Picture frame viewer powered by raspberry with homeassistant integration
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Project description
PictureFrame powered by pi3d
- PictureFrame powered by pi3d
- What Is PictureFrame?
- History of PictureFrame
- Highlights of PictureFrame
- Documentation
- Acknowledgement
What Is PictureFrame?
This is a viewer for a raspberry powered picture frame. For remote control it provides an automatic integration into Home Assistant via MQTT discovery.
- https://github.com/helgeerbe/picframe
- Paddy Gaunt, Jeff Godfrey, Helge Erbe
- Licence: MIT
- Tested on rasberry 3B+/4, Ubuntu 20.10 and Python 3.7
History of PictureFrame
When I started 2019 my DIY project building a raspberry powered digital picture frame I came across Wolfgang's website www.thedigitalpictureframe.com. I ran my frame with the pi3d PictureFrame2020.py viewer, but always missed a more deeply integration to my smart home server running Home Assistant.As my personel corona project I decided to rewrite the viewer to my needs. Hoping someone can make use of it.
Highlights of PictureFrame
- Viewer
- blend effects
- auto mat generation
- photo metadata overlays (title, location, date, ...)
- live clock
- automatic pairing of portrait images
- keyboard, mouse and touch screen support
- Filter by
- IPTC tags
- location
- directories
- date
- Remote Control
- control interface for mqtt, http(s)
- tun on/off display
- next/prev/pause image
- shuffle play
- toggle metadata overlays
- toggle clock visibility
- retrieve image meta info (exif, IPTC)
Documentation
Full documentation can be found at the project's wiki.
Please note that PictureFrame may change significantly during its development. Bug reports, comments, feature requests and fixes are most welcome!
To find out what's new or improved have a look at the changelog.
Acknowledgement
glenvorel Thanks for the new keyboard, mouse and touch screen support.
Many Thanks to Wolfgang www.thedigitalpictureframe.com for your inspiring work.
A special Thank to Paddy Gaunt one of the authors of the pi3d project. You are doing a great job!
Last but no least a big Thank You to Jeff Godfrey. Your auto mat feature and database driven cache is an outstanding piece of code.
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