Hallo,
Da ich bald nach Linz ziehen werde, habe ich einige Gegenstände aus meiner alten Wohnung in Steyr zu verkaufen.
Link: http://bit.ly/umzug-steyr
HealthRider Crosstrainer 1050t
Zustand: Gebraucht, Höhe (cm): 158, Trainingsgerät: Crosstrainer, Breite (cm): 120, Marke: HealthRider, Tiefe (cm): 50, Programmanzahl: 8, Schwungmasse: 19kg
Rote Couch
Zustand: wenig Gebraucht, Farbe: Rot, Art: Sofa, Sitzhöhe (cm): 40, Breite (cm): 210, Tiefe (cm): 90, Mit Bettfunktion: Nein, Material: Textil
Couchtisch aus Glas
Zustand: Gebraucht, Höhe (cm): 40, Art: Couchtisch
Breite (cm): 120, Form: Rechteckig, Tiefe (cm): 60, Material: Glas
Drehsessel, blau
Zustand: kaum gebraucht, Verarbeitung: Gepolstert, Art: Drehstuhl, Material: Stoff. Verstellbare Sitzhöhe, Lehnenhöhe, Lehnenwinkel.
Deckenfluter, dimmbar mit Leselampe
Zustand: Gebraucht, Dimmbar: Ja, Art: Stehleuchten, Produktart: Stehleuchten, Sub-Type: Deckenfluter, Präzise Produktart: Deckenfluter, Stil: Modern, Höhe: 182cm, Material: Edelstahl, Durchmesser: 29cm
svn-shortlog — Compact & Beautiful Subversion Changelog
At work we periodically have short developer meetings to discuss what has happened in the last month. To do this, we go through the bugs in our issue tracking system, and the subversion commits in our repository. Unfortunately, getting an overview of the subversion commits was rather cumbersome, and we could not find any efficient tool to do this. Hence, svn-shortlog was born.
This is an attempt to format the subversion log of a one-month period in the following way:
- Beautiful HTML output.
- Compact representation of lots of information
- Usable with a not-so color rich beamer.
- Fully automatic.
Usage
- Install Ruby (both 1.8 or 1.9 should work).
- Download svn-shortlog.rb.
- Open svn-shortlog.rb with your favourite text editor, and configure the config section according to your needs.
- Doubleclick svn-shortlog.rb
- Open the generated changelog_....html file with your favourite browser.
Sample Output
Here is a sample output of one month of boost commits into trunk, taken from the public repository. The output is quite information dense, a quick description is in the screenshot:
Issues
Ideas, suggestions, problems? Please post them as a comment here, at the bug tracker.
Credits
This tool is based on the idea from my colleague Christoph Heindl and inspired by Linus’ Kernel shortlog and Gmail.
How to Generate Random Colors Programmatically
Creating random colors is actually more difficult than it seems. The randomness itself is easy, but aesthetically pleasing randomness is more difficult. For a little project at work I needed to automatically generate multiple background colors with the following properties:
- Text over the colored background should be easily readable
- Colors should be very distinct
- The number of required colors is not initially known
Naïve Approach
The first and simplest approach is to create random colors by simply using a random number between [0, 256[ for the R, G, B values. I have created a little Ruby script to generate sample HTML code:
# generates HTML code for 26 background colors given R, G, B values.
def gen_html
('A'..'Z').each do |c|
r, g, b = yield
printf "<span style=\"background-color:#%02x%02x%02x; padding:5px; -moz-border-radius:3px; -webkit-border-radius:3px;\">#{c}</span> ", r, g, b
end
end
# naive approach: generate purely random colors
gen_html { [rand(256), rand(256), rand(256)] }
The generated output looks like this:
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
As you can see this is quite suboptimal. Some letters are hard to read because the background is too dark (B, Q, S), other colors look very similar (F, R).
Using HSV Color Space
Let's fix the too dark / too bright problem first. A convenient way to do this is to not use the RGB color space, but HSV (Hue, Saturation, Value). Here you get equally bright and colorful colors by using a fixed value for saturation and value, and just modifying the hue.
Based on the description provided by the wikipedia article on conversion from HSV to RGB I have implemented a converter:
# HSV values in [0..1[ # returns [r, g, b] values from 0 to 255 def hsv_to_rgb(h, s, v) h_i = (h*6).to_i f = h*6 - h_i p = v * (1 - s) q = v * (1 - f*s) t = v * (1 - (1 - f) * s) r, g, b = v, t, p if h_i==0 r, g, b = q, v, p if h_i==1 r, g, b = p, v, t if h_i==2 r, g, b = p, q, v if h_i==3 r, g, b = t, p, v if h_i==4 r, g, b = v, p, q if h_i==5 [(r*256).to_i, (g*256).to_i, (b*256).to_i] end
Using the generator and fixed values for saturation and value:
# using HSV with variable hue
gen_html { hsv_to_rgb(rand, 0.5, 0.95) }
returns something like this:
Much better. The text is easily readable, and all colors have a similar brightness. Unfortunately, since we have limited us to less colors now, the difference between the randomly generated colors is even less than in the first approach.
Golden Ratio
Using just rand() to choose different values for hue does not lead to a good use of the whole color spectrum, it simply is too random.
Here I have generated 2, 4, 8, 16, and 32 random values and printed them all on a scale. Its easy to see that some values are very tightly packed together, which we do not want.
Lo and behold, some mathematician has discovered the Golden Ratio more than 2400 years ago. It has lots of interesting properties, but for us only one is interesting:
[...] Furthermore, it is a property of the golden ratio, Φ, that each subsequent hash value divides the interval into which it falls according to the golden ratio!
-- Bruno R. Preiss, P.Eng.
Using the golden ratio as the spacing, the generated values look like this:
Much better! The values are very evenly distributed, regardless how many values are used. Also, the algorithm for this is extremly simple. Just add 1/Φ and modulo 1 for each subsequent color.
# use golden ratio
golden_ratio_conjugate = 0.618033988749895
h = rand # use random start value
gen_html {
h += golden_ratio_conjugate
h %= 1
hsv_to_rgb(h, 0.5, 0.95)
}
The final result:
You can see that the first few values are very different, and the difference decreases as more colors are added (Z and E are already quite similar). Anyways, this is good enough for me.
And because it is so beautiful, here are some more colors 
s=0.99, v=0.99, s=0.25, h=0.8, and s=0.3, v=0.99
Have fun!
Martin
How To: Download Any Flash Video with flashrip in Ubuntu
Downloading flash videos in Linux was already not too difficult, but thanks to flashrip, it has gotten very easy. Here is a little demo how it works:
Once installed, you basically use one click to get a video preview and then a prompt with the filename to save the file. The script works by looking into the newest flash files in your /tmp folder, and creates a hardlink to the save destination. When the video has fully loaded, you can close the browser window. The temp file will get deleted, and the linked copy will remain.
Installing flashrip
Open a terminal like gnome-terminal or konsole, and run these commands:
wget http://martin.ankerl.com/wp-content/uploads/2009/11/flashrip.sh chmod 755 flashrip.sh sudo mv flashrip.sh /usr/local/bin
Now all thats left to do is to create a link in your gnome panel for ease of use: Right click the gnome panel, “Add to panel…”, choose “Custom Application Launcher…”. Choose a proper name, and a command like this:
/usr/local/bin/flashrip.sh /home/manker/Videos
For the command, replace the second parameter with the default location where you want to save the ripped videos (you have to use the full path here!)
I have tested this in Ubuntu, but it should work on any linux where gnome is installed.
Have fun!
iRob Feeder in Action (Video)
Finally! PROFACTOR (the company I work for) has decided to get a youtube account and upload some videos. Best of all, this gives me a chance to show off a bit of my (our) work
iRob Feeder is a solution for equipping of industry facilities. We can recognize the 3D position of different pices, grasp it, put it wherever you want them, and all of this quickly. Actually, the whole thing is a bit more than that, since it is possible to reuse components from it. We have a nice demonstrator for very fast object recognition moving along on a conveyer belt.
Here you can see it in action:
I am mostly involved in the algorithm development on the object recognition side. We have put quite some effort into making it fast: depending on the kind of object, we can have a reliable recognition in as low as 0.1 second on a standard desktop PC.
Hopefully Profactor will post some more videos about this in the near future.
PS: The article here are my personal opinions and do not necessarily reflect the position of my employee.