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Michael Mayer 2018-09-27 22:02:18 +02:00
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README.md
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@ -13,28 +13,26 @@ PhotoPrism
[issues]: https://github.com/photoprism/photoprism/issues
[ci]: https://travis-ci.org/photoprism/photoprism
PhotoPrism is a server-based application that makes it simple to automatically tag, search and organize digital photo collections.
It is functionally similar to popular cloud services such as Flickr or Google Photos and runs on every computer that has Docker installed.
You can easily create backups as originals are stored in the file system sorted by year and month.
We love taking photos and they belong to our most valuable (and storage consuming) assets. Privacy concerns and the wish to properly
archive them for the next generation brought us to the conclusion that existing cloud solutions are not the right tool to keep them organized.
At the same time, traditional desktop software like Adobe Lightroom lacks many features and can only be used on a single computer.
That's why we started working on an easy-to-use application that can be hosted at home or on a private server.
![](assets/docs/img/screenshot-detailview.jpg)
History
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We love taking photos and they belong to our most valuable (and storage consuming) assets.
Privacy concerns and the wish to properly archive them for the next generation brought us
to the conclusion that existing cloud solutions are not the right tool to keep them
organized. At the same time, traditional desktop software like Adobe Lightroom lacks many
features and can only be used on a single computer.
We started in January 2018 with brainstorming and finding the right technologies.
Our first milestone was a proof-of-concept which got completed in September 2018:
That's why we started working on an easy-to-use application that can be
hosted at home or on a private server. The first step was a
proof-of-concept which got completed in September 2018.
You can import all your photos from a local directory and they are
getting automatically labeled, tagged and sorted. It is possible to
instantly search for objects and locations or filter by camera model.
- It can import all your photos from a local directory and re-index them later
- Photos are getting automatically labeled, tagged and sorted
- It is possible to instantly search for objects and locations or filter by camera model
- You can view individual photos
- Thumbnails are created using a high-quality resampling filter (Lanczos)
- The application layout is fully responsive
- Contains all important technologies such as TensorFlow
We think this is pretty impressive and we got lots of positive feedback. Thank you for that.
@ -45,21 +43,23 @@ Our next goal is to implement the following features in good quality for the fir
- Easy-to-use Web interface based on [Material Design](https://material.io/) (20% implemented)
- High-performance command line tool (80% implemented)
- No proprietary or binary data formats
- No difficult installation, all you need is Docker (done)
- No proprietary or binary data formats (done)
- Automatic RAW to JPEG conversion (implemented using [Darktable](https://www.darktable.org/))
- Duplicate detection (RAW plus multiple JPEG files can be used simultaneously) (implemented)
- Duplicate detection (RAW plus multiple JPEG files can be used simultaneously) (done)
- Automated tagging using [Google TensorFlow](https://www.tensorflow.org/install/install_go) (90% implemented)
- [Reverse geocoding](https://wiki.openstreetmap.org/wiki/Nominatim#Reverse_Geocoding) based on latitude and longitude (implemented using OpenStreetMap; support for Google Maps on the todo list)
- Image search with powerful filters (40% implemented)
- Albums to organize your photos (0% implemented)
- Easy backup and export (10% implemented)
- Project Web site including a demo and end-user documentation (0% implemented)
More advanced features will follow later:
- Sharing with friends
- Improved search based on Solr
- Facial recognition
Please ask if you have any questions. A more detailed documentation - also for non-developers - will follow.
Please ask if you have any questions. We value feedback. A more detailed documentation - also for non-developers - will follow.
Donations
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