Android Q - Get depth map from portrait mode photos

Question

I'm trying to build a sample Android App to extract the depth map of portrait mode photos taken with the google camera app. I know that it's saved along the blurred photos.

I read the Dynamic Depth Format documentation coming from Google : https://developer.android.com/training/camera2/Dynamic-depth-v1.0.pdf It's pretty new and I don't find any resource related to this subject or how to manage the extraction of an android portrait's depth map.

I used metadata-extractor library to read file's metadata programmatically, particularly the XMP Part as it's where informations are described for depth. I wrote a sample code in Kotlin to try to extract the depth map:

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()
}

the resulting output :

    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

according to the Google's documentation, the depth map image is serialize as a base64 string XMP property. but i don't know how to extract it to generate a new image based this depth data. I think that I almost solved my issue but I miss some acknowledgment about Adobe XMP standard.

I found something called "sidecar Xmp files" and maybe the depth map that I'm trying to find is in it.

I managed to see that the depth map is embedded in the photo by uploading it on https://www.photopea.com

I get largely the same XMP output as you when grabbing an ImageFormat.DEPTH_JPEG from the camera2 API and parsing the Image. There's a URI for "android/depthmap", but still a bit of a mystery where this is. Note that the dynamic depth PDF actually says the files themselves are in the "Concatenated File Container", and it's just the order and properties of these files that are in the XMP metadata. But there's little information on this Concatenated File Container. Francois, @riggaroo, any further luck? — Kent Mewhort, May 12 '20 at 02:29

score 1 · Answer 1 · answered Jan 08 '21 at 15:44

Pixel phone portrait mode photo is concatenated of 4 JFIF structure https://en.wikipedia.org/wiki/JPEG_File_Interchange_Format. Each JFIF structure is an jpeg image.

A JFIF structure starts with marker 0xFFD8 and ends with marker 0xFFD9. Therefore, we can split a portrait mode image into 4 jpeg files.

The following python code prints the marker positions and splits PXL_20210107_114027740.PORTRAIT.jpg into,

pxl_out_0.jpg: display image
pxl_out_1.jpg: original image
pxl_out_2.jpg: depthmap with 256 grey level
pxl_out_3.jpg: dummy image filled with 255

with open('PXL_20210107_114027740.PORTRAIT.jpg', mode='rb') as infile:
    buffer = infile.read()

bufferlen = len(buffer)
pos = 0
pos_d8 = 0
n = 0
i = 0
while i < bufferlen:
    if buffer[i] == 0xff:
        pos = i
        i += 1
        if buffer[i] == 0xd8:
            print('ffd8: {0}'.format(pos))
            pos_d8 = pos
        elif buffer[i] == 0xd9:
            print('ffd9: {0} len: {1}'.format(pos, pos - pos_d8 + 2))
            with open('pxl_out_{0}.jpg'.format(n), mode='wb') as outfile:
                n += 1
                outfile.write(buffer[pos_d8: pos + 2])
    i += 1

On my Moto G Stylus (2021) I just got two small sideways images exported `ffd8: 0 ffd8: 1984 ffd9: 18529 len: 16547 ffd9: 4410131 len: 4408149 ` — Jonathan, Jul 29 '21 at 04:02
It's not as simple as that to split a jpeg file. The strings 0xffd8 and 0xffd9 may also be found in other segments of the jpeg when it would be wrong to treat them as markers. — user258279, Nov 21 '21 at 09:26

score 0 · Answer 2 · answered Jan 27 '20 at 11:23

0

I managed to extract the depth image using "exiftool". But I'm also trying to find a way to do that programmatically directly from the metadata.

answered Jan 27 '20 at 11:23

Lumi Wang

73
3
10

How did you do that with exiftool? – Jonathan Jul 29 '21 at 03:55
`exiftool -depthmapdata -b FILE > depth.dat` but thats not a JPG. Much easier to just use Muttyans Stereo 3D Photo Maker – Jonathan Jul 29 '21 at 04:19

Android Q - Get depth map from portrait mode photos

2 Answers2

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