CropAndResize
tensorflow C++ API
tensorflow::ops::CropAndResize
Extracts crops from the input image tensor and bilinearly resizes them (possibly with aspect ratio change) to a common output size specified bycrop_size
.
Summary
This is more general than thecrop_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 withcrops
from the inputimage
at positions defined at the bounding box locations inboxes
. The cropped boxes are all resized (with bilinear interpolation) to a fixedsize = [crop_height, crop_width]
. The result is a 4-D tensor[num_boxes, crop_height, crop_width, depth]
.
Arguments:
- scope: A Scope object
- image: A 4-D tensor of shape
[batch, image_height, image_width, depth]
. Bothimage_height
andimage_width
need to be positive. - boxes: A 2-D tensor of shape
[num_boxes, 4]
. Thei
-th row of the tensor specifies the coordinates of a box in thebox_ind[i]
image and is specified in normalized coordinates[y1, x1, y2, x2]
. A normalized coordinate value ofy
is mapped to the image coordinate aty * (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 allowy1
>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 useextrapolation_value
to extrapolate the input image values. - box_ind: A 1-D tensor of shap
[num_boxes]
with int32 values in[0, batch)
. The value ofbox_ind[i]
specifies the image that thei
-th box refers to.crop_size: 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. Bothcrop_height
andcrop_width
need to be positive. - crop_size: 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.
Optional attributes (seeAttrs
):
- method: A string specifying the interpolation method. Only ‘bilinear’ is supported for now.
- extrapolation_value: Value used for extrapolation, when applicable.
Returns:
Output
: A 4-D tensor of shape[num_boxes, crop_height, crop_width, depth]
.
Constructor
- CropAndResize(const ::tensorflow::Scope & scope, ::tensorflow::Input image, ::tensorflow::Input boxes, ::tensorflow::Input box_ind, ::tensorflow::Input crop_size, const CropAndResize::Attrs & attrs) .
Public attributes
- tensorflow::Output crops.
CropAndResize block
Source link : https://github.com/EXPNUNI/enuSpaceTensorflow/blob/master/enuSpaceTensorflow/tf_image_ops.cpp
Argument:
- Scope scope : A Scope object (A scope is generated automatically each page. A scope is not connected.)
- image : connect Input node.
- boxes : connect Input node or input float value.
- box_ind : connect Input node or input int32 value.
- crop_size : connect Input node or input int32 value.
- CropAndResize::Attrs attrs : input attrs. ex) method_ = “bilinear”;extrapolation_value_ = 0.0f;
Return:
- Output crops: Output object of CropAndResize class object.
Result:
- std::vector(Tensor) product_result : Returned object of executed result by calling session.