def create_mtcnn(self, sess, model_path):
tf.disable_eager_execution()
if not model_path:
model_path, _ = os.path.split(os.path.realpath(__file__))
with tf.variable_scope('pnet'):
data = tf.placeholder(tf.float32, (None, None, None, 3), 'input')
pnet = mtcnn_detect_face.PNet({'data': data})
pnet.load(os.path.join(model_path, 'det1.npy'), sess)
with tf.variable_scope('rnet'):
data = tf.placeholder(tf.float32, (None, 24, 24, 3), 'input')
rnet = mtcnn_detect_face.RNet({'data': data})
rnet.load(os.path.join(model_path, 'det2.npy'), sess)
with tf.variable_scope('onet'):
data = tf.placeholder(tf.float32, (None, 48, 48, 3), 'input')
onet = mtcnn_detect_face.ONet({'data': data})
onet.load(os.path.join(model_path, 'det3.npy'), sess)
self.pnet = K.function([pnet.layers['data']],
[pnet.layers['conv4-2'], pnet.layers['prob1']])
self.rnet = K.function([rnet.layers['data']],
[rnet.layers['conv5-2'], rnet.layers['prob1']])
self.onet = K.function([onet.layers['data']], [
onet.layers['conv6-2'], onet.layers['conv6-3'],
onet.layers['prob1']
])
def create_mtcnn(sess, model_path):
with tf.variable_scope('pnet'):
data = tf.placeholder(tf.float32, (None,None,None,3), 'input')
pnet = mtcnn_detect_face.PNet({'data':data})
pnet.load(os.path.join(model_path, 'det1.npy'), sess)
with tf.variable_scope('rnet'):
data = tf.placeholder(tf.float32, (None,24,24,3), 'input')
rnet = mtcnn_detect_face.RNet({'data':data})
rnet.load(os.path.join(model_path, 'det2.npy'), sess)
with tf.variable_scope('onet'):
data = tf.placeholder(tf.float32, (None,48,48,3), 'input')
onet = mtcnn_detect_face.ONet({'data':data})
onet.load(os.path.join(model_path, 'det3.npy'), sess)
return pnet, rnet, onet
