Extracts crops from the input image tensor and resizes them.
tf.raw_ops.CropAndResize(
image,
boxes,
box_ind,
crop_size,
method='bilinear',
extrapolation_value=0,
name=None
)
Extracts crops from the input image tensor and resizes them using bilinear
sampling or nearest neighbor sampling (possibly with aspect ratio change) to a
common output size specified by crop_size
. This is more general than the
crop_to_bounding_box
op which extracts a fixed size slice from the input image
and does not allow resizing or aspect ratio change.
Returns a tensor with crops
from the input image
at positions defined at the
bounding box locations in boxes
. The cropped boxes are all resized (with
bilinear or nearest neighbor interpolation) to a fixed
size = [crop_height, crop_width]
. The result is a 4-D tensor
[num_boxes, crop_height, crop_width, depth]
. The resizing is corner aligned.
In particular, if boxes = [[0, 0, 1, 1]]
, the method will give identical
results to using tf.image.resize_bilinear()
or
tf.image.resize_nearest_neighbor()
(depends on the method
argument) with
align_corners=True
.
Args |
image
|
A Tensor . Must be one of the following types: uint8 , uint16 , int8 , int16 , int32 , int64 , half , float32 , float64 .
A 4-D tensor of shape [batch, image_height, image_width, depth] .
Both image_height and image_width need to be positive.
|
boxes
|
A Tensor of type float32 .
A 2-D tensor of shape [num_boxes, 4] . The i -th row of the tensor
specifies the coordinates of a box in the box_ind[i] image and is specified
in normalized coordinates [y1, x1, y2, x2] . A normalized coordinate value of
y is mapped to the image coordinate at y * (image_height - 1) , so as the
[0, 1] interval of normalized image height is mapped to
[0, image_height - 1] in image height coordinates. We do allow y1 > y2 , in
which case the sampled crop is an up-down flipped version of the original
image. The width dimension is treated similarly. Normalized coordinates
outside the [0, 1] range are allowed, in which case we use
extrapolation_value to extrapolate the input image values.
|
box_ind
|
A Tensor of type int32 .
A 1-D tensor of shape [num_boxes] with int32 values in [0, batch) .
The value of box_ind[i] specifies the image that the i -th box refers to.
|
crop_size
|
A Tensor of type int32 .
A 1-D tensor of 2 elements, size = [crop_height, crop_width] . All
cropped image patches are resized to this size. The aspect ratio of the image
content is not preserved. Both crop_height and crop_width need to be
positive.
|
method
|
An optional string from: "bilinear", "nearest" . Defaults to "bilinear" .
A string specifying the sampling method for resizing. It can be either
"bilinear" or "nearest" and default to "bilinear" . Currently two sampling
methods are supported: Bilinear and Nearest Neighbor.
|
extrapolation_value
|
An optional float . Defaults to 0 .
Value used for extrapolation, when applicable.
|
name
|
A name for the operation (optional).
|
Returns |
A Tensor of type float32 .
|