Is it possible to access additional EXIF tags #7486
Replies: 4 comments 13 replies
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Rather than using with Image.open("Tests/images/flower.jpg") as im:
exif = im.getexif()
print(exif.get_ifd(ExifTags.IFD.Exif)) |
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Hi Radar -I appreciate your quick response. IFD is defined as class IFD(IntEnum): Do you know what the value 34665 stems from, and could that be the key to accessing additional tags? I'm completely new to this project and trying to solve what I initially thought to be a simple problem. |
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The tags are probably be under 'Exif Private IFD' as you mentioned because I checked IFD0 and didn't find them. I will need to find a way to identify the sub-IFDs (groups) and traverse those nodes. Do you know if that is possible with Pillow's latest build?
Source: https://www.awaresystems.be/imaging/tiff/tifftags/private.html |
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I'm not sure how to answer this. I can't easily help you track down... 132 EXIF tags. If there is a specific piece of information you would like to get out of an image, you can mention the tag, attach the image, and we can investigate that. We've discussed how to access the IFD0, Exif, GPS, Interop and IFD1 groups. IFD1 is a special case though, as it's not using a tag offset like the others, but is just the next IFD. There is also Makernote, but that's specific to the manufacturer, and Pillow only supports Fujifilm and Nintendo Makernote data at the moment. A large portion of the tags you listed mention DNG, which Pillow doesn't support at the moment, see #6482. As for the general question of if it is possible to identify all IFD data... I think the following part of the TIFF specification might explain things a bit further (emphasis mine).
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Thank you so much for your response, your insight, and your offer to help with additional data. This is the ultimate list that I need right now, with an emphasis on the critical and highs. <style> </style>
Looking forward to your response. |
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Could you attach a copy of IMG_2115.jpg? |
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Is it possible for me to send it to you in email? |
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According to information I am finding via AI It seems perhaps the data I am looking for is nestled under Sub-IFDs.
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@radarhere |
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import os
from PIL import Image, ExifTags, IptcImagePlugin
with Image.open("IMG_2115.jpg") as im:
print("FileName =", im.filename)
print("FileSize =", os.path.getsize("IMG_2115.jpg"))
print("FileType =", im.format)
print("FileTypeExtension =", os.path.splitext(im.filename)[1][1:].upper())
print("MIMEType =", im.get_format_mimetype())
description = im.getxmp()["xmpmeta"]["RDF"]["Description"]
print("| City =", description["City"])
print("| State =", description["State"])
print("| Country =", description["Country"])
print("| Headline =", description["Headline"])
print("| CountryCode =", description["CountryCode"])
print("| Location =", description["Location"])
print("| DocumentID =", description["DocumentID"])
print("| Creator =", description["creator"]["Seq"]["li"])
print("| Description =", description["description"]["Alt"]["li"]["text"])
print("| Subject =", description["subject"]["Bag"]["li"])
print("|| ObjectName =", description["title"]["Alt"]["li"]["text"])
print("|| Keywords =", IptcImagePlugin.getiptcinfo(im)[(2, 25)])gives |
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Hi! I didn't get an email notification like usual, so I thought you were busy. Thanks so much for this code. I'll use this. You are awesome!!! |
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Radarhere, thanks again. You need to import defusedxml |
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Hello Everyone!
Can someone have a look and give some assistance here?
I am working with image files' Exif data, rather than the image itself. Things were going pretty good until I reached a roadblock after having realized that the population of EXIF tags available by default is about 46.
There are some important tags that I need for my project, but. they aren't accessible:
For example:
Tag ID | Tag Name
0x9c9e | XPKeywords
0x9c9f | XPSubject
0xa436 | Title
Is there a way to extend the tags that _getexif() returns? If you can suggest what direction I need to take in order to access the information I need, then I would really appreciate it.
Thanks
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