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LibrePhotos: A Self-Hosted Google Photos Alternative (github.com/librephotos)
386 points by hanklazard on Dec 31, 2020 | hide | past | favorite | 136 comments



There are two projects I would mention in the same spirit:

- https://github.com/photoprism/photoprism

- https://github.com/pixelfed/pixelfed

While I think photoprism has a very similar scope, pixelfed has stronger emphasis on federation. The project website gives a nice overview over different providers:

https://pixelfed.org/


Photoprism looks great, thanks! I've been looking for a project like this, but my biggest requirement is that it doesn't move my photos from where they are, which no project I've found can satisfy. Everything insists on moving things to its own store.


Photoprism doesn't move photos around, I ran it in a docker container and just mounted my existing folder to /photoprism/originals and it worked fine.


Yep, I installed it and it seems quite good so far, thanks!


I have the exact same issue. I've been looking for something that will just work and have both facial detection and "object" detection (dogs mostly). I think I tried photoprism a long time ago and it failed on my requirements unfortunately.


Which requirement did it fail, do you remember? I just installed it and it's indexing, and it found both faces and dogs fine so far (hasn't indexed much yet, though).


So, my memory failed me. The one which I couldn't make work was Photonix not PhotoPrism. It is still indexing my pictures and it kinda succeeded identifying some things (and others with lots of errors, eg. Dog as Hummingbird!). I'll wait it finish to confirm, but I feel already the need of two things: - fix tags & retrain? - face tags to identify and search for persons


It was maybe 1 year ago, it was failing any recognition, it was just unable to index anything. I'll try again today and will test these other alternatives listed in other comments too, hopefully something will actually work now.


There is another interesting project. It's more of a lightweight and simple photo gallery. - https://photoview.github.io - https://github.com/photoview/photoview


Love seeing Pixelfed mentioned here. I've thought of it as an Instagram replacement but if it's practical as a Google photos alternative that's an added bonus.


I also know of it as an Instagram-type experience, and it's quite good at that, too. From my limited usage, I don't think it could replace Google Photos, though.


Right, that's what got me wondering. I've got an account on the flagship Pixelfed instance, and I started thinking whether that's a plausible use case - setting all uploads to private (or, I guess "unlisted" is the only available option) and effectively using it like Google Photos.

I guess it's a bit of a stretch but my preferred attitude is to be open minded and generally to cheer on the activitypub projects. They are, in the end, a force for good.


Certainly, but it's a free service hosted by volunteers, and I think uploading gigabytes of private photos would hurt the service for no benefit to them.


It's a Fediverse program (uses ActivityPub) which lets people follow Pixelfed servers from any Mastoson, Pleroma or other server that implements ActivityPub. PeerTube is a similar service for video hosting.

The Fediverse is the future, and the future is distributed.


Can you _hide_ everything? Because my main goal is to share within my family, but surely it must not be accessed from others without my authorization first


Oh, I'm very aware, and very happy that this is the case. This to me is a major advantage that Pixelfed has over basically everything else in the thread.

I had never considered Pixelfed as a google photos alternative but am glad that something in the activitypub universe might be used that way.


Thanks for posting these links.

What I miss in those solutions is the possibility to add text to your photos like it is done in Google Photos. The ability to give albums contextual background with a nice and simple typesetting is a key differentiator from the classic solution to keep picture files in folders (on-/offline). photoprism seems to have such functionality. The text, however, is associated to a photo, and not to an album like Google Photos.


I've been using the Beta version of Photostructure[0] for a while and am generally very happy with it.

It doesn't have all the bells and whistles, no ML etc, but it's also much lighter. Running on my Synology NAS inside a docker container just fine (with ~30k photos).

I also heard about Mylio[1] which looks nice, but haven't tried it. Somehow the privacy policy left me a little more concerned compared to the bold promises elsewhere. The pricing model also feels a bit off to me.

Neither are open-source though.

[0] https://photostructure.com/

[1] https://mylio.com/


Which Synology NAS model did you go with, and how are you finding the performance? Thanks


I've been using photostructure for a while, but it lacks everything related to albums which is the most important part to me.


Howdy! I'm the author of PhotoStructure.

The next release (I expect alpha builds to be available in a week or two) has album support: including automatic album importing from Google Takeouts.

https://forum.photostructure.com/t/support-for-manually-crea...

This next release is a biggie, btw:

https://photostructure.com/about/2020-release-notes/#vnext


I built and installed PhotoPrism including the TensorFlow lib, but had to do some link-hacking to get TensorFlow to start on Debian, in my case. Once it was working and ingested a few thousand home photos, searching for color names was fun.

Shortly thereafter, the site was "bombed" with uploaded pictures. I tore the whole thing down. Beware.


How is the album sharing? All i really want is to be able to build albums and create a link to send to family members, possibly password protected and optionally with expiration. Or just the ability to share/unshare in some way.


Pixelfed though is more of an Instagram replacement. It's for publishing photos as opposed to archiving and managing them.


Listed on https://github.com/awesome-selfhosted/awesome-selfhosted#pho... though that does not mention the advanced capabilities like face recognition.

How does it perform with huge collections? https://github.com/Webreaper/Damselfly claims staying fast even with 4+TB 500,000 photo collection.


What's the current recommended way of getting your photos out from Google Photos? And I don't mean manually via Google Takeout (that's a dumpster fire and doesn't work most of the time) but I'd like to automate it for periodic backups. You never know when you Google Account might be killed, taking tens of years of pictures and videos with it :(


Check out this google photos export tool by the perkeep team: https://github.com/perkeep/gphotos-cdp

> This program uses the Chrome DevTools Protocol to drive a Chrome session that downloads your photos stored in Google Photos. By default, it starts at the most ancient item in the library, and progresses towards the most recent. It can be run incrementally, as it keeps track of the last item that was downloaded. It only works with the main library for now, i.e. it does not support the photos moved to Archive, or albums. For each downloaded photo, an external program can be run on it (with the -run flag) right after it is downloaded to e.g. upload it somewhere else.


Be aware that Google Photos' API does not provide geolocation (lat/long) information from the photos; it's wiped.

AFAIK The only way to get the photos with all metadata intact is to use Google Takeout.


I use rclone[1] to do a daily local backup, just in case.

[1] https://rclone.org/


What’s wrong with google takeout? I’ve transferred everything to iCloud without any issue.


I'd say about 90% of the time I get the dreaded "However, we were unable to create a copy of all your files" message in the takeout email.

After multiple retries, it eventually succeeds but it's a manual process and using this for regular backups is extremely time consuming and frustrating.

Going through the process just once is definitely doable though :)


Can I ask how exactly you went about doing that? I would like to try iCloud for photos, but how did you manage to combine the image files Takeout gives to you with the metadata in the JSON files?


I use gphotos-sync: https://github.com/gilesknap/gphotos-sync

Run nightly


Why rely on google photos in the first place? If you are taking photos with android devices, you can backup the device folder containing the photos/videos.

Also, I just tried google checkout, and it took about 30 seconds to schedule a google photos only every-2-months-for-a-year recurring takeout of my data. We'll see if it actually works...if it does, it isn't so bad.


There’s a subset of users who click the takeout button, get the message saying we’ll email you in a bit and then... nothing. If you’re affected it’s not possible to get help from Google according to Mike Elgin.

I did a full export (circa 8Gb) around 18 months ago and i have around 1,000 pictures of someone else’s in my archives. I suppose other people have some of my pictures too.


With the whole self isolation thing going on currently it's actually nice to see another face again every now and then. :-)


Were the photos shared with you? or a security hole leaking private photos of random people??


It’s just under 1,000 photos of various landscapes but they’re not landscapes i’ve seen IRL and the smoking gun is the EXIF data shows they were taken on a Canon camera. I’ve only ever had Nikon or Fuji.

There’s a bunch of other small things that initially roused my suspicions that these weren’t my photos:

Whoever took the photos kept all the photos they took, there are sequences of 50+ photos of the exact same thing, I never save the extra shots, i always just choose the one i want to keep and discard the rest at import time.

It’s possible they were shared photos but my gut feeling is no. The photos date from around the time i was a heavy user of google photos, well i was a heavy user of picasa anyway and used gphotos as a backup. I would definitely have spotted these photos if they were in my collection back then.


It's simple to use and cheap. It's like comparing Dropbox and a FTP server.

Also Google Photos has a nice search feature with machine learning behind. I can search things such as "beach name of family member or "classic car" and it works.


It cannot distinguish between two black dogs (different breeds, different sizes) so if I want to filter for pictures of only one of the dogs I’m out of luck.


Does the service provided in the OP (or any other free service) distinguish between two black dogs?


This looks and feels very promising, nice.

Is there any documentation on the difference between this fork and the original project?

https://github.com/hooram/ownphotos


Appears there have been a bunch of fixes. There are also 217 forks of OwnPhotos.

https://github.com/hooram/ownphotos/compare/dev...LibrePhoto...

I don't know if the original repo and LibrePhotos will permanently diverge (that appears to be the intention), but I like you am a bit confused at the necessity for a permanent fork and I'd like to know more too before committing to a version.


Wow, I didn't know Github had that feature, thanks for the link!

Maybe the two repo authors can come together and sync the projects since both are so closely related. Nonetheless, I hope there will be more information via a changelog or an outline with differences and intentions.

It's one of the more impressive projects I've seen to replace Google Photos so I hope there's a lot of transparency!


My understanding from the reddit post was that it was forked due to the original seemingly being abandoned.


Given the last commit on ownphotos is from 2019, that seems likely and reasonable


At some point it might also be worth detaching the fork too in that case.


What do you mean by detaching the fork?


You can send a ticket to GitHub support to have a project appear to have no parent project (detach the fork)


Gotcha. Thanks for the explanation!

I think that's a terrible idea, disregarding the origins and removing an element of credit and attribution to the original authors. Be proud of where you came from, don't try to hide it.


The problem is that the original is defunct but "fork" on GitHub assumes that the fork is going to merge changes upstream.

Credit goes in the credits file, not polluting every interaction with the project.


Plus I believe there is at least one way in which forks may be removed en masse if the original is removed.


What pollution? It's just a link to the project's origin.


Looking at this project and some of the alternatives provided, they seem to be quite memory hungry. I assume this is related to the ML model.

Is there any way to run this (or one fo the alternatives) in a "Lite" mode without any ML?

I see that Photoprism has a ton of flags, but it's not obvious how those affect memory usage.


PhotoPrism uses TensorFlow for the image classification / ML stuff (to add labels to your images), but it can be completely disabled via a flag (or toggle under advanced settings) before you begin indexing if you don't need it.

PhotoPrism's ML object detection is no doubt not as powerful as Google's, but it seems to work pretty well based on the demo, and I know the devs are working on improving it frequently.


PhotoStructure will run comfortably with 1gb RAM, and scales to very large (>1mm file) libraries.

The ML models I'm loading for the next version may take a bit more RAM than that, but (as most features with PhotoStructure), you'll be able to selectively disable them to taste.

https://photostructure.com/faq/why-photostructure/


We are not sure why it needs that much RAM. We know that it has something to do, with the ML models. I am pretty sure we can optimize it in the future.


Yeah, I think for users of Google Photos, the ML was a big part of it. Lots of other options without, I’ve used and like Lychee (1).

(1) https://lychee.electerious.com/


yeah, 8 GB of RAM for a photo gallery seems completely insane...


How do this and the other alternatives handle Apple’s “Live Photos”?

This pernicious feature is adored in my family and they won’t consider options that would take it away.


In the Android world, Samsung and Google support eachothers live picture format. As far as I can tell for Google they embed video in the picture, Samsung has their own format for this.

Im on an older version of android and the live photos dont have the snappiness of Apple's, but that could be a processor power issue or even stylistic choice. Particularly the length of the live photo is noticeably different.

Im not sure how Apple stores the live picture info, but having it crossplatform would be fantastic for services like these.



Is this the same thing as Samsung's Motion Photo? If so, it is just a .mp4 attached to the jpeg, should be easy to support in the future.


Incidentally I've been trying out Digikam for the last couple days, mostly because of face recognition. The whole app is pretty slow on lower end hardware, they even recommend having an SSD which my travel laptop which I tested it on doesn't have.

That's when I thought I should look for a web based solution because that would also solve acessing and managing the lib from multiple devices, and now there's this post here. I guess before making another switch I should check out other solutions too and compare their feature matrix and how well those work. With digikam I noticed that it seems to overfit once you tagged a couple hundred faces of the same person, for example, and is less likely to identify that person in new photos.


I am also trying digiKam this week. Sadly the face recognition is unusable. For example I tagged one photo with Name1 and many other photos with other names. But it always suggests Name1.


Yes, I found tagging a person less than about ten times tends to mess up the recognition. The sweet spot is about 20-50, then as described above as soon as you have a couple hundred for one person it seems to overfit. I could identify half the detected faces pretty easily by re-running detection two or three times but eventually I ended up with a remaining set of faces that always got detected as the wrong person, if at all, and it's not that they are all blurry or otherwise low quality.

Also I wonder how bad it is to accidentally assign the wrong tag to a person. I noticed that it happened three or four times, so I ended up having maybe 400 proper assignments and then one false tag. Could they even add a function to detect this?

The next thing for me would be to research which management tools support face recognition and what they use to do it. Anything using what digikam uses would not be worth trying to me.


For anyone moving from google photos and looking for alternatives, I recently transitioned to a NAS from Synology. They offer many apps, and one is very similar to this project, although a bit more polished. It's not open source, though (AFAIK). Performance with 2TB of movies and raw photos is awesome (60k files+). Indexing and face recognition took a few days, though.

https://www.synology.com/en-global/dsm/feature/moments


A bit off-topic, but I've just bought a small 2-bay synology NAS and I'm wondering if I should go ext4 or btrfs for my family photos/videos. I like the idea of data safety features like checksums & scrubbing, but ext4 seems more robust & tested. Which did you go with?


btrfs works fine in Synology's implementation. Please keep in mind that RAID is not a backup. You can backup to a cloud service or to a friend's house with its own Synology.


Thanks, I was hoping it would. I understand that raid is not backup. I have two external drives and will probably also use a cloud service for off-site. I was also considering htl blurays for archives, but we'll see. The NAS will become the central storage hub so we don't keep files scattered around on family laptops and smartphones.


It's amazing that synology would hold themselves back with a proprietary app when they are trying to sell hardware and are competing against Google and Apple.


Synology is selling an experience, like Apple, not hardware. It's a plug-it-and-it-works private-on-premise cloud. They are not competing with Google or Apple in the sense that customer usually decide on-premise or cloud-based and only then look for a solution (prices are on the same scale, so the reason to choose one over the other is usually not price).


You could still run docker on the x86 models and host one of the solutions mentioned here.


Can someone enlighten me on storage? Is it stored on the docker container (locally) or does it allow for storage within say Google Storage or S3, even Backblaze perhaps?

I tried the demo on Firefox but I couldn't actually figure out how to upload an image to test it out. Firefox / Linux user.


https://github.com/LibrePhotos/librephotos#first-steps-after...

Local directories (so mount whatever you want to that path) or NextCloud native integration


I think I'm able to answer this myself. Supports Nextcloud for storage; not sure I'm happy with just that.


Darn. Doesn’t look like it runs on ARM. No Raspberry Pi. I can appreciate that it is difficult to port things.

On a side note: I’m eager to see how much support for non-x86 architectures will grow with the introduction of the M1 chip.


it also requires 8 GB of ram, apparently, so you'd have to get one of the beefiest rpi4s even if it ran on ARM.


Is there a good android app for librephotos (or any other application) that offers similar features than Google Photos? A while ago I tried adding photos to my nextcloud instance, but the nextcloud app in my opinion is very rudimentary. I really missed face grouping, location search, the year based scrollbar, etc.


Google Photos also uses other means to add location metadata to photos, if you have Google Maps Timeline enabled that logs your location, and you've uploaded photos from another camera (e.g. DSLR), it will assume, based on the timestamps, that photos were taken at the location your phone says you were at that time. Sadly I doubt librephotos has that integration.

Hmm, one could take out one's Google Maps Timeline info as JSON, and write a parser for librephotos (or others) that adds the location metadata into the photos.


How good is the search in practice? Unsurprisingly, Google Photos is excellent at automatically categorizing photos.


I am looking for a solution like this, can folks with experience comment on their experience with this(LibrePhotos) NextCloud or alternatives.

Aspects that I think are important include the community of maintainers in addition to the current state of functionality


I love my home nextcloud instance. Came for the Dropbox replacement, stayed for solid apps on android/IOS, Notes, 360 image viewer, good sharing, face ID, and extension ecosystem. I back up to Azure Blob, but there's nothing quite like having 10TB available on all your devices on a gigabit line at home. Also I really notice the absence of the creeping sense of unease I had when keeping all my everything on Google.

Maintenance has been zero, aside from when I want to add functionality.

My only feature gripe is that gPhotos has a wonderful "archive photos" feature to delete local copies of media already uploaded. You can still see uploaded photos (thumbnails stay local) and any interaction with them stays "as if local", there's just a delay while it downloads a temporary copy. I wish nextcloud had this capability.


For "giant pile of photos I can't be bothered sorting" scenarios (e.g. phone backups), I like Photoprism [0], which is fairly similar to this but seemed more complete last time I tried it out.

Photoprism is also somewhat unique in that it uses Darktable to process RAW photos, so if you use Darktable and have it write XMP sidecars, Photoprism will be able to process the adjustments.

For more curated collections, I prefer Piwigo, as it has a mode where it converts a directory tree into an album tree. It also has pretty good sharing features. Photoprism on the other hand is horrible for pre-curated photos.

[0]: https://photoprism.org/

[1]: https://piwigo.org/


I'm currently working to use more NextCloud. My prime objectives are for notes/b9kmark keeping and photos/media.

So far the setup was pretty easy on my VM but I kicked the tires with their VM image first. And so far the Android app is doing mostly OK. There is a lot to get into. And extensions out the wazoo.

I've not had to work with any community (yet) cause so far, it's just work - or there is some config I need to tweak (docs are great!)

With their VM and docker images tho, super easy to kick tires.


I use Nextcloud for many years now and for many different use-cases, but photos is not part of it. Mostly because my Nextcloud runs on a SSD and my photos are too many. In addition, I feel like the Nextcloud performance and feature set would not be able to deliver a good user-experience.

So if we are talking a just about a few hundred MB of photos, you are probably fine, but for anything larger I would recommend to consider one of the more specialized projects.


Any recommendation for personal photo gallery backed by S3 compatible API?


I've used Nextcloud. Auto-upload from your phone is nice, but I haven't found a way to share arbitrary groups of photos except by copying them into a folder and sharing the folder. Also, thumbnail generation is slow and I haven't put in the time to try to speed it up.

I haven't used PhotoPrism, but wanted to toss it out there as an alternative.


https://apps.nextcloud.com/apps/previewgenerator

This builds the thumbnails in the background. I think it used to get triggered on upload but says it needs a cronjob now. Works OK on a folder of 40GB of photos.

What I still find irritating about photos in nextcloud is I keep mine in high resolution but nextcloud won't downscale them to fit the viewing device screen, so I use 20mb a photo with all the UX impairment one might imagine when actually a few kB would do. It'd be nice if it cached light, fullscreen versions and offered a "view in full resolution" button.


PhotoPrism (https://photoprism.app/) generates a few different preview image ('thumbnail') sizes to support efficient use in different situations

More info: https://docs.photoprism.org/user-guide/settings/advanced/#im...


I have just about finished setting this up on my own home lab- the documentation isn't as comprehensive as I would like but it has ingested my 52GB of photos and is serving them up nicely!


> fullscreen versions and offered a "view in full resolution" button.

Yes, I have no idea what they don't do this. This makes the gallery barely usable.


Yes, agreed. I'm going to draw their attention to this thread.


I really like the look of this however bare it mind that it not able to run on raspberry pi / ARM processors.


How does DropBox handle customer data? Is it protected from any analysis or scanning at least according to the ToS? Or do they also inspect and/or sell my data?



I used to use apache-gallery (apache perl module that would turn directories of photos in galleries with thumbnails and different sized photos to view) and had it setup that each user on my machine could drop photos into their ~/gallery dir it would automatically turn them into galleries with little fuss or muss.

while this seems more featurefull, I wonder if I'd use them.


That’s super for publishing photos for the web. Thus seems to be focused towards managing your entire photo collection for you, in a similar way that google photos and iCloud photos does.


> You will need at least 10 GB of HDD Space for the docker images. It needs that space because of the machine learning models.

Are face detection models on the iPhone not run locally? Do they take up this much space on-device? Multi GBs just seems “large” for this?


Docker Image means it includes an extra OS install. Your iPhone uses the same OS for all apps.


I wonder how this will perform when you have tens or hundreds of thousands of photos.


There was a fantastic article by one of the frontend engineers at Google about how they built the UI for photos to be scalable: https://medium.com/google-design/google-photos-45b714dfbed1

There's no reason why the lessons learnt here couldn't be incorporated into an OS project.


That article addresses how to do a "scrubbable" infinite scroll for their timeline view.

Rendering correctly-scaled images is a different issue: Google Photos renders the image to the precise viewport dimensions (which is why it takes sometimes a couple seconds to render).

When I designed PhotoStructure, I knew I wanted everything to show instantly, so resizing is done to several common viewport sizes at import time (and these sizes are customizable). When you're browsing your library, your browser fetches the smallest variant that will still show with high quality based on native display resolution.


I tested it a few months ago hosted on my desktop (Ryzen 2600 6 core CPU, 16gb of RAM) with my entire photo library of around 100k photos - or about 60gb of data, and the performance was better than I expected. The ML image classification stuff it does took a few hours for sure, I left it go overnight, but then in the morning the ability to filter for specific classifications or jump to a specific date was pretty much as fast as you'd expect it to be (almost instant). This was using the default SQLite config.

The one thing I wished was that the ML Classification stuff it did was better - because it was nowhere near as good as what Google does with Photos, and nowhere near as useful for that reason. I still deeply miss Google Photos.

For context, my setup is pretty old fashioned these days. I plug my phone in, and use Shotwell to import the photos into my local photo library. Duplicati does a backup of all my photos once a week to Backblaze. Photoprism reads from my local copy and allows me to effectively browse my photos at home.


Sadly it won't.

I have been following it since release of OwnPhotos. Back then it was a messy university project of the original developer mixing different tech to achieve the goal. It simply stopped working with bigger sets of images.

I tried this fork as well, it has the same problem. Normally I would provide some pull requests but in this case the code base seemed too much hacked together from random things.

What doesn't work is the backend indexing part.


My personal photo archive is 100k+

I'll test this out and report back.


I would love to hear your update. I have 80k+ and also need a solution for many pictures.


The problem with this thing is that it doesn't work. So having played with this for several hours today

* installation was ok, but I had to reach out to the discord channel to be able to configure it properly * started to index the photos; at 16480 photos (After about 1h) it stopped progressing with no error message * for the photos that are listed as indexed, when going to the gallery, there are no thumbnails * it appears that there is no metadata being indexed for those photos either

In short, this is not ready for prime time yet

I currently run PhotoStructure what works ok with indexing, but has other gaps (no tagging, face recognition, etc..)


The next release (alpha build will drop in a week or two) will include keyword, album, and person tag imports from Google Takeouts, Lightroom, Picasa, and digiKam. See: https://photostructure.com/about/2020-release-notes/#vnext

Local face recognition, if it doesn't make it into this release, will be in the following release: most of the detection, aggregation, and backend storage is already implemented in my feature branch.

Please vote for features you want on the new forum! https://forum.photostructure.com/c/feature-requests/7/l/late...


Thanks for pointing these out!

What I'm looking for is Lightroom-album style tagging (keyword and star-rating) that I can apply to photos manually - I dont' have my archive tagged in anywhere, and I need to do that somewhere

I'm thinking about biting the bullet and import everything in Lightroom just to get tagging :(


Got it. FWIW, arbitrary tagging (and rating and flags) are on my to-do list. https://forum.photostructure.com/t/support-for-manually-edit...


Thank you so much for the update and giving it a try!


The trainable face classifier will go a long way. I've been unfortunately trained by Google's unlimited upload behaviour that it's going to be impossible to parse through my archive without Google's semantic identification of contents.


I’d really like to get off of iCloud Photo Library, but I’m not sure of a way to reliably and automatically sync photos off of my iPhone to a provider like LibrePhotos.

Has anyone figured this out?


I'm trying to figure this out myself. I've gone from Google Photos -> iCloud -> testing out Unraid + PhotoPrism + NextCloud. That is, point PhotoPrism's import folder to the NextCloud photos folder. Both hosted on Unraid. And then on my iPhone, have the photos automatically uploaded. Only issue so far is I don't see an auto-detect and import option in PhotoPrism so I have to manually click 'import'.


Several of my beta users have recommended PhotoSync. I've used Resilio Sync on my iOS test device successfully as well.

Most NAS providers (like Synology and QNAP) also have native sync apps.

It's good to have options so if one gives you attitude, you can switch it out.

I wrote up more details here: https://photostructure.com/faq/how-do-i-safely-store-files/#...


Not sure about the upload part, but for getting photos out of iCloud, this works:

https://github.com/icloud-photos-downloader/icloud_photos_do...


> You need a x86 processor and it is recommended to have 8GBs of RAM.

This is a bit much for a home cloud installation, but I could see it becoming what Invidious is to YouTube.


Most likely the machine learning features are what cause that.


I just use jAlbum and put up a static website, no need for fancy dynamic server stuff, while it offers lots of tools for image processing.


Are photos encrypted, both in-transit and at rest?


It's self hosted, so both parts are up to you.


Not necessarily. Is unencrypted data even sent to the server? That's controlled at the application layer.

Of course you could setup TLS and FDE but this doesn't guarantee that your data will be safe.


Huh? It's a web app. If you set up https, no data is ever sent to the server unencrypted.

Likewise setting up FDE means your data is encrypted on the server.

> but this doesn't guarantee that your data will be safe

I don't get what you're trying to get at here. If you're taking about bugs compromising the encryption then I guess this applies to practically every software out there making this a moot discussion.


What's like this, but perhaps without machine learning and targets "s3 compatible APIs"?


No screenshots and a broken demo


Huh, the demo looks empty at first glance, only if you go to Photos > Without Timestamp do you see any content.

It's easy to criticize, but huh, if this were a commercial product, a manager would be complaining to the appropriate team about how crappy the demo is. The Github page says the app has "slight focus on cool graphs" but the demo's "Data Viz" section is completely empty. EDIT: Oh not completely empty, the face recognition library has data.

I'm interested to see my frequency of photos per day/week/month, etc, so if I want to try that out I would have to install the whole thing locally.


Demo works fine for me.


Amazing, I was looking for a replacement (I have a beefy home server)


my crappy solution = gnome-photos with the broadway backend, but this is a terrible hack that only allows one connection at a time.


Can't we come up with better names than Libre{X}?


They are perfectly good names, no? Assuming you know what libre means, it tells you it's free as in beer and self-hostable, and X is, well, whatever X is.


I wonder what the purpose of such tools is. Archiving? Safe storage? Offering stock-photos for sale? Or just dropping an uncurated pile images into the interwebs?

When publising curated photo-sets myself (<1k pics per feed), I use a static-site-generator approach https://notabug.org/mro/Photos2Atom and rather sacrifice features but long-term robustness and installability.


Actually being able to find your photos, especially if you have friends and family who share photos with you and aren't willing to adapt to your organizational scheme. Google Photos really shines when you give up trying to organize your photos and let the AI take over. If I want to find a photo of my wife from 3 months ago -- I just tap on her face and it shows up, whether she took it or I did or her mom did, without needing to get everyone to collaborate on a photo organization scheme.

If I could get that from a self-hosted option, given Google's... track record... I'd definitely be interested, though it doesn't seem this is quite there yet.


You can takeout your photos and albums to store in a backup (locally or on another cloud provider)


Some people might take photos of themselves on vacations, or their kids and are not satisfied with throwing them all in a folder and using Windows image preview to look at them.




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