tfa.image.connected_components

Labels the connected components in a batch of images.

@tf.function
tfa.image.connected_components(
    images: tfa.types.TensorLike,
    name: Optional[Text] = None
) -> tf.Tensor

A component is a set of pixels in a single input image, which are all adjacent and all have the same non-zero value. The components using a squared connectivity of one (all equal entries are joined with their neighbors above,below, left, and right). Components across all images have consecutive ids 1 through n. Components are labeled according to the first pixel of the component appearing in row-major order (lexicographic order by image_index_in_batch, row, col). Zero entries all have an output id of 0. This op is equivalent with scipy.ndimage.measurements.label on a 2D array with the default structuring element (which is the connectivity used here).

images A 2D (H, W) or 3D (N, H, W) Tensor of image (integer, floating point and boolean types are supported).
name The name of the op.

Components with the same shape as images. entries that evaluate to False (e.g. 0/0.0f, False) in images have value 0, and all other entries map to a component id > 0.

TypeError if images is not 2D or 3D.