Struct NeuralNetworkImageScaler 

pub struct NeuralNetworkImageScaler {
    pub channel_scale: f32,
    pub blue_bias: f32,
    pub green_bias: f32,
    pub red_bias: f32,
    pub gray_bias: f32,
}

A neural network preprocessor that performs a scalar multiplication of an image followed by addition of scalar biases to the channels.

Input: X An image in BGR or RGB format with shape \[3, H, W\] or in grayscale format with shape \[1, H, W\]. Output: Y An image with format and shape corresponding to the input.

If the input image is in BGR format:

.. code::

 Y\[0, :, :\] = channelScale * X\[0, :, :\] + blueBias
 Y\[1, :, :\] = channelScale * X\[1, :, :\] + greenBias
 Y\[2, :, :\] = channelScale * X\[2, :, :\] + redBias

If the input image is in RGB format:

.. code::

 Y\[0, :, :\] = channelScale * X\[0, :, :\] + redBias
 Y\[1, :, :\] = channelScale * X\[1, :, :\] + greenBias
 Y\[2, :, :\] = channelScale * X\[2, :, :\] + blueBias

If the input image is in grayscale format:

.. code::

 Y\[0, :, :\] = channelScale * X\[0, :, :\] + grayBias

Fields

channel_scale: f32

Scalar to be multiplied.

blue_bias: f32

Scalar blue bias to be added.

green_bias: f32

Scalar green bias to be added.

red_bias: f32

Scalar red bias to be added.

gray_bias: f32

Scalar bias to be added for grayscale images.

Trait Implementations

impl Clone for NeuralNetworkImageScaler

fn clone(&self) -> NeuralNetworkImageScaler

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for NeuralNetworkImageScaler

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for NeuralNetworkImageScaler

fn default() -> Self

Returns the “default value” for a type.

impl Message for NeuralNetworkImageScaler

fn encoded_len(&self) -> usize

Returns the encoded length of the message without a length delimiter.

fn clear(&mut self)

Clears the message, resetting all fields to their default.

fn encode(&self, buf: &mut impl BufMut) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message to a buffer.

fn encode_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message to a newly allocated buffer.

fn encode_length_delimited( &self, buf: &mut impl BufMut, ) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message with a length-delimiter to a buffer.

fn encode_length_delimited_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message with a length-delimiter to a newly allocated buffer.

fn decode(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes an instance of the message from a buffer.

fn decode_length_delimited(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes a length-delimited instance of the message from the buffer.

fn merge(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes an instance of the message from a buffer, and merges it into self.

fn merge_length_delimited(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes a length-delimited instance of the message from buffer, and merges it into self.

impl PartialEq for NeuralNetworkImageScaler

fn eq(&self, other: &NeuralNetworkImageScaler) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Copy for NeuralNetworkImageScaler

impl StructuralPartialEq for NeuralNetworkImageScaler