def test_create_local_storage_config(self, accesskey, url):
gas_client = GAS(access_key=accesskey, url=url)
local_storage_name = "local_storage_config"
local_storage = {
"name": local_storage_name,
"file_path": "file_path/",
"endpoint": "http://192.168.0.1:9000",
}
gas_client.create_local_storage_config(**local_storage)
gas_client.delete_storage_config(local_storage_name)
from tensorbay.dataset import Dataset
from tensorbay.label import Classification
# Use AuthData to organize a dataset by the "Dataset" class before importing.
dataset = Dataset("<DATASET_NAME>")
# 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 label.open() as fp:
auth_data.label.classification = Classification.loads(json.load(fp))
segment.append(auth_data)
dataset_client = gas.upload_dataset(dataset, jobs=8)
""""""
"""Create local storage config"""
gas.create_local_storage_config(
name="<LOCAL_STORAGE_CONFIG>",
file_path="<path/to/dataset>",
endpoint="<external IP address of the local storage service>",
)
""""""
"""Create authorized local storage dataset"""
dataset_client = gas.create_dataset("<DATASET_NAME>",
config_name="<LOCAL_STORAGE_CONFIG>")
""""""
