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