TensorBay Python SDK is a python library to access TensorBay
and manage your datasets.
It provides:
- A pythonic way to access your TensorBay resources by TensorBay OpenAPI.
- An easy-to-use CLI tool
gas(Graviti AI service) to communicate with TensorBay. - A consistent dataset format to read and write your datasets.
pip3 install tensorbayMore information can be found on the documentation site
An AccessKey is needed to communicate with TensorBay. Please visit this page to get an AccessKey first.
from tensorbay import GAS
gas = GAS("<YOUR_ACCESSKEY>")gas.create_dataset("DatasetName")# Method "list_dataset_names()" returns an iterator, use "list()" to transfer it to a "list".
dataset_list = list(gas.list_dataset_names())from tensorbay.dataset import Data, Dataset
# Organize the local dataset by the "Dataset" class before uploading.
dataset = Dataset("DatasetName")
# TensorBay uses "segment" to separate different parts in a dataset.
segment = dataset.create_segment()
segment.append(Data("0000001.jpg"))
segment.append(Data("0000002.jpg"))
dataset_client = gas.upload_dataset(dataset)
# TensorBay provides dataset version control feature, commit the uploaded data before using it.
dataset_client.commit("Initial commit")from PIL import Image
from tensorbay.dataset import Segment
dataset_client = gas.get_dataset("DatasetName")
segment = Segment("", dataset_client)
for data in segment:
with data.open() as fp:
image = Image.open(fp)
width, height = image.size
image.show()gas.delete_dataset("DatasetName")