Wheelodex » Projects » facenet » facenet-1.0.5-py3-none-any.whl

facenet

View on PyPI — Reverse Dependencies (0)

1.0.5 facenet-1.0.5-py3-none-any.whl

Wheel Details

Project: facenet
Version: 1.0.5
Filename: facenet-1.0.5-py3-none-any.whl
Download: [link]
Size: 2011248
MD5: 0195311b97f10da95ffb169d525d7c9a
SHA256: d89476525c79245a19e6778d4cb0afe51fe69b35b6c3359d8ca1f67c04616de4
Uploaded: 2019-09-29 23:22:56 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.1
Name: facenet
Version: 1.0.5
Summary: Face recognition using TensorFlow
Maintainer: Jonathan Lancar
Maintainer-Email: jonaphin[at]gmail.com
Home-Page: https://github.com/jonaphin/facenet
License: MIT
Requires-Dist: tensorflow
Requires-Dist: scipy
Requires-Dist: scikit-learn
Requires-Dist: opencv-python
Requires-Dist: h5py
Requires-Dist: matplotlib
Requires-Dist: Pillow
Requires-Dist: requests
Requires-Dist: psutil
[Description omitted; length: 74 characters]

WHEEL

Wheel-Version: 1.0
Generator: bdist_wheel (0.33.4)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
contributed/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
contributed/batch_represent.py sha256=dlvtxdhG-oZOb-q1tG4CR9Gr4Z5T5tJ-u7-BI_xeWBQ 5667
contributed/cluster.py sha256=Zm5ipLI81e8a4G_DgRu6ImbSYKVqwpCTj5f22yWjOcs 8734
contributed/clustering.py sha256=BNOWSqoPBTU8WpWQ0y84WfslCDYs7z0aXsmG5PZ6wac 10000
contributed/export_embeddings.py sha256=qw0YcXfEk-9ipbcT8fh6yeJ4SJSYMAB-CnO4lcdm8bU 8782
contributed/face.py sha256=G_XnPOxVS8fu7hcvLZ89umb0S44oKDT1_Q6jyt2Yw4Q 6090
contributed/predict.py sha256=jPZ9_9Vx_9aJxwVLILN5hdww4eX7vCpKCyG-iSdPoew 6314
contributed/real_time_face_recognition.py sha256=NR9P6HBM7ybr4WtP8R0_DayedCN6RGY5sVllWQebTNE 3516
facenet/__init__.py sha256=7G4NB48eGQoBcHRaIAseIzIfwOKZjJb0aXG8FWtGm64 18
facenet/src/__init__.py sha256=7G4NB48eGQoBcHRaIAseIzIfwOKZjJb0aXG8FWtGm64 18
facenet/src/calculate_filtering_metrics.py sha256=SDPkkEIpkGcOniDOm4ERO1qsGVCCvwdBqZUVxZuF0Sg 6152
facenet/src/classifier.py sha256=3GTtlPDVV6-OR1TyNNg6_kcMC9-ejA5ysUaLX-UdvGk 8281
facenet/src/compare.py sha256=V914T_MYDIh4wDWxi-8iFcXLG2ewCwNPuJY-5JSc_DE 5625
facenet/src/decode_msceleb_dataset.py sha256=WIpZk3UvhIS3NuCxJHQVOOIhfx-SOuOIZwH2qGFWTVI 3717
facenet/src/download_and_extract.py sha256=X7e8FoFpOF3RNkGM0x46AX35plVp0j1jHvQCebOxZRs 1742
facenet/src/face.py sha256=ROicVhW5myr7BrDJsv6sbqOA-BO26SKachHjOHz3Wk8 6556
facenet/src/facenet.py sha256=rgc6PhALidoYAC346wbElqbn-5uTazKJmOInC-3TT1k 25509
facenet/src/freeze_graph.py sha256=rHxvHPToM7IqAXMhz7zNBpFfLap2-_p9UMxwc5wUYaM 4750
facenet/src/lfw.py sha256=Pzv3lI3_CCRof5n35BMRafve9adECOr8P4FyS9UfP50 3654
facenet/src/train_softmax.py sha256=9d9GNX_2QPnP6XdIL2Tgu_V9biG_RIz2F8nuHYmd1ss 33196
facenet/src/train_tripletloss.py sha256=PMzxETzHF86GZjycak-Ah4pm6iAzoh4bLz8dBdYQZCw 25354
facenet/src/validate_on_lfw.py sha256=xCPQytQzYElXZv9hjoyvw5b3Ps8KOzTJe2qIOse3UWM 5344
facenet/src/align/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
facenet/src/align/align_dataset_mtcnn.py sha256=mep-TwLMv1TNZkwVlQezHWRvj2jPFRKJ7NKvajB_8x8 8406
facenet/src/align/det1.npy sha256=MoXPej3iZRxXhMueMgE_WRmq6V_R7RvDcd2Wka_7Oa8 27368
facenet/src/align/det2.npy sha256=cWuLg-QkdnkckJbxTbsJ_vyIv1x-yHaxaD-azVKz85w 401681
facenet/src/align/det3.npy sha256=OW6tgD2F00QzB_-PRftq7SU2V5tBWk9NTLj5PqaxR2o 1557360
facenet/src/align/detect_face.py sha256=C1iT83qTIF8DW575LDu8yXlIMSiwmPkzqBSMfyMp-6A 32495
facenet/src/generative/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
facenet/src/generative/calculate_attribute_vectors.py sha256=ePkQylQMnpKPonyZjC4y3RCvZOtdYCyrSs87hKPmeWs 9096
facenet/src/generative/modify_attribute.py sha256=0R0Zs2pxVVWqobZ8htDZZJoob77-KSE6uSrJD8XWBc4 6271
facenet/src/generative/train_vae.py sha256=oQ01dsGvmvy5zKes_BJQI4oD_7qXIeUjyUQStDv0jxE 14222
facenet/src/generative/models/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
facenet/src/generative/models/dfc_vae.py sha256=uoZ8Ovfy42KFiGa70gs-v_Bbr0AaKdl3UVnMU_bHJHY 5007
facenet/src/generative/models/dfc_vae_large.py sha256=b5YkDCVfEhOzS3RAMBK3TSR5efd-CgXRcFnOU8J7eNw 5374
facenet/src/generative/models/dfc_vae_resnet.py sha256=DSVamLRtveQ2i0jPKKO4BqcSoH9Ye-9jiS2mI1A2fWQ 6366
facenet/src/generative/models/vae_base.py sha256=Pyh7sqLArQcijdSvHst7TAo4VGMhZBejmuIwXH1ygZI 2332
facenet/src/models/__init__.py sha256=7G4NB48eGQoBcHRaIAseIzIfwOKZjJb0aXG8FWtGm64 18
facenet/src/models/dummy.py sha256=yp4wn5DrsJpBgSL9g1J9lkRaDqW3wJPhWL023H4MwLc 2610
facenet/src/models/inception_resnet_v1.py sha256=y7I8skjiXGDyA7xMbFF6th8XM7a6fhbHlHKuCTxdguY 12014
facenet/src/models/inception_resnet_v2.py sha256=VXFwJjBEt0SBwr41JmtzpoHj1Bq2wdAcKes5iU4XXVU 13619
facenet/src/models/squeezenet.py sha256=bp74BJHrwrzi212XJLGkJlSY-z59cYxkOsAZdKlTiD0 3470
tmp/__init__.py sha256=7G4NB48eGQoBcHRaIAseIzIfwOKZjJb0aXG8FWtGm64 18
tmp/align_dataset.py sha256=J9_FilM2I7lwYQMNHlEMm-0A2NfN245TG2HveHmc0HM 7139
tmp/align_dlib.py sha256=3BFe9o6lje8Y63553kuNMnBC4Xj4XwWiQLld2GYgQcc 8994
tmp/cacd2000_split_identities.py sha256=STXoiGrg5EeO5QDTnGnLHj4Hny5W92-ALX48tAB9zMw 1162
tmp/dataset_read_speed.py sha256=mr4KcMF3IOipzyjfKYUBbG1q2HoLwQ1xlvT3H9YJ998 934
tmp/deepdream.py sha256=EHZ-T8Nknqxk2ewhcjpQWNy4bh5BVj6OOf12HqieyAw 10696
tmp/download_vgg_face_dataset.py sha256=TblfshBuwQd63XuHvpbyz4cjKd6iiqxn9b4ytOTMvIY 5120
tmp/funnel_dataset.py sha256=xzYyB6f1jarMS5ajtapPsw7cEcwEjUTJgkdZdP_PSkU 4360
tmp/mnist_center_loss.py sha256=ltnApKi4kGM9f_l_EFqVX5ePXwjRdc7ZhiBQ68oyoRA 19007
tmp/mnist_noise_labels.py sha256=A1owzC_pTYVduFSZslHh5rElaWy2WVEPdLRgCmROjdo 15779
tmp/mtcnn.py sha256=r70I66UPw-vqquwiuWiOXt7wtuAWprIqOgiv4SToqMQ 2894
tmp/mtcnn_test.py sha256=5o06k6k5MZSpxWc9Gr5RSpeskiatINxZ67xNvzLJ8lI 4496
tmp/mtcnn_test_pnet_dbg.py sha256=VI0vxWAxLgc-730a7KapB3z_MSUeR2TIfHpbR95F53s 4674
tmp/network.py sha256=wtwHXKTM0o3yJC2qdQu__g1M0jeOzjzfznOgUDfagAM 9007
tmp/nn2.py sha256=9W5yx1AP3R4t3YLIfK9pjEiME0bexjS8t4z_Y1-WKnM 4751
tmp/nn3.py sha256=UZAhaI2lCkK2Nm5EsNsuP3hzSMGhBh7_j1Da32wN9bQ 4751
tmp/nn4.py sha256=kGAt-UivIBmAiIHt6ZBp-MBzxWSyumEj4tdUllRcJ9M 4743
tmp/nn4_small2_v1.py sha256=C18qbd1ROh0sCKAThZquVrdW2sXo9YLaOryFg59bRqA 4167
tmp/random_test.py sha256=7y-H0w-HJ7U9vDhS8EIgAfKoQPuunBaH-dCZzfZfoYQ 3924
tmp/rename_casia_directories.py sha256=G3IOCiBsAJ-cIE_GmBW0_B23immgP-agatJ48bis6kI 1387
tmp/seed_test.py sha256=bXEhAPGiCfYaEZZY6hzbvb-vlngcodoU3VVMxRZkhFo 5689
tmp/select_triplets_test.py sha256=sBCrpSB814tAEO7JO6FWDc6zq5gBdDyqyj8v8hKX61c 804
tmp/test1.py sha256=YMvyBMpVYk8wZziuGXpLosavqY4Zu17_L1YNMmQL_Ns 22
tmp/test_align.py sha256=TXT2aX1acJyhnIP5QaAozEYfK-ooRsqn58HWIn71gtA 1547
tmp/test_invariance_on_lfw.py sha256=qBdPTFb4kfXWiJJxR1w1x6_lODNMXTeFW1BYKVA6lmQ 11336
tmp/vggface16.py sha256=OZ6pD_VEmaLMRM3w5hn_BZlRj0ZsUCUNH1TAlNaIoFw 4878
tmp/vggverydeep19.py sha256=ICYpQJ9oqKtYvwQLc3G3-U2b217Wxmtg2GV16OLJXsE 4073
tmp/visualize.py sha256=awT4b5ZdtoPpkTSLPVwtPdYGpaWL8BxGwRZ9kAsdETw 5157
tmp/visualize_vgg_model.py sha256=qFgBNKnBqVMg1-oOVt3l5MqUuxFtovV69rfoTPCOF9c 3650
tmp/visualize_vggface.py sha256=y1HEg8gIg7AysormkuJnCv-vY9au5ZWwA19P7HZDvNQ 1689
facenet-1.0.5.dist-info/LICENSE.md sha256=VENk-BrnrnBoe5JxrBBMF_nw_558qRX8cBbsi_UtbCg 1092
facenet-1.0.5.dist-info/METADATA sha256=oWv4VQOmNRyaQUeM4tAMgf9vPOazzt9tb1W9gCzhDF0 530
facenet-1.0.5.dist-info/WHEEL sha256=QBOOAdG2icRHGBs2s94rfaUlHrdfNBp-TceubUYCwOE 97
facenet-1.0.5.dist-info/top_level.txt sha256=LX4Omnv5bL4uozOJ2W9tDysszBOr7VqUcKVFAbyhzi0 24
facenet-1.0.5.dist-info/RECORD — —

top_level.txt

contributed
facenet
tmp