def test_compare(self):
print('test_compare')
argv = [os.path.join('data/', self.pretrained_model_name),
'data/images/Anthony_Hopkins_0001.jpg',
'data/images/Anthony_Hopkins_0002.jpg' ]
args = compare.parse_arguments(argv)
compare.main(args)
def init():
global authorized_image_embeddings, pnet, rnet, onet, args, eval_graph
model_location = './outputs/20180402-114759.pb'
authorized_pictures = ['./outputs/IMG_9820.JPG',
'./outputs/IMG_9822.JPG',
'./outputs/ktXdtHO.JPG']
argv = [model_location]
for pic in authorized_pictures:
argv.append(pic)
args = compare.parse_arguments(argv)
print('Creating networks and loading parameters')
with tf.Graph().as_default():
sess = tf.Session()
with sess.as_default():
pnet, rnet, onet = align.detect_face.create_mtcnn(sess, None)
authorized_images = load_and_align_data(args.image_files, args.image_size, args.margin)
with tf.Graph().as_default():
with tf.Session() as sess:
# Load the model
facenet.load_model(args.model)
eval_graph = tf.get_default_graph()
images_placeholder = tf.get_default_graph().get_tensor_by_name("input:0")
embeddings = tf.get_default_graph().get_tensor_by_name("embeddings:0")
phase_train_placeholder = tf.get_default_graph().get_tensor_by_name("phase_train:0")
# Run forward pass to calculate embeddings
feed_dict = {images_placeholder: authorized_images, phase_train_placeholder: False}
authorized_image_embeddings = sess.run(embeddings, feed_dict=feed_dict)
def test_compare(self):
argv = [
'../data/model/20160620-173927/model.ckpt-500000',
'../data/images/Anthony_Hopkins_0001.png',
'../data/images/Anthony_Hopkins_0002.png'
]
args = compare.parse_arguments(argv)
compare.main(args)
def test_compare(self):
argv = [
os.path.join('data/', self.pretrained_model_name),
'data/images/Anthony_Hopkins_0001.jpg',
'data/images/Anthony_Hopkins_0002.jpg'
]
args = compare.parse_arguments(argv)
compare.main(args)
def test_compare(self):
argv = ['../data/model/20161030-023650/',
'model-20161030-023650.meta',
'model-20161030-023650.ckpt-80000',
'../data/images/Anthony_Hopkins_0001.jpg',
'../data/images/Anthony_Hopkins_0002.jpg' ]
args = compare.parse_arguments(argv)
compare.main(args)
def test_compare(self):
argv = ['../data/model/20161030-023650/',
'model-20161030-023650.meta',
'model-20161030-023650.ckpt-80000',
'../data/images/Anthony_Hopkins_0001.jpg',
'../data/images/Anthony_Hopkins_0002.jpg' ]
args = compare.parse_arguments(argv)
compare.main(args)
def compare2():
sys.argv[1:] = [e1.get(), e2.get()]
dist, time1 = compare.main(compare.parse_arguments(sys.argv[1:]))
if dist < 1:
var3.set(dist)
var4.set("判断为同一个人脸")
else:
var3.set(dist)
var4.set("判断为不是同一个人脸")
var5.set(time1)
def init():
global authorized_image_embeddings, pnet, rnet, onet, args, eval_graph
model_location = "C:\\Users\\typollak\\Documents\\Hackathon2018-20180723T192115Z-001\\Hackathon2018\\facenet\\src\\VGGFace2\\20180402-114759.pb"
authorized_pictures = [
'C:\\Users\\typollak\\Documents\\Hackathon2018-20180723T192115Z-001\\Hackathon2018\\facenet\\src\\pics\\IMG_9822.JPG'
]
argv = [model_location]
for pic in authorized_pictures:
argv.append(pic)
args = compare.parse_arguments(argv)
print('Creating networks and loading parameters')
with tf.Graph().as_default():
gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=.3)
sess = tf.Session(config=tf.ConfigProto(gpu_options=gpu_options,
log_device_placement=False))
with sess.as_default():
pnet, rnet, onet = align.detect_face.create_mtcnn(sess, None)
authorized_images = load_and_align_data(args.image_files, args.image_size,
args.margin)
with tf.Graph().as_default():
with tf.Session() as sess:
# Load the model
facenet.load_model(args.model)
eval_graph = tf.get_default_graph()
images_placeholder = tf.get_default_graph().get_tensor_by_name(
"input:0")
embeddings = tf.get_default_graph().get_tensor_by_name(
"embeddings:0")
phase_train_placeholder = tf.get_default_graph(
).get_tensor_by_name("phase_train:0")
# Run forward pass to calculate embeddings
feed_dict = {
images_placeholder: authorized_images,
phase_train_placeholder: False
}
authorized_image_embeddings = sess.run(embeddings,
feed_dict=feed_dict)
args.image_files.append("input")
def test_compare(self):
argv = ['../data/model/20160620-173927/model.ckpt-500000',
'../data/images/Anthony_Hopkins_0001.png',
'../data/images/Anthony_Hopkins_0002.png' ]
args = compare.parse_arguments(argv)
compare.main(args)
