Source code for facemovie.FaceParams

"""
.. module:: FaceParams
   :platform: Unix, Windows
   :synopsis: Simple class used to store parameters used for Face detection.

.. moduleauthor:: Julien Lengrand-Lambert <jlengrand@gmail.com>

"""
import cv
import os

import training_types

class FaceParams(object):
    '''
    Simple class used to store parameters used for Face detection
    '''
    def __init__(self, xml_folder, training_type, i_scale=2, h_scale=1.2, h_flags=0, mn=2):
        """
        Creates dictionary for all types of training files
        some of them shall never be used. Perhaps would it be good to lower the dict size, or hide some of them
        postpend .xml

        :param xml_folder: the location where xml files are located
        :type xml_folder: string
        :param training_type: the type of profile we are going to use
        :type training_type: string

        :param i_scale: Image scaling chosen for classification (2) 
        :type i_scale: float
        :param h_scale: Haar scaling chosen for classification (1.2) 
        :type h_scale: float
        :param h_flags: the chosen number of haar flags (0)
        :type h_flags: int                                                
        :param mn: the Minimum number of neighbors to be defined (2) 
        :type mn: int                                        
        """

        cascade_name = training_types.simple_set[training_type] + ".xml"
        # Setting up some default parameters for Face Detection
        self.face_cascade = cv.Load(os.path.join(xml_folder, cascade_name))

        # To be defined more precisely
        self.min_size = (20,20)
        self.image_scale = i_scale
        self.haar_scale = h_scale
        self.min_neighbors = mn
        self.haar_flags = h_flags
        
    def __str__(self):
        """
        More convenient print method
        """
        print "---------"
        print "Selected parameters for Face Detection:"
        print "Selected cascade for Face detection : %s" % ("haarcascade_frontalface_alt")
        print "Minimum Size (x, y): %d" % (self.min_size[0], self.min_size[1])
        print "Image scaling: %d, %d)" % (self.image_scale)
        print "Haar scaling: %f" % (self.haar_scale)
        print "Number of Haar flags: %d" % (self.haar_flags)
        print "Minimum number of neighbors: %d" % (self.min_neighbors)
        print "---------"