mirror of
https://github.com/jlengrand/Ivolution.git
synced 2026-03-10 08:21:18 +00:00
46 lines
1.6 KiB
Python
46 lines
1.6 KiB
Python
'''
|
|
Created on 30 mars 2012
|
|
|
|
@author: jll
|
|
'''
|
|
import cv
|
|
import os
|
|
|
|
from facemovie 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):
|
|
'''
|
|
Constructor
|
|
'''
|
|
# 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
|
|
cascade_name = training_types.simple_set[training_type] + ".xml"
|
|
# Setting up some default parameters for Face Detection
|
|
print os.path.join(xml_folder, cascade_name)
|
|
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 "---------" |