anatools 1.0.1

Tools for development with the Rendered.AI Ana Platform.

AnaTools

Project Description

Anatools is a python package with modules for developing with the Ana Platform from Rendered.AI. With AnaTools you can generate and access synthetic datasets, and much more!

>>> import anatools
>>> ana = anatools.AnaClient()
'Enter your credentials for Ana.'
'email:' [e-mail]
'password:' ***************
'Signed into Ana with [e-mail], using workspace 123456789.'
>>> ana.get_channels()
['mychannel1', 'mychannel2']
>>> graphs = ana.get_graphs()
>>> datasets = ana.get_datasets()

Install the AnaTools Package

(Optional) Create a new Conda Environment

1. Install conda for your operating system: https://www.anaconda.com/products/individual.
2. Create a new conda environment and activate it.
3. Install anatools from the Python Package Index.

$ conda create -n renderedai python=3.7
$ conda activate renderedai

Install AnaTools to the Python Environment

1. Install AnaTools from the Python Package Index.

$ pip install anatools

Dependencies

The anatools package requires python 3.6 or higher and has dependencies on the following packages:

Package	Description
pyrebase	A python wrapper for Google Firebase API.
keyring	A python library for storing and accessing passwords securely.

If you have any questions or comments, contact Rendered.AI at [e-mail].

Quickstart Guide

What is Ana?

Ana is a synthetic dataset generation tool where graphs describe what and how synthetic datasets are generated.

Terms	Definitions
workspace	A workspace is a collection of data used for a particular use-case, for example workspaces can be used to organize data for different projects.
dataset	A dataset is a collection of data, for many use-cases these are images with text-based annotation files.
graph	A graph is defined by nodes and links, it describes the what and the how a dataset is generated.
node	A node can be described as an executable block of code, it has inputs and runs some algorithm to generate outputs.
link	A link is used to transfer data from the output of one node, to the input of other nodes.
channel	A channel is a collection of nodes, it is used to limit the scope of what is possible to generate in a dataset (like content from a tv channel).

How do you use Ana?

Ana creates synthetic datasets by processing a graph, so we will need to create our Ana client, create a graph, then create a dataset.

1. Create a client and login to Ana. In this example we are instantiating a client with no workspace or environment variables, so it is setting our default workspace. To access the tool, you will need to use your email and password for https://deckard.rendered.ai.

>>> from anatools import AnaClient
>>> ana = anatools.AnaClient()
'Enter your credentials for Ana.'
'email:' [e-mail]
'password:' ***************
'Signed into Ana with [e-mail], using workspace 123456789.'

2. Define a graph. We are defining a simplistic graph for this example with a camera and sphere. Graphs are usually stored in json or yaml format, but read into a python dictionary to be passed to the API.

nodes:

  Sphere:
    class: Sphere
    inputs:
      Size: 1

  SphereLocation:
    class: SetObjectLocation
    inputs:
      Object: {$link: [Sphere, Object]}
      Location: [0,0,0]

  Camera:
    class: Camera
    inputs:
      Resolution: [1920,1080]
      FOV: 29.0

  CameraLocation:
    class: SetObjectLocation
    inputs:
      Object: {$link: [Camera, Object]}
      Location: [0,0,0]

  Render:
    class: Render
    inputs:
      Camera: {$link: [CameraLocation, Object]}
      Scene: {$link: [SphereLocation, Object]}

3. Create a graph using the client. To creat new graph, we load the graph defined above into a python dictionary using the yaml python package. Then we create a graph using the client, this graph is being name 'testgraph' and is using the 'channelA' channel. The client will return a graphid so we can reference this graph later.

>>> import yaml
>>> with open('graph.yml') as graphfile:
>>>     graph = yaml.load(graphfile)
>>> graphid = ana.create_graph(name='testgraph',channel='channelA',graph=graph)
>>> graphid
'e175a44e-23a5-11eb-adc1-0242ac120002'

4. Create a dataset using the client. Using the graphid, we can create a new job to generate a dataset.

The client will return a datasetid that can be used for reference later.

>>> datasetid = ana.create_dataset(name='testdataset',interpretations=10,description='A simple dataset with a sphere.')
>>> datasetid
'ce66e81c-23a6-11eb-adc1-0242ac120002 '

Data Structure

graph TD
  id1[(Workspace)] --> id3[(Graphs)];
  id1[(Workspace)] --> id4[(Datasets)];