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tfa.image.connected_components
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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.
|
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Last updated 2023-05-25 UTC.
[null,null,["Last updated 2023-05-25 UTC."],[],[],null,["# tfa.image.connected_components\n\n\u003cbr /\u003e\n\n|-------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/addons/blob/v0.20.0/tensorflow_addons/image/connected_components.py#L27-L100) |\n\nLabels the connected components in a batch of images. \n\n @tf.function\n tfa.image.connected_components(\n images: ../../tfa/types/TensorLike,\n name: Optional[Text] = None\n ) -\u003e tf.Tensor\n\nA component is a set of pixels in a single input image, which are\nall adjacent and all have the same non-zero value. The components\nusing a squared connectivity of one (all equal entries are joined with\ntheir neighbors above,below, left, and right). Components across all\nimages have consecutive ids 1 through n.\nComponents are labeled according to the first pixel of the\ncomponent appearing in row-major order (lexicographic order by\nimage_index_in_batch, row, col).\nZero entries all have an output id of 0.\nThis op is equivalent with `scipy.ndimage.measurements.label`\non a 2D array with the default structuring element\n(which is the connectivity used here).\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------|----------------------------------------------------------------------------------------------------------|\n| `images` | A 2D (H, W) or 3D (N, H, W) `Tensor` of image (integer, floating point and boolean types are supported). |\n| `name` | The name of the op. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| 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 \\\u003e 0. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|-------------|------------------------------|\n| `TypeError` | if `images` is not 2D or 3D. |\n\n\u003cbr /\u003e"]]
View source on GitHub