KQueryBrowser

I'm on roll. Just pushed my latest project, KQueryBrowser, to github. KQB is a database query tool for KDE that uses qt-webkit to format the query results nicely. And yes, I know the name is highly unoriginal and follows that annoying K<something> pattern, but at least it's descriptive.

The motivation for this yet another query tool was simply that I did not like any of the other query tools. The command like clients are nice, but awkward when browsing through very large tables. MySQL query browser was great, but was replaced by MySQL Workbench, which is way too cumbersome when I just want to run some SELECTs. Pgadmin suffers from the same problem. And most of the graphical tools use GTK, which makes them look ugly or (in the case of MySQL workbench) simply broken on KDE.

So here's KQB. Looks pretty on KDE, works with multiple databases and lets you get straight to writing queries.

Piqs

I just created a new repository on github for yet another hobby project I've been working on: piqs. It's a lightweight image gallery program with advanced tagging capabilities.

It's an experiment in alternative categorization; rather than sorting images into albums/folders, they are all shown in a single flat view, but that view can be filtered with tag queries. Of course, lots of gallery software have tagging capabilities nowadays, but piqs takes it a bit further. You can set up tag aliases and implication rules and something I don't think I've seen elsewhere: tag namespaces. For example, the tag string "[cat, orange], [dog, yellow], backyard" might be applied to a photo of an orange cat and a black dog taken in the backyard. The search string "cat, orange" will return all pictures with a cat and something orange, but the more specific "[cat, orange]" will return pictures of orange cats only. Further, boolean operators are supported: "cat, !dog" will return pictures with cats, but not dogs. "cat, (!dog|[dog,black])" will return pictures with cats and no dogs, unless the dog is black.

This sort of tagging only really starts to pay off once the image collection starts getting very large, so I've tried to design piqs to support huge galleries. So far, I've tried it with about 50000 untagged images and it hasn't choked yet. To help tag every image comprehensively, piqs can infer new tags based on a set of rules. E.g. the rules "cat --> mammal, carnivore", "mammal --> animal" will automatically add the tags "animal", "carnivore" and "mammal" to a picture tagged with "cat".

Limit switches, part 2

In the previous post, I showed how I added limit switch inputs to my CNC driver box. Now its time to attach the actual switches to the machine.

Limit switches, part 1

The CNC3040 machine doesn't come with limit switches and having already crashed the machine once I thought it was high time to add ones. The problem is that the driver box doesn't have inputs for the switches. My first idea was to build a passthrough box to break out the input pins, but peeking inside the case I found a nicer solution.

Griffin powermate + EMC2

I'm currently designing a physical control panel for use with EMC2 and for that I needed to learn how to use the HAL. HAL is EMC's hardware abstraction layer that provides a sort of virtual breadboard for connecting components, both hardware and software, together. One great thing about it is that it's really easy to write your own userspace HAL components in python. A short tutorial from EMC's documentation shows how. Also, Just Milling Around has a great tutorial on how to interface an Arduino with EMC using a python script.

As an exercise before getting started with my control panel, I decided to write a driver script for a piece of hardware I already have: A powermate jog wheel. My script creates two HAL pins: An output pin that can be connected to axis.N.jog-counts and a boolean input pin to turn the LED on and off.

The powermate HAL script is available here: powermate.py

Improved image carving

JGCGen now has better support for image carving. Since the previous post, I've added two major features. The first is a roughing strategy for removing lots of material fast and in multiple passes so you can carve deeper. The second is the decoupling of image resolution from carving resolution. Stepover distance can now be smaller than a single pixel and jgcgen will interpolate the values in between. Another important change was a rather embarrassing bug fix: the tool shape profiles for flat and ballnose endmills were swapped! No wonder the previous test looked flatter than I expected...

Still on the TODO list: optimize rough path generation to minimize rapids and implement a waterline strategy.

Image carving

JGCGen now includes rudimentary support for heightmap carving. You can see the first test carving below. (source)

 Currently only a simple scanning style toolpath generation strategy is implemented, but different methods can be added easily.
Current limitations are:

• No interpolation. The minimum stepover is image width or height divided by target width or height. This results in the striated look visible in the above image. A workaround is to use a higher resolution image.
• Single pass only. This limits the depth of the image to the maximum depth your bit can handle.

My current plan is to add a strategy for a roughing pass that can be run with a bigger bit before running the finishing pass.