This is the source code for a Lego+Raspberry Pi-powered analog film roll scanner. Watch it in action:
You'll need these items to build RoboScan:
- A digital camera with a macro lens: must be compatible with libgphoto2 with image capture and preview support.
- A Raspberry Pi: you may choose a Pi 4 if your camera supports USB 3, otherwise a Pi 2 or 3 is fine.
- A 28BYJ-48 Stepper Motor with Driver: easy to find and cheap (about $6)
- 3D-print an adapter to integrate the stepper motor in the legos: use the stepper mount and axis adapter provided by this project (you'll need some bolts to attach the motor to the adapter): https://create.arduino.cc/projecthub/fredrikstridsman/lego-stepperbot-df26b9.
- Adafruit White LED Backlight Module.
- A LED driver such as Recom Power RCD-24-0.70/PL/B.
- A high-power LED, such as New Energy LST1-01G03-4095-01: a 4000K white LED, with a CRI (Color Rendering Index) of 95.
- Build the lego part: https://www.mecabricks.com/en/models/r121kn4gvlB.
First build the Angular frontend:
cd scanner-frontend
npm install
ng build --prod
cd ..Then deploy the docker-compose:
cd docker
# Adjust the hostname to your Raspberry Pi
export DOCKER_HOST=tcp://piscanner:2376 DOCKER_TLS_VERIFY=
docker-compose up -d --build
cd ..The camera must be connected to the Raspberry Pi via USB. It must be compatible with libgphoto2.
Simply navigate to http://piscanner/ (adjust the hostname to your Raspberry Pi)
You can improve the machine learning inference performance by using a Google Coral Edge TPU USB Accelerator plugged on a USB port of the Raspberry Pi. To do so, you have to change the file src/Dockerfile. Replace:
CMD ["python", "webapp.py", "--destination", "/storage/share", "--archive", "/storage/archive", "--temp", "/storage/tmp"]by:
CMD ["python", "webapp.py", "-tpu", "--destination", "/storage/share", "--archive", "/storage/archive", "--temp", "/storage/tmp"]