Wolfram 언어

계산 사진학

소셜 미디어에서 컬랙션 가져오기 및 분석

ServiceConnect를 사용하여 Flickr에서 이미지를 수집하고 Import를 사용하여 임베드된 메타 정보를 취득하고 획득한 이미지에 대한 다양한 통계를 계산할 수 있습니다.

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ServiceConnect["Flickr"]
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Flickr 사용자의 앨범 ID를 얻습니다.

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albumIDs = ServiceExecute["Flickr", "UserAlbums", "User" -> username];

ID로부터 실제 앨범에 대한 링크를 구축합니다.

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listOfAlbums = Normal@albumIDs[All, "ID"];

앨범에서 모든 사진에 대한 링크를 만들고 Exif 메타 데이터를 가져옵니다.

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links = ServiceExecute["Flickr", "AlbumImages", "AlbumID" -> ToString[#]] & /@ listOfAlbums;
전체 Wolfram 언어 입력 표시하기
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urlString = Flatten[Table[ Options[#[i, "Thumbnail"], MetaInformation][[1, 2, "Source", 1]], {i, Range[Length[#]]}] & /@ links]; paths = Quiet[ Flatten[Block[{constrURL}, constrURL = URLBuild[{"https://www.flickr.com", StringJoin[URLExpand[URLExpand[#]], "sizes/o"]}]; First[ Select[Import[constrURL, "ImageLinks"], StringMatchQ[#, "https" ~~ ___ ~~ ".jpg"] &]]] & /@ urlString]];
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exif = Quiet[Import[#, "Exif"] & /@ paths]; exif = Select[exif, MatchQ[#, _Association] &];

사진을 찍은 하루 동안의 시간의 분포를 시각화합니다.

전체 Wolfram 언어 입력 표시하기
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times = TimeObject /@ DeleteMissing[Lookup[exif, "DateTime"]]; times = If[# < TimeObject[{7, 0}], DateObject[Tomorrow, #], DateObject[Today, #]] & /@ times;
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DateHistogram[times, {DateObject[Today, TimeObject[{7, 0}]], DateObject[Tomorrow, TimeObject[{7, 0}] - Quantity[1, "Second"]], Quantity[.5, "Hours"]}, "Count", DateTicksFormat -> {"Hour12", " ", "AMPM"}, ImageSize -> 400]
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초점 거리의 정규화된 주파수를 시간에 따라 시각화합니다.

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Show[Table[ SmoothHistogram[selectFocal[dateFocal, year], PlotTheme -> "Marketing", GridLines -> None, FrameLabel -> {"Focal Length", "Normalized Frequency"}, FrameStyle -> Directive[Gray, Dotted, 12], PlotStyle -> colors[year], PlotLegends -> {year}, ImageSize -> Large, PlotRange -> {0, 0.035}], {year, yrs}], ImageSize -> 400]
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다양한 Exif 태그에 대한 시각화 요약 정리를 만듭니다.

전체 Wolfram 언어 입력 표시하기
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pieChart[prop_, t_: 80] := With[ {data = AssociationThread @@ Transpose[ Tally[SortBy[DeleteMissing[Lookup[exif, prop]], If[StringQ, ToExpression, Identity]]]]}, Labeled[ PieChart[Select[data, # > t &], ChartLabels -> Placed[Automatic, "RadialOutside"], PerformanceGoal -> "speed", PlotRange -> All], prop] ] props = Sort@{"ExposureTime", "FNumber", "ExposureProgram", "ISOSpeedRatings", "ApertureValue", "FocalLength", "ExposureMode", "WhiteBalance", "MeteringMode"};
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Multicolumn[pieChart /@ props]
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다음의 더 정교한 그래픽에서 시간에 따른 렌즈 사용 변화를 볼 수 있습니다.

전체 Wolfram 언어 입력 표시하기
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minThreshold = 70; granularity = {"Year", "Month"}; (*granularity={"Year","Month","Day"};*) palette = 97; pairs = Sort@ DeleteMissing[Lookup[exif, {"DateTime", "LensModel"}], 1, 2]; common = Select[Tally[pairs[[All, 2]]], Last[#] > minThreshold &][[ All, 1]]; models = GroupBy[ Select[pairs, MemberQ[common, Last[#]] &], (DateValue[First[#], granularity] &) -> Last, Rule @@@ Tally[#] &]; data = Accumulate@*(Normalize[#, Total] &) /@ (Map[ Replace[common, #, 1] &, Values@models] /. Thread[common -> 0]) // N; legend = SwatchLegend[ColorData[palette] /@ Range[Length[common]], common, LegendLayout -> "Row"]; filling = Prepend[Most[ Thread[RotateLeft[ Range[Length[common]]] -> ({{#}, ColorData[palette][# + 1]} & /@ Range[Length[common]])]], 1 -> {0, ColorData[palette][1]}]; Legended[DateListPlot[TemporalData[Transpose[data], {Keys[models]}], Joined -> True, Filling -> filling, AspectRatio -> 1/5, PlotStyle -> Transparent, FrameTicks -> {{None, None}, {None, All}}, LabelStyle -> Directive[GrayLevel[0, 1], FontFamily -> "Helvetica"], PlotRangePadding -> None, ImageSize -> 550, PlotLabel -> "Fraction of pictures by lens model"], Placed[legend, Bottom]]
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