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authorGravatar Yu-Cheng Ling <ycling@google.com>2018-02-08 16:15:41 -0800
committerGravatar TensorFlower Gardener <gardener@tensorflow.org>2018-02-08 16:21:30 -0800
commit06a93f8d14d5f154d96b5576e454eaa4272facb4 (patch)
tree37d308c5dedafec37d4a13da383d98f4127c8245 /tensorflow/contrib/lite/README.md
parent899b00b2dd594fc7772eb3917437a90256598e3d (diff)
Improve the flow to build TFLite iOS demo app
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@@ -92,7 +92,7 @@ Similar to the Android demo app, there's an iOS camera app that uses exactly the
This demo app requires a camera so it doesn't work with simulators. It need to be executed on a real iOS device. Follow the instructions to build and run the demo app:
-1. Follow the Building section [here](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/lite/g3doc/ios.md#building) to build the universal iOS library for TensorFlow Lite.
+1. Run `third_party/tensorflow/contrib/lite/examples/ios/download_models.sh` to download the model files used by the demo app.
1. Install [CocoaPods](https://cocoapods.org/) if it wasn't installed yet: `sudo gem install cocoapods`.
1. Run `pod install` in `tensorflow/contrib/lite/examples/ios/camera` to generate the workspace file.
1. Open the project by running `open tflite_camera_example.xcworkspace`, and build the app in XCode.