You can run Fréchet-View in "headless" mode from a command line terminal. The program processes just one input file.

Select an algorithm:

• -c Fréchet distance for curves
• -p Fréchet distance für simple polygons
• -k k-Fréchet distance

Options -c and -p support three variants:

• --dec=<eps> decision problem: is d_F <= epsilon ?
• --opt optimization problem: computes the exact value of d_F
• --app=<accuracy> approximates d_F by nested intervals

The k-Frechet algorithm -k accepts only --dec=<eps>. It computes the smallest k for a given epsilon. There is no other optimization variant for the k-Frechet algorithm (i.e. there is no option to compute the smallest epsilon for a given k).

--cores=<p> defines the number of parallel threads on a multi-core system. Results are usually best if you choose the number of physical CPU cores. Performance does not benefit from hyperthreading on Intel processors.

Example for a quad core processor: --cores=4 is fine, but --cores=8 does not improve.

--large minimizes memory usage (for really large input data).

--gpu enables GPGPU support. You need an OpenCL 1.2 compatible card and driver. Significant speedups require really powerful graphics cards. --tile=<a,b> fine-tuning parameter for GPGPU support.

Use --help to view available options.

Examples:

    Frechet-View.app/Contents/MacOS/frechet-view "Demo Data/trousers.jscript" -p --dec=45
    Frechet-View.app/Contents/MacOS/frechet-view "Demo Data/trousers.jscript" -p --opt --cores=4
    Frechet-View.app/Contents/MacOS/frechet-view "Demo Data/trousers.jscript" -c --approx=1-e6
    Frechet-View.app/Contents/MacOS/frechet-view "Demo Data/criss-cross-2.jscript" -k --dec=0.4
    Frechet-View.app/Contents/MacOS/frechet-view "Demo Data/trousers.jscript" -p --dec60 --cores=4 --gpu