I'm a big fan of Apple's Core Image technology: my Nodality application is based entirely around Core Image filters. However, for new users, the code for adding a simple filter to an image is a little oblique and the implementation is very "stringly" typed.

 This post looks at an alternative, GPUImage from Brad Larson. GPUImage is a framework containing a rich set of image filters, many of which aren't in Core Image. It has a far simpler and more strongly typed API and, in some cases, is faster than Core Image.

 To kick off, let's look at the code required to apply a Gaussian blue to an image (inputImage) using Core Filter:
        let inputImage = UIImage()
        let ciContext = CIContext(options: nil)
        
        let blurFilter = CIFilter(name: "CIGaussianBlur")
        blurFilter.setValue(CIImage(image: inputImage), forKey: "inputImage")
        blurFilter.setValue(10, forKey: "inputRadius")
        
        let outputImageData = blurFilter.valueForKey("outputImage") as CIImage!
        let outputImageRef: CGImage = ciContext.createCGImage(outputImageData, fromRect: outputImageData.extent())

        let outputImage = UIImage(CGImage: outputImageRef)!

 ...not only do we need to explicitly define the context, both the filter name and parameter are strings and we need a few steps to convert the filter's output into a UIImage. 

Here's the same functionality using GPUImage:
        let inputImage = UIImage()
        
        let blurFilter = GPUImageGaussianBlurFilter()
        blurFilter.blurRadiusInPixels = 10
        
        let outputImage = blurFilter.imageByFilteringImage(inputImage)

 Here, both the filter and its blur radius parameter are properly typed and the filter returns a UIImage instance.

 On the flip-side, there is some setting up to do. Once you've got a local copy of GPUImage, drag the framework project into your application's project. Then under the application target's build phases, add a target dependency, a reference to GPUImage.framework under link binaries and a copy files stage.

 Your build phases screen should look like this:

Then, by simply importing GPUImage, you're ready to roll.

 To show off some of the funkier filters contained in GPUImage, I've created a little demonstration app, GPUImageDemo.

 The app demonstrates Polar Pixellate, Polka Dot, Sketch, Threshold Sketch, Toon, Smooth Toon, Emboss, Sphere Refraction and Glass Sphere - none of which are available in Core Image. 

 The filtering work is all done in my GPUImageDelegate class where a switch statement declares a GPUImageOutput variable (the class that includes the imageByFiltering() method) and sets it to the appropriate concrete class depending on the user interface.

 For example, if the picker is set the threshold sketch, the following case statement is executed:
       case ImageFilter.ThresholdSketch:

            gpuImageFilter =  GPUImageThresholdSketchFilter()
            
            if let gpuImageFilter = gpuImageFilter as? GPUImageThresholdSketchFilter
            {
                if values.count > 1
                {
                    gpuImageFilter.edgeStrength = values[0]
                    gpuImageFilter.threshold = values[1]
                }
            }

 If you build this project, you may encounter a build error on the documentation target. I've simply deleted this target on affected machines.

 GPUImage is fast enough to filter video. I've taken my recent two million particles experiment and added a post processing step that consists of a cartoon filter and an emboss filter. These are packaged together in a GPUImageFilterGroup:
        let toonFilter = GPUImageSmoothToonFilter()
        let embossFilter = GPUImageEmbossFilter()

        let filterGroup = GPUImageFilterGroup()
        toonFilter.threshold = 1
        embossFilter.intensity = 2
        filterGroup.addFilter(toonFilter)
        filterGroup.addFilter(embossFilter)
        
        toonFilter.addTarget(embossFilter)
        
        filterGroup.initialFilters = [ toonFilter ]

        filterGroup.terminalFilter = embossFilter

 Since GPUImageFilterGroup extends GPUImageFilterOutput, I can take the output from the  Metal texture, create a UIImage instance of it and pass it to the composite filter:
        self.imageView.image = self.filterGroup.imageByFilteringImage(UIImage(CGImage: imageRef)!)

 On my iPad Air 2, the final result of 2,000,000 particles with a two filter post process on a 1,024 x 1,024 image still runs at around 20 frames per second. Here's a real time screen capture:

The source code for my GPUImageDemo is available at my GitHub repository here and GPUImage lives here.
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Labels: CIImageFilter GPUImage image editing swift
4

View comments

  1. their is errors when i tried to run the application
    how can i solve it i use xcode 7.2

    ReplyDelete

  2. I'm using an old version of GPUImage. I'll try to find time to update it.

    ReplyDelete

  3. Same problem. We would all be thankful if you could update it. Thanks.

    ReplyDelete

  4. Just updated that project - runs fine now under Xcode 7.2. Cheers!

    ReplyDelete

It's been a fairly busy few months at my "proper" job, so my recreational Houdini tinkering has taken a bit of a back seat.

5

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3

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After watching this excellent tutorial that discusses advecting particles by magnetic fields to create an animation of the sun, I was inspired to use the same technique to advect particles by fields that are a function of reaction diffusion systems.

1

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4

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1

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1

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1

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1

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2

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1

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2

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The simulation is based on a point cloud which is wrangled inside a solver. My main network looks like:

The initial point cloud is crated with a Point Generate.

4

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1

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1

My recent post, Swarm Chemistry in SideFX Houdini, illustrates an interesting effect, but tweaking the values in the swarm chemistry solver is a pain. What would be great is a user interface to vary the simulation parameters rather than having to edit the VEX by hand.

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1

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1

I posted recently about simulating the Belousov-Zhabotinsky reaction in Houdini. Although it worked, it wasn't particularly aesthetically pleasing, so here's a hopefully prettier version using a slightly different approach.

As I explore Houdini, I find myself continually in awe at the ease with which I can create complex and physically realistic effects. This post looks at creating geometry and applying a heat source to it to cause it to glow and melt.

2

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I recently posted Chaos in Swift! Visualizing the Lorenz Attractor with Metal, which was inspired by a Houdini tweet from Erwin Santacruz.

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Inspired by this tweet from Erwin Santacruz, the owner of http://houdinitricks.com, I thought it was high time that I played with some strange attractors in Swift.

After reading Paul Hudson's excellent What's new in Swift 3.0 article, I thought I'd take an early dive into Swift 3.0 myself to see how it affects Core Image development.

4

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1

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Simon Gladman - Advanced image processing with Core Image from Daniel Haight on Vimeo.

I'm pleased to announce that version 1.3 of my book, Core Image for Swift, is now available through Apple's iBooks Store and, as a PDF, through Gumroad.

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