tf.image.crop_to_bounding_box
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Crops an image
to a specified bounding box.
tf.image.crop_to_bounding_box(
image, offset_height, offset_width, target_height, target_width
)
Used in the notebooks
This op cuts a rectangular bounding box out of image
. The top-left corner
of the bounding box is at offset_height, offset_width
in image
, and the
lower-right corner is at
offset_height + target_height, offset_width + target_width
.
Example Usage:
image = tf.constant(np.arange(1, 28, dtype=np.float32), shape=[3, 3, 3])
image[:,:,0] # print the first channel of the 3-D tensor
<tf.Tensor: shape=(3, 3), dtype=float32, numpy=
array([[ 1., 4., 7.],
[10., 13., 16.],
[19., 22., 25.]], dtype=float32)>
cropped_image = tf.image.crop_to_bounding_box(image, 0, 0, 2, 2)
cropped_image[:,:,0] # print the first channel of the cropped 3-D tensor
<tf.Tensor: shape=(2, 2), dtype=float32, numpy=
array([[ 1., 4.],
[10., 13.]], dtype=float32)>
Args |
image
|
4-D Tensor of shape [batch, height, width, channels] or 3-D
Tensor of shape [height, width, channels] .
|
offset_height
|
Vertical coordinate of the top-left corner of the bounding
box in image . Must be 0-D int32 Tensor or python integer.
|
offset_width
|
Horizontal coordinate of the top-left corner of the bounding
box in image . Must be 0-D int32 Tensor or python integer.
|
target_height
|
Height of the bounding box. Must be 0-D int32 Tensor or
python integer.
|
target_width
|
Width of the bounding box. Must be 0-D int32 Tensor or
python integer.
|
Returns |
If image was 4-D, a 4-D Tensor of shape
[batch, target_height, target_width, channels] .
If image was 3-D, a 3-D Tensor of shape
[target_height, target_width, channels] .
It has the same dtype with image .
|
Raises |
ValueError
|
image is not a 3-D or 4-D Tensor .
|
ValueError
|
offset_width < 0 or offset_height < 0 .
|
ValueError
|
target_width <= 0 or target_height <= 0 .
|
ValueError
|
width < offset_width + target_width or
height < offset_height + target_height .
|
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Last updated 2024-04-26 UTC.
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