【文件属性】：
文件名称：facenet master(state of art face recognition technic
文件大小：2.1MB
文件格式：ZIP
更新时间：2021-06-07 23:55:44
face recognition
facenet Implementation based on google's paper :A unified embedding for face recognition and clustering
【文件预览】：
facenet-master
----.project(361B)
----tmp()
--------test_align.py(1KB)
--------funnel_dataset.py(4KB)
--------test_invariance_on_lfw.py(11KB)
--------mnist_center_loss.py(18KB)
--------nn3.py(5KB)
--------vggverydeep19.py(4KB)
--------mnist_noise_labels.py(15KB)
--------vggface16.py(5KB)
--------align_dataset.m(8KB)
--------align_dataset.py(7KB)
--------pilatus800.jpg(106KB)
--------deepdream.py(10KB)
--------test1.py(21B)
--------nn2.py(5KB)
--------invariance_test.txt(2KB)
--------seed_test.py(5KB)
--------nn4.py(5KB)
--------__init__.py(16B)
--------visualize.py(5KB)
--------dataset_read_speed.py(903B)
--------mtcnn.py(3KB)
--------mtcnn_test.py(4KB)
--------detect_face_v2.m(9KB)
--------visualize_vgg_model.py(3KB)
--------detect_face_v1.m(8KB)
--------cacd2000_split_identities.py(1KB)
--------random_test.py(4KB)
--------network.py(9KB)
--------rename_casia_directories.py(1KB)
--------select_triplets_test.py(774B)
--------mtcnn_test_pnet_dbg.py(4KB)
--------visualize_vggface.py(2KB)
--------download_vgg_face_dataset.py(5KB)
--------nn4_small2_v1.py(4KB)
--------align_dlib.py(9KB)
----src()
--------generative()
--------compare.py(5KB)
--------freeze_graph.py(5KB)
--------models()
--------facenet.py(23KB)
--------train_tripletloss.py(24KB)
--------download_and_extract.py(2KB)
--------classifier.py(8KB)
--------__init__.py(16B)
--------validate_on_lfw.py(9KB)
--------calculate_filtering_metrics.py(6KB)
--------train_softmax.py(32KB)
--------align()
--------lfw.py(3KB)
--------decode_msceleb_dataset.py(4KB)
----.pylintrc(13KB)
----requirements.txt(88B)
----__init__.py(0B)
----contributed()
--------face.py(6KB)
--------export_embeddings.py(8KB)
--------real_time_face_recognition.py(3KB)
--------__init__.py(0B)
--------predict.py(6KB)
--------cluster.py(8KB)
--------batch_represent.py(5KB)
--------clustering.py(10KB)
----.travis.yml(458B)
----util()
--------plot_learning_curves.m(11KB)
----test()
--------train_test.py(10KB)
--------batch_norm_test.py(2KB)
--------triplet_loss_test.py(2KB)
--------center_loss_test.py(4KB)
--------restore_test.py(7KB)
----LICENSE.md(1KB)
----README.md(6KB)
----.pydevproject(461B)
----data()
--------learning_rate_schedule_classifier_casia.txt(104B)
--------learning_rate_schedule_classifier_vggface2.txt(107B)
--------learning_rate_retrain_tripletloss.txt(108B)
--------images()
--------pairs.txt(152KB)
--------learning_rate_schedule_classifier_msceleb.txt(107B)
----.gitignore(1KB)