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► Keras 3 API documentation / Layers API / Preprocessing layers / Image augmentation layers / MaxNumBoundingBoxes layer

MaxNumBoundingBoxes layer

[source]

MaxNumBoundingBoxes class

keras.layers.MaxNumBoundingBoxes(max_number, fill_value=-1, **kwargs)

Ensure the maximum number of bounding boxes.

Note: This layer is safe to use inside a tf.data or grain pipeline (independently of which backend you're using).

Arguments

  • max_number: Desired output number of bounding boxes.
  • padding_value: The padding value of the boxes and labels in bounding_boxes. Defaults to -1.

Example

max_boxes_layer = keras.layers.MaxNumBoundingBoxes(
    max_number=10,
    fill_value=-1
)

images = np.random.randint(0, 255, (1, 224, 224, 3), dtype="uint8")

bounding_boxes = {
    "boxes": np.array([
        [[10, 20, 100, 150], [50, 60, 200, 250], [0, 0, 50, 50]],
    ]),
    "labels": np.array([[1, 2, 3]])
}

result = max_boxes_layer({
    "images": images,
    "bounding_boxes": bounding_boxes
})

Guides and examples using MaxNumBoundingBoxes

MaxNumBoundingBoxes layer
MaxNumBoundingBoxes class