------------Allfilenameandstructureshouldbethesame.Forexample,animageat:cohn-kanade-images/S005/001/S005_001_00000011.png------------------------------------------------------------------------------------willhavethecorrespondinglandmarkat:Landmarks/S005/001/S005_001_00000011_landmarks.txt------------------------------------------------------------------------------------FACScodeat:FACS/S005/001/S0005_001_00000

输出灰度图像,RGB彩色图像会自动转换为灰度图像输出图像的多重分形谱参考文献："fractalanalysisandmultifractalspectrafortheimages"

TheCAS-PEALfacedatabasehasbeenconstructedunderthesponsorsofNationalHi-TechProgramandISVISIONbytheFaceRecognitionGroupofJDL,ICT,CAS.ThegoalstocreatethePEALfacedatabaseinclude:providingtheworldwideresearchersofFRcommunityalarge-scaleChinesefacedatabasefortrainingandevaluatingtheiralgorithms;facilitatingthedevelopmentofFRbyprovidinglarge-scalefaceimageswithdifferentsourcesofvariations,especiallyPose,Expression,Accessories,andLighting(PEAL);advancingthestate-of-the-artfacerecognitiontechnologiesaimingatpracticalapplicationsespeciallyfortheoriental.Currently,theCAS-PEALfacedatabasecontains99,594imagesof1040individuals(595malesand445females)withvaryingPose,Expression,Accessory,andLighting(PEAL).Foreachsubject,9camerasspacedequallyinahorizontalsemicircularshelfaresetuptosimultaneouslycaptureimagesacrossdifferentposesinoneshot.Eachsubjectisalsoaskedtolookupanddowntocapture18imagesinanothertwoshots.Wealsoconsidered5kindsofexpressions,6kindsaccessories(3glasses,and3caps),and15lightingdirections.Thisfacedatabaseisnowpartlymadeavailable(asubsetnamedbyCAS-PEAL-R1,contain30,900imagesof1040subjects)forresearchpurposeonlyonacase-by-casebasisonly.JDLisservingasthetechnicalagentfordistributionofthedatabaseandreservesthecopyrightofalltheimagesinthedatabase.

Thishandbookpresentsandillustratesanextensivecollectionofimageprocessingtoolstohelptheuserandprospectiveuserofcomputer-basedsystemsunderstandthemethodsprovidedinvarioussoftwarepackagesanddeterminethosestepsthatmaybebestsuitedforparticularapplications.

Wesuggesttailoringoftheillumination’scomplexdegreeofcoherenceforimagingspecifictwo-andthree-pointobjectswithresolutionfarexceedingtheRayleighlimit.Wefirstderiveaformulafortheimageintensityviathepseudo-modedecompositionandthefastFouriertransformvalidforanypartiallycoherentillumination(Schell-like,non-uniformlycorrelated,twisted)andthenshowhowitcanbeusedfornumericalimagemanipulations.Further,forSchell-modelsources,weshowtheimpr

SSM权限管理零碎

（含源码及报告）本程序分析了自2016年到2021年（外加）每年我国原油加工的产量，并且分析了2020年全国各地区原油加工量等，含饼状图，柱状图，折线图，数据在地图上显示。
运转本程序需要requests、bs4、csv、pandas、matplotlib、pyecharts库的支持，如果缺少某库请自行安装后再运转。
文件含6个excel表，若干个csv文件以及一个名字为render的html文件（需要用浏览器打开），直观的数据处理部分是图片以及html文件，可在地图中显示，数据处理的是excel文件。
不懂可以扫文件中二维码在QQ里面问。

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在日常工作中，钉钉打卡成了我生活中不可或缺的一部分。然而，有时候这个看似简单的任务却给我带来了不少烦恼。 每天早晚，我总是得牢记打开钉钉应用，点击"工作台"，再找到"考勤打卡"进行签到。有时候因为工作忙碌，会忘记打卡，导致考勤异常，影响当月的工作评价。而且，由于我使用的是苹果手机，有时候系统更新后，钉钉的某些功能会出现异常，使得打卡变得更加麻烦。 另外，我的家人使用的是安卓手机，他们也经常抱怨钉钉打卡的繁琐。尤其是对于那些不太熟悉手机操作的长辈来说，每次打卡都是一次挑战。他们总是担心自己会操作失误，导致打卡失败。 为了解决这些烦恼，我开始思考是否可以通过编写一个全自动化脚本来实现钉钉打卡。经过一段时间的摸索和学习，我终于成功编写出了一个适用于苹果和安卓系统的钉钉打卡脚本。