The zpy client enables you to generate and download synthetic datasets.
This API is in early access. If you're interested in using it, email us at firstname.lastname@example.org.
Quick start guide
You can install
zpy with pip:
pip install zpy-zumo
Generating your first dataset
# Make sure you're using the latest version of the zpy library: # pip install zpy-zumo --upgrade import zpy.client as zpy # We'll provide your project id during on-boarding project_uuid="..." # This is your temporary auth token. It can be found by visiting: # https://app.zumolabs.ai/settings/auth-token # # The auth token will expire when you log out of the web app auth_token="..." zpy.init(project_uuid=project_uuid, auth_token=auth_token) # The simulation (sim) is the packaged version of the blender assets and # generations script. # # We'll give you the sim for your specific project and share new sim names when we # create new versions. sim_name = "demo_sim_v1" # A DatasetConfig defines what synthetic data you want generated. # # For now, there are no parameters to configure. But in the future, this will include # sim specific parameters like: changing the cropping style or selecting which classes # should be included in a dataset. dataset_config = zpy.DatasetConfig(sim_name) # The generate call will cause our backend to actually generate a dataset. # # There are a few known issues: # * Takes ~5 minutes to provision and spin up machines for larger generation jobs >200 # images # * Each dataset needs a unique name, e.g. 'dataset.01'. In the future, we may remove # the concept of dataset names. Instead datasets will only be specified by their # config. # * Calls to `generate` for a config that has already been generated take longer than # they should. In the future, if the data has already been generated it will start # downloading immediately. zpy.generate('dataset.01', dataset_config, num_datapoints=50, materialize=True)