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)