def __init__(self, minsize=20, threshold=[0.7, 0.7, 0.9], factor=0.71):
with tf.Graph().as_default():
self.sess = tf.Session()
self.pnet, self.rnet, self.onet = detect_face.create_mtcnn(
self.sess, None)
self.mtcnn_img_size = (250, 250)
self.minsize = minsize # minimum size of face
self.threshold = threshold # three steps's threshold
self.factor = factor # scale factor
def __init__(self):
gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.2)
self.session = tf.Session(config=tf.ConfigProto(
gpu_options=gpu_options))
self.pnet, self.rnet, self.onet = detect_face.create_mtcnn(
self.session, None)
print("loading model....")
file = open("clf_model.sav", 'rb')
model = pickle.load(file)
print("model loaded sucessfully")
from detection.mtcnn import detect_face
default_color = (0, 255, 0) #BGR
default_thickness = 2
color = (255, 0, 0)
with tf.Graph().as_default():
sess = tf.Session()
pnet, rnet, onet = detect_face.create_mtcnn(sess, None)
minsize = 20 # minimum size of face
threshold = [0.6, 0.7, 0.7] # three steps's threshold
factor = 0.709
font = cv2.FONT_HERSHEY_SIMPLEX
org = (50, 50)
fontScale = 1
color = (255, 0, 0)
thickness = 2
#
def test_model_for_url(image):
encodings = []
encodings_list = []
prediction_list = []