Remove outdated information

docs/development/contribution/backend/index.md

@@ -69,9 +69,7 @@ Here you can find our API implemented. They are separated, similar to the models
 
 #### serializer
 
-You have your python model and want to somehow convert that to JSON. That's what the serializer does! There are two different types of serializers: normal ones and serpy serializer. Serpy serializer is faster, and we sometimes need it if we need to serialize a lot of data. The package is no longer maintained, though, and we are looking for a replacement or for refactoring to serialize fewer data at once.
-
-We are currently in the process of splitting them up, similar to how we did it in views.
+You have your python model and want to somehow convert that to JSON. That's what the serializer does!
 
 ### Machine Learning
 

docs/development/contribution/frontend/to-do.md

@@ -8,8 +8,6 @@ category: 5
 You can look into the issues [here](https://github.com/LibrePhotos/librephotos/issues?q=is%3Aopen+is%3Aissue+label%3Afrontend),
 on what features are missing from the frontend.
 
-We currently are working on improving maintainability, by converting our code base to TypeScript. Right now, it's mostly migrated, but there are still a lot of any's in the codebase. You can help out by replacing them with types!
-
 We are in the process of migrating from Redux to redux-toolkit and redux-query.
 
 It would be also create if you could write E2E tests with [Cypress](https://www.cypress.io/) for the frontend.

docs/installation/standard-install.md

@@ -14,8 +14,7 @@ You need an x86 or ARM64 processor, and it is recommended to have 4GBs of RAM. D
 
 ### Size
 
-You will need at least 10 GB of HDD Space for the docker images. It needs that space because of the machine learning
-models. Librephotos will also create a database and thumbnails, which will need additional space.
+You will need at least 10 GB of HDD Space for the docker images, thumbnails, database and machine learning models.
 
 ### 🚀 Installation
 

docs/intro.md

@@ -25,11 +25,12 @@ Unlike commercial service that store your photos in the cloud and scan/index the
 
 ## What does it use?
 
-- **Image Conversion:** [ImageMagick](https://github.com/ImageMagick/ImageMagick)
+- **Image Conversion:** [libvips](https://github.com/libvips/libvips)
+- **RAW Conversion:** [ImageMagick](https://github.com/ImageMagick/ImageMagick)
 - **Video Conversion:** [FFmpeg](https://github.com/FFmpeg/FFmpeg)
 - **EXIF Support:** [ExifTool](https://github.com/exiftool/exiftool)
 - **Face detection:** [face_recognition](https://github.com/ageitgey/face_recognition)
 - **Face classification/clusterization:** scikit-learn
-- **Image captioning:** [im2txt](https://github.com/HughKu/Im2txt),
+- **Image captioning:** [im2txt](https://github.com/HughKu/Im2txt)
 - **Scene classification** [places365](http://places.csail.mit.edu/)
-- **Reverse geocoding:** [Mapbox](https://www.mapbox.com/): You need to have an API key. The first 50,000 geocode lookups are free every month.
+- **Reverse geocoding:**: [photon](https://photon.komoot.io/) and other providers

docs/user-guide/job-system.md

@@ -6,7 +6,7 @@ sidebar_position: 5
 
 ## How does it work
 
-The job system manages all long-running jobs. It gives information, which job is running, which job is in the queue, how far it progressed and when it started and stopped. At the moment, there are eight long-running jobs:
+The job system gives you information about the long-running jobs, including which job is running, in a queue, how far it progressed and when it started and stopped. At the moment, there are nine long-running jobs:
 
 ### Scan Photos
 
@@ -40,14 +40,14 @@ Looks for faces in the images and save them to the database
 
 Clusters the faces into known and unknown groups.
 
-## Where to manage the jobs
+### Download Models
+
+This downloads the needed machine learning models to data/protected_media/data_models/.
+
+## Where to get information about previous run jobs
 
 When you are logged in as an admin, click on the profile picture in the top right corner and then navigate to `Admin Area`. You should see the jobs at the bottom of the page in a table called `Worker Logs`
 
 ## What to do when a job gets stuck
 
 When a job gets stuck, that usually means, that it crashed, and we could not catch the error correctly. You can just remove the entry from the list to start another job.
-
-## Current Limitations
-
-Right now, queuing does not work. It forgets all jobs that are queued after a bit of time. Another recurring issue is that when a job crashes, it usually does not represent it correctly in the view.