New scrypt image-to-gcode.py - how to put on GIT ?

My name is Alex. Sorry for my english.

I was refactoring code in python scrypt image-to-gcode.py. (I work this 1,5 years .)


2014-12-26 - new ver 3.8.7




I expanded functionality. Added 2 mode "Rows objectiv" "Cols objectiv" and some other functions.
You can see the results of these modes here:











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original url cnc-club.ru/forum/viewtopic.php?f=15&t=3541#p110429 and cnc-club.ru/forum/viewtopic.php?f=15&t=2460


I think that it is necessary to update the script on GIT for it to become available to all users LinuxCNC. But I do not know much English and I can not write the correct documentation and comments.

Could you advise me of those engaged in finalizing LinuxCNC so I sent him this question?

Looks good and very interesting.

Rick G

<jepler> the code's not obviously terrible

This is my first work on Python. In processing a serious bug: it uncontrolled eating memory (for large pictures 4000x2000 - eaten 1.5GB memory). Somewhere I do not clear the memory ... I would be grateful if someone would find this bug and fix it.

<BigJohnT> So, would you like to be the new maintainer?

I am very pleased your suggestion, but unfortunately I ran out of gas.
During development I understood almost everything code (except for a pair of functions), and now I see a lot of flaws that (I think) can be eliminated only by creating g-code for 3d models.
Some of the most significant are:
- To increase the accuracy necessary to increase the size of the image, while increasing the size of the image - growing time "compilation" g-code.

While CAM has turned very functional. It has the features that I have not seen in traditional CAM. I think using the image-to-gcode can even get 3d model - without turning preform from different sides, but only by making rotation axis Y.

I plan to describe the basic algorithm that I developed in the pictures, that any developer understands how it works and could freely continue improving the image-to-gcode or its CAM ...
This is the algorithm that makes the g-code only in those places where it is not included roughing cutter and depth of these locations exceed the maximum permissible maximum. Only in such places formed g-code for fine milling at a predetermined pitch penetration. It is necessary to thin cutters that can break down these locations - if this location does not pass layers but at one time.





(Because many CAM is no such algorithm - not to break the cutter users are layers - all the model - which increases the receipt of the product at times.)
With a little refinement can be done to to fine milling formed g-code in one pass, but when you approach these "narrow" and "deep" places pictures - special g-codes - to reduce movement speed by XX% ...

I think it is undertaken for the project BlenderСAM. This (free) plug-in for Blender for make g-code.

Now I understand a set of approximation points NURBS splines to modify another script called LinuxCNC autors.py. This script makes g-code (arc and lines) on the set of points, which gives him the image-to-gcode. But the quality of train code does not suit me: geometric lines it does well, but the model with smooth lines - if you closer the g-code in LinuxCNC - you can see the following ...


I plan to make a set point optimization algorithm instead of Douglas-Peusker - NURBS spline approximation algorithm described in documents "Optimal Single Biarc Fitting and its Applications" Hyungjun Park and papper "CAD/CAM interpolation for NURBS path interpolation on PC based real-time numerical control" by M.Leto, R.Licari, E.LoValvo, M.Piacentini...

new ver 3.8.7 - look on top post








for comparison - I made in Gimp this picture to show that the regime RMF - is something else than just filter depth images



Function Optimize path: