Forked from Danal's hard work at https://github.com/DanalEstes/TAMV because while his efforts were a great start, nozzle detection was not great without very particular lighting setups. This fork aims to improve detection by searching for partially complete circles (using OpenCV's Hough circle detection) rather than using blobs.
The main aim of this fork is to reach a point where a v6-style nozzle is detectable with ambient light, or at most using a neopixel ring light.
TAMV.py = Tool Align Machine Vision - for Duet based tool changing 3D printers.
- Runs on the Pi that has the USB or Pi camera
- Requires network connection to DUET RepRap V2 or V3 based printer.
- This MAY be, but is not required to be, the Pi in a Duet3+Pi configuration
- Requires OpenCV installed on the Pi.
- See https://github.com/Xonman/installOpenCV for one way to install OpenCV
- MUST run on the graphic console, not SSH. This can be physical, VNC, or any combination of the two.
P.S. Reminder: Never NEVER run a graphic app with 'sudo'. It can break your XWindows (graphic) setup. Badly.
cd
git clone https://github.com/Xonman/TAMV
git clone https://github.com/DanalEstes/DuetWebAPI
cd TAMV
./TAMV.py
It will guide you from there. And/or run with -h for help.
ZTATP.py = Z Tool Align Touch Plate - for Duet based tool changing 3D printers.
- Requires network connection to DUET RepRap V2 or V3 based printer.
- This MAY be, but is not required to be, the Pi in a Duet3+Pi configuration
See instructions above for TAMV. It will be in the same directory.
cd TAMV
./ZTATP.py -touchplate X Y
NOTE: Requires Wiring! Each nozzle must be wired to the GPIO specified (default is io5.in, can be overriden on command line). The touchplate must be grounded. Recommend about running with finger on power switch, in case a given touch does not stop.