SunsetCam

Description

A Su Lab project to automatically take a time lapse video of the San Diego sunset (and sunrise) from our lab space at Scripps Research.

The original incarnation drove a Nikon DSLR over USB with gphoto2 and posted the finished timelapse to @ScrippsCam on Twitter. This modernized version runs on a Raspberry Pi 3B with a Camera Module 3 Wide and posts to Bluesky.

Architecture

• scheduler.sh — daily cron entrypoint. Uses R + suncalc to compute today's sunrise and sunset times and queues two SunsetCam.sh runs via at.
• SunsetCam.sh — captures frames with rpicam-still, optionally deflickers, assembles an mp4 with ffmpeg, and posts to Bluesky.
• getBestShutter.sh — empirical shutter calibration: walks shutter speeds in 2/3-stop steps and picks the one with the most unique colors (per imagemagick identify).
• calc_brightness_pil_histogram.py — PIL-based luminance check used by the auto-exposure feedback loop.
• uploadToBluesky.sh / uploadToBluesky.py — post the finished mp4 to Bluesky using the atproto SDK; credentials read from .env.

Dependencies

Dependency	Type	Used by
rpicam-apps	system	rpicam-still for frame capture
imagemagick	system	identify for unique-color counting in getBestShutter.sh
ffmpeg	system	mp4 assembly
at / atd	system	scheduler.sh queues timed jobs
python3	system	per-frame shutter ramp calculation; Bluesky upload
r-base	system	Rscript for sunrise/sunset time computation
atproto	Python	Bluesky SDK
httpx	Python	HTTP calls to the Bluesky video service
python-dotenv	Python	reads Bluesky credentials from .env
suncalc	R	astronomical sunrise/sunset times
timelapse-deflicker.pl	optional	inter-frame deflickering (see step 6 below)

Setup (Raspberry Pi OS Bookworm, Pi 3B + Camera Module 3 Wide)

1. Install system packages

   sudo apt-get update
   sudo apt-get install -y rpicam-apps imagemagick ffmpeg at \
                           python3-pip r-base
   

2. Verify the camera works

   rpicam-still -n -t 100 -o /tmp/test.jpg
   

3. Install R packages and Python libraries

   sudo R -e "install.packages('suncalc', repos='https://cloud.r-project.org')"
   pip install --break-system-packages atproto httpx python-dotenv
   

4. Clone and configure

   git clone https://github.com/andrewsu/SunsetCam.git
   cd SunsetCam
   cp config_sample.txt config.txt           # set ROOT and LOG_FILE
   cp .env.sample .env                       # add Bluesky credentials
   mkdir -p img tmp final
   

5. Get Bluesky credentials

   • At https://bsky.app go to Settings → App Passwords and create one.
   • Put your handle and the app password into .env:

     BLUESKY_HANDLE=yourhandle.bsky.social
     BLUESKY_APP_PASSWORD=xxxx-xxxx-xxxx-xxxx
     

   • Smoke test:

     ./uploadToBluesky.sh -m "test from SunsetCam" -f /path/to/test.mp4
     

6. (Optional) Drop in timelapse-deflicker Grab timelapse-deflicker.pl from https://github.com/cyberang3l/timelapse-deflicker, place it in the repo root, and chmod +x. Skip with -d 0 if you don't want it.

7. Schedule via cron

   crontab -e
   

   Add:

   0 1 * * * /home/asu/SunsetCam/scheduler.sh
   

Manual run

./SunsetCam.sh -i 5 -n 480 -e 1 -d 1 -t 1 -c 17 -a 0 -m "A sunset timelapse from Scripps"

Flags (preserved from the original gphoto2 era for backward compatibility):

flag	meaning
-i	seconds between shots
-n	total number of shots
-e	run empirical exposure calibration first (getBestShutter.sh)
-d	run timelapse-deflicker after capture
-t	post finished mp4 (now to Bluesky, formerly Twitter)
-c	exposure compensation index 0..30 (1/3 EV per step, 15 = 0 EV)
-a	ramp shutter exponentially from calibrated start to 0.5 s over the run
-b	scp the frames to the archive host
-m	post text

Credits

Inspiration from Laura Hughes and Karthik Gangavarapu. Most coding done by Andrew Su. Modernized for Raspberry Pi 3B + Camera Module 3 Wide and Bluesky posting in 2026.