the folded hierarchy of classifiers for cat detection described in
F. Fleuret and D. Geman, "Stationary Features and Cat Detection",
- Journal of Machine Learning Research (JMLR), 2008, to appear.
+ Journal of Machine Learning Research (JMLR), 9, 2549-2578, 2008.
- Please use that citation when referring to this software.
+ Please use that citation and the URL
- Contact Francois Fleuret at fleuret@idiap.ch for comments and bug
- reports.
+ http://www.idiap.ch/folded-ctf/
-INSTALLATION
-------------
+ when referring to this software.
- If you have installed the RateMyKitten images provided on
+ Contact Francois Fleuret at francois.fleuret@idiap.ch for comments
+ and bug reports.
- http://www.idiap.ch/folded-ctf
+INSTALLATION
+------------
- in the source directory, everything should work seamlessly by
- invoking the ./run.sh script.
+ If you have installed in the same directory as the source code the
+ RateMyKitten images available on the same web page as the source
+ code, everything should work seamlessly by invoking the ./run.sh
+ script.
It will
* Compile the source code entirely
* Generate the "pool file" containing the uncompressed images
- converted to gray levels, labeled with the ground truth.
+ converted to gray levels, labelled with the ground truth.
* Run 20 rounds of training / test (ten rounds for each of HB and
H+B detectors with different random seeds)
You can run the full thing with the following commands if you have
wget installed
- > wget http://www.idiap.ch/folded-ctf/data/folding-gpl.tgz
- > tar zxvf folding-gpl.tgz
- > cd folding
- > wget http://www.idiap.ch/folded-ctf/data/rmk.tgz
- > tar zxvf rmk.tgz
- > ./run.sh
-
- Note that every one of the twenty rounds of training/testing takes
- more than three days on a powerful PC. However, the script detects
+ > wget http://www.idiap.ch/folded-ctf/data/folding-v1.0.tgz
+ > tar zxvf folding-v1.0.tgz
+ > cd folding
+ > wget http://www.idiap.ch/folded-ctf/data/rmk-v1.0.tgz
+ > tar zxvf rmk-v1.0.tgz
+ > ./run.sh
+
+ Note that for every round, we have to fully train a detector and run
+ the test through all the test scenes at 10 different thresholds,
+ including at very conservative thresholds for which the
+ computational efforts is very high. Hence, each round takes more
+ than three days on a powerful PC. However, the script detects
already running computations by looking at the presence of the
corresponding result directories. Hence, it can be run in parallel
on several machines as long as they see the same result directory.
When all or some of the experimental rounds are over, you can
- generate the ROC curves by invoking the ./graph.sh script. You need
- a fairly recent version of Gnuplot.
+ generate ROC curves by invoking ./graph.sh script. You need a fairly
+ recent version of Gnuplot.
+
+ If you pass the argument "pics" to the ./graphs.sh script, it will
+ save images from the data set with the ground truth plotted on them,
+ the pose-indexed referential, and examples of the pose-indexed
+ feature windows.
This program was developed on Debian GNU/Linux computers with the
following main tool versions
---------------------
The main command has to be invoked with a list of parameter values,
- followed by commands to execute.
-
- To set the value of a parameter, just add an argument of the form
- --parameter-name=value before the commands that should take it into
- account.
+ followed by commands to execute. A parameter value is modified by
+ adding an argument of the form --parameter-name=value.
For instance, to open a scene pool ./something.pool, train a
- detector and save it, you would do
+ detector and save it with all other parameters kept at their default
+ value, you would do
./folding --pool-name=./something.pool open-pool train-detector write-detector
projects / folded-ctf.git / blobdiff