def __init__(self, upsample_times=1, num_jitters=0, model='hog'):
g.logger.debug('Initializing face recognition with model:{} upsample:{}, jitters:{}'
.format(model, upsample_times, num_jitters))
self.upsample_times = upsample_times
self.num_jitters = num_jitters
self.model = model
self.knn = None
encoding_file_name = g.config['known_images_path']+'/faces.dat'
try:
if (os.path.isfile(g.config['known_images_path']+'/faces.pickle')):
# old version, we no longer want it. begone
g.logger.debug ('removing old faces.pickle, we have moved to clustering')
os.remove (g.config['known_images_path']+'/faces.pickle')
except Exception as e:
g.logger.error('Error deleting old pickle file: {}'.format(e))
# to increase performance, read encodings from file
if (os.path.isfile(encoding_file_name)):
g.logger.debug ('pre-trained faces found, using that. If you want to add new images, remove: {}'.format(encoding_file_name))
#self.known_face_encodings = data["encodings"]
#self.known_face_names = data["names"]
else:
# no encodings, we have to read and train
g.logger.debug ('trained file not found, reading from images and doing training...')
g.logger.debug ('If you are using a GPU and run out of memory, do the training using zm_train_faces.py. In this case, other models like yolo may already take up a lot of GPU memory')
train.train()
with open(encoding_file_name, 'rb') as f:
self.knn = pickle.load(f)
#!/usr/bin/python3
import argparse
import ssl
import zmes_hook_helpers.log as log
import zmes_hook_helpers.common_params as g
import zmes_hook_helpers.utils as utils
import zmes_hook_helpers.face_train as train
if __name__ == "__main__":
g.ctx = ssl.create_default_context()
ap = argparse.ArgumentParser()
ap.add_argument('-c',
'--config',
default='/etc/zm/objectconfig.ini',
help='config file with path')
args, u = ap.parse_known_args()
args = vars(args)
log.init(process_name='zm_train_faces', dump_console=True)
utils.process_config(args, g.ctx)
train.train()