CORe50

Core50 is a dataset proposed in “CORe50: a new Dataset and Benchmark for Continuous Object Recognition”. This dataset proposed small videos of of 50 objects from 10 differents classes with 11 background environments (more info in core50 doc ). This dataset was originally created to propose various continual learning settings. 3 background environments are allocated for test and the remaining for training.

Continuum Scenarios

You can create automatically scenarios with continuum by setting the scenario and classification parameter in Core50 dataset. It will provide different types of annotation for targets and tasks. For classification, you can choose to use category (10 classes) annotation or object annotation (50 classes)> For the task ids, you can choose among “classes”, “domains” and “objects” how the task labels will be affected to data.

• Class Incremental

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We can create a simple class incremental setting.

from continuum.datasets import COre50
# Same as :
# dataset=Core50("/your/path", scenario="classes", classification="object", train=True)
dataset = Core50("/your/path", train=True)
# 5 tasks with 10 classes each
scenario = ClassIncremental(dataset, nb_tasks=5)

• Instance Incremental

from continuum.datasets import COre50
dataset = Core50("/your/path", scenario="domains", classification="category", train=True)
# 8 tasks in 1 environment each with 10 classes
scenario = ContinualScenario(dataset, nb_tasks=5)

– Object incremental Scenario – .. code-block:: python

from continuum.datasets import COre50 dataset = Core50(“/your/path”, scenario=”objects”, classification=”object”, train=True) # 50 tasks with 1 object videos in the 8 training environments # classes are object ids (50 classes then) scenario = ContinualScenario(dataset)

• Classes and Instances Incremental

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Class and Instances Incremental scenarios are proposed in the scenario from the original paper (next section).

from continuum.datasets import COre50
dataset = Core50("/your/path", scenario="objects", classification="category", train=True)
# 50 tasks with 1 object videos in the 8 training environments
# classes are object ids (10 classes then), new tasks might contains new label or known label
scenario = ContinualScenario(dataset)

Original scenarios:

CORe50 provides domain ids which are automatically picked up by the InstanceIncremental scenario:

from continuum import InstanceIncremental
from continuum.datasets import Core50v2_79, Core50v2_196, Core50v2_391

scenario_79 = InstanceIncremental(dataset=Core50v2_79("/my/path"))
scenario_196 = InstanceIncremental(dataset=Core50v2_196("/my/path"))
scenario_391 = InstanceIncremental(dataset=Core50v2_391("/my/path"))

The three available version of CORe50 have respectively 79, 196, and 391 tasks. Each task may bring new classes AND new instances of past classes, akin to the NIC scenario.