Wheelodex » Projects » vjepa

vjepa

View on PyPI — Reverse Dependencies (1)

0.1.2 vjepa-0.1.2-py3-none-any.whl

Wheel Details

Project: vjepa
Version: 0.1.2
Filename: vjepa-0.1.2-py3-none-any.whl
Download: [link]
Size: 58864
MD5: e0faf6831572134140c2e83edc034758
SHA256: 63f87f9d66bd5367342e48347c476d2cb94985c11ff0373b04ff9e8502a73085
Uploaded: 2024-10-07 16:10:45 +0000

dist-info

METADATA · WHEEL · RECORD

METADATA

Metadata-Version: 2.1
Name: vjepa
Version: 0.1.2
Summary: Moedified from the official PyTorch codebase for the video joint-embedding predictive architecture, V-JEPA, a method for self-supervised learning of visual representations from video.
Author: Adrien Bardes
Author-Email: abardes[at]meta.com
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Python: >=3.9,<4.0
Requires-Dist: beartype (<0.20.0,>=0.19.0)
Requires-Dist: braceexpand (<0.2.0,>=0.1.7)
Requires-Dist: decord (<0.7.0,>=0.6.0)
Requires-Dist: einops (<0.9.0,>=0.8.0)
Requires-Dist: numpy (>=1.24.0)
Requires-Dist: opencv-python (<5.0.0.0,>=4.10.0.84)
Requires-Dist: pandas (==2.2.2)
Requires-Dist: pyyaml (<7.0.0,>=6.0.2)
Requires-Dist: submitit (<2.0.0,>=1.5.2)
Requires-Dist: timm (<2.0.0,>=1.0.9)
Requires-Dist: torch (>=2)
Requires-Dist: torchvision (<0.20.0,>=0.19.1)
Requires-Dist: webdataset (<0.3.0,>=0.2.100)
Description-Content-Type: text/markdown
[Description omitted; length: 18329 characters]

WHEEL

Wheel-Version: 1.0
Generator: poetry-core 1.9.0
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
vjepa/__init__.py sha256=B7ZnNoLLOgeOnDLS5kYjD9otHvtKAYLQU_RYop56RaQ 1522
vjepa/datasets/__init__.py sha256=S_pkudZDkt90l0Pv-Kt4qiLrAxsP5yFPZ6wfVoCwHG4 89
vjepa/datasets/data_manager.py sha256=EVGrUArnKRvR-cfTMqWtmj4VZD_Wmr68E46T_G78_4c 2638
vjepa/datasets/image_dataset.py sha256=e4rjI_MOU-fS7jhj6iZ5v0AYe4SprWj76T_bt3-fbVo 2079
vjepa/datasets/utils/__init__.py sha256=QTakhgy-peOLLSAFRIBSgAOiRy3vOr6grChSpyFcNn4 119
vjepa/datasets/utils/video/__init__.py sha256=0kB74jwrB1XHKEaV7mXEMfy4HV_5lb9KsATlxGFqOMQ 124
vjepa/datasets/utils/video/functional.py sha256=mjaMoeGoRQo0gDA3L5cxicXBBDzIDcwvIcHBCA3Wju0 3116
vjepa/datasets/utils/video/randaugment.py sha256=s6p9BtdrViAocf-GNh59SYFzB_2rfCPHPjUcWQEaUtg 15452
vjepa/datasets/utils/video/randerase.py sha256=8BHdmRBTEyQ1rNhwFO1YJtKu1PQ8DIWqcGSAqUwP6KY 6809
vjepa/datasets/utils/video/transforms.py sha256=yOTfPs7DV0vcoxpOKKY0ZC7yNgtILLXPrCUzXRdgSH4 40405
vjepa/datasets/utils/video/volume_transforms.py sha256=4HTiEh_ZnWVsn-teX5TTnv0EicNhf9ewb4hmgRoipf4 4729
vjepa/datasets/utils/weighted_sampler.py sha256=Y-LTsqROSF2ic5L8wlhut3xt515b6hv4iCv1hDrswys 2727
vjepa/datasets/video_dataset.py sha256=wp2vKslkc3yDilbvosjkGPEQ3cTUnLFY91c5fM1DEWU 9500
vjepa/masks/__init__.py sha256=BipCbZyMt2Atda-28XLErdJLFWiKX0ce4x5OeJuFOJY 57
vjepa/masks/default.py sha256=bhep2uRxQuriUYztA3Bczh3T3WVACB40vvVNGonYt24 456
vjepa/masks/multiblock3d.py sha256=mg0huWM3lwVq6dvUffbF9vjMcEoXIdOA2D-UnSJNPcw 7259
vjepa/masks/random_tube.py sha256=EchahYH9r_7lUBl1reCjNCis8ovHAxC7IafFsu_QvBI 3643
vjepa/masks/utils.py sha256=Ipf7MKq9vGNae56Xk4Bs6-xiNn8DLUub1X-7ThaBo4E 681
vjepa/models/__init__.py sha256=QhHaDjGmn4MNpykXz2Sfgu2EjTWN5SAJJL6kTDMY0CU 316
vjepa/models/attentive_pooler.py sha256=SvpUt63wdp_hly6a10r1IhwY2VeVDR8p-My-sjPBPpQ 4124
vjepa/models/predictor.py sha256=0GUx5eNvNbUQgAd43sebD60ETvMcGsXIg43SzStN0Hw 8570
vjepa/models/utils/__init__.py sha256=deY__TCW4dIedmKkQ6pV7ppnHSAvO0t3MK-UYWt22GI 252
vjepa/models/utils/modules.py sha256=VoARoCF9q7URwRt6uyWv6pSTNJkHFbsByqW2TxykWHs 5334
vjepa/models/utils/multimask.py sha256=khCeMDNSfMhp6CXkqU_Df9FEcjNa7F3marBis-cBTSI 1322
vjepa/models/utils/patch_embed.py sha256=gWfHqamhXf_4Gg47jN_L-raIHMDaOWzBMMRynMunXBE 1372
vjepa/models/utils/pos_embs.py sha256=P_99CajpnqrKDD5DbsxXlNyeYiRf4-VInozTeiP3cag 3579
vjepa/models/vision_transformer.py sha256=GxUukbrBRixBP5tRPtoczB7L8gP4FlnLfUq4c95XL_0 10139
vjepa/utils/__init__.py sha256=OQuTApB0_mYp5c2535sV-JD94n_ppuPjuWNce_TYgEo 63
vjepa/utils/distributed.py sha256=ARIl53lHS-f50Kq8rx675oNV1oAS6lBISOseinf4vuo 3037
vjepa/utils/logging.py sha256=1rTm1AF4WFU9jtaCP-Xw5zyfC2yCgvn0HNgl57HpMgI 3519
vjepa/utils/monitoring.py sha256=hqzzXpMOs5E_bKXKPrF1vh0uDn-6zVJgDEseon3C57M 5973
vjepa/utils/schedulers.py sha256=DiYnWn_EPuS6HXfzkQDerXqaeufxgLdA4RsxFD33e20 2138
vjepa/utils/tensors.py sha256=d0oPge6lLS_MQ3OBjYqrBOeQwU8CnjfkFewOX23yqMs 2220
vjepa/version.py sha256=3K9tXlL5Ndwa6lGJUjRxqvnor1zZgCdyaTPCa9bRDts 781
vjepa-0.1.2.dist-info/LICENSE sha256=GwVW79x-crF7cGwEEALGzcHgqiV_XlZ26g-Iey8IVOw 19337
vjepa-0.1.2.dist-info/METADATA sha256=Ewbpk-OX8s28Myd0PlWr-qF-9hi1qznOs3-w8jGbqD4 19790
vjepa-0.1.2.dist-info/WHEEL sha256=sP946D7jFCHeNz5Iq4fL4Lu-PrWrFsgfLXbbkciIZwg 88
vjepa-0.1.2.dist-info/RECORD — —