tensorflow
Can't download "seleb_a"
/!\ PLEASE INCLUDE THE FULL STACKTRACE AND CODE SNIPPET
Short description Can't download "seleb_a"
Environment information
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Operating System: <Ubuntu 20.04 focal (x86-64)>
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Python version: <3.8.10>
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tensorflow-datasets/tfds-nightlyversion: <4.5.2+nightly> -
tensorflow/tf-nightlyversion: <2.8.0> -
Does the issue still exists with the last
tfds-nightlypackage (pip install --upgrade tfds-nightly) ? YES Reproduction instructions
import tensorflow_datasets as tfds
celeba_bldr = tfds.builder('celeb_a')
print(celeba_bldr.info)
celeba_bldr.download_and_prepare()
If you share a colab, make sure to update the permissions to share it.
Link to logs If applicable, <link to gist with logs, stack trace>
Expected behavior I need celeb_a dataset
Additional context Output: build_celeba.py
2022-03-23 18:57:25.652770: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory 2022-03-23 18:57:25.652786: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine. 2022-03-23 18:57:26.961914: W tensorflow/core/platform/cloud/google_auth_provider.cc:184] All attempts to get a Google authentication bearer token failed, returning an empty token. Retrieving token from files failed with "NOT_FOUND: Could not locate the credentials file.". Retrieving token from GCE failed with "FAILED_PRECONDITION: Error executing an HTTP request: libcurl code 6 meaning 'Couldn't resolve host name', error details: Could not resolve host: metadata". tfds.core.DatasetInfo( name='celeb_a', full_name='celeb_a/2.0.1', description=""" CelebFaces Attributes Dataset (CelebA) is a large-scale face attributes dataset with more than 200K celebrity images, each with 40 attribute annotations. The images in this dataset cover large pose variations and background clutter. CelebA has large diversities, large quantities, and rich annotations, including - 10,177 number of identities, - 202,599 number of face images, and - 5 landmark locations, 40 binary attributes annotations per image.
The dataset can be employed as the training and test sets for the following computer vision tasks: face attribute recognition, face detection, and landmark (or facial part) localization.
Note: CelebA dataset may contain potential bias. The fairness indicators
[example](https://www.tensorflow.org/responsible_ai/fairness_indicators/tutorials/Fairness_Indicators_TFCO_CelebA_Case_Study)
goes into detail about several considerations to keep in mind while using the
CelebA dataset.
""",
homepage='http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html',
data_path='~/tensorflow_datasets/celeb_a/2.0.1',
download_size=1.38 GiB,
dataset_size=1.62 GiB,
features=FeaturesDict({
'attributes': FeaturesDict({
'5_o_Clock_Shadow': tf.bool,
'Arched_Eyebrows': tf.bool,
'Attractive': tf.bool,
'Bags_Under_Eyes': tf.bool,
'Bald': tf.bool,
'Bangs': tf.bool,
'Big_Lips': tf.bool,
'Big_Nose': tf.bool,
'Black_Hair': tf.bool,
'Blond_Hair': tf.bool,
'Blurry': tf.bool,
'Brown_Hair': tf.bool,
'Bushy_Eyebrows': tf.bool,
'Chubby': tf.bool,
'Double_Chin': tf.bool,
'Eyeglasses': tf.bool,
'Goatee': tf.bool,
'Gray_Hair': tf.bool,
'Heavy_Makeup': tf.bool,
'High_Cheekbones': tf.bool,
'Male': tf.bool,
'Mouth_Slightly_Open': tf.bool,
'Mustache': tf.bool,
'Narrow_Eyes': tf.bool,
'No_Beard': tf.bool,
'Oval_Face': tf.bool,
'Pale_Skin': tf.bool,
'Pointy_Nose': tf.bool,
'Receding_Hairline': tf.bool,
'Rosy_Cheeks': tf.bool,
'Sideburns': tf.bool,
'Smiling': tf.bool,
'Straight_Hair': tf.bool,
'Wavy_Hair': tf.bool,
'Wearing_Earrings': tf.bool,
'Wearing_Hat': tf.bool,
'Wearing_Lipstick': tf.bool,
'Wearing_Necklace': tf.bool,
'Wearing_Necktie': tf.bool,
'Young': tf.bool,
}),
'image': Image(shape=(218, 178, 3), dtype=tf.uint8),
'landmarks': FeaturesDict({
'lefteye_x': tf.int64,
'lefteye_y': tf.int64,
'leftmouth_x': tf.int64,
'leftmouth_y': tf.int64,
'nose_x': tf.int64,
'nose_y': tf.int64,
'righteye_x': tf.int64,
'righteye_y': tf.int64,
'rightmouth_x': tf.int64,
'rightmouth_y': tf.int64,
}),
}),
supervised_keys=None,
disable_shuffling=False,
splits={
'test': <SplitInfo num_examples=19962, num_shards=2>,
'train': <SplitInfo num_examples=162770, num_shards=16>,
'validation': <SplitInfo num_examples=19867, num_shards=2>,
},
citation="""@inproceedings{conf/iccv/LiuLWT15,
added-at = {2018-10-09T00:00:00.000+0200},
author = {Liu, Ziwei and Luo, Ping and Wang, Xiaogang and Tang, Xiaoou},
biburl = {https://www.bibsonomy.org/bibtex/250e4959be61db325d2f02c1d8cd7bfbb/dblp},
booktitle = {ICCV},
crossref = {conf/iccv/2015},
ee = {http://doi.ieeecomputersociety.org/10.1109/ICCV.2015.425},
interhash = {3f735aaa11957e73914bbe2ca9d5e702},
intrahash = {50e4959be61db325d2f02c1d8cd7bfbb},
isbn = {978-1-4673-8391-2},
keywords = {dblp},
pages = {3730-3738},
publisher = {IEEE Computer Society},
timestamp = {2018-10-11T11:43:28.000+0200},
title = {Deep Learning Face Attributes in the Wild.},
url = {http://dblp.uni-trier.de/db/conf/iccv/iccv2015.html#LiuLWT15},
year = 2015
}""",
)
Downloading and preparing dataset 1.38 GiB (download: 1.38 GiB, generated: 1.62 GiB, total: 3.00 GiB) to ~/tensorflow_datasets/celeb_a/2.0.1...
Dl Size...: 0 MiB [00:00, ? MiB/s] | 0/4 [00:00<?, ? url/s]
Dl Completed...: 0%| | 0/4 [00:00<?, ? url/s]
Traceback (most recent call last):
File "/media/a1/SW/python-machine-learning-book-3rd-edition/ch15/build_celeba.py", line 5, in
I have the same issue. Did you solve it? But I find this issue may help as an alternative: https://github.com/tensorflow/tensorflow/issues/41492
Unfortunately, not yet.
Look here https://github.com/rasbt/python-machine-learning-book-3rd-edition/tree/master/ch15/downloading-celeba
[https://repository-images.githubusercontent.com/190687137/70787000-14ec-11ea-84f7-6cc9843d119e]https://github.com/rasbt/python-machine-learning-book-3rd-edition/tree/master/ch15/downloading-celeba
python-machine-learning-book-3rd-edition/ch15/downloading-celeba at master · rasbt/python-machine-learning-book-3rd-edition · GitHubhttps://github.com/rasbt/python-machine-learning-book-3rd-edition/tree/master/ch15/downloading-celeba github.com The "Python Machine Learning (3rd edition)" book code repository - python-machine-learning-book-3rd-edition/ch15/downloading-celeba at master · rasbt/python-machine-learning-book-3rd-edition
may be it will help U
Regards
Felix Teplitsky RAFAEL Ltd.
From: HouyiDu @.***> Sent: Monday, March 28, 2022 0:19 To: tensorflow/datasets Cc: TEPLITSKY FELIX; Author Subject: [Marketing Mail] Re: [tensorflow/datasets] Can't download "seleb_a" (Issue #3855)
I have the same issue. Did you solve it?
— Reply to this email directly, view it on GitHubhttps://github.com/tensorflow/datasets/issues/3855#issuecomment-1080021142, or unsubscribehttps://github.com/notifications/unsubscribe-auth/AA53JPOBP6SQJ5KZYNUBTITVCDGE7ANCNFSM5RORR3KQ. You are receiving this because you authored the thread.Message ID: @.***>
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