def download(self, cloud_path):
"""Download cityscapes dataset
Note:
The current implementation assumes a GCS cloud path.
Should we keep this method here if we want to support other cloud
storage system?
Args:
cloud_path (str): cloud path of the dataset
"""
path = Path(self.root)
path.mkdir(parents=True, exist_ok=True)
for zipfile in ZIPFILES:
localfile = os.path.join(self.root, zipfile)
if os.path.isfile(localfile):
# TODO: Check file hash to verify file integrity
logger.debug(f"File {localfile} exists. Skip download.")
continue
client = GCSClient()
object_key = os.path.join(CITYSCAPES_GCS_PATH, zipfile)
logger.debug(
f"Downloading file {localfile} from gs://{const.GCS_BUCKET}/"
f"{object_key}")
client.download(const.GCS_BUCKET, object_key, localfile)
def __init__(self, cloud_path, prefix, *, suffix=DEFAULT_SUFFIX):
self._tempdir = tempfile.TemporaryDirectory().name
self._client = GCSClient()
self.cloud_path = cloud_path
self._writer = LocalEstimatorWriter(self._tempdir,
prefix,
create_dir=True,
suffix=suffix)
def test_MD5_hex():
mocked_gcs_client = MagicMock()
with patch(
"datasetinsights.io.gcs.Client",
MagicMock(return_value=mocked_gcs_client),
):
client = GCSClient()
actual_result = client._md5_hex(md5_hash)
expected_result = "69b7"
assert actual_result == expected_result
def test_gcs_client_download_folder_url(mock_download_folder, mock_is_file):
mocked_gcs_client = MagicMock()
mock_is_file.return_value = False
with patch(
"datasetinsights.io.gcs.Client",
MagicMock(return_value=mocked_gcs_client),
):
client = GCSClient()
client.download(local_path=local_path, url=base_url)
mock_download_folder.assert_called_with(mocked_gcs_client.get_bucket(),
base_key, local_path)
def download(self, cloud_path):
"""Download nyu_v2 dataset
The directory structure of the downloaded data is
|--self.root
|--nyudepth
|--nyu_data.zip
|--data
|--nyu2_test.csv
|--nyu2_test
|--00000_colors.png
|--00000_depth.png ...
|--01448_colors.png
|--01448_depth.png
|--nyu2_train.csv
|--nyu2_train
|--basement_0001a_out
|--1.jpg
|--1.png ...
|--281.jpg
|--281.png
...
|--study_room_0005b_out
|--1.jpg
|--1.png ...
|--133.jpg
|--133.png
Args:
cloud_path (str): cloud path of the dataset
"""
zip_file = os.path.join(self.root, ZIPFILE)
unzip_dir = os.path.join(self.root, UNZIP_NAME)
if os.path.isfile(zip_file):
logger.debug(f"File {zip_file} exists. Skip download.")
else:
client = GCSClient()
object_key = os.path.join(NYU_GCS_PATH, ZIPFILE)
logger.debug(
f"Downloading file {zip_file} from gs://{const.GCS_BUCKET}/"
f"{object_key}")
client.download(
local_path=self.root,
bucket=const.GCS_BUCKET,
key=object_key,
)
if os.path.isdir(unzip_dir):
logger.debug(f"File {unzip_dir} exists. Skip unzip.")
else:
# unzip the file
with ZipFile(zip_file, "r") as zip_ref:
zip_ref.extractall(self.root)
logger.debug(f"Unzip file from {zip_file}")
def test_download_validate(mock_checksum, mock_download_blob):
mocked_gcs_client = MagicMock()
with patch(
"datasetinsights.io.gcs.Client",
MagicMock(return_value=mocked_gcs_client),
):
client = GCSClient()
mocked_blob = MagicMock()
client._download_validate(mocked_blob, local_path)
mock_checksum.assert_called_with(mocked_blob, local_path)
mock_download_blob.assert_called_with(mocked_blob, local_path)
def test_download_folder(mock_download_validate):
object_key = "path/to" + file_name
mocked_gcs_client = MagicMock()
with patch(
"datasetinsights.io.gcs.Client",
MagicMock(return_value=mocked_gcs_client),
):
client = GCSClient()
mocked_blob = MagicMock()
mocked_bucket = MagicMock()
mocked_bucket.list_blobs = MagicMock(return_value=[mocked_blob])
mocked_blob.name = object_key
client._download_folder(mocked_bucket, object_key, local_path)
mock_download_validate.assert_called_with(mocked_blob, local_path)
def test_gcs_client_download_file_bucket_key(mock_download_file, mock_is_file):
mocked_gcs_client = MagicMock()
mock_is_file.return_value = True
object_key = base_key + file_name
with patch(
"datasetinsights.io.gcs.Client",
MagicMock(return_value=mocked_gcs_client),
):
client = GCSClient()
client.download(local_path=local_path,
bucket=bucket_name,
key=object_key)
mock_download_file.assert_called_with(mocked_gcs_client.get_bucket(),
object_key, local_path)
def test_gcs_client_upload_file_bucket_key(mock_isdir, mock_upload_file):
localfile = local_path + file_name
mocked_gcs_client = MagicMock()
mock_isdir.return_value = False
with patch(
"datasetinsights.io.gcs.Client",
MagicMock(return_value=mocked_gcs_client),
):
client = GCSClient()
client.upload(local_path=localfile, bucket=bucket_name, key=base_key)
mock_upload_file.assert_called_with(
bucket=mocked_gcs_client.get_bucket(),
key=base_key,
local_path=localfile,
)
def load_from_gcs(estimator, full_cloud_path):
"""Load estimator from checkpoint files on GCS.
Args:
estimator (datasetinsights.estimators.Estimator):
datasetinsights estimator object.
full_cloud_path: full path to the checkpoint file
"""
filename = os.path.basename(full_cloud_path)
with tempfile.TemporaryDirectory() as temp_dir:
path = os.path.join(temp_dir, filename)
logger.debug(f"Downloading estimator from {full_cloud_path} to {path}")
client = GCSClient()
client.download(local_path=temp_dir, url=full_cloud_path)
estimator.load(path)
def download(self, version="v1.0-mini"):
"""
download the nuscenes dataset version specified to /data/sets/nuscenes
"""
self.cloud_client = GCSClient()
if version == "v1.0-mini":
return self._download_mini()
elif version == "v1.0-trainval":
meta_local_path, trainval_tars = self._download_trainval_tars()
with tarfile.open(meta_local_path) as t:
t.extractall(self.root)
first_data_blob = trainval_tars[0]
with tarfile.open(first_data_blob) as t:
logger.info(f"extracting files from {first_data_blob}")
t.extractall(self.root)
os.remove(trainval_tars[0])
for tar_path in trainval_tars[1:]:
with tarfile.open(tar_path) as t:
logger.info(f"extracting files from {tar_path}")
with tempfile.TemporaryDirectory() as tmpdirname:
t.extractall(tmpdirname)
self._merge_data_blobs(blob=tmpdirname,
canonical_dir=self.root)
return self.root
else:
raise ValueError()
def download(self, cloud_path=KITTI_GCS_PATH):
logger.info(f"downloading kitti dataset from cloud storage")
# todo is currently only downloading left color images
cloud_client = GCSClient()
self._download_sample_indices_file(cloud_client=cloud_client)
calib_zip, left_images_zip, labels_zip = self.download_kitti_zips(
cloud_client=cloud_client)
with zipfile.ZipFile(left_images_zip, "r") as zip_ref:
zip_ref.extractall(self.root)
testing_dir = os.path.join(self.root, "testing")
training_dir = os.path.join(self.root, "training")
self._unzip2dir(
zip_path=calib_zip,
src=os.path.join("testing", "calib"),
dst=os.path.join(testing_dir, "calib"),
)
self._unzip2dir(
zip_path=calib_zip,
src=os.path.join("training", "calib"),
dst=os.path.join(training_dir, "calib"),
)
self._unzip2dir(
zip_path=labels_zip,
src=os.path.join("training", "label_2"),
dst=os.path.join(training_dir, "label_2"),
)
def test_is_file():
object_key = base_key + file_name
mocked_gcs_client = MagicMock()
with patch(
"datasetinsights.io.gcs.Client",
MagicMock(return_value=mocked_gcs_client),
):
client = GCSClient()
mocked_bucket = MagicMock()
mocked_blob = MagicMock()
mocked_bucket.get_blob = MagicMock(return_value=mocked_blob)
mocked_blob.name = object_key
actual_result = client._is_file(mocked_bucket, object_key)
mocked_bucket.get_blob.assert_called_with(object_key)
expected_result = True
assert actual_result == expected_result
def test_download_file(mock_download_validate):
object_key = base_key + file_name
mocked_gcs_client = MagicMock()
with patch(
"datasetinsights.io.gcs.Client",
MagicMock(return_value=mocked_gcs_client),
):
client = GCSClient()
mocked_bucket = MagicMock()
mocked_blob = MagicMock()
mocked_bucket.get_blob = MagicMock(return_value=mocked_blob)
mocked_blob.name = object_key
client._download_file(mocked_bucket, object_key, local_path)
mocked_bucket.get_blob.assert_called_with(object_key)
mock_download_validate.assert_called_with(mocked_blob,
local_path + file_name)
def test_download_blob(mock_isdir):
mocked_gcs_client = MagicMock()
with patch(
"datasetinsights.io.gcs.Client",
MagicMock(return_value=mocked_gcs_client),
):
mock_isdir.return_value = True
object_key = base_key + file_name
client = GCSClient()
mocked_blob = MagicMock()
mocked_blob.name = object_key
mocked_download_blob = MagicMock()
mocked_blob.download_to_filename = mocked_download_blob
client._download_blob(mocked_blob, local_path)
mocked_blob.download_to_filename.assert_called_with(local_path)
def test_gcs_parse():
mocked_gcs_client = MagicMock()
with patch(
"datasetinsights.io.gcs.Client",
MagicMock(return_value=mocked_gcs_client),
):
client = GCSClient()
th_bucket = "some_bucket_name"
th_path = "some/cloud/path"
url = "gs://some_bucket_name/some/cloud/path"
bucket, path = client._parse(url)
assert (bucket, path) == (th_bucket, th_path)
bad_url = "s3://path/to/bad/url"
with pytest.raises(ValueError, match=r"Specified destination prefix:"):
client._parse(bad_url)
def test_upload_file():
localfile = local_path + file_name
mocked_gcs_client = MagicMock()
with patch(
"datasetinsights.io.gcs.Client",
MagicMock(return_value=mocked_gcs_client),
):
client = GCSClient()
mocked_bucket = MagicMock()
mocked_blob = MagicMock()
mocked_gcs_client.get_bucket = MagicMock(return_value=mocked_bucket)
mocked_bucket.blob = MagicMock(return_value=mocked_blob)
mocked_blob.upload_from_filename = MagicMock()
client._upload_file(local_path=localfile,
bucket=mocked_bucket,
key=base_key)
mocked_blob.upload_from_filename.assert_called_with(localfile)
def test_checksum(mock_checksum, mock_md5_hex):
local_file_path = local_path + file_name
mocked_gcs_client = MagicMock()
mock_md5_hex.return_value = md5_hash_hex
with patch(
"datasetinsights.io.gcs.Client",
MagicMock(return_value=mocked_gcs_client),
):
client = GCSClient()
mocked_bucket = MagicMock()
mocked_blob = MagicMock()
mocked_gcs_client.get_bucket = MagicMock(return_value=mocked_bucket)
mocked_bucket.get_blob = MagicMock(return_value=mocked_blob)
mocked_blob.md5_hash = md5_hash
client._checksum(mocked_blob, local_file_path)
mock_checksum.assert_called_with(local_file_path,
md5_hash_hex,
algorithm="MD5")
class GCSDatasetDownloader(DatasetDownloader, protocol="gs://"):
""" This class is used to download data from GCS
"""
def __init__(self, **kwargs):
""" initiating GCSDownloader
"""
self.client = GCSClient()
def download(self, source_uri=None, output=None, **kwargs):
"""
Args:
source_uri: This is the downloader-uri that indicates where on
GCS the dataset should be downloaded from.
The expected source-uri follows these patterns
gs://bucket/folder or gs://bucket/folder/data.zip
output: This is the path to the directory
where the download will store the dataset.
"""
self.client.download(local_path=output, url=source_uri)
class GCSEstimatorWriter:
"""Writes (saves) estimator checkpoints on GCS.
Args:
cloud_path (str): GCS cloud path (e.g. gs://bucket/path/to/directoy)
prefix (str): filename prefix of the checkpoint files
suffix (str): filename suffix of the checkpoint files
"""
def __init__(self, cloud_path, prefix, *, suffix=DEFAULT_SUFFIX):
self._tempdir = tempfile.TemporaryDirectory().name
self._client = GCSClient()
self._bucket, self._gcs_path = gcs_bucket_and_path(cloud_path)
self._writer = LocalEstimatorWriter(self._tempdir,
prefix,
create_dir=True,
suffix=suffix)
def save(self, estimator, epoch=None):
"""Save estimator to checkpoint files on GCS.
Args:
estimator (datasetinsights.estimators.Estimator):
datasetinsights estimator object.
epoch (int): the current epoch number. Default: None
Returns:
Full GCS cloud path to the saved checkpoint file.
"""
path = self._writer.save(estimator, epoch)
filename = os.path.basename(path)
object_key = os.path.join(self._gcs_path, filename)
full_cloud_path = f"gs://{self._bucket}/{object_key}"
logger.debug(f"Copying estimator from {path} to {full_cloud_path}")
self._client.upload(path, self._bucket, object_key)
return full_cloud_path
def download(self, cloud_path=COCO_GCS_PATH):
path = Path(self.root)
path.mkdir(parents=True, exist_ok=True)
client = GCSClient()
annotations_zip_gcs = f"{cloud_path}/annotations_trainval2017.zip"
annotations_zip_2017 = self._get_local_annotations_zip()
logger.info(f"checking for local copy of data")
if not os.path.exists(annotations_zip_2017):
logger.info(f"no annotations zip file found, will download.")
client.download(
bucket_name=const.GCS_BUCKET,
object_key=annotations_zip_gcs,
localfile=annotations_zip_2017,
)
with zipfile.ZipFile(annotations_zip_2017, "r") as zip_dir:
zip_dir.extractall(self.root)
images_local = self._get_local_images_zip()
images_gcs = f"{cloud_path}/{self.split}2017.zip"
if not os.path.exists(images_local):
logger.info(f"no zip file for images for {self.split} found,"
f" will download")
client.download(
bucket_name=const.GCS_BUCKET,
object_key=images_gcs,
localfile=images_local,
)
with zipfile.ZipFile(images_local, "r") as zip_dir:
zip_dir.extractall(self.root)
def test_gcs_client_warpper():
bucket_name = "fake_bucket"
object_key = "path/to/object"
localfile = "path/to/local/file"
mocked_gcs_client = MagicMock()
with patch(
"datasetinsights.io.gcs.Client",
MagicMock(return_value=mocked_gcs_client),
):
client = GCSClient()
mocked_bucket = MagicMock()
mocked_blob = MagicMock()
mocked_gcs_client.get_bucket = MagicMock(return_value=mocked_bucket)
mocked_bucket.blob = MagicMock(return_value=mocked_blob)
mocked_blob.download_to_filename = MagicMock()
client.download(bucket_name, object_key, localfile)
mocked_gcs_client.get_bucket.assert_called_with(bucket_name)
mocked_bucket.blob.assert_called_with(object_key)
mocked_blob.download_to_filename.assert_called_with(localfile)
mocked_blob.upload_from_filename = MagicMock()
client.upload(localfile, bucket_name, object_key)
mocked_blob.upload_from_filename.assert_called_with(localfile)
def download(self):
"""Download dataset from GCS
"""
cloud_path = f"gs://{const.GCS_BUCKET}/{self.GCS_PATH}"
client = GCSClient()
# download label file
label_zip = self.LABEL_ZIP
client.download(url=cloud_path, local_path=self.root)
with zipfile.ZipFile(label_zip, "r") as zip_dir:
zip_dir.extractall(self.root)
# download tfexamples for a dataset split
tfexamples_zip = self.SPLITS_ZIP.get(self.split)
client.download(url=cloud_path, local_path=self.root)
with zipfile.ZipFile(tfexamples_zip, "r") as zip_dir:
zip_dir.extractall(self.root)
def test_checksum_error(mock_checksum, mock_remove):
local_file_path = local_path + file_name
mocked_gcs_client = MagicMock()
with patch(
"datasetinsights.io.gcs.Client",
MagicMock(return_value=mocked_gcs_client),
):
client = GCSClient()
mocked_bucket = MagicMock()
mocked_blob = MagicMock()
mocked_gcs_client.get_bucket = MagicMock(return_value=mocked_bucket)
mocked_bucket.get_blob = MagicMock(return_value=mocked_blob)
mocked_blob.md5_hash = md5_hash
client._MD5_hex = MagicMock(return_value=md5_hash_hex)
client._checksum(mocked_blob, local_file_path)
mock_checksum.side_effect = ChecksumError
with pytest.raises(ChecksumError):
client._checksum(mocked_blob, local_file_path)
mock_remove.assert_called_once()
def __init__(self, **kwargs):
""" initiating GCSDownloader
"""
self.client = GCSClient()