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Extracts crops from the input image tensor and resizes them.
tf.compat.v1.image.crop_and_resize(
image, boxes, box_ind=None, crop_size=None, method='bilinear',
extrapolation_value=0, name=None, box_indices=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
.
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).A Tensor
of type float32
.