Parallelized pixelization inside AutoCAD using F#

As promised in the last post, we're now going to look at how to change the code to make the colour averaging routine work in parallel. The overall performance is marginally better on my dual-core machine, but I fully expect it to get quicker and quicker as the number of cores multiply.

To start with, though, here's the modified "synchronous" version of the code - as I went through making the code work in parallel, I noticed a bunch of general enhancements that were applicable to both versions. Here's the updated F# code:

// Use lightweight F# syntax

 

#light

 

// Declare a specific namespace and module name

 

module SyncPixelizer.Commands

 

// Import managed assemblies

 

#nowarn "9" // ... because we're using NativePtr

 

open Autodesk.AutoCAD.Runtime

open Autodesk.AutoCAD.ApplicationServices

open Autodesk.AutoCAD.DatabaseServices

open Autodesk.AutoCAD.EditorInput

open Autodesk.AutoCAD.Geometry

open Autodesk.AutoCAD.Colors

open System.Drawing.Imaging

open Microsoft.FSharp.NativeInterop

 

// Add up the RGB values of a list of pixels

 

// We use a recursive function with an accumulator argument,

// (rt, gt, bt), to allow tail call optimization

 

let rec sumColors (pix : List<(byte*byte*byte)>) (rt,gt,bt) =

  match pix with

    | [] -> (rt, gt, bt)

    | (r, g, b) :: tl ->

        sumColors tl

          (rt + Byte.to_int r,

          gt + Byte.to_int g,

          bt + Byte.to_int b)

 

// Average out the RGB values of a list of pixels

 

let getAverageColour (pixels : List<(byte*byte*byte)>) =

  let (rsum, gsum, bsum) =

    sumColors pixels (0, 0, 0)

  let count = pixels.Length

  let ravg = Byte.of_int (rsum / count)

  let gavg = Byte.of_int (gsum / count)

  let bavg = Byte.of_int (bsum / count)

 

  // For some reason the pixel needs ro be reversed - probably

  // because of the bitmap format (needs investigation)

 

  Color.FromRgb(bavg, gavg, ravg)

 

// Function to get an index into our flat array

// from an x,y pair

 

let getIndexFromXY ysize x y =

  (x * ysize) + y

 

//  Get a chunk of pixels to average from one row

 

// We use a recursive function with an accumulator argument

// to allow tail call optimization

 

let rec getChunkRowPixels p xsamp acc =

  if xsamp = 0 then

    acc

  else

    let pix =

      [(NativePtr.get p 0,

        NativePtr.get p 1,

        NativePtr.get p 2)]

    let p = NativePtr.add p 3 // We do *not* mutate here

    getChunkRowPixels p (xsamp-1) (pix @ acc)

 

// Get a chunk of pixels to average from multiple rows

 

// We use a recursive function with an accumulator argument

// to allow tail call optimization

 

let rec getChunkPixels p stride xsamp ysamp acc =

  if ysamp = 0 then

    acc

  else

    let pix = getChunkRowPixels p xsamp []

    let p = NativePtr.add p stride  // We do *not* mutate here

    getChunkPixels p stride xsamp (ysamp-1) (pix @ acc)

 

// Get the various chunks of pixels to average across

// a complete bitmap image

 

let pixelizeBitmap (image:System.Drawing.Bitmap) xsize ysize =

 

  // Create a 1-dimensional array of pixel lists (one list,

  // which then needs averaging, per final pixel)

 

  let (arr : List<(byte*byte*byte)>[]) =

    Array.create (xsize * ysize) []

 

  // Lock the entire memory block related to our image

 

  let bd =

    image.LockBits

      (System.Drawing.Rectangle

        (0, 0, image.Width ,image.Height),

      ImageLockMode.ReadOnly, image.PixelFormat)

 

  // Establish the number of pixels to sample per chunk

  // in each of the x and y directions

 

  let xsamp = image.Width / xsize

  let ysamp = image.Height / ysize

 

  // We have a mutable pointer to step through the image

 

  let mutable (p:nativeptr<byte>) =

    NativePtr.of_nativeint (bd.Scan0)

 

  // Loop through the various chunks

 

  for i = 0 to ysize - 1 do

 

    // We take a copy of the current value of p, as we

    // don't want to mutate p while extracting the pixels

    // within a row

 

    let mutable xp = p

    for j = 0 to xsize - 1 do

 

      // Get the square chunk of pixels starting at

      // this x,y position

 

      let chk =

        getChunkPixels xp bd.Stride xsamp ysamp []

 

      // Add it into our array

 

      let idx = getIndexFromXY ysize j (ysize-1-i)

      arr.[idx] <- chk

 

      // Mutate the pointer to move along to the right

      // by a value of 3 (our RGB value) times the

      // number of pixels we're sampling in x

 

      xp <- NativePtr.add xp (xsamp * 3)

    done

 

    // Mutate the original p pointer to move on one row

 

    p <- NativePtr.add p (bd.Stride * ysamp)

  done

 

  // Finally unlock the bitmap data and return the array

 

  image.UnlockBits(bd)

  arr

 

// Create an array of ObjectIds from a collection

 

let getIdArray (ids : ObjectIdCollection) =

  [| for i in [0..ids.Count-1] -> ids.[i] |]

 

// Declare our command

 

[<CommandMethod("pix")>]

let pixelize() =

 

  // Let's get the usual helpful AutoCAD objects

 

  let doc =

    Application.DocumentManager.MdiActiveDocument

  let ed = doc.Editor

  let db = doc.Database

 

  // Prompt the user for the file and the width of the image

 

  let pofo =

    new PromptOpenFileOptions

      ("Select an image to import and pixelize")

  pofo.Filter <-

    "Jpeg Image (*.jpg)|*.jpg|All files (*.*)|*.*"

  let pfnr = ed.GetFileNameForOpen(pofo)

 

  let file =

    match pfnr.Status with

    | PromptStatus.OK ->

        pfnr.StringResult

    | _ ->

        ""

 

  if System.IO.File.Exists(file) then

 

    let img = System.Drawing.Image.FromFile(file)

 

    let pio =

      new PromptIntegerOptions

        ("\nEnter number of horizontal pixels: ")

    pio.AllowNone <- true

    pio.UseDefaultValue <- true

    pio.LowerLimit <- 1

    pio.UpperLimit <- img.Width

    pio.DefaultValue <- 100

 

    let pir = ed.GetInteger(pio)

    let xsize =

      match pir.Status with

        | PromptStatus.None ->

            img.Width

        | PromptStatus.OK ->

            pir.Value

        | _ -> -1

 

    if xsize > 0 then

 

      // Calculate the vertical size from the horizontal

 

      let ysize = img.Height * xsize / img.Width

 

      if ysize > 0 then

 

        // We'll time the command, so we can check the

        // sync vs. async efficiency

 

        let starttime = System.DateTime.Now

 

        // "use" has the same effect as "using" in C#

 

        use tr =

          db.TransactionManager.StartTransaction()

 

        // Get appropriately-typed BlockTable and BTRs

 

        let bt =

          tr.GetObject

            (db.BlockTableId,OpenMode.ForRead)

          :?> BlockTable

 

        let ms =

          tr.GetObject

            (bt.[BlockTableRecord.ModelSpace],

            OpenMode.ForWrite)

          :?> BlockTableRecord

 

        // Function to create a filled circle (hatch) at a

        // specific location

 

        // Note the valid use of tr and ms, as they are in scope

 

        let createCircle pt rad =

          let hat = new Hatch()

          hat.SetDatabaseDefaults()

          hat.SetHatchPattern

            (HatchPatternType.PreDefined,

            "SOLID")

 

          let id = ms.AppendEntity(hat)

          tr.AddNewlyCreatedDBObject(hat, true)

 

          // Now we create the loop, which we make db-resident

          // (appending a transient loop caused problems, so

          // we're going to use the circle and then erase it)

 

          let cir = new Circle()

          cir.Radius <- rad

          cir.Center <- pt

 

          let lid = ms.AppendEntity(cir)

          tr.AddNewlyCreatedDBObject(cir, true)

 

          // Have the hatch use the loop we created

 

          let loops = new ObjectIdCollection()

          loops.Add(lid) |> ignore

          hat.AppendLoop(HatchLoopTypes.Default, loops)

          hat.EvaluateHatch(true)

 

          // Now we erase the loop

 

          cir.Erase()

          id

 

        // Function to create our grid of circles

 

        let createGrid xsize ysize rad offset =

          let ids = new ObjectIdCollection()

          for i = 0 to xsize - 1 do

            for j = 0 to ysize - 1 do

              let pt =

                new Point3d

                  (offset * (Int32.to_float i),

                   offset * (Int32.to_float j),

                   0.0)

              let id = createCircle pt rad

              ids.Add(id) |> ignore

          ids

 

        // Function to change the colour of an entity

 

        let changeColour (id : ObjectId) (col : Color) =

          if id.IsValid then

            let ent =

              tr.GetObject(id, OpenMode.ForWrite) :?> Entity

            ent.Color <- col

 

        // Create our basic grid

 

        let ids = createGrid xsize ysize 0.5 1.2

 

        // Cast our image to a bitmap and then

        // get the chunked pixels

 

        let bmp = img :?> System.Drawing.Bitmap

        let arr = pixelizeBitmap bmp xsize ysize

 

        // Loop through the pixel list and average them out

        // (which could be parallelized), using the results

        // to change the colour of the circles in our grid

 

        Array.map getAverageColour arr |>

          Array.iter2 changeColour (getIdArray ids)

 

        // Commit the transaction

 

        tr.Commit()

 

        // Check how long it took

 

        let elapsed =

          System.DateTime.op_Subtraction

            (System.DateTime.Now, starttime)

 

        ed.WriteMessage

          ("\nElapsed time: " + elapsed.ToString())

To change this to run the colour averaging asynchronously (in parallel, if you have the cores) is really simple. We replace one line of code "Array.map getAverageColour arr" with the following:

Async.Run

  (Async.Parallel

    [ for a in arr ->

        async { return getAverageColour a }])

This essentially performs a parallel array map (albeit a somewhat naive one), returning basically the same results as the previous line - just hopefully a little more quickly. In case you want to build the two files into one project to test them side-by-side, here they are, the synchronous and asynchronous versions, with the changes needed to allow them to live in and execute from the same assembly.

Here's one more image that's been processed by the PIX command:

In case you're interested, the original image can be found here.