Cloud Storage

All data on TensorBay are hosted on cloud.
TensorBay supports two cloud storage modes:
  • DEFAULT CLOUD STORAGE: data are stored on TensorBay cloud

  • AUTHORIZED CLOUD STORAGE: data are stored on other providers’ cloud

Default Cloud Storage

In default cloud storage mode, data are stored on TensorBay cloud.
Create a dataset with default storage:

Authorized Cloud Storage

You can also upload data to your public cloud storage space.
Now TensorBay support following cloud providers:
  • Aliyun OSS

  • Amazon S3

  • Azure Blob


See cloud storage instruction for details about how to configure cloud storage on TensorBay.

TensorBay SDK supports following methods to configure cloud storage.

For example:

    endpoint="<YOUR_ENDPOINT>",  # like

TensorBay SDK supports a method to list a user’s all previous configurations.


Create Authorized Storage Dataset

Create a dataset with authorized cloud storage:

dataset_client = gas.create_dataset("dataset_name", config_name="config_name")

Import Cloud Files into Authorized Storage Dataset

Take the following cloud directory as an example:

├── images/
│   ├── 00001.png
│   ├── 00002.png
│   └── ...
├── labels/
│   ├── 00001.json
│   ├── 00002.json
│   └── ...
└── ...

Get a cloud client.

from tensorbay import GAS

gas = GAS("Accesskey-*****")
cloud_client = gas.get_cloud_client("config_name")

Import the AuthData from cloud platform and load label file to an authorized storage dataset.

import json

from tensorbay.dataset import Dataset
from tensorbay.label import Classification

# Use AuthData to organize a dataset by the "Dataset" class before importing.
dataset = Dataset("DatasetName")

# TensorBay uses "segment" to separate different parts in a dataset.
segment = dataset.create_segment()

images = cloud_client.list_auth_data("data/images/")
labels = cloud_client.list_auth_data("data/labels/")

for auth_data, label in zip(images, labels):
    with as fp:
        auth_data.label.classification = Classification.loads(json.load(fp))

dataset_client = gas.upload_dataset(dataset, jobs=8)


Files will be copied from raw directory to the authorized cloud storage dataset path, thus the storage space will be doubled on the cloud platform.