Matting/deploy/human_matting_android_demo/app/build.gradle

import java.security.MessageDigest

apply plugin: 'com.android.application'

android {
    compileSdkVersion 28
    defaultConfig {
        applicationId "com.baidu.paddleseg.lite.demo.human_matting"
        minSdkVersion 15
        versionCode 1
        versionName "1.0"
        testInstrumentationRunner "android.support.test.runner.AndroidJUnitRunner"
    }
    buildTypes {
        release {
            minifyEnabled false
            proguardFiles getDefaultProguardFile('proguard-android-optimize.txt'), 'proguard-rules.pro'
        }
    }
}

dependencies {
    implementation fileTree(include: ['*.jar'], dir: 'libs')
    implementation 'com.android.support:appcompat-v7:28.0.0'
    implementation 'com.android.support.constraint:constraint-layout:1.1.3'
    implementation 'com.android.support:design:28.0.0'
    testImplementation 'junit:junit:4.12'
    androidTestImplementation 'com.android.support.test:runner:1.0.2'
    androidTestImplementation 'com.android.support.test.espresso:espresso-core:3.0.2'
    implementation files('libs/PaddlePredictor.jar')  //添加PaddleLite包
}

def paddleLiteLibs = 'https://paddlelite-demo.bj.bcebos.com/libs/android/paddle_lite_libs_v2_8_0.tar.gz'
task downloadAndExtractPaddleLiteLibs(type: DefaultTask) {
    doFirst {
        println "Downloading and extracting Paddle Lite libs"
    }
    doLast {
        // Prepare cache folder for libs
        if (!file("cache").exists()) {
            mkdir "cache"
        }
        // Generate cache name for libs
        MessageDigest messageDigest = MessageDigest.getInstance('MD5')
        messageDigest.update(paddleLiteLibs.bytes)
        String cacheName = new BigInteger(1, messageDigest.digest()).toString(32)
        // Download libs
        if (!file("cache/${cacheName}.tar.gz").exists()) {
            ant.get(src: paddleLiteLibs, dest: file("cache/${cacheName}.tar.gz"))
        }
        // Unpack libs
        copy {
            from tarTree("cache/${cacheName}.tar.gz")
            into "cache/${cacheName}"
        }
        // Copy PaddlePredictor.jar
        if (!file("libs/PaddlePredictor.jar").exists()) {
            copy {
                from "cache/${cacheName}/java/PaddlePredictor.jar"
                into "libs"
            }
        }
        // Copy libpaddle_lite_jni.so for armeabi-v7a and arm64-v8a
        if (!file("src/main/jniLibs/armeabi-v7a/libpaddle_lite_jni.so").exists()) {
            copy {
                from "cache/${cacheName}/java/libs/armeabi-v7a/"
                into "src/main/jniLibs/armeabi-v7a"
            }
        }
        if (!file("src/main/jniLibs/arm64-v8a/libpaddle_lite_jni.so").exists()) {
            copy {
                from "cache/${cacheName}/java/libs/arm64-v8a/"
                into "src/main/jniLibs/arm64-v8a"
            }
        }
    }
}
preBuild.dependsOn downloadAndExtractPaddleLiteLibs

def paddleLiteModels = [
        [
                'src' : 'https://paddleseg.bj.bcebos.com/matting/models/deploy/hrnet_w18.tar.gz',
                'dest' : 'src/main/assets/image_matting/models/modnet'
        ],
]
task downloadAndExtractPaddleLiteModels(type: DefaultTask) {
    doFirst {
        println "Downloading and extracting Paddle Lite models"
    }
    doLast {
        // Prepare cache folder for models
        if (!file("cache").exists()) {
            mkdir "cache"
        }
        paddleLiteModels.eachWithIndex { model, index ->
            MessageDigest messageDigest = MessageDigest.getInstance('MD5')
            messageDigest.update(model.src.bytes)
            String cacheName = new BigInteger(1, messageDigest.digest()).toString(32)
            // Download model file
            if (!file("cache/${cacheName}.tar.gz").exists()) {
                ant.get(src: model.src, dest: file("cache/${cacheName}.tar.gz"))
            }
            // Unpack model file
            copy {
                from tarTree("cache/${cacheName}.tar.gz")
                into "cache/${cacheName}"
            }
            // Copy model file
            if (!file("${model.dest}/hrnet_w18.nb").exists()) {
                copy {
                    from "cache/${cacheName}"
                    into "${model.dest}"
                }
            }
        }
    }
}
preBuild.dependsOn downloadAndExtractPaddleLiteModels