tf.image.resize_area

resize_area(
    images,
    size,
    align_corners=False,
    name=None
)

Defined in tensorflow/python/ops/gen_image_ops.py.

See the guide: Images > Resizing

Resize images to size using area interpolation.

Input images can be of different types but output images are always float.

Each output pixel is computed by first transforming the pixel's footprint into the input tensor and then averaging the pixels that intersect the footprint. An input pixel's contribution to the average is weighted by the fraction of its area that intersects the footprint. This is the same as OpenCV's INTER_AREA.

Args:

• images: A Tensor. Must be one of the following types: uint8, int8, int16, int32, int64, half, float32, float64. 4-D with shape [batch, height, width, channels].
• size: A 1-D int32 Tensor of 2 elements: new_height, new_width. The new size for the images.
• align_corners: An optional bool. Defaults to False. If true, rescale input by (new_height - 1) / (height - 1), which exactly aligns the 4 corners of images and resized images. If false, rescale by new_height / height. Treat similarly the width dimension.
• name: A name for the operation (optional).

Returns:

A Tensor of type float32. 4-D with shape [batch, new_height, new_width, channels].