Android apk too big using OpenCV and Nd4j

DL4J
1

I have an android application that needs the OpenCV and Nd4j libraries. The problem is, the app is too big (almost 700MB), and i have no idea how to slim it down.

build.gradle:

implementation fileTree(dir: 'libs', include: ['*.jar'])
    // https://mvnrepository.com/artifact/org.nd4j/nd4j-api
implementation group: 'org.nd4j', name: 'nd4j-api', version: '1.0.0-beta7'
implementation group: 'org.nd4j', name: 'nd4j-native-platform', version: '1.0.0-beta7'
implementation group: 'org.datavec', name: 'datavec-data-image', version: '1.0.0-beta7'

implementation 'androidx.appcompat:appcompat:1.1.0'
implementation 'androidx.constraintlayout:constraintlayout:1.1.3'
implementation 'org.tensorflow:tensorflow-lite:+'
testImplementation 'junit:junit:4.12'
androidTestImplementation 'androidx.test.ext:junit:1.1.1'
androidTestImplementation 'androidx.test.espresso:espresso-core:3.2.0'

apk: https://i.stack.imgur.com/3OZ2y.png

How can i reduce the size?

2

It is pretty easy to do. See this: Reducing the Number of Dependencies · bytedeco/javacpp-presets Wiki · GitHub

1 Like
3

The most popular architectures now are arm64 and x86_64?

4

Do i need all?

implementation group: ‘org.nd4j’, name: ‘nd4j-native’, version: ‘1.0.0-beta6’

implementation group: ‘org.nd4j’, name: ‘nd4j-native’, version: ‘1.0.0-beta6’, classifier: “android-arm”

implementation group: ‘org.nd4j’, name: ‘nd4j-native’, version: ‘1.0.0-beta6’, classifier: “android-arm64”

implementation group: ‘org.nd4j’, name: ‘nd4j-native’, version: ‘1.0.0-beta6’, classifier: “android-x86”

implementation group: ‘org.nd4j’, name: ‘nd4j-native’, version: ‘1.0.0-beta6’, classifier: “android-x86_64”

implementation group: ‘org.bytedeco’, name: ‘openblas’, version: ‘0.3.7-1.5.2’

implementation group: ‘org.bytedeco’, name: ‘openblas’, version: ‘0.3.7-1.5.2’, classifier: “android-arm”

implementation group: ‘org.bytedeco’, name: ‘openblas’, version: ‘0.3.7-1.5.2’, classifier: “android-arm64”

implementation group: ‘org.bytedeco’, name: ‘openblas’, version: ‘0.3.7-1.5.2’, classifier: “android-x86”

implementation group: ‘org.bytedeco’, name: ‘openblas’, version: ‘0.3.7-1.5.2’, classifier: “android-x86_64”

implementation group: ‘org.bytedeco’, name: ‘opencv’, version: ‘4.1.2-1.5.2’

implementation group: ‘org.bytedeco’, name: ‘opencv’, version: ‘4.1.2-1.5.2’, classifier: “android-arm”

implementation group: ‘org.bytedeco’, name: ‘opencv’, version: ‘4.1.2-1.5.2’, classifier: “android-arm64”

implementation group: ‘org.bytedeco’, name: ‘opencv’, version: ‘4.1.2-1.5.2’, classifier: “android-x86”

implementation group: ‘org.bytedeco’, name: ‘opencv’, version: ‘4.1.2-1.5.2’, classifier: “android-x86_64”

implementation group: ‘org.bytedeco’, name: ‘leptonica’, version: ‘1.78.0-1.5.2’

implementation group: ‘org.bytedeco’, name: ‘leptonica’, version: ‘1.78.0-1.5.2’, classifier: “android-arm”

implementation group: ‘org.bytedeco’, name: ‘leptonica’, version: ‘1.78.0-1.5.2’, classifier: “android-arm64”

implementation group: ‘org.bytedeco’, name: ‘leptonica’, version: ‘1.78.0-1.5.2’, classifier: “android-x86”

implementation group: ‘org.bytedeco’, name: ‘leptonica’, version: ‘1.78.0-1.5.2’, classifier: “android-x86_64”

5

The most popular architectures are arm and arm64. x86_64 is only really needed when you run your application in the Android emulator.

1 Like
6

and for my purpose which libraries should i include?

7

those that you’ve listed look like a good start.

8

I mainly have to use INDarray, OpenCV (like Mat) and NativeImageLoader

9

Yes, and INDArray, i.e. ND4J, uses Openblas and OpenCV and NativeImageLoader need both opencv and leptonica.

12

Now apk size is 480MB but still big…