tf.image.draw_bounding_boxes

TensorFlow 1 version View source on GitHub

Draw bounding boxes on a batch of images.

tf.image.draw_bounding_boxes(
    images, boxes, colors, name=None
)

Outputs a copy of images but draws on top of the pixels zero or more bounding boxes specified by the locations in boxes. The coordinates of the each bounding box in boxes are encoded as [y_min, x_min, y_max, x_max]. The bounding box coordinates are floats in [0.0, 1.0] relative to the width and the height of the underlying image.

For example, if an image is 100 x 200 pixels (height x width) and the bounding box is [0.1, 0.2, 0.5, 0.9], the upper-left and bottom-right coordinates of the bounding box will be (40, 10) to (180, 50) (in (x,y) coordinates).

Parts of the bounding box may fall outside the image.

images A Tensor. Must be one of the following types: float32, half. 4-D with shape [batch, height, width, depth]. A batch of images.
boxes A Tensor of type float32. 3-D with shape [batch, num_bounding_boxes, 4] containing bounding boxes.
colors A Tensor of type float32. 2-D. A list of RGBA colors to cycle through for the boxes.
name A name for the operation (optional).

A Tensor. Has the same type as images.

Usage Example:

# create an empty image
img = tf.zeros([1, 3, 3, 3])
# draw a box around the image
box = np.array([0, 0, 1, 1])
boxes = box.reshape([1, 1, 4])
# alternate between red and blue
colors = np.array([[1.0, 0.0, 0.0], [0.0, 0.0, 1.0]])
tf.image.draw_bounding_boxes(img, boxes, colors)
<tf.Tensor: shape=(1, 3, 3, 3), dtype=float32, numpy=
array([[[[1., 0., 0.],
        [1., 0., 0.],
        [1., 0., 0.]],
        [[1., 0., 0.],
        [0., 0., 0.],
        [1., 0., 0.]],
        [[1., 0., 0.],
        [1., 0., 0.],
        [1., 0., 0.]]]], dtype=float32)>