tf.image.crop_and_resize(image, boxes, box_ind, crop_size, method=None, extrapolation_value=None, name=None)
Extracts crops from the input image tensor and bilinearly resizes them (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 interpolation) to a fixed size = [crop_height, crop_width]. The result is a 4-D tensor [num_boxes, crop_height, crop_width, depth].
Args:
-
image: ATensor. Must be one of the following types:uint8,int8,int16,int32,int64,half,float32,float64. A 4-D tensor of shape[batch, image_height, image_width, depth]. Bothimage_heightandimage_widthneed to be positive. -
boxes: ATensorof typefloat32. 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 ofyis 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 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 useextrapolation_value` to extrapolate the input image values. -
box_ind: ATensorof typeint32. A 1-D tensor of shape[num_boxes]with int32 values in[0, batch). The value ofbox_ind[i]specifies the image that thei-th box refers to. -
crop_size: ATensorof typeint32. 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_heightandcrop_widthneed to be positive. -
method: An optionalstringfrom:"bilinear". Defaults to"bilinear". A string specifying the interpolation method. Only 'bilinear' is supported for now. -
extrapolation_value: An optionalfloat. Defaults to0. Value used for extrapolation, when applicable. -
name: A name for the operation (optional).
Returns:
A Tensor of type float32. A 4-D tensor of shape [num_boxes, crop_height, crop_width, depth].
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