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diff --git a/tensorflow/contrib/lite/g3doc/tfmobile/android_build.md b/tensorflow/contrib/lite/g3doc/tfmobile/android_build.md new file mode 100644 index 0000000000..76e16fc9db --- /dev/null +++ b/tensorflow/contrib/lite/g3doc/tfmobile/android_build.md @@ -0,0 +1,181 @@ +book_path: /mobile/_book.yaml +project_path: /mobile/_project.yaml + +# Building TensorFlow on Android + +To get you started working with TensorFlow on Android, we'll walk through two +ways to build our TensorFlow mobile demos and deploying them on an Android +device. The first is Android Studio, which lets you build and deploy in an +IDE. The second is building with Bazel and deploying with ADB on the command +line. + +Why choose one or the other of these methods? + +The simplest way to use TensorFlow on Android is to use Android Studio. If you +aren't planning to customize your TensorFlow build at all, or if you want to use +Android Studio's editor and other features to build an app and just want to add +TensorFlow to it, we recommend using Android Studio. + +If you are using custom ops, or have some other reason to build TensorFlow from +scratch, scroll down and see our instructions +for [building the demo with Bazel](#build_the_demo_using_bazel). + +## Build the demo using Android Studio + +**Prerequisites** + +If you haven't already, do the following two things: + +- Install [Android Studio](https://developer.android.com/studio/index.html), + following the instructions on their website. + +- Clone the TensorFlow repository from GitHub: + + git clone https://github.com/tensorflow/tensorflow + +**Building** + +1. Open Android Studio, and from the Welcome screen, select **Open an existing + Android Studio project**. + +2. From the **Open File or Project** window that appears, navigate to and select + the `tensorflow/examples/android` directory from wherever you cloned the + TensorFlow GitHub repo. Click OK. + + If it asks you to do a Gradle Sync, click OK. + + You may also need to install various platforms and tools, if you get + errors like "Failed to find target with hash string 'android-23' and similar. + +3. Open the `build.gradle` file (you can go to **1:Project** in the side panel + and find it under the **Gradle Scripts** zippy under **Android**). Look for + the `nativeBuildSystem` variable and set it to `none` if it isn't already: + + // set to 'bazel', 'cmake', 'makefile', 'none' + def nativeBuildSystem = 'none' + +4. Click the *Run* button (the green arrow) or select *Run > Run 'android'* from the + top menu. You may need to rebuild the project using *Build > Rebuild Project*. + + If it asks you to use Instant Run, click **Proceed Without Instant Run**. + + Also, you need to have an Android device plugged in with developer options + enabled at this + point. See [here](https://developer.android.com/studio/run/device.html) for + more details on setting up developer devices. + +This installs three apps on your phone that are all part of the TensorFlow +Demo. See [Android Sample Apps](#android_sample_apps) for more information about +them. + +## Adding TensorFlow to your apps using Android Studio + +To add TensorFlow to your own apps on Android, the simplest way is to add the +following lines to your Gradle build file: + + allprojects { + repositories { + jcenter() + } + } + + dependencies { + compile 'org.tensorflow:tensorflow-android:+' + } + +This automatically downloads the latest stable version of TensorFlow as an AAR +and installs it in your project. + +## Build the demo using Bazel + +Another way to use TensorFlow on Android is to build an APK +using [Bazel](https://bazel.build/) and load it onto your device +using [ADB](https://developer.android.com/studio/command-line/adb.html). This +requires some knowledge of build systems and Android developer tools, but we'll +guide you through the basics here. + +- First, follow our instructions for + <a href="http://www.tensorflow.org/install/install_sources">installing from sources</a>. + This will also guide you through installing Bazel and cloning the + TensorFlow code. + +- Download the Android [SDK](https://developer.android.com/studio/index.html) + and [NDK](https://developer.android.com/ndk/downloads/index.html) if you do + not already have them. You need at least version 12b of the NDK, and 23 of the + SDK. + +- In your copy of the TensorFlow source, update the + [WORKSPACE](https://github.com/tensorflow/tensorflow/blob/master/WORKSPACE) + file with the location of your SDK and NDK, where it says <PATH_TO_NDK> + and <PATH_TO_SDK>. + +- Run Bazel to build the demo APK: + + bazel build -c opt //tensorflow/examples/android:tensorflow_demo + +- Use [ADB](https://developer.android.com/studio/command-line/adb.html#move) to + install the APK onto your device: + + adb install -r bazel-bin/tensorflow/examples/android/tensorflow_demo.apk + +Note: In general when compiling for Android with Bazel you need +`--config=android` on the Bazel command line, though in this case this +particular example is Android-only, so you don't need it here. + +This installs three apps on your phone that are all part of the TensorFlow +Demo. See [Android Sample Apps](#android_sample_apps) for more information about +them. + +## Android Sample Apps + +The +[Android example code](https://www.tensorflow.org/code/tensorflow/examples/android/) is +a single project that builds and installs three sample apps which all use the +same underlying code. The sample apps all take video input from a phone's +camera: + +- **TF Classify** uses the Inception v3 model to label the objects it’s pointed + at with classes from Imagenet. There are only 1,000 categories in Imagenet, + which misses most everyday objects and includes many things you’re unlikely to + encounter often in real life, so the results can often be quite amusing. For + example there’s no ‘person’ category, so instead it will often guess things it + does know that are often associated with pictures of people, like a seat belt + or an oxygen mask. If you do want to customize this example to recognize + objects you care about, you can use + the + [TensorFlow for Poets codelab](https://codelabs.developers.google.com/codelabs/tensorflow-for-poets/index.html#0) as + an example for how to train a model based on your own data. + +- **TF Detect** uses a multibox model to try to draw bounding boxes around the + locations of people in the camera. These boxes are annotated with the + confidence for each detection result. Results will not be perfect, as this + kind of object detection is still an active research topic. The demo also + includes optical tracking for when objects move between frames, which runs + more frequently than the TensorFlow inference. This improves the user + experience since the apparent frame rate is faster, but it also gives the + ability to estimate which boxes refer to the same object between frames, which + is important for counting objects over time. + +- **TF Stylize** implements a real-time style transfer algorithm on the camera + feed. You can select which styles to use and mix between them using the + palette at the bottom of the screen, and also switch out the resolution of the + processing to go higher or lower rez. + +When you build and install the demo, you'll see three app icons on your phone, +one for each of the demos. Tapping on them should open up the app and let you +explore what they do. You can enable profiling statistics on-screen by tapping +the volume up button while they’re running. + +### Android Inference Library + +Because Android apps need to be written in Java, and core TensorFlow is in C++, +TensorFlow has a JNI library to interface between the two. Its interface is aimed +only at inference, so it provides the ability to load a graph, set up inputs, +and run the model to calculate particular outputs. You can see the full +documentation for the minimal set of methods in +[TensorFlowInferenceInterface.java](https://www.tensorflow.org/code/tensorflow/contrib/android/java/org/tensorflow/contrib/android/TensorFlowInferenceInterface.java) + +The demos applications use this interface, so they’re a good place to look for +example usage. You can download prebuilt binary jars +at +[ci.tensorflow.org](https://ci.tensorflow.org/view/Nightly/job/nightly-android/). |