Setting things up

The following must be set for things to work.

• Set an environment variable $DETDIR to base. In csh add the line setenv DETDIR base to your .cshrc file. In bash add the line DETDIR=base to your .bashrc file.

 
• Add base/bin and base/bin/script to your path.

In csh add the linesetenv PATH $PATH:base/bin:/base/bin/script.
In bash add the linePATH=''$PATH:base/bin:/base/bin/script''
 
• Add the bash shell program to your /bin directory. All the scripts are written in bash and assume it is in directory/bin

• source. Contains the code with graphic options.cd into source and typemake. The program will compile and face base/bin

 
• sourcenox. Contains the code with no graphic options.cd into sourcenox and typemake. The program will compile and facenox will be written to base/bin

 
• bin. Contains the compiled executables, face andfacenox, and a subdirectory scripts where all the script files written in bash are stored.

 
• book. This directory has subdirectories corresponding to the chapters of the book ( chap1, chap2, ...), as well as some subdirectories with data written in upper case. Within each subdirectory corresponding to a particular chapter are parameter files that more or less reproduce the figures in that Chapter. Running these scripts is a good way to begin getting acquainted with the program and the relevant parameters.

• FACES. Contains a subdirectory train with 300, $110 × 96$, images of faces from the Olivetti dataset, ten images per person. These are used to train the detectors. There is an additional directory test with 100 faces from the same dataset. The directory pgm contains a number of pgm images on which detectors can be tested. The directories filt1, filt_d2, filt_from_edges contain different sparse models trained using different parameters.

 
• HEART. Contains ultrasound images of heart ventricles in directoriespat1, pat2, pat3, and a couple of angiograms in directory ang.

 
• BRAIN. Contains two directories of axial MRI brain scans, train and test, as well as a directory filt3 which contains a sparse model for these images, and a directory grmtch containing parameters for a sparse model of these scans for detection with dynamic programming.

 
• LATEX. Contains a directory protos with the prototypes of all the 293 LaTeX symbols, and a subdirectory latex_0 with a sparse model for the symbol 0 as well as a classifier for the hits of this detector (see Chapter 10). Subdirectories latex_1, latex_4, latex_7 contain models for the 1, the 4 and the 7.

 
• ESCR. Contains a sparse model and various templates for the `Epsilon' used in Chapter 3. Also the classifier for hits of this detector on other script style symbols.

 
• CLIP. Contains a sparse model for the clip shown in Chapter 8.

 
• CHESS. Contains the sparse model and classifiers for the chess-pieces.

 
• NIST. Contains one set of classification trees trained on the NIST data set and a small sample of 10,000 NIST digits for testing. The full data set is very large but can be obtained upon request. 

Running the program

The parameter file, if used, must come first. Parameters set on the command line override values set in the parameter file. Among the parameters opt must be set to a particular option which tells the program what routine to use. If no graphics is needed then facenox can be run the same way. The list of parameters needed for each of the algorithms is detailed in Chapter 12. In each subdirectory of book with a name corresponding to a chapter are prepared parameter files for the figures in that chapter. Type face f.par on the command line to have the program run the algoritmh producing the corresponding figure.

Graphics