def ready(self):
# This global variable will be used by views.py.
# read_trained_data() only needs to be read once here, instead
# of every time a request comes in.``
global myFaceRecognizer
myFaceRecognizer = FaceRecognizer()
logger.info("Created myFaceRecognizer")
def __init__(self,
dataset=FaceRecData.Yalefaces_A,
data_directory='data',
part=[70, 10, 20],
loud=False,
d_tuning=[25, 100, 25],
k_tuning=[1, 15],
var_tuning=[1000, 10000, 1000],
skip_tuning=False,
d_value=0,
k_value=3,
var_value=10000,
use_kernel=False): # TODO: Better way to init this?
'''
Constructor for FaceRecTest.
Args (optional):
dataset (FaceRecData.value): The dataset to use.
data_directory (str): The directory where the data lives.
part (int): What percentage of the data should be used for
training, dev, and test.
loud (bool): Whether the classifier should print out fine details.
d_tuning (tuple<int>): The range of PCA dimensions to observe
during tuning.
k_tuning (tuple<int>): The ranke of k for the kNN classifier to
observe during tuning.
'''
self.dataset = dataset
self.data_directory = data_directory
self.trn_part = part[0]
self.dev_part = part[1]
self.tst_part = part[2]
self.loud = loud
self.d_tuning = d_tuning
self.k_tuning = k_tuning
self.var_tuning = var_tuning
self.skip_tuning = skip_tuning
self.d_value = d_value
self.k_value = k_value
self.var_value = var_value
self.use_kernel = use_kernel
self.face_recognizer = FaceRecognizer(use_kernel=use_kernel)
self.instances = None
self.trn_data = None
self.dev_data = None
self.tst_data = None
if sum(part) != 100:
raise RuntimeError('Train/Dev/Test partitions don\'t add up '
'to 100%')
if len(d_tuning) != 3:
raise RuntimeError('3 parameters are required for tuning d '
'({} found)'.format(len(d_tuning)))
if len(k_tuning) != 2:
raise RuntimeError('2 parameters are required for tuning k '
'({} found)'.format(len(d_tuning)))
