Image processing

[jjjkkkjjj]

Create OpenCV Mat by https://stackoverflow.com/questions/39579398/opencv-how-to-create-mat-from-uint8-t-pointer

and pass it by “with” statements.

simple image processing function is vImage Module

FFFF means float types (8888 means UInt8)

https://developer.apple.com/documentation/accelerate/1515929-vimageconvolve_argbffff

[jjjkkkjjj]

https://docs.opencv.org/3.1.0/d3/d63/classcv_1_1Mat.html#a5fafc033e089143062fd31015b5d0f40

Pointer to the user data. Matrix constructors that take data and step parameters do not allocate matrix data. Instead, they just initialize the matrix header that points to the specified data, which means that no data is copied. This operation is very efficient and can be used to process external data using OpenCV functions. The external data is not automatically deallocated, so you should take care of it.

[jjjkkkjjj]

Matft/Sources/Matft/library/vDSP.swift

Line 1415 in 7bd5406

let contextRef = CGContext(data: $0.baseAddress!, width: width, height: height, bitsPerComponent: 8, bytesPerRow: width*channel, space: colorSpace, bitmapInfo: bitmapInfo.rawValue)

bitspercomponent = 32 means float?
If so, this is more efficient

According to core graphics supposed pixel formats, it only supports RGB with float format on iOS not Gray on iOS

ref: CGContext

[jjjkkkjjj]

I think CGContext documents implies passing data pointer will not be freed (= not copied )

data: A pointer to the destination in memory where the drawing is to be rendered. The size of this memory block should be at least (bytesPerRow*height) bytes.
Pass NULL if you want this function to allocate memory for the bitmap. This frees you from managing your own memory, which reduces memory leak issues.

[jjjkkkjjj]

Ref: Float CGContext

https://stackoverflow.com/questions/55433107/how-to-normalize-pixel-values-of-an-uiimage-in-swift

[jjjkkkjjj]

The difference between Planar and interleaved image link
Planar: Column contiguous
Interleaved: Row contiguous

https://developer.apple.com/documentation/accelerate/optimizing_image-processing_performance