VisionData#
- class VisionData[source]#
VisionData is the base data object of deepcheck vision used as input to checks and suites.
- Parameters
- batch_loader
A batch_loader which load a batch of data in an iterative manner. Batch loader batch output must be a dictionary in BatchOutputFormat format. The batch loader must provide SHUFFLED batches.
- task_typestr
The task type of the data. can be one of the following: ‘classification’, ‘semantic_segmentation’, ‘object_detection’, ‘other’. For ‘other’, only image related checks (such as ImagePropertyOutliers) will be run.
- label_mapDict[int, str], optional
A dictionary mapping class ids to their names.
- dataset_name: str, optional
Name of the dataset to use in the displays instead of “Train” or “Test”.
- reshuffle_data: bool, default=True
If True we will attempt to shuffle the batch loader. Only set this to False if the data is already shuffled.
- __init__(batch_loader, task_type: typing_extensions.Literal[classification, object_detection, semantic_segmentation, other], label_map: Optional[Dict[int, str]] = None, dataset_name: Optional[str] = None, reshuffle_data: bool = True)[source]#
- __new__(*args, **kwargs)#
Attributes
Return the batch loader used be the vision data. |
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Return True if the batch loader contains additional_data. |
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Return True if the batch loader contains embeddings. |
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Return True if the batch loader contains image identifiers. |
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Return True if the batch loader contains images. |
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Return True if the batch loader contains labels. |
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Return True if the batch loader contains predictions. |
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Return a number of possible classes based on model proba, label map or observed classes. |
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Return True if the number of images processed and whose statistics were cached. |
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Return True if the batch loader contains labels. |
Methods
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Create new copy of the vision data object with clean cache. |
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Return a dictionary of stored cache. |
Return a dictionary of observed classes either as class ids or as the class names. |
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Show data from a single batch of this VisionData. |
Initialize the cache. |
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Update cache based on newly arrived batch. |
Validate the VisionData functionalities implemented by the user and set which formatters were implemented. |