@Namespace(value="tensorflow::ops") @NoOffset public static class tensorflow.CropAndResize extends Pointer
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.
Arguments:
* scope: A Scope object
* image: A 4-D tensor of shape [batch, image_height, image_width, depth].
Both image_height and image_width need to be positive.
* boxes: 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 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 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 (see Attrs):
* method: 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: Value used for extrapolation, when applicable.
Returns:
* Output: A 4-D tensor of shape [num_boxes, crop_height, crop_width, depth].| Modifier and Type | Class and Description |
|---|---|
static class |
tensorflow.CropAndResize.Attrs
Optional attribute setters for CropAndResize
|
Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator| Constructor and Description |
|---|
CropAndResize(Pointer p)
Pointer cast constructor.
|
CropAndResize(tensorflow.Scope scope,
tensorflow.Input image,
tensorflow.Input boxes,
tensorflow.Input box_ind,
tensorflow.Input crop_size) |
CropAndResize(tensorflow.Scope scope,
tensorflow.Input image,
tensorflow.Input boxes,
tensorflow.Input box_ind,
tensorflow.Input crop_size,
tensorflow.CropAndResize.Attrs attrs) |
| Modifier and Type | Method and Description |
|---|---|
tensorflow.Input |
asInput() |
tensorflow.Output |
asOutput() |
tensorflow.Output |
crops() |
tensorflow.CropAndResize |
crops(tensorflow.Output crops) |
static tensorflow.CropAndResize.Attrs |
ExtrapolationValue(float x) |
static tensorflow.CropAndResize.Attrs |
Method(BytePointer x) |
static tensorflow.CropAndResize.Attrs |
Method(String x) |
tensorflow.Node |
node() |
tensorflow.Operation |
operation() |
tensorflow.CropAndResize |
operation(tensorflow.Operation operation) |
address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, hashCode, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, parseBytes, physicalBytes, position, position, put, realloc, setNull, sizeof, toString, totalBytes, totalPhysicalBytes, withDeallocator, zeropublic CropAndResize(Pointer p)
Pointer.Pointer(Pointer).public CropAndResize(@Const @ByRef tensorflow.Scope scope, @ByVal tensorflow.Input image, @ByVal tensorflow.Input boxes, @ByVal tensorflow.Input box_ind, @ByVal tensorflow.Input crop_size)
public CropAndResize(@Const @ByRef tensorflow.Scope scope, @ByVal tensorflow.Input image, @ByVal tensorflow.Input boxes, @ByVal tensorflow.Input box_ind, @ByVal tensorflow.Input crop_size, @Const @ByRef tensorflow.CropAndResize.Attrs attrs)
@ByVal @Name(value="operator tensorflow::Output") public tensorflow.Output asOutput()
@ByVal @Name(value="operator tensorflow::Input") public tensorflow.Input asInput()
public tensorflow.Node node()
@ByVal public static tensorflow.CropAndResize.Attrs Method(@tensorflow.StringPiece BytePointer x)
@ByVal public static tensorflow.CropAndResize.Attrs Method(@tensorflow.StringPiece String x)
@ByVal public static tensorflow.CropAndResize.Attrs ExtrapolationValue(float x)
@ByRef public tensorflow.Operation operation()
public tensorflow.CropAndResize operation(tensorflow.Operation operation)
@ByRef public tensorflow.Output crops()
public tensorflow.CropAndResize crops(tensorflow.Output crops)
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