SegmentationAnnotation¶
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class
scenebox.models.annotation.SegmentationAnnotation(labels, mask_colors, mask_urls=None, mask_uris=None, mask_file_paths=None, mask_ids=None, mask_types=None, confidences=None, attributes_list=None, **kwargs)¶ Create a Segmentation annotation.
Mask segments are automatically extracted from the provided mask images (each containing colored segments) supplied in mask_url/uri/file_paths. Mask attributes are interpreted in the order passed (the first label listed in``labels`` is associated with the first mask color listed in
mask_colors, etc.)- Parameters:
labels – Names of each of the segmented regions.
mask_colors – Colors of the segmented regions. Colors must be represented in hex format.
mask_urls – URLs of the mask images. Each mask must contain its associated color listed in mask_colors.
mask_uris – URIs of the mask images. Each mask must contain its associated color listed in mask_colors.
mask_file_paths – Filepaths of the mask images. Each mask must contain its associated color listed in mask_colors.
mask_ids – IDs to give to the generated masks.
mask_types – Denotes the mask image color scheme. There are two accepted mask color schemes: “MultiColor”, or “SingleColor”. A “MultiColor” mask image may contain several colors (but must include its respective mask_colors color - these areas denote the mask region). A “SingleColor” mask only contains transparent and white colors (White areas denote the mask region). All entries of this list must be either “Multicolor” or “SingleColor”.
confidences – Labelling confidence. Must be between 0 and 1.
attributes_list – List of attributes
**kwargs – Additional annotation attributes. The keyword arguments are passed to
scenebox.models.annotation.
Methods
return a dictionary object representative of Annotation :return: dictionary object
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to_dic()¶ return a dictionary object representative of Annotation :return: dictionary object