Clean up more

README.md

@@ -3,12 +3,13 @@
 A small e-ink photo frame for our home. It pulls from our self-hosted [Immich](https://immich.app/) library, checks the self-hosted [Home Assistant](https://www.home-assistant.io/) to see if anyone is home, and shows a photo on the [PhotoPainter](https://www.waveshare.com/wiki/PhotoPainter) (Waveshare 7.3" 6-colour panel hooked up to a Raspberry Pi Zero 2W) for everyone to enjoy.
 
 <p align="center"><img src="photos/frame.jpg" alt="The frame showing a dithered landscape photo with a small overlay reading '2 years ago' and 'Palmeiras'" width="420"></p>
+<p align="center"><sub><em>The bottom corners show the photo's capture age and EXIF location. This one was taken in Palmeiras two years ago.</em></sub></p>
 
 ## Why
 
 Most digital frames either require you to pick and preprocess photos that you put on an SD card or they want to talk to a cloud service like Google Photos. Realistically, you're not going to update the photos more than once a year on the SD card. As for cloud providers, I'd rather not give them access to my cherished memories or let them be held hostage.
 
-It's magical to come home from a day out to immediately see photos taken from the day, or see memories from years ago pop up within the living space, unconfined by an app on your phone.
+Coming home to a photo from earlier that day, or one from five years ago, hits differently when it's just sitting on the wall instead of buried in your phone.
 
 It was a fun afternoon project with Claude Code, a bit of experimenting with different dithering and post-processing, and then fine tuning the photo picking algorithm. Besides powering my frame, I share this repo as a reference and as inspiration for self-hosting, to show that the combination of these services can produce something that otherwise wouldn't have been possible to hack together so quickly.
 
@@ -18,8 +19,8 @@ It was a fun afternoon project with Claude Code, a bit of experimenting with dif
 
 1. Quits if it's between midnight and 7am.
 2. Asks Home Assistant whether anyone in `HA_PRESENCE` is home. If not, quits to preserve power and not strain the e-ink unnecessarily.
-3. Picks a random photo from Immich, weighted toward "on this day" memories, favourites, and recent uploads (see [immich.py](./src/lib/immich.py)).
+3. Picks a random photo from Immich. The pool is weighted: ~30% "on this day" memories (10% if only the ±3-day fallback fires), ~18% favourites, ~36% the last 30 days, and ~36% everything else. A 7-day rolling history avoids repeats; orientation match gets 4x the weight of mismatch. See [immich.py](./src/lib/immich.py).
-4. Crops around any detected faces, applies post-processing to boost contrast and saturation (which are both lacking in e-ink displays), dithers down to the 6-colour palette, and pushes it to the panel.
+4. Crops around any detected faces, boosts contrast and saturation (both lacking on e-ink), dithers down to the 6-colour palette, and pushes it to the panel. The capture age and EXIF location are painted into the bottom corners as white-on-black-stroke text, so dithering can't smear the edges.
 
 ## Image pipeline
 
@@ -27,7 +28,7 @@ The two choices that matter most are `face_aware_crop` and Atkinson dithering.
 
 ### Cropping
 
-The frame has one orientation but I didn't want to limit it to only show portrait or landscape photos. So the `face_aware_crop` function resize-crops to fill the frame while keeping all faces within the frame. This can nicely turn a landscape with extra background into a crop that works well on the portrait frame. For finding faces, it relies on the bounding boxes returned by Immich.
+Obviously, the frame can only be in orientation at a time but I didn't want to limit it to only show portrait or landscape photos. So the `face_aware_crop` function resize-crops to fill the frame while keeping all faces within the frame. A landscape shot with room around the subject usually crops cleanly to portrait this way. For finding faces, it relies on the bounding boxes returned by Immich.
 
 See the following example from [crop_compare.ipynb](./notebooks/crop_compare.ipynb) that shows how the head bounding boxes affect the final crop.
 
@@ -35,13 +36,15 @@ See the following example from [crop_compare.ipynb](./notebooks/crop_compare.ipy
   <img src="photos/crop_compare_portrait.png" alt="Crop comparison showing original photos with face boxes, naive centre crops, and face-aware crops for a portrait frame target" width="760">
 </p>
 
-The second issue is the limited 6-colour palette. The intensity of these colours can't be changed like on an LCD panel, they're either shown or not. So to get any legible results, we have to turn to dithering. Turns out, there are many dithering algorithms with wildly different running times. [dither_compare.ipynb](./notebooks/dither_compare.ipynb) shows a comparison between a few.
+### Dithering
+
+The panel can only show six colours: black, white, red, yellow, blue, and green. There's no intensity control like on an LCD, every pixel is one of those six. To get anything legible we have to dither, and there are many algorithms with wildly different running times. [dither_compare.ipynb](./notebooks/dither_compare.ipynb) shows a comparison between a few.
 
 <p align="center">
   <img src="photos/dither_compare_hiker_in_mountains.png" alt="Palette-preserving dither comparison showing several 6-colour algorithms on a mountain hiker photo" width="760">
 </p>
 
-Ultimately, I chose Atkinson dithering which seems to keep the highest contrast without too much artifacting. Of course, its performance on the Raspberry Pi was abysmal so the final version relies on numba for compiling the array operations, resulting in a 100x speed improvement.
+Ultimately, I chose Atkinson dithering which seems to keep the highest contrast without too much artifacting. Pure Python was unusably slow on the Pi Zero, so the inner loop runs through numba with perceptual-weighted (0.299/0.587/0.114) nearest-colour matching. Roughly 100x faster after the first warm cache.
 
 ## Setup
 
@@ -77,6 +80,8 @@ python3 src/display.py --saturation 1.5 --contrast 1.1 --gamma 0.85  # change pr
 
 ## Learnings
 
-Honestly, the Pi Zero 2W is overkill for this. It chews through battery if you try to run untethered, and most of the time it's just sitting idle waiting for the next cron tick. If I were doing this again for a battery-powered build I'd probably reach for an ESP32 with deep sleep. Mine stays plugged in, so I haven't bothered.
+The Pi Zero 2W is overkill for this. It chews through battery if you try to run untethered, and most of the time it's just sitting idle waiting for the next cron tick. If I were doing this again for a battery-powered build I'd probably reach for an ESP32 with deep sleep. Mine stays plugged in, so I haven't bothered.
+
+A few small reliability quirks worth knowing: the Pi Zero 2W's wifi drops if power-save kicks in, so a separate cron job runs `wifi-check.sh` every 5 minutes to reconnect. Swap is masked and journald set to volatile because SD card writes are the only thing likely to slowly kill this build. The render holds an `flock` so a slow refresh never overlaps the next 15-minute tick.
 
 I would also give [Inky Impression](https://shop.pimoroni.com/products/inky-impression?variant=55186435244411) a try with a custom-made frame for a larger display and perhaps integrated lights, as the e-ink looks a bit muddled in the evening lights. I think a separate light source would be the greatest improvement by far.