Skip to main content

​
class Image

data_or_path: 'ImageDataOrPathType',
mode: 'str | None' = None,
caption: 'str | None' = None,
grouping: 'int | None' = None,
classes: 'Classes | Sequence[dict] | None' = None,
boxes: 'dict[str, BoundingBoxes2D] | dict[str, dict] | None' = None,
masks: 'dict[str, ImageMask] | dict[str, dict] | None' = None,
file_type: 'str | None' = None,
normalize: 'bool' = True

​
Description

A class for logging images to W&B.

​
Args

  • data_or_path: Accepts NumPy array/pytorch tensor of image data, a PIL image object, or a path to an image file. If a NumPy array or pytorch tensor is provided, the image data will be saved to the given file type. If the values are not in the range [0, 255] or all values are in the range [0, 1], the image pixel values will be normalized to the range [0, 255] unless normalize is set to False. - pytorch tensor should be in the format (channel, height, width) - NumPy array should be in the format (height, width, channel)
  • mode: The PIL mode for an image. Most common are “L”, “RGB”, “RGBA”.
  • caption: Label for display of image.
  • grouping: The grouping number for the image.
  • classes: A list of class information for the image, used for labeling bounding boxes, and image masks.
  • boxes: A dictionary containing bounding box information for the image.
  • masks: A dictionary containing mask information for the image.
  • file_type: The file type to save the image as. This parameter has no effect if data_or_path is a path to an image file.
  • normalize: If True, normalize the image pixel values to fall within the range of [0, 255]. Normalize is only applied if data_or_path is a numpy array or pytorch tensor.

​
Properties

​
property image