For myself and my family, I wrote my own tool [1] that runs everyday on an "input folder". A quick google on "github photo organizer" shows a lot of others having done the same :)
It organizes all traversed photos by date (extracted from exif or from filename), and puts them in a "failed" folder if it can't parse the date.
If any photos get the same name, they are either deduped because they are exact duplicates, or are marked as conflicts (e.g. A.jpg and A_conflict1.jpg) if they are different.
Last time I used it for a large input it took 3h for 200GB, though I suspect network latency was the main bottleneck.
It's around 300 lines of python - verify the code for yourself if you want to use it! You probably also need to fork it if you don't intend to run it on a Synology NAS.
However, as I mentioned last time I pitched this, elodie [2] might be more suitable for others than my little hack. Haven't used it though!
For all the posters saying Google Photos: make sure you have a backup of your originals. Google strips most of the metadata from your images when you pull down a Takeout or use the photos API, including GPS.
You can copy your original images and videos directly to a home computer/server/desktop/raspberry pi via either SyncThing or Resilio Sync.
i have a copy on dropbox, a backup of that folder on onedrive with arq backup. For easy viewing I also upload them to smugmug and make sure they are tagged correctly.
It works mostly in that we can find photo's most of the time and have not yet lost a single one.
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For myself and my family, I wrote my own tool [1] that runs everyday on an "input folder". A quick google on "github photo organizer" shows a lot of others having done the same :)
It organizes all traversed photos by date (extracted from exif or from filename), and puts them in a "failed" folder if it can't parse the date.
If any photos get the same name, they are either deduped because they are exact duplicates, or are marked as conflicts (e.g. A.jpg and A_conflict1.jpg) if they are different.
Last time I used it for a large input it took 3h for 200GB, though I suspect network latency was the main bottleneck.
It's around 300 lines of python - verify the code for yourself if you want to use it! You probably also need to fork it if you don't intend to run it on a Synology NAS.
However, as I mentioned last time I pitched this, elodie [2] might be more suitable for others than my little hack. Haven't used it though!
1: (https://github.com/johan-andersson01/photo_organizer
2: https://github.com/jmathai/elodie
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0: https://news.ycombinator.com/item?id=24019612