我正在尝试构建一个示例Android应用，以提取使用Google相机应用拍摄的人像模式照片的深度图。我知道它会随模糊的照片一起保存。
我阅读了来自Google的动态深度格式文档：https://developer.android.com/training/camera2/Dynamic-depth-v1.0.pdf这是很新的东西，我找不到与此主题相关的任何资源，也没有找到如何管理android portrait深度图提取的资源。
我使用元数据提取器库以编程方式读取文件的元数据，尤其是XMP Part，因为它是在其中深度介绍信息的。我在Kotlin中编写了一个示例代码来尝试提取深度图：
val inputStream = contentResolver.openInputStream(imageUri)
inputStream?.let { stream ->
val metadata = JpegMetadataReader.readMetadata(stream)
val directories = metadata.directories
val xmpDirectories = metadata.getDirectoriesOfType(XmpDirectory::class.java)
for (xmpDirectory in xmpDirectories) {
val xmpMeta = xmpDirectory.xmpMeta
val itr = xmpMeta.iterator()
while (itr.hasNext()) {
val propertyInfo = itr.next() as XMPPropertyInfo
println(propertyInfo.path + " :: " + propertyInfo.value)
}
}
stream.close()
}
结果输出：
xmpNote:HasExtendedXMP :: 5c970bbab778024b23c5a8269325455c
null :: null
GCreations:CameraBurstID :: 9e286063-a919-4a74-96ee-d7e02d2a17d2
null :: null
GCamera:BurstID :: 9e286063-a919-4a74-96ee-d7e02d2a17d2
GCamera:BurstPrimary :: 1
GCamera:SpecialTypeID ::
GCamera:SpecialTypeID[1] :: com.google.android.apps.camera.gallery.specialtype.SpecialType-PORTRAIT
null :: null
Device:Container ::
Device:Container/Container:Directory ::
Device:Container/Container:Directory[1] ::
Device:Container/Container:Directory[1]/Item:Mime :: image/jpeg
Device:Container/Container:Directory[1]/Item:Length :: 0
Device:Container/Container:Directory[1]/Item:DataURI :: primary_image
Device:Container/Container:Directory[1]/rdf:type :: http://ns.google.com/photos/dd/1.0/container/:Item
Device:Container/Container:Directory[2] ::
Device:Container/Container:Directory[2]/Item:Mime :: image/jpeg
Device:Container/Container:Directory[2]/Item:Length :: 1499039
Device:Container/Container:Directory[2]/Item:DataURI :: android/original_image
Device:Container/Container:Directory[2]/rdf:type :: http://ns.google.com/photos/dd/1.0/container/:Item
Device:Container/Container:Directory[3] ::
Device:Container/Container:Directory[3]/Item:Mime :: image/jpeg
Device:Container/Container:Directory[3]/Item:Length :: 316885
Device:Container/Container:Directory[3]/Item:DataURI :: android/depthmap
Device:Container/Container:Directory[3]/rdf:type :: http://ns.google.com/photos/dd/1.0/container/:Item
Device:Container/Container:Directory[4] ::
Device:Container/Container:Directory[4]/Item:Mime :: image/jpeg
Device:Container/Container:Directory[4]/Item:Length :: 65189
Device:Container/Container:Directory[4]/Item:DataURI :: android/confidencemap
Device:Container/Container:Directory[4]/rdf:type :: http://ns.google.com/photos/dd/1.0/container/:Item
Device:Profiles ::
Device:Profiles[1] ::
Device:Profiles[1]/Profile:Type :: DepthPhoto
Device:Profiles[1]/Profile:CameraIndices ::
Device:Profiles[1]/Profile:CameraIndices[1] :: 0
Device:Profiles[1]/rdf:type :: http://ns.google.com/photos/dd/1.0/device/:Profile
Device:Cameras ::
Device:Cameras[1] ::
Device:Cameras[1]/Camera:Trait :: Physical
Device:Cameras[1]/Camera:Image ::
Device:Cameras[1]/Camera:Image/Image:ItemSemantic :: Original
Device:Cameras[1]/Camera:Image/Image:ItemURI :: android/original_image
Device:Cameras[1]/Camera:DepthMap ::
Device:Cameras[1]/Camera:DepthMap/DepthMap:ItemSemantic :: Depth
Device:Cameras[1]/Camera:DepthMap/DepthMap:Format :: RangeInverse
Device:Cameras[1]/Camera:DepthMap/DepthMap:Units :: Diopters
Device:Cameras[1]/Camera:DepthMap/DepthMap:Near :: 0.302570
Device:Cameras[1]/Camera:DepthMap/DepthMap:Far :: 1.754560
Device:Cameras[1]/Camera:DepthMap/DepthMap:DepthURI :: android/depthmap
Device:Cameras[1]/Camera:DepthMap/DepthMap:MeasureType :: OpticalAxis
Device:Cameras[1]/Camera:DepthMap/DepthMap:ConfidenceURI :: android/confidencemap
Device:Cameras[1]/Camera:DepthMap/DepthMap:FocalTableEntryCount :: 256
Device:Cameras[1]/Camera:DepthMap/DepthMap:FocalTable :: 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
Device:Cameras[1]/Camera:ImagingModel ::
Device:Cameras[1]/Camera:ImagingModel/ImagingModel:FocalLengthX :: 3187.589355
Device:Cameras[1]/Camera:ImagingModel/ImagingModel:FocalLengthY :: 3187.589355
Device:Cameras[1]/Camera:ImagingModel/ImagingModel:ImageWidth :: 4032
Device:Cameras[1]/Camera:ImagingModel/ImagingModel:ImageHeight :: 3024
Device:Cameras[1]/Camera:ImagingModel/ImagingModel:PrincipalPointX :: 2000.483154
Device:Cameras[1]/Camera:ImagingModel/ImagingModel:PrincipalPointY :: 1541.417236
Device:Cameras[1]/Camera:ImagingModel/ImagingModel:Skew :: 0.000000
Device:Cameras[1]/Camera:ImagingModel/ImagingModel:PixelAspectRatio :: 1.000000
Device:Cameras[1]/Camera:ImagingModel/ImagingModel:DistortionCount :: 4
Device:Cameras[1]/Camera:ImagingModel/ImagingModel:Distortion :: AACAPwAAAABBQ7w9AAAAAEgGf74AAAAA5SpFPgAAAAA
Device:Cameras[1]/rdf:type :: http://ns.google.com/photos/dd/1.0/device/:Camera
根据Google的文档，深度图图像被序列化为base64字符串XMP属性。但我不知道如何提取该图像以基于此深度数据生成新图像。我认为我几乎解决了我的问题，但是我错过了一些有关Adobe XMP标准的认可。
我发现了一个叫做“ sidecar Xmp文件”的东西，也许我想找到的深度图就在其中。
通过将照片上传到https://www.photopea.com，我设法看到照片中嵌入了深度图
我设法使用“ exiftool”提取深度图像。但是我也在尝试找到一种直接从元数据中以编程方式进行此操作的方法。
@@ Lumi Wang，您是如何使用exiftool提取它的？你可以发布命令吗？我也设法在https://www.photopea.com中看到了深度图，但无法系统地提取。