# coreMLModel() Filters an image with a Core ML model. ``` class func coreMLModel() -> any CIFilter & CICoreMLModel ``` ## Return Value The modified image. ## Discussion This method applies the Core ML model filter to an image. The effect filters the image using a trained Core ML model to produce the result. Specifying the head index allows you to produce a result from various components of a multiheaded coreML model. The Core ML model filter uses the following properties: - `inputImage`: An image with the type [`CIImage`](/documentation/CoreImage/CIImage). - `headIndex`: A `float` representing which output of a multihead Core ML model should be used for applying the effect to an image. - `softmaxNormalization`: A `Boolean` value representing the softmax normalization to be applied to the output image created by the model. - `inputModel`: The Core ML model to be used for applying effect on the image. The following code creates a filter that results in the flowers appearing to be glass panes: ```swift func coreML(inputImage: CIImage) -> CIImage { let coreMLFilter = CIFilter.coreMLModel() let model = GlassModel().model coreMLFilter.inputImage = inputImage coreMLFilter.headIndex = 0 coreMLFilter.softmaxNormalization = false return coreMLFilter.outputImage! } ```  --- Copyright © 2026 Apple Inc. All rights reserved. | [Terms of Use](https://www.apple.com/legal/internet-services/terms/site.html) | [Privacy Policy](https://www.apple.com/privacy/privacy-policy)