This is a basic Super Resolution example application for ONNX Runtime on iOS with Ort-Extensions support for pre/post processing. The demo app accomplishes the task of recovering a high resolution (HR) image from its low resolution counterpart.

The model used here is from source: Pytorch Super Resolution and accomodated into ONNX version with pre/post processing support.

• Install Xcode 13.0 and above (preferably latest version)
• A valid Apple Developer ID
• An iOS device or iOS simulator
• Xcode command line tools xcode-select --install
• Clone the onnxruntime-inference-examples source code repo

1. Install CocoaPods. sudo gem install cocoapods

2. In terminal, run pod install under <ONNXRuntime-inference-example-root>/mobile/examples/super_resolution/ios/ORTSuperResolution to generate the workspace file and install required pod files.

   Note: At the end of this step, you should get a file called ORTSuperResolution.xcworkspace.

3. Open <ONNXRuntime-inference-example-root>/mobile/examples/super_resolution/ios/ORTSuperResolution.xcworkspace in Xcode and make sure to select your corresponding development team under Target-General-Signing for a proper codesign procedure to run the app (only on device required, if running on iOS simulator can skip this step.)

4. Connect your iOS device/simulator, build and run the app. Click Perform Super Resolution button to see performed result on displayed sample image.

Here's an example screenshot of the app: