Free random image 1.0 software for linux

create Image is an amarok script that can create an image of the current playlist and save the files to an iso image.

The iso image is found in the respective home folders.

For a long time I wanted to play a random "album" in Amarok. I could not find how to do it with what existed, so I got around to write my own (first) amarok script.
Random Album should be a playlist really, but I dont know yet how to do that.
So here it is. It will play a random album from your collection. Upon reaching the last song, it will load a new one in the playlist.
Alternatively, you can select to play a random artist (see the configuration)
The script acces the database. Ive only tried with MySQL. I think that the "album" mode will work with SQLite, but not the "Artist" mode.
Enhancements:
- For amarok 1.4.3 and above(?) ONLY! For ealier versions use 0.2
- Changed script to work with Amarol 1.4.3
- The "tags" table in the database now contains the path of a file below a given "device" (defined in table "devices"). The script now handles that correctly using KURL.
- The "album path" filter filters according to the path below the "device" path. The device path is not taken into account
BUG
- No attempt is made to check that the files do exists... This may be problem.... There seem to be no such a method with KURL and the "unicode" function refuse to take a QString (PyQt says it should) so I cant convert things to use os.path.isfile()

Mr. Random project is a utility useful for filling a portable MP3 audio player with music randomly selected from a larger collection situated on a computer hard drive.

This is a good idea if you cant make up your mind what you want to hear, you prefer to be surprised by a selection of music you may not have heard in a while, or want to hear familiar music juxtaposed in novel combinations.

Prima::image-load is a Perl module using image subsystem.

Simple loading

Simplest case, loading a single image would look like:

my $x = Prima::Image-> load( filename.duf);
die "$@" unless $x;

Image functions can work being either invoked from package, or from existing Prima::Image object, in latter case the caller object itself is changing. The code above could be also written as

my $x = Prima::Image-> create;
die "$@" unless $x-> load( filename.duf);

In both cases $x contains image data upon success. Error is returned into $@ variable ( see perldoc perlvar for more info).

Perceptual Image Diff is an image comparison utility that makes use of a computational model of the human visual system to compare two images.
Its useful for running automated regression testing on images that are perceptually identical but have minor pixel noise from different random number generators or small changes to algorithms.
Build Instructions:
This project makes use of the Cross Platform Make Utility and the libtiff library. You will also need Subversion to obtain the source.
1. Edit CMakeLists.txt as necessary to point to libtiff
2. Type cmake .
3. Type make .
4. pdiff should be compiled for your target system
Usage:
pdiff image1.tif image2.tif [options]
-verbose : Turns on verbose mode
-fov deg: field of view, deg, in degrees. Usually between 10.0 to 85.0. This controls how much of the screen the oberserver is seeing. Front row of a theatre has a field of view of around 25 degrees. Back row has a field of view of around 60 degrees.
-threshold p : Sets the number of pixels, p, to reject. For example if p is 100, then the test fails if 100 or more pixels are perceptably different.
-gamma g : The gamma to use to convert to RGB linear space. Default is 2.2
-luminance l: The luminance of the display the observer is seeing. Default is 100 candela per meter squared.
Enhancements:
- Incorporated bug fix from Cairo team that fixed a memory access error
- Changed the way the program releases memory from libpng to fix linking error with new versions of libpng.
- Tested with libpng version 1.2.8

HAVEGE (HArdware Volatile Entropy Gathering and Expansion) is a user-level software unpredictable random number generator for general-purpose computers that exploits these modifications of the internal volatile hardware states as a source of uncertainty. During an initialization phase, the hardware clock cycle counter of the processor is used to gather part of this entropy: tens of thousands of unpredictable bits can be gathered per operating system call in average.

HAVEGE combines on-the-fly hardware volatile entropy gathering with pseudo-random number generation. The internal state of HAVEGE includes thousands of internal volatile hardware states and is merely unmonitorable.

Therefore HAVEGE features a very high security level. HAVEGE can reach an unprecedented throughput for a software unpredictable random number generator: several hundreds of megabits per second on current workstations and PCs.

The throughput of HAVEGE favorably competes with usual pseudo-random number generators such as rand() or random(). While HAVEGE was initially designed for cryptology-like application, this high throughput makes HAVEGE usable for all application domains demanding for high performance and high quality random number generators, e.g. Monte Carlo simulations.

Java Games project is a collection of simple games that are compiled into Java applets and meant to be played online in a Web browser.

Currently the collection contains four games: XO World (similar to tic-tac-toe, but with lines of 5 on a 10x10 board); 100 Mack (guess the random combination of 4 images out of a set of six); Memory (flip 2 plates at a time to find matching pairs); and Tetris.