def test_create_dataset_with_config(self, accesskey, url, config_name):
gas_client = GAS(access_key=accesskey, url=url)
try:
gas_client.get_cloud_client(config_name)
except ResourceNotExistError:
pytest.skip(f"skip this case because there's no {config_name} config")
dataset_name = get_dataset_name()
gas_client.create_dataset(dataset_name, config_name=config_name)
gas_client.get_dataset(dataset_name)
gas_client.delete_dataset(dataset_name)
def test_import_cloud_files(self, accesskey, url, config_name):
gas_client = GAS(access_key=accesskey, url=url)
try:
cloud_client = gas_client.get_cloud_client(config_name)
except ResourceNotExistError:
pytest.skip(
f"skip this case because there's no {config_name} config")
auth_data = cloud_client.list_auth_data("tests")
dataset_name = get_dataset_name()
dataset_client = gas_client.create_dataset(dataset_name,
config_name=config_name)
dataset = Dataset(name=dataset_name)
segment = dataset.create_segment("Segment1")
for data in auth_data:
segment.append(data)
dataset_client = gas_client.upload_dataset(dataset, jobs=5)
dataset_client.commit("import data")
segment1 = Segment("Segment1", client=dataset_client)
assert len(segment1) == len(segment)
assert segment1[0].path == segment[0].path.split("/")[-1]
assert not segment1[0].label
assert len(auth_data) == len(segment)
gas_client.delete_dataset(dataset_name)
def test_import_cloud_files_to_fusiondataset(self, accesskey, url, config_name):
gas_client = GAS(access_key=accesskey, url=url)
try:
cloud_client = gas_client.get_cloud_client(config_name)
except ResourceNotExistError:
pytest.skip(f"skip this case because there's no {config_name} config")
auth_data = cloud_client.list_auth_data("tests")[:5]
dataset_name = get_dataset_name()
dataset_client = gas_client.create_dataset(dataset_name, True, config_name=config_name)
dataset = FusionDataset(name=dataset_name)
segment = dataset.create_segment("Segment1")
lidar = Lidar("LIDAR")
segment.sensors.add(lidar)
for data in auth_data:
data.label.classification = Classification("cat", attributes={"color": "red"})
frame = Frame()
frame["LIDAR"] = data
segment.append(frame)
dataset_client = gas_client.upload_dataset(dataset, jobs=5)
dataset_client.commit("import data")
segment1 = FusionSegment("Segment1", client=dataset_client)
assert len(segment1) == len(segment)
assert segment1[0]["LIDAR"].path == segment[0]["LIDAR"].path.split("/")[-1]
assert segment1[0]["LIDAR"].label.classification.category == "cat"
assert segment1[0]["LIDAR"].label.classification.attributes["color"] == "red"
assert len(auth_data) == len(segment)
gas_client.delete_dataset(dataset_name)
def test_upload_frame_with_auth_data(self, accesskey, url, config_name):
gas_client = GAS(access_key=accesskey, url=url)
try:
cloud_client = gas_client.get_cloud_client(config_name)
except ResourceNotExistError:
pytest.skip(f"skip this case because there's no {config_name} config")
auth_data = cloud_client.list_auth_data("tests")[:5]
dataset_name = get_dataset_name()
dataset_client = gas_client.create_dataset(dataset_name, True, config_name=config_name)
dataset_client.create_draft("draft-1")
segment_client = dataset_client.get_or_create_segment("segment1")
segment_client.upload_sensor(Sensor.loads(LIDAR_DATA))
for index, data in enumerate(auth_data):
frame = Frame()
frame[LIDAR_DATA["name"]] = data
segment_client.upload_frame(frame, timestamp=index)
frames = segment_client.list_frames()
assert len(frames) == len(auth_data)
assert frames[0][LIDAR_DATA["name"]].path == auth_data[0].path.split("/")[-1]
gas_client.delete_dataset(dataset_name)
#!/usr/bin/env python3
#
# Copyright 2021 Graviti. Licensed under MIT License.
#
# pylint: disable=wrong-import-position
# pylint: disable=wrong-import-order
# pylint: disable=pointless-string-statement
# pylint: disable=invalid-name
"""This file includes the python code of auth cloud storage import."""
"""Get cloud client"""
from tensorbay import GAS
# Please visit `https://gas.graviti.com/tensorbay/developer` to get the AccessKey.
gas = GAS("<YOUR_ACCESSKEY>")
cloud_client = gas.get_cloud_client("<CONFIG_NAME>")
""""""
"""Create storage config"""
gas.create_oss_storage_config(
"<OSS_CONFIG_NAME>",
"<path/to/dataset>",
endpoint="<YOUR_ENDPOINT>", # like oss-cn-qingdao.aliyuncs.com
accesskey_id="<YOUR_ACCESSKEYID>",
accesskey_secret="<YOUR_ACCESSKEYSECRET>",
bucket_name="<YOUR_BUCKETNAME>",
)
""""""
"""Import dataset from cloud platform to the authorized storage dataset"""
import json
from tensorbay.dataset import Dataset
#!/usr/bin/env python3
#
# Copyright 2021 Graviti. Licensed under MIT License.
#
# pylint: disable=wrong-import-position
# pylint: disable=wrong-import-order
# pylint: disable=pointless-string-statement
# pylint: disable=invalid-name
"""This file includes the python code of auth cloud storage import."""
"""Get cloud client"""
from tensorbay import GAS
gas = GAS("Accesskey-*****")
cloud_client = gas.get_cloud_client("config_name")
""""""
"""Create storage config"""
gas.create_oss_storage_config(
"oss_config",
"tests",
endpoint="<YOUR_ENDPOINT>", # like oss-cn-qingdao.aliyuncs.com
accesskey_id="<YOUR_ACCESSKEYID>",
accesskey_secret="<YOUR_ACCESSKEYSECRET>",
bucket_name="<YOUR_BUCKETNAME>",
)
""""""
"""Import dataset from cloud platform to the authorized storage dataset"""
import json
from tensorbay.dataset import Dataset
from tensorbay.label import Classification
