How to Extract Image Metadata in Python - The Python Code (2024)

Abdeladim Fadheli · 4 min read · Updated jul 2022 · Ethical Hacking · Web Scraping

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In this tutorial, you will learn how you can extract some useful metadata within images using the Pillow library in Python.

Devices such as digital cameras, smartphones, and scanners use the EXIF standard to save images or audio files. This standard contains many useful tags to extract, which can be useful for forensic investigation, such as the make, model of the device, the exact date and time of image creation, and even the GPS information on some devices.

Please note that there are free tools to extract metadata such as ImageMagick or ExifTool on Linux, the goal of this tutorial is to extract metadata with the Python programming language.

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To get started, you need to install Pillow library:

pip3 install Pillow

Open up a new Python file and follow along:

from PIL import Imagefrom PIL.ExifTags import TAGS

Now this will only work on JPEG image files, take any image you took and test it for this tutorial (if you want to test on my image, you'll find it in the tutorial's repository):

# path to the image or videoimagename = "image.jpg"# read the image data using PILimage = Image.open(imagename)

We loaded the image using the Image.open() method. Before calling the getexif() function, the Pillow library has some attributes on the image object, let's print them out:

# extract other basic metadatainfo_dict = { "Filename": image.filename, "Image Size": image.size, "Image Height": image.height, "Image Width": image.width, "Image Format": image.format, "Image Mode": image.mode, "Image is Animated": getattr(image, "is_animated", False), "Frames in Image": getattr(image, "n_frames", 1)}for label,value in info_dict.items(): print(f"{label:25}: {value}")

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Now let's call the getexif() method on the image which returns image metadata:

# extract EXIF dataexifdata = image.getexif()

The problem with exifdata variable now is that the field names are just IDs, not a human-readable field name, that's why we gonna need the TAGS dictionary from PIL.ExifTags module which maps each tag ID into a human-readable text:

# iterating over all EXIF data fieldsfor tag_id in exifdata: # get the tag name, instead of human unreadable tag id tag = TAGS.get(tag_id, tag_id) data = exifdata.get(tag_id) # decode bytes if isinstance(data, bytes): data = data.decode() print(f"{tag:25}: {data}")

Here is my output:

Filename : .\image.jpgImage Size : (5312, 2988) Image Height : 2988Image Width : 5312Image Format : JPEGImage Mode : RGBImage is Animated : FalseFrames in Image : 1ExifVersion : 0220ShutterSpeedValue : 4.32ApertureValue : 1.85DateTimeOriginal : 2016:11:10 19:33:22DateTimeDigitized : 2016:11:10 19:33:22BrightnessValue : -1.57ExposureBiasValue : 0.0MaxApertureValue : 1.85MeteringMode : 3Flash : 0FocalLength : 4.3ColorSpace : 1ExifImageWidth : 5312FocalLengthIn35mmFilm : 28SceneCaptureType : 0ImageWidth : 5312ExifImageHeight : 2988ImageLength : 2988Make : samsungModel : SM-G920FOrientation : 1YCbCrPositioning : 1XResolution : 72.0YResolution : 72.0ImageUniqueID : A16LLIC08SM A16LLIL02GMExposureProgram : 2ISOSpeedRatings : 640ResolutionUnit : 2ExposureMode : 0FlashPixVersion : 0100WhiteBalance : 0Software : G920FXXS4DPI4DateTime : 2016:11:10 19:33:22ExifOffset : 226MakerNote : 0100 Z@PUserComment :ExposureTime : 0.05FNumber : 1.9

A bunch of useful stuff; by quickly googling the Model, I concluded that this image was taken by a Samsung Galaxy S6. Run this on images that were captured by other devices, and you'll see different (maybe more) fields.

Alright, we're done. A good challenge for you is to download all images from a URL and then run this tutorial's script on every image you find and investigate the interesting results!

Related: How to Extract Video Metadata in Python

Want to Learn More?

If you're a beginner and want to learn Python, I suggest you take the Python For Everybody Coursera course, in which you'll learn a lot about Python. You can also check ourresources and courses pageto see the Python resources I recommend!

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Learn also:How to Use Steganography to Hide Secret Data in Images in Python.

Happy Coding ♥

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