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).

Args
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.

Returns
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.

Raises
TypeError	if images is not 2D or 3D.