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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.
Args | |
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image
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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.
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boxes
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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.
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box_ind
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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.
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crop_size
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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.
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method
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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.
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extrapolation_value
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An optional float. Defaults to 0.
Value used for extrapolation, when applicable.
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name
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A name for the operation (optional). |
Returns | |
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A Tensor of type float32.
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