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diff --git a/tensorflow/contrib/lite/g3doc/demo_ios.md b/tensorflow/contrib/lite/g3doc/demo_ios.md new file mode 100644 index 0000000000..a554898899 --- /dev/null +++ b/tensorflow/contrib/lite/g3doc/demo_ios.md @@ -0,0 +1,71 @@ +book_path: /mobile/_book.yaml +project_path: /mobile/_project.yaml + +# iOS Demo App + +The TensorFlow Lite demo is a camera app that continuously classifies whatever +it sees from your device's back camera, using a quantized MobileNet model. These +instructions walk you through building and running the demo on an iOS device. + +## Prerequisites + +* You must have [Xcode](https://developer.apple.com/xcode/) installed and have a + valid Apple Developer ID, and have an iOS device set up and linked to your + developer account with all of the appropriate certificates. For these + instructions, we assume that you have already been able to build and deploy an + app to an iOS device with your current developer environment. + +* The demo app requires a camera and must be executed on a real iOS device. You + can build it and run with the iPhone Simulator but it won't have any camera + information to classify. + +* You don't need to build the entire TensorFlow library to run the demo, but you + will need to clone the TensorFlow repository if you haven't already: + + git clone https://github.com/tensorflow/tensorflow + +* You'll also need the Xcode command-line tools: + + xcode-select --install + + If this is a new install, you will need to run the Xcode application once to + agree to the license before continuing. + +## Building the iOS Demo App + +1. Install CocoaPods if you don't have it: + + sudo gem install cocoapods + +2. Download the model files used by the demo app (this is done from inside the + cloned directory): + + sh tensorflow/contrib/lite/examples/ios/download_models.sh + +3. Install the pod to generate the workspace file: + + cd tensorflow/contrib/lite/examples/ios/camera + pod install + + If you have installed this pod before and that command doesn't work, try + + pod update + + At the end of this step you should have a file called + `tflite_camera_example.xcworkspace`. + +4. Open the project in Xcode by typing this on the command line: + + open tflite_camera_example.xcworkspace + + This launches Xcode if it isn't open already and opens the + `tflite_camera_example` project. + +5. Build and run the app in Xcode. + + Note that as mentioned earlier, you must already have a device set up and + linked to your Apple Developer account in order to deploy the app on a + device. + +You'll have to grant permissions for the app to use the device's camera. Point +the camera at various objects and enjoy seeing how the model classifies things! |