Convert a bounding box dictionary batched Ragged tensors

• Original Link : https://keras.io/api/keras_cv/bounding_box/utils/to_ragged/
• Last Checked at : 2024-11-25

source

to_ragged function

keras_cv.bounding_box.to_ragged(bounding_boxes, sentinel=-1, dtype=tf.float32)

converts a Dense padded bounding box tf.Tensor to a tf.RaggedTensor.

Bounding boxes are ragged tensors in most use cases. Converting them to a dense tensor makes it easier to work with Tensorflow ecosystem. This function can be used to filter out the masked out bounding boxes by checking for padded sentinel value of the class_id axis of the bounding_boxes.

Example

bounding_boxes = {
    "boxes": tf.constant([[2, 3, 4, 5], [0, 1, 2, 3]]),
    "classes": tf.constant([[-1, 1]]),
}
bounding_boxes = bounding_box.to_ragged(bounding_boxes)
print(bounding_boxes)
# {
#     "boxes": [[0, 1, 2, 3]],
#     "classes": [[1]]
# }

Arguments

• bounding_boxes: a Tensor of bounding boxes. May be batched, or unbatched.
• sentinel: The value indicating that a bounding box does not exist at the current index, and the corresponding box is padding, defaults to -1.
• dtype: the data type to use for the underlying Tensors.

Returns

dictionary of tf.RaggedTensor or ’tf.Tensor’ containing the filtered bounding boxes.