Metadata-Version: 2.1
Name: dollarN
Version: 1.2.4
Summary: Implementation of the $N 2D gesture recognizer
Home-page: https://github.com/mikefromlig/dollarN
Author: Michael Ortega
Author-email: michael.ortega@imag.fr
License: UNKNOWN
Description: # dollarN
        **_Python implementation of $N, the 2D multistrokes recognizer_**
        
        http://depts.washington.edu/acelab/proj/dollar/ndollar.html
        
        > The $N Multistroke Recognizer is a 2-D multistroke recognizer designed
        > for rapid prototyping of gesture-based user interfaces. $N is built upon
        > the $1 Unistroke Recognizer. $N automatically generalizes examples of
        > multistrokes to encompass all possible stroke orders and directions,
        > meaning you can make and define multistrokes using any stroke order and
        > direction you wish, provided you begin at either endpoint of each
        > component stroke, and $N will generalize so as to recognize other ways
        > to articulate that same multistroke. A version of $N utilizing
        > Protractor, optional here, improves $N's speed.
        
        ## Features
        - [Python 3](https://www.python.org/)
        - [Numpy](https://numpy.org/)
        
        ## Example of use:
        ```
        import dollarN as dN
        
        r = dN.recognizer()
        #By default, a recognizer gives a positive result when gestures have
        #the same number of strokes only. This can be turned off:
        #r.set_same_nb_strokes(False)
        
        #Rotation invariance can also be turned off:
        #r.set_rotation_invariance(False)
        
        #Adding gestures: multistrokes with names
        r.add_gesture('U', [   [[0.,5.], [0.,0.], [5.,0.], [5.,5.]]    ]) # one stroke
        r.add_gesture('X', [   [[0.,0.], [5.,5.]], [[0.,5.], [5.,0.]]  ]) # two strokes
        r.add_gesture('T', [   [[0.,5.], [5.,5.]], [[2.5,0.], [2.5,5.]]]) # two strokes
        
        #Launching a recognition
        test = [[[0, 5.2], [5.,5.]], [[2.5, 0.], [2.5,5.]]]
        print( r.recognize(test) )
        ```
        ```
        {'name': 'T', 'value': 0.9484976300936439, 'time': 0.006083965301513672}
        ```
        ## Demo
        A demo is available with tkDollarN.py [here](https://github.com/mikefromlig/dollarN)
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
