pub struct RawImage {
Show 16 fields pub make: String, pub model: String, pub clean_make: String, pub clean_model: String, pub width: usize, pub height: usize, pub cpp: usize, pub wb_coeffs: [f32; 4], pub whitelevels: [u16; 4], pub blacklevels: [u16; 4], pub xyz_to_cam: [[f32; 3]; 4], pub cfa: CFA, pub crops: [usize; 4], pub blackareas: Vec<(u64, u64, u64, u64)>, pub orientation: Orientation, pub data: RawImageData,
}
Expand description

All the data needed to process this raw image, including the image data itself as well as all the needed metadata

Fields

make: String

camera make as encoded in the file

model: String

camera model as encoded in the file

clean_make: String

make cleaned up to be consistent and short

clean_model: String

model cleaned up to be consistent and short

width: usize

width of the full image

height: usize

height of the full image

cpp: usize

number of components per pixel (1 for bayer, 3 for RGB images)

wb_coeffs: [f32; 4]

whitebalance coefficients encoded in the file in RGBE order

whitelevels: [u16; 4]

image whitelevels in RGBE order

blacklevels: [u16; 4]

image blacklevels in RGBE order

xyz_to_cam: [[f32; 3]; 4]

matrix to convert XYZ to camera RGBE

cfa: CFA

color filter array

crops: [usize; 4]

how much to crop the image to get all the usable area, order is top, right, bottom, left

blackareas: Vec<(u64, u64, u64, u64)>

Areas of the sensor that is masked to prevent it from receiving light. Used to calculate black levels and noise. Each tuple represents a masked rectangle’s top, right, bottom, left

orientation: Orientation

orientation of the image as indicated by the image metadata

data: RawImageData

image data itself, has width*height*cpp elements

Implementations

Outputs the inverted matrix that converts pixels in the camera colorspace into XYZ components.

Outputs the inverted matrix that converts pixels in the camera colorspace into XYZ components normalized to be easily used to convert to Lab or a RGB output space

Not all cameras encode a whitebalance so in those cases just using a 6500K neutral one is a good compromise

Normalize matrix so that inm * (1,1,1) is (1,1,1,1) and then invert

Matrix inversion that deals with 4x3 matrices

Returns the CFA pattern after the crop has been applied (and thus the pattern potentially shifted)

Checks if the image is monochrome

Trait Implementations

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Formats the value using the given formatter. Read more

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