def get_frames(self):
sheet = pg.image.load("p1_walk.png").convert()
sheet.set_colorkey(c.SPRITESHEET_BACKGROUND)
return tools.get_images(sheet, self.rect.size)
def get_frames(self):
sheet = pg.image.load("p1_walk.png").convert()
sheet.set_colorkey(c.SPRITESHEET_BACKGROUND)
return tools.get_images(sheet, self.rect.size)
t0 = time.time() # count execution-time for whole programm
localtime = time.asctime( time.localtime(time.time()) )
print "Local current time :", localtime
logging.info('Current Log-Level: %s' % logging.getLevelName(logging.getLogger('myLogger').root.getEffectiveLevel()))
if parameter.train == 1:
#start train
##############################################
print 'TRAINING STARTED'
# foldername containing the training images
trainfolder = "train"
# make list with all images in the folder
image_filenames = tools.get_images(trainfolder)
# detect faces and features in images
trained_data = train.get_face_data(image_filenames)
if parameter.pickle_data == 1:
# safe (pickle) data
persistence.safe_data(trained_data)
print time.time() - t0, "seconds" # print execution-time for Training
print 'TRAINING FINISHED'
#optional evaluation
###############################################
# show training-images and paint keypoints into the pictures
