Function harris 

pub fn harris<T>(
    input: &Array<T>,
    max_corners: u32,
    min_response: f32,
    sigma: f32,
    block_size: u32,
    k_thr: f32,
) -> Features
where
    T: HasAfEnum + RealFloating,

Harris corner detector.

Compute corners using the Harris corner detector approach. For each pixel, a small window is used to calculate the determinant and trace of such a window, from which a response is calculated. Pixels are considered corners if they are local maximas and have a high positive response.

Parameters

• input is the array containing a grayscale image (color images are not supported)
• max_corners is the maximum number of corners to keep, only retains those with highest Harris responses
• min_response is the minimum response in order for a corner to be retained, only used if max_corners = 0
• sigma is the standard deviation of a circular window (its dimensions will be calculated according to the standard deviation), the covariation matrix will be calculated to a circular neighborhood of this standard deviation (only used when block_size == 0, must be >= 0.5f and <= 5.0f)
• block_size is square window size, the covariation matrix will be calculated to a square neighborhood of this size (must be >= 3 and <= 31)
• k_thr is the Harris constant, usually set empirically to 0.04f (must be >= 0.01f)

Return Values

This function returns an object of struct Features containing Arrays for x and y coordinates and score, while array oreientation & size are set to 0 & 1, respectively, since harris doesn’t compute that information