SnapchatMemoriesCaptionAdder

Adds metadata (captions and timestamps) to your exported Snapchat memories.

Background

Snapchat allows you to save images/videos to their servers with their memories feature. When you export your memories from Snapchat from their accounts website, you get all the memories, but with no metadata and the captions are stored separately!

Base Image	Overlay Image

You may then go to an alternate project like ToTheMax's Snapchat-All-Memories-Downloader, which is fantastic! It uses a memories_history.json file to download all memories and add a timestamp, but this technique loses all the captions! They aren't included in memories_history.json :(

{
  "Date": "2020-01-02 23:08:19 UTC",
  "Media Type": "Image",
  "Location": "Latitude, Longitude: 0.0, 0.0",
  "Download Link": "https://app.snapchat.com/dmd/memories?..."
}

So in short, memories_history.json has all the metadata we need, but we need to combine it with the full memory export if we want captions. So this project serves as a bridge between these two methods! We have all the metadata and we have all the memory photos/videos and captions, we just need to combine them. The final result:

Note the caption is on the image, the file name and metadata has a timestamp! The file's creation date is also set to the correct date.

Install

Note

This project and docmumentation is not very friendly to non-developers :( If you have questions, I'm happy to try and help if you make a new Github issue. I'm very open to any PRs that want to work on this (see the Contributing section below!)

This project relies on two major libraries.

• ffmpeg is "a complete, cross-platform solution to record, convert and stream audio and video." This project uses it to overlay the captions onto videos. If you're on Linux, download it from your package manager, if you're on MacOS, install it from brew, and if you're on Windows, install it from winget (package here).
• libvips is "a demand-driven, horizontally threaded image processing library. Compared to similar libraries, libvips runs quickly and uses little memory." This project uses it to overlay the captions onto images. If you're on Linux, download it from your package manager, if you're on macOS install it from brew, and if you're on Windows download a compiled version here and add the bin folder to your path.

Finally, this project requires Python to be installed on your computer. Once installed, you can clone this repo and run

python -m pip install -r requirements.txt

to install the Python requirements for the project.

Usage

Note

This project and docmumentation is not very friendly to non-developers :( If you have questions, I'm happy to try and help if you make a new Github issue. I'm very open to any PRs that want to work on this (see the Contributing section below!)

First, we need to get our data.

• Follow Snapchat's instructions to download your data, making sure to "Include your memories as a downloadable file" and put no date range to get all memories! Wait for an email and download when ready. (Note: this may take up a significant amount of space!) If you get multiple zip files, merge all the memories folders into one memories folder. This is the only folder you need.
• Next, request your data again, but do not include your memories. This should be much quicker :) In this data export, make sure you have a json/memories_history.json. This is the metadata for the memories.

Now, make a folder in this repo called input and put the memories folder from the first export and the memories_history.json file from the second export into it.

• Alternatively, you can provide the location of the memories_history.json file with the --memories-history flag and the memories folder with the memories flag, for example python main.py --memories-history test/memories_history.json --memories-folder test/memories --output test_output.

With this folder prepared, you can now run python main.py to run the script! It will create a new folder called output that will hold all memories with timestamps and captions. (Note: this will create a new copy of each photo/video, so make sure you have enough space!) Alternatively, use the --output flag to provide a different location to dump the photos.

If you run into issues, please run the script with the -v or --verbose flag, which will output information on what the script is doing. If that doesn't help you with the issue, open a github issue with that output! You can also use the -vv flag to get logs from ffmpeg/vips.

Warning

If your captions are important to you, double check the final result against the photos in the Snapchat app! I found that the memories export did not include overlays/captions from some of my photos in 2017-2018. So check the final photos to make sure captions are there. If they aren't, you may need to download those impacted photos/videos directly from the Snapchat app. The majority of photos were successfully exported with all their captions.

Note: The timezone applied to the photos is set by your computer's local timezone! I'm open to any PRs to improve this (see below), but for a quick hack you can set the default timezone in SnapchatMemoriesCaptionAdder/adder.py in the add_metadata signature.

Thanks

• @n-katti for fixing issues on Windows and new Snapchat export format (issue #3)
• @Enricon27 for fixing a problem with the earlier fix :) (issue #3)
• @autumnesponda for adding location metadata

Contributing

This achieved what I needed it to do, so I don't anticipate adding many more features. I'd be happy to accept PRs for some feaures I didn't implement:

• Making this much more user friendly. This is currently not accessible to anyone who doesn't have knowledge of installing and using libraries.
  • Bundling libraries with the app
  • Creating a GUI
• Cleaning the project up :) Introducing python-ffmpeg's async definitely made this functional but messy.
• Snapchat uses UTC as the timezone for the timestamps. This script takes a guess that your computer's local time zone is the timezone you want the timestamps in. Allowing the user to specify a timezone, or automatically determine the timezone from the photo's location data, would be an improvement.
• I believe ffmpeg could also do photos, but it's less efficient than VIPS. Adding a fallback to ffmpeg would make installation easier for those who can't easily install VIPS.

License

MIT