tensorflow_graphics.datasets.modelnet40

[taiya]

Security certificate on the Stanford side is expired, so auto-download of resources fails.

Major hack to get it working in the meantime:

1. download https://shapenet.cs.stanford.edu/media/modelnet40_ply_hdf5_2048.zip manually
2. in the download folder, start a server with python3 -m http.server 8080
3. modify _URL in tensorflow_graphics/datasets/modelnet40/modelnet40.pyto be _URL = 'http://localhost:8080/modelnet40_ply_hdf5_2048.zip'
4. allow dataset to be built by executing

from tensorflow_graphics.datasets.modelnet40 import ModelNet40
ds_train, info = ModelNet40.load(split='train', with_info=True)

5. after this, ensure you do not re-download:

data_dir = '~/tensorflow_datasets'
ds_train, info = ModelNet40.load(split='train', with_info=True, data_dir=data_dir, download=False)

[jackd]

Pretty sure this can be resolved using tfds.download.DownloadConfig with verify_ssl=False.

[taiya]

If the error message would have told me that, I would have saved 1h of my time :) Just left a trace for others that might run into this.

@Conchylicultor perhaps that's something to consider?

In any case, we need to contact the Stanford folks and get this fixed. That's the primary reason for opening the bug.

[ma7555]

@jackd

Trying with the below code still throws SSL error

from tensorflow_graphics.datasets.modelnet40 import ModelNet40
import tensorflow_datasets as tfds
dl_config = tfds.download.DownloadConfig()
dl_config.verify_ssl = False
dataset = ModelNet40()
dataset.download_and_prepare(download_config=dl_config)

This throws SSL error too

dataset.load(split='train',  download_and_prepare_kwargs={'download_config': dl_config})

Also

tfds.download.DownloadConfig(verify_ssl = False)

throws an unexpected argument error

EDIT: my bad, was using an older version of TFDS. With v4.5.2 the below code works

import tensorflow_datasets as tfds
from tensorflow_graphics.datasets.modelnet40 import ModelNet40
dl_config = tfds.download.DownloadConfig(verify_ssl=False)
dataset = ModelNet40()
train_ds = dataset.load(split = 'train', download_and_prepare_kwargs={'download_config': dl_config}, with_info=True)