Merge branch 'develop' into python_inference

.gitignore

@@ -4,7 +4,6 @@ __pycache__/
 *$py.class
 
 # C extensions
-*.so
 
 # Distribution / packaging
 .Python

README.md

@@ -64,12 +64,15 @@ $ pip install -r requirements.txt
 * [如何训练U-Net](./turtorial/finetune_unet.md)
 * [如何训练ICNet](./turtorial/finetune_icnet.md)
 * [如何训练PSPNet](./turtorial/finetune_pspnet.md)
+* [如何训练HRNet](./turtorial/finetune_hrnet.md)
 
 ### 预测部署
 
 * [模型导出](./docs/model_export.md)
 * [使用Python预测](./deploy/python/)
 * [使用C++预测](./deploy/cpp/)
+* [移动端预测部署](./deploy/lite/)
+
 
 ### 高级功能
 

configs/hrnet_w18_pet.yaml

+TRAIN_CROP_SIZE: (512, 512) # (width, height), for unpadding rangescaling and stepscaling
+EVAL_CROP_SIZE: (512, 512) # (width, height), for unpadding rangescaling and stepscaling
+AUG:
+    AUG_METHOD: "unpadding" # choice unpadding rangescaling and stepscaling
+    FIX_RESIZE_SIZE: (512, 512) # (width, height), for unpadding
+
+    INF_RESIZE_VALUE: 500  # for rangescaling
+    MAX_RESIZE_VALUE: 600  # for rangescaling
+    MIN_RESIZE_VALUE: 400  # for rangescaling
+
+    MAX_SCALE_FACTOR: 1.25  # for stepscaling
+    MIN_SCALE_FACTOR: 0.75  # for stepscaling
+    SCALE_STEP_SIZE: 0.25  # for stepscaling
+    MIRROR: True
+BATCH_SIZE: 4
+DATASET:
+    DATA_DIR: "./dataset/mini_pet/"
+    IMAGE_TYPE: "rgb"  # choice rgb or rgba
+    NUM_CLASSES: 3
+    TEST_FILE_LIST: "./dataset/mini_pet/file_list/test_list.txt"
+    TRAIN_FILE_LIST: "./dataset/mini_pet/file_list/train_list.txt"
+    VAL_FILE_LIST: "./dataset/mini_pet/file_list/val_list.txt"
+    VIS_FILE_LIST: "./dataset/mini_pet/file_list/test_list.txt"
+    IGNORE_INDEX: 255
+    SEPARATOR: " "
+FREEZE:
+    MODEL_FILENAME: "__model__"
+    PARAMS_FILENAME: "__params__"
+MODEL:
+    MODEL_NAME: "hrnet"
+    DEFAULT_NORM_TYPE: "bn"
+    HRNET:
+      STAGE2:
+        NUM_CHANNELS: [18, 36]
+      STAGE3:
+        NUM_CHANNELS: [18, 36, 72]
+      STAGE4:
+        NUM_CHANNELS: [18, 36, 72, 144]
+TRAIN:
+    PRETRAINED_MODEL_DIR: "./pretrained_model/hrnet_w18_bn_cityscapes/"
+    MODEL_SAVE_DIR: "./saved_model/hrnet_w18_bn_pet/"
+    SNAPSHOT_EPOCH: 10
+TEST:
+    TEST_MODEL: "./saved_model/hrnet_w18_bn_pet/final"
+SOLVER:
+    NUM_EPOCHS: 100
+    LR: 0.005
+    LR_POLICY: "poly"
+    OPTIMIZER: "sgd"

deploy/README.md

@@ -8,3 +8,5 @@
 
 [3. 服务化部署(仅支持 Linux)](./serving)
 
+[4. 移动端部署(仅支持Android)](./lite)
+

deploy/lite/README.md

+# 人像分割在移动端的部署
+
+## 1.介绍
+以人像分割在安卓端的部署为例，介绍如何使用[Paddle-Lite](https://github.com/PaddlePaddle/Paddle-Lite)对分割模型进行移动端的部署。文档第二节介绍如何使用人像分割安卓端的demo，后面几章节介绍如何将PaddleSeg的Model部署到安卓设备。
+
+## 2.安卓Demo使用
+
+### 2.1 要求
+* Android Studio 3.4；
+* Android手机或开发板；
+
+### 2.2 安装
+* git clone https://github.com/PaddlePaddle/PaddleSeg.git  ；
+* 打开Android Studio，在"Welcome to Android Studio"窗口点击"Open an existing Android Studio project"，在弹出的路径选择窗口中进入"/PaddleSeg/lite/humanseg-android-demo/"目录，然后点击右下角的"Open"按钮即可导入工程
+* 通过USB连接Android手机或开发板；
+* 载入工程后，点击菜单栏的Run->Run 'App'按钮，在弹出的"Select Deployment Target"窗口选择已经连接的Android设备，然后点击"OK"按钮；
+* 手机上会出现Demo的主界面，选择"Image Segmentation"图标，进入的人像分割示例程序；
+* 在人像分割Demo中，默认会载入一张人像图像，并会在图像下方给出CPU的预测结果；
+* 在人像分割Demo中，你还可以通过上方的"Gallery"和"Take Photo"按钮从相册或相机中加载测试图像；
+
+### 2.3 其他
+此安卓demo基于[Paddle-Lite-Demo](https://github.com/PaddlePaddle/Paddle-Lite-Demo)开发，更多的细节请参考该repo。<br>
+*注意：demo中拍照时照片会自动压缩，想测试拍照原图效果，可使用手机相机拍照后从相册中打开进行预测。*
+
+### 2.4 效果展示
+<img src="example/human_1.png"  width="20%" ><img src="example/human_2.png"  width="20%" ><img src="example/human_3.png"  width="20%" >
+## 3.模型导出
+此demo的人像分割模型为[下载链接](https://paddleseg.bj.bcebos.com/models/humanseg_mobilenetv2_1_0_bn_freeze_model_pr_po.zip)，是基于Deeplab_v3+mobileNet_v2的humanseg模型，关于humanseg的介绍移步[特色垂类分割模型](./contrib)，更多的分割模型导出可参考：[模型导出](https://github.com/PaddlePaddle/PaddleSeg/blob/release/v0.2.0/docs/model_export.md)
+
+## 4.模型转换
+
+### 4.1模型转换工具
+准备好PaddleSeg导出来的模型和参数文件后，需要使用Paddle-Lite提供的model_optimize_tool对模型进行优化，并转换成Paddle-Lite支持的文件格式，这里有两种方式来实现：
+
+* 手动编译model_optimize_tool
+详细的模型转换方法参考paddlelite提供的官方文档：[模型转化方法](https://paddlepaddle.github.io/Paddle-Lite/v2.0.0/model_optimize_tool/)，从PaddleSeg里面导出来的模型使用model_optimize_tool即可导出model.nb和param.nb文件。
+
+* 使用预编译版本的model_optimize_tool，最新的预编译文件参考[release](https://github.com/PaddlePaddle/Paddle-Lite/releases/)，此demo使用的版本为[model_optimize_tool](https://github.com/PaddlePaddle/Paddle-Lite/releases/download/v2.0.0/model_optimize_tool) ；
+
+	*注意：如果运行失败，请在[Paddle-Lite源码编译](https://paddlepaddle.github.io/Paddle-Lite/v2.0.0/source_compile/)的开发环境中使用model_optimize_tool*
+
+### 4.2 更新模型
+将优化好的model.nb和param.nb文件，替换app/src/main/assets/image_segmentation/
+models/deeplab_mobilenet_for_cpu下面的文件即可。
+
+## 5. 更新预测库
+Paddle-Lite的编译目前支持Docker，Linux和Mac OS开发环境，建议使用Docker开发环境，以免存在各种依赖问题，同时也提供了预编译版本的预测库。准备Paddle-Lite在安卓端的预测库，主要包括三个文件：
+
+* PaddlePredictor.jar；
+* arm64-v8a/libpaddle_lite_jni.so；
+*  armeabi-v7a/libpaddle_lite_jni.so；
+
+下面分别介绍两种方法：
+
+* 使用预编译版本的预测库，最新的预编译文件参考：[release](https://github.com/PaddlePaddle/Paddle-Lite/releases/)，此demo使用的版本：
+
+	* arm64-v8a: [inference_lite_lib.android.armv8](https://github.com/PaddlePaddle/Paddle-Lite/releases/download/v2.0.0/inference_lite_lib.android.armv8.gcc.c++_shared.with_extra.full_publish.tar.gz) ；
+	
+	* armeabi-v7a: [inference_lite_lib.android.armv7](https://github.com/PaddlePaddle/Paddle-Lite/releases/download/v2.0.0/inference_lite_lib.android.armv7.gcc.c++_shared.with_extra.full_publish.tar.gz) ；
+
+	解压上面两个文件，PaddlePredictor.jar位于任一文件夹：inference_lite_lib.android.xxx/java/jar/PaddlePredictor.jar；
+	    
+	解压上述inference_lite_lib.android.armv8文件，arm64-v8a/libpaddle_lite_jni.so位于：inference_lite_lib.android.armv8/java/so/libpaddle_lite_jni.so；
+	
+	解压上述inference_lite_lib.android.armv7文件，armeabi-v7a/libpaddle_lite_jni.so位于：inference_lite_lib.android.armv7/java/so/libpaddle_lite_jni.so；
+
+* 手动编译Paddle-Lite预测库
+开发环境的准备和编译方法参考：[Paddle-Lite源码编译](https://paddlepaddle.github.io/Paddle-Lite/v2.0.0/source_compile/)。
+
+准备好上述文件，即可参考[java_api](https://paddlepaddle.github.io/Paddle-Lite/v2.0.0/java_api_doc/)在安卓端进行推理。具体使用预测库的方法可参考[Paddle-Lite-Demo](https://github.com/PaddlePaddle/Paddle-Lite-Demo)中更新预测库部分的文档。

deploy/lite/humanseg-android-demo/.gitignore

+*.iml
+.gradle
+/local.properties
+/.idea/caches
+/.idea/libraries
+/.idea/modules.xml
+/.idea/workspace.xml
+/.idea/navEditor.xml
+/.idea/assetWizardSettings.xml
+.DS_Store
+/build
+/captures
+.externalNativeBuild

deploy/lite/humanseg-android-demo/app/.gitignore

+/build

deploy/lite/humanseg-android-demo/app/build.gradle

+apply plugin: 'com.android.application'
+
+android {
+    compileSdkVersion 28
+    defaultConfig {
+        applicationId "com.baidu.paddle.lite.demo"
+        minSdkVersion 15
+        targetSdkVersion 28
+        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')
+}

deploy/lite/humanseg-android-demo/app/gradle/wrapper/gradle-wrapper.properties

+#Mon Nov 25 17:01:58 CST 2019
+distributionBase=GRADLE_USER_HOME
+distributionPath=wrapper/dists
+zipStoreBase=GRADLE_USER_HOME
+zipStorePath=wrapper/dists
+distributionUrl=https\://services.gradle.org/distributions/gradle-5.4.1-all.zip

deploy/lite/humanseg-android-demo/app/gradlew

+#!/usr/bin/env sh
+
+##############################################################################
+##
+##  Gradle start up script for UN*X
+##
+##############################################################################
+
+# Attempt to set APP_HOME
+# Resolve links: $0 may be a link
+PRG="$0"
+# Need this for relative symlinks.
+while [ -h "$PRG" ] ; do
+    ls=`ls -ld "$PRG"`
+    link=`expr "$ls" : '.*-> \(.*\)$'`
+    if expr "$link" : '/.*' > /dev/null; then
+        PRG="$link"
+    else
+        PRG=`dirname "$PRG"`"/$link"
+    fi
+done
+SAVED="`pwd`"
+cd "`dirname \"$PRG\"`/" >/dev/null
+APP_HOME="`pwd -P`"
+cd "$SAVED" >/dev/null
+
+APP_NAME="Gradle"
+APP_BASE_NAME=`basename "$0"`
+
+# Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script.
+DEFAULT_JVM_OPTS=""
+
+# Use the maximum available, or set MAX_FD != -1 to use that value.
+MAX_FD="maximum"
+
+warn () {
+    echo "$*"
+}
+
+die () {
+    echo
+    echo "$*"
+    echo
+    exit 1
+}
+
+# OS specific support (must be 'true' or 'false').
+cygwin=false
+msys=false
+darwin=false
+nonstop=false
+case "`uname`" in
+  CYGWIN* )
+    cygwin=true
+    ;;
+  Darwin* )
+    darwin=true
+    ;;
+  MINGW* )
+    msys=true
+    ;;
+  NONSTOP* )
+    nonstop=true
+    ;;
+esac
+
+CLASSPATH=$APP_HOME/gradle/wrapper/gradle-wrapper.jar
+
+# Determine the Java command to use to start the JVM.
+if [ -n "$JAVA_HOME" ] ; then
+    if [ -x "$JAVA_HOME/jre/sh/java" ] ; then
+        # IBM's JDK on AIX uses strange locations for the executables
+        JAVACMD="$JAVA_HOME/jre/sh/java"
+    else
+        JAVACMD="$JAVA_HOME/bin/java"
+    fi
+    if [ ! -x "$JAVACMD" ] ; then
+        die "ERROR: JAVA_HOME is set to an invalid directory: $JAVA_HOME
+
+Please set the JAVA_HOME variable in your environment to match the
+location of your Java installation."
+    fi
+else
+    JAVACMD="java"
+    which java >/dev/null 2>&1 || die "ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH.
+
+Please set the JAVA_HOME variable in your environment to match the
+location of your Java installation."
+fi
+
+# Increase the maximum file descriptors if we can.
+if [ "$cygwin" = "false" -a "$darwin" = "false" -a "$nonstop" = "false" ] ; then
+    MAX_FD_LIMIT=`ulimit -H -n`
+    if [ $? -eq 0 ] ; then
+        if [ "$MAX_FD" = "maximum" -o "$MAX_FD" = "max" ] ; then
+            MAX_FD="$MAX_FD_LIMIT"
+        fi
+        ulimit -n $MAX_FD
+        if [ $? -ne 0 ] ; then
+            warn "Could not set maximum file descriptor limit: $MAX_FD"
+        fi
+    else
+        warn "Could not query maximum file descriptor limit: $MAX_FD_LIMIT"
+    fi
+fi
+
+# For Darwin, add options to specify how the application appears in the dock
+if $darwin; then
+    GRADLE_OPTS="$GRADLE_OPTS \"-Xdock:name=$APP_NAME\" \"-Xdock:icon=$APP_HOME/media/gradle.icns\""
+fi
+
+# For Cygwin, switch paths to Windows format before running java
+if $cygwin ; then
+    APP_HOME=`cygpath --path --mixed "$APP_HOME"`
+    CLASSPATH=`cygpath --path --mixed "$CLASSPATH"`
+    JAVACMD=`cygpath --unix "$JAVACMD"`
+
+    # We build the pattern for arguments to be converted via cygpath
+    ROOTDIRSRAW=`find -L / -maxdepth 1 -mindepth 1 -type d 2>/dev/null`
+    SEP=""
+    for dir in $ROOTDIRSRAW ; do
+        ROOTDIRS="$ROOTDIRS$SEP$dir"
+        SEP="|"
+    done
+    OURCYGPATTERN="(^($ROOTDIRS))"
+    # Add a user-defined pattern to the cygpath arguments
+    if [ "$GRADLE_CYGPATTERN" != "" ] ; then
+        OURCYGPATTERN="$OURCYGPATTERN|($GRADLE_CYGPATTERN)"
+    fi
+    # Now convert the arguments - kludge to limit ourselves to /bin/sh
+    i=0
+    for arg in "$@" ; do
+        CHECK=`echo "$arg"|egrep -c "$OURCYGPATTERN" -`
+        CHECK2=`echo "$arg"|egrep -c "^-"`                                 ### Determine if an option
+
+        if [ $CHECK -ne 0 ] && [ $CHECK2 -eq 0 ] ; then                    ### Added a condition
+            eval `echo args$i`=`cygpath --path --ignore --mixed "$arg"`
+        else
+            eval `echo args$i`="\"$arg\""
+        fi
+        i=$((i+1))
+    done
+    case $i in
+        (0) set -- ;;
+        (1) set -- "$args0" ;;
+        (2) set -- "$args0" "$args1" ;;
+        (3) set -- "$args0" "$args1" "$args2" ;;
+        (4) set -- "$args0" "$args1" "$args2" "$args3" ;;
+        (5) set -- "$args0" "$args1" "$args2" "$args3" "$args4" ;;
+        (6) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" ;;
+        (7) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" ;;
+        (8) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" "$args7" ;;
+        (9) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" "$args7" "$args8" ;;
+    esac
+fi
+
+# Escape application args
+save () {
+    for i do printf %s\\n "$i" | sed "s/'/'\\\\''/g;1s/^/'/;\$s/\$/' \\\\/" ; done
+    echo " "
+}
+APP_ARGS=$(save "$@")
+
+# Collect all arguments for the java command, following the shell quoting and substitution rules
+eval set -- $DEFAULT_JVM_OPTS $JAVA_OPTS $GRADLE_OPTS "\"-Dorg.gradle.appname=$APP_BASE_NAME\"" -classpath "\"$CLASSPATH\"" org.gradle.wrapper.GradleWrapperMain "$APP_ARGS"
+
+# by default we should be in the correct project dir, but when run from Finder on Mac, the cwd is wrong
+if [ "$(uname)" = "Darwin" ] && [ "$HOME" = "$PWD" ]; then
+  cd "$(dirname "$0")"
+fi
+
+exec "$JAVACMD" "$@"

deploy/lite/humanseg-android-demo/app/gradlew.bat

+@if "%DEBUG%" == "" @echo off
+@rem ##########################################################################
+@rem
+@rem  Gradle startup script for Windows
+@rem
+@rem ##########################################################################
+
+@rem Set local scope for the variables with windows NT shell
+if "%OS%"=="Windows_NT" setlocal
+
+set DIRNAME=%~dp0
+if "%DIRNAME%" == "" set DIRNAME=.
+set APP_BASE_NAME=%~n0
+set APP_HOME=%DIRNAME%
+
+@rem Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script.
+set DEFAULT_JVM_OPTS=
+
+@rem Find java.exe
+if defined JAVA_HOME goto findJavaFromJavaHome
+
+set JAVA_EXE=java.exe
+%JAVA_EXE% -version >NUL 2>&1
+if "%ERRORLEVEL%" == "0" goto init
+
+echo.
+echo ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH.
+echo.
+echo Please set the JAVA_HOME variable in your environment to match the
+echo location of your Java installation.
+
+goto fail
+
+:findJavaFromJavaHome
+set JAVA_HOME=%JAVA_HOME:"=%
+set JAVA_EXE=%JAVA_HOME%/bin/java.exe
+
+if exist "%JAVA_EXE%" goto init
+
+echo.
+echo ERROR: JAVA_HOME is set to an invalid directory: %JAVA_HOME%
+echo.
+echo Please set the JAVA_HOME variable in your environment to match the
+echo location of your Java installation.
+
+goto fail
+
+:init
+@rem Get command-line arguments, handling Windows variants
+
+if not "%OS%" == "Windows_NT" goto win9xME_args
+
+:win9xME_args
+@rem Slurp the command line arguments.
+set CMD_LINE_ARGS=
+set _SKIP=2
+
+:win9xME_args_slurp
+if "x%~1" == "x" goto execute
+
+set CMD_LINE_ARGS=%*
+
+:execute
+@rem Setup the command line
+
+set CLASSPATH=%APP_HOME%\gradle\wrapper\gradle-wrapper.jar
+
+@rem Execute Gradle
+"%JAVA_EXE%" %DEFAULT_JVM_OPTS% %JAVA_OPTS% %GRADLE_OPTS% "-Dorg.gradle.appname=%APP_BASE_NAME%" -classpath "%CLASSPATH%" org.gradle.wrapper.GradleWrapperMain %CMD_LINE_ARGS%
+
+:end
+@rem End local scope for the variables with windows NT shell
+if "%ERRORLEVEL%"=="0" goto mainEnd
+
+:fail
+rem Set variable GRADLE_EXIT_CONSOLE if you need the _script_ return code instead of
+rem the _cmd.exe /c_ return code!
+if  not "" == "%GRADLE_EXIT_CONSOLE%" exit 1
+exit /b 1
+
+:mainEnd
+if "%OS%"=="Windows_NT" endlocal
+
+:omega

deploy/lite/humanseg-android-demo/app/proguard-rules.pro

+# Add project specific ProGuard rules here.
+# You can control the set of applied configuration files using the
+# proguardFiles setting in build.gradle.
+#
+# For more details, see
+#   http://developer.android.com/guide/developing/tools/proguard.html
+
+# If your project uses WebView with JS, uncomment the following
+# and specify the fully qualified class name to the JavaScript interface
+# class:
+#-keepclassmembers class fqcn.of.javascript.interface.for.webview {
+#   public *;
+#}
+
+# Uncomment this to preserve the line number information for
+# debugging stack traces.
+#-keepattributes SourceFile,LineNumberTable
+
+# If you keep the line number information, uncomment this to
+# hide the original source file name.
+#-renamesourcefileattribute SourceFile

deploy/lite/humanseg-android-demo/app/src/androidTest/java/com/baidu/paddle/lite/demo/ExampleInstrumentedTest.java

+package com.baidu.paddle.lite.demo;
+
+import android.content.Context;
+import android.support.test.InstrumentationRegistry;
+import android.support.test.runner.AndroidJUnit4;
+
+import org.junit.Test;
+import org.junit.runner.RunWith;
+
+import static org.junit.Assert.*;
+
+/**
+ * Instrumented test, which will execute on an Android device.
+ *
+ * @see <a href="http://d.android.com/tools/testing">Testing documentation</a>
+ */
+@RunWith(AndroidJUnit4.class)
+public class ExampleInstrumentedTest {
+    @Test
+    public void useAppContext() {
+        // Context of the app under test.
+        Context appContext = InstrumentationRegistry.getTargetContext();
+
+        assertEquals("com.baidu.paddle.lite.demo", appContext.getPackageName());
+    }
+}

deploy/lite/humanseg-android-demo/app/src/main/AndroidManifest.xml

+<?xml version="1.0" encoding="utf-8"?>
+<manifest xmlns:android="http://schemas.android.com/apk/res/android"
+          package="com.baidu.paddle.lite.demo">
+
+    <uses-permission android:name="android.permission.WRITE_EXTERNAL_STORAGE"/>
+    <uses-permission android:name="android.permission.READ_EXTERNAL_STORAGE"/>
+    <uses-permission android:name="android.permission.CAMERA"/>
+
+    <application
+            android:allowBackup="true"
+            android:largeHeap="true"
+            android:icon="@mipmap/ic_launcher"
+            android:label="@string/app_name"
+            android:roundIcon="@mipmap/ic_launcher_round"
+            android:supportsRtl="true"
+            android:theme="@style/AppTheme">
+        <activity android:name=".MainActivity">
+            <intent-filter>
+                <action android:name="android.intent.action.MAIN"/>
+
+                <category android:name="android.intent.category.LAUNCHER"/>
+            </intent-filter>
+        </activity>
+        <activity
+                android:name=".segmentation.ImgSegActivity"
+                android:label="Image Segmentation"/>
+        <activity
+                android:name=".segmentation.ImgSegSettingsActivity"
+                android:label="Settings">
+        </activity>
+    </application>
+
+</manifest>
\ No newline at end of file

deploy/lite/humanseg-android-demo/app/src/main/assets/image_segmentation/labels/label_list

+background
+human

deploy/lite/humanseg-android-demo/app/src/main/java/com/baidu/paddle/lite/demo/AppCompatPreferenceActivity.java

+/*
+ * Copyright (C) 2014 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package com.baidu.paddle.lite.demo;
+
+import android.content.res.Configuration;
+import android.os.Bundle;
+import android.preference.PreferenceActivity;
+import android.support.annotation.LayoutRes;
+import android.support.annotation.Nullable;
+import android.support.v7.app.ActionBar;
+import android.support.v7.app.AppCompatDelegate;
+import android.support.v7.widget.Toolbar;
+import android.view.MenuInflater;
+import android.view.View;
+import android.view.ViewGroup;
+
+/**
+ * A {@link android.preference.PreferenceActivity} which implements and proxies the necessary calls
+ * to be used with AppCompat.
+ * <p>
+ * This technique can be used with an {@link android.app.Activity} class, not just
+ * {@link android.preference.PreferenceActivity}.
+ */
+public abstract class AppCompatPreferenceActivity extends PreferenceActivity {
+    private AppCompatDelegate mDelegate;
+
+    @Override
+    protected void onCreate(Bundle savedInstanceState) {
+        getDelegate().installViewFactory();
+        getDelegate().onCreate(savedInstanceState);
+        super.onCreate(savedInstanceState);
+    }
+
+    @Override
+    protected void onPostCreate(Bundle savedInstanceState) {
+        super.onPostCreate(savedInstanceState);
+        getDelegate().onPostCreate(savedInstanceState);
+    }
+
+    public ActionBar getSupportActionBar() {
+        return getDelegate().getSupportActionBar();
+    }
+
+    public void setSupportActionBar(@Nullable Toolbar toolbar) {
+        getDelegate().setSupportActionBar(toolbar);
+    }
+
+    @Override
+    public MenuInflater getMenuInflater() {
+        return getDelegate().getMenuInflater();
+    }
+
+    @Override
+    public void setContentView(@LayoutRes int layoutResID) {
+        getDelegate().setContentView(layoutResID);
+    }
+
+    @Override
+    public void setContentView(View view) {
+        getDelegate().setContentView(view);
+    }
+
+    @Override
+    public void setContentView(View view, ViewGroup.LayoutParams params) {
+        getDelegate().setContentView(view, params);
+    }
+
+    @Override
+    public void addContentView(View view, ViewGroup.LayoutParams params) {
+        getDelegate().addContentView(view, params);
+    }
+
+    @Override
+    protected void onPostResume() {
+        super.onPostResume();
+        getDelegate().onPostResume();
+    }
+
+    @Override
+    protected void onTitleChanged(CharSequence title, int color) {
+        super.onTitleChanged(title, color);
+        getDelegate().setTitle(title);
+    }
+
+    @Override
+    public void onConfigurationChanged(Configuration newConfig) {
+        super.onConfigurationChanged(newConfig);
+        getDelegate().onConfigurationChanged(newConfig);
+    }
+
+    @Override
+    protected void onStop() {
+        super.onStop();
+        getDelegate().onStop();
+    }
+
+    @Override
+    protected void onDestroy() {
+        super.onDestroy();
+        getDelegate().onDestroy();
+    }
+
+    public void invalidateOptionsMenu() {
+        getDelegate().invalidateOptionsMenu();
+    }
+
+    private AppCompatDelegate getDelegate() {
+        if (mDelegate == null) {
+            mDelegate = AppCompatDelegate.create(this, null);
+        }
+        return mDelegate;
+    }
+}

deploy/lite/humanseg-android-demo/app/src/main/java/com/baidu/paddle/lite/demo/CommonActivity.java

+package com.baidu.paddle.lite.demo;
+
+import android.Manifest;
+import android.app.ProgressDialog;
+import android.content.ContentResolver;
+import android.content.Intent;
+import android.content.pm.PackageManager;
+import android.database.Cursor;
+import android.graphics.Bitmap;
+import android.graphics.BitmapFactory;
+import android.net.Uri;
+import android.os.Bundle;
+import android.os.Environment;
+import android.os.Handler;
+import android.os.HandlerThread;
+import android.os.Message;
+import android.provider.MediaStore;
+import android.support.annotation.NonNull;
+import android.support.v4.app.ActivityCompat;
+import android.support.v4.content.ContextCompat;
+import android.support.v4.content.FileProvider;
+import android.support.v7.app.ActionBar;
+import android.support.v7.app.AppCompatActivity;
+import android.util.Log;
+import android.view.Menu;
+import android.view.MenuInflater;
+import android.view.MenuItem;
+import android.widget.Toast;
+
+import java.io.File;
+import java.io.IOException;
+import java.text.SimpleDateFormat;
+import java.util.Date;
+
+public class CommonActivity extends AppCompatActivity {
+    private static final String TAG = CommonActivity.class.getSimpleName();
+    public static final int OPEN_GALLERY_REQUEST_CODE = 0;
+    public static final int TAKE_PHOTO_REQUEST_CODE = 1;
+
+    public static final int REQUEST_LOAD_MODEL = 0;
+    public static final int REQUEST_RUN_MODEL = 1;
+    public static final int RESPONSE_LOAD_MODEL_SUCCESSED = 0;
+    public static final int RESPONSE_LOAD_MODEL_FAILED = 1;
+    public static final int RESPONSE_RUN_MODEL_SUCCESSED = 2;
+    public static final int RESPONSE_RUN_MODEL_FAILED = 3;
+
+    protected ProgressDialog pbLoadModel = null;
+    protected ProgressDialog pbRunModel = null;
+
+    protected Handler receiver = null; // receive messages from worker thread
+    protected Handler sender = null; // send command to worker thread
+    protected HandlerThread worker = null; // worker thread to load&run model
+
+    @Override
+    protected void onCreate(Bundle savedInstanceState) {
+        super.onCreate(savedInstanceState);
+        ActionBar supportActionBar = getSupportActionBar();
+        if (supportActionBar != null) {
+            supportActionBar.setDisplayHomeAsUpEnabled(true);
+        }
+
+        receiver = new Handler() {
+            @Override
+            public void handleMessage(Message msg) {
+                switch (msg.what) {
+                    case RESPONSE_LOAD_MODEL_SUCCESSED:
+                        pbLoadModel.dismiss();
+                        onLoadModelSuccessed();
+                        break;
+                    case RESPONSE_LOAD_MODEL_FAILED:
+                        pbLoadModel.dismiss();
+                        Toast.makeText(CommonActivity.this, "Load model failed!", Toast.LENGTH_SHORT).show();
+                        onLoadModelFailed();
+                        break;
+                    case RESPONSE_RUN_MODEL_SUCCESSED:
+                        pbRunModel.dismiss();
+                        onRunModelSuccessed();
+                        break;
+                    case RESPONSE_RUN_MODEL_FAILED:
+                        pbRunModel.dismiss();
+                        Toast.makeText(CommonActivity.this, "Run model failed!", Toast.LENGTH_SHORT).show();
+                        onRunModelFailed();
+                        break;
+                    default:
+                        break;
+                }
+            }
+        };
+
+        worker = new HandlerThread("Predictor Worker");
+        worker.start();
+        sender = new Handler(worker.getLooper()) {
+            public void handleMessage(Message msg) {
+                switch (msg.what) {
+                    case REQUEST_LOAD_MODEL:
+                        // load model and reload test image
+                        if (onLoadModel()) {
+                            receiver.sendEmptyMessage(RESPONSE_LOAD_MODEL_SUCCESSED);
+                        } else {
+                            receiver.sendEmptyMessage(RESPONSE_LOAD_MODEL_FAILED);
+                        }
+                        break;
+                    case REQUEST_RUN_MODEL:
+                        // run model if model is loaded
+                        if (onRunModel()) {
+                            receiver.sendEmptyMessage(RESPONSE_RUN_MODEL_SUCCESSED);
+                        } else {
+                            receiver.sendEmptyMessage(RESPONSE_RUN_MODEL_FAILED);
+                        }
+                        break;
+                    default:
+                        break;
+                }
+            }
+        };
+    }
+
+    public void loadModel() {
+        pbLoadModel = ProgressDialog.show(this, "", "Loading model...", false, false);
+        sender.sendEmptyMessage(REQUEST_LOAD_MODEL);
+    }
+
+    public void runModel() {
+        pbRunModel = ProgressDialog.show(this, "", "Running model...", false, false);
+        sender.sendEmptyMessage(REQUEST_RUN_MODEL);
+    }
+
+    public boolean onLoadModel() {
+        return true;
+    }
+
+    public boolean onRunModel() {
+        return true;
+    }
+
+    public void onLoadModelSuccessed() {
+    }
+
+    public void onLoadModelFailed() {
+    }
+
+    public void onRunModelSuccessed() {
+    }
+
+    public void onRunModelFailed() {
+    }
+
+    public void onImageChanged(Bitmap image) {
+    }
+
+    public void onImageChanged(String path) {
+
+    }
+    public void onSettingsClicked() {
+    }
+
+    @Override
+    public boolean onCreateOptionsMenu(Menu menu) {
+        MenuInflater inflater = getMenuInflater();
+        inflater.inflate(R.menu.menu_action_options, menu);
+        return true;
+    }
+
+    @Override
+    public boolean onOptionsItemSelected(MenuItem item) {
+        switch (item.getItemId()) {
+            case android.R.id.home:
+                finish();
+                break;
+            case R.id.open_gallery:
+                if (requestAllPermissions()) {
+                    openGallery();
+                }
+                break;
+            case R.id.take_photo:
+                if (requestAllPermissions()) {
+                    takePhoto();
+                }
+                break;
+            case R.id.settings:
+                if (requestAllPermissions()) {
+                    // make sure we have SDCard r&w permissions to load model from SDCard
+                    onSettingsClicked();
+                }
+                break;
+        }
+        return super.onOptionsItemSelected(item);
+    }
+
+    @Override
+    public void onRequestPermissionsResult(int requestCode, @NonNull String[] permissions,
+                                           @NonNull int[] grantResults) {
+        super.onRequestPermissionsResult(requestCode, permissions, grantResults);
+        if (grantResults[0] != PackageManager.PERMISSION_GRANTED || grantResults[1] != PackageManager.PERMISSION_GRANTED) {
+            Toast.makeText(this, "Permission Denied", Toast.LENGTH_SHORT).show();
+        }
+    }
+
+    private boolean requestAllPermissions() {
+        if (ContextCompat.checkSelfPermission(this, Manifest.permission.WRITE_EXTERNAL_STORAGE)
+                != PackageManager.PERMISSION_GRANTED || ContextCompat.checkSelfPermission(this,
+                Manifest.permission.CAMERA)
+                != PackageManager.PERMISSION_GRANTED) {
+            ActivityCompat.requestPermissions(this, new String[]{Manifest.permission.WRITE_EXTERNAL_STORAGE,
+                            Manifest.permission.CAMERA},
+                    0);
+            return false;
+        }
+        return true;
+    }
+
+    private void openGallery() {
+        Intent intent = new Intent(Intent.ACTION_PICK, null);
+        intent.setDataAndType(MediaStore.Images.Media.EXTERNAL_CONTENT_URI, "image/*");
+        startActivityForResult(intent, OPEN_GALLERY_REQUEST_CODE);
+    }
+
+    private void takePhoto() {
+        Intent takePhotoIntent = new Intent(MediaStore.ACTION_IMAGE_CAPTURE);
+        if (takePhotoIntent.resolveActivity(getPackageManager()) != null) {
+            startActivityForResult(takePhotoIntent, TAKE_PHOTO_REQUEST_CODE);
+        }
+    }
+
+    @Override
+    protected void onActivityResult(int requestCode, int resultCode, Intent data) {
+        super.onActivityResult(requestCode, resultCode, data);
+        if (resultCode == RESULT_OK && data != null) {
+            switch (requestCode) {
+                case OPEN_GALLERY_REQUEST_CODE:
+                    try {
+                        ContentResolver resolver = getContentResolver();
+                        Uri uri = data.getData();
+                        Bitmap image = MediaStore.Images.Media.getBitmap(resolver, uri);
+                        String[] proj = {MediaStore.Images.Media.DATA};
+                        Cursor cursor = managedQuery(uri, proj, null, null, null);
+                        cursor.moveToFirst();
+                        onImageChanged(image);
+                    } catch (IOException e) {
+                        Log.e(TAG, e.toString());
+                    }
+                    break;
+
+                case TAKE_PHOTO_REQUEST_CODE:
+                    Bitmap image = (Bitmap) data.getParcelableExtra("data");
+                    onImageChanged(image);
+
+                    break;
+                default:
+                    break;
+            }
+        }
+    }
+
+    @Override
+    protected void onResume() {
+        super.onResume();
+    }
+
+    @Override
+    protected void onDestroy() {
+        worker.quit();
+        super.onDestroy();
+    }
+}

deploy/lite/humanseg-android-demo/app/src/main/java/com/baidu/paddle/lite/demo/MainActivity.java

+package com.baidu.paddle.lite.demo;
+
+import android.content.Intent;
+import android.content.SharedPreferences;
+import android.os.Bundle;
+import android.preference.PreferenceManager;
+import android.support.v7.app.AppCompatActivity;
+import android.util.Log;
+import android.view.View;
+
+import com.baidu.paddle.lite.demo.segmentation.ImgSegActivity;
+
+public class MainActivity extends AppCompatActivity implements View.OnClickListener {
+    private static final String TAG = MainActivity.class.getSimpleName();
+
+    @Override
+    protected void onCreate(Bundle savedInstanceState) {
+        super.onCreate(savedInstanceState);
+        setContentView(R.layout.activity_main);
+
+        // clear all setting items to avoid app crashing due to the incorrect settings
+        SharedPreferences sharedPreferences = PreferenceManager.getDefaultSharedPreferences(this);
+        SharedPreferences.Editor editor = sharedPreferences.edit();
+        editor.clear();
+        editor.commit();
+    }
+
+    @Override
+    public void onClick(View v) {
+        switch (v.getId()) {
+            case R.id.v_img_seg: {
+                Intent intent = new Intent(MainActivity.this, ImgSegActivity.class);
+                startActivity(intent);
+            } break;
+        }
+    }
+
+    @Override
+    protected void onDestroy() {
+        super.onDestroy();
+        System.exit(0);
+    }
+}

deploy/lite/humanseg-android-demo/app/src/main/java/com/baidu/paddle/lite/demo/Predictor.java

+package com.baidu.paddle.lite.demo;
+
+import android.content.Context;
+import android.util.Log;
+import com.baidu.paddle.lite.*;
+
+import java.util.ArrayList;
+import java.util.Date;
+
+public class Predictor {
+    private static final String TAG = Predictor.class.getSimpleName();
+
+    public boolean isLoaded = false;
+    public int warmupIterNum = 0;
+    public int inferIterNum = 1;
+    protected Context appCtx = null;
+    public int cpuThreadNum = 1;
+    public String cpuPowerMode = "LITE_POWER_HIGH";
+    public String modelPath = "";
+    public String modelName = "";
+    protected PaddlePredictor paddlePredictor = null;
+    protected float inferenceTime = 0;
+
+    public Predictor() {
+    }
+
+    public boolean init(Context appCtx, String modelPath, int cpuThreadNum, String cpuPowerMode) {
+        this.appCtx = appCtx;
+        isLoaded = loadModel(modelPath, cpuThreadNum, cpuPowerMode);
+        return isLoaded;
+    }
+
+    protected boolean loadModel(String modelPath, int cpuThreadNum, String cpuPowerMode) {
+        // release model if exists
+        releaseModel();
+
+        // load model
+        if (modelPath.isEmpty()) {
+            return false;
+        }
+        String realPath = modelPath;
+        if (!modelPath.substring(0, 1).equals("/")) {
+            // read model files from custom file_paths if the first character of mode file_paths is '/'
+            // otherwise copy model to cache from assets
+            realPath = appCtx.getCacheDir() + "/" + modelPath;
+            Utils.copyDirectoryFromAssets(appCtx, modelPath, realPath);
+        }
+        if (realPath.isEmpty()) {
+            return false;
+        }
+        MobileConfig config = new MobileConfig();
+        config.setModelDir(realPath);
+        config.setThreads(cpuThreadNum);
+        if (cpuPowerMode.equalsIgnoreCase("LITE_POWER_HIGH")) {
+            config.setPowerMode(PowerMode.LITE_POWER_HIGH);
+        } else if (cpuPowerMode.equalsIgnoreCase("LITE_POWER_LOW")) {
+            config.setPowerMode(PowerMode.LITE_POWER_LOW);
+        } else if (cpuPowerMode.equalsIgnoreCase("LITE_POWER_FULL")) {
+            config.setPowerMode(PowerMode.LITE_POWER_FULL);
+        } else if (cpuPowerMode.equalsIgnoreCase("LITE_POWER_NO_BIND")) {
+            config.setPowerMode(PowerMode.LITE_POWER_NO_BIND);
+        } else if (cpuPowerMode.equalsIgnoreCase("LITE_POWER_RAND_HIGH")) {
+            config.setPowerMode(PowerMode.LITE_POWER_RAND_HIGH);
+        } else if (cpuPowerMode.equalsIgnoreCase("LITE_POWER_RAND_LOW")) {
+            config.setPowerMode(PowerMode.LITE_POWER_RAND_LOW);
+        } else {
+            Log.e(TAG, "unknown cpu power mode!");
+            return false;
+        }
+        paddlePredictor = PaddlePredictor.createPaddlePredictor(config);
+
+        this.cpuThreadNum = cpuThreadNum;
+        this.cpuPowerMode = cpuPowerMode;
+        this.modelPath = realPath;
+        this.modelName = realPath.substring(realPath.lastIndexOf("/") + 1);
+        return true;
+    }
+
+    public void releaseModel() {
+        paddlePredictor = null;
+        isLoaded = false;
+        cpuThreadNum = 1;
+        cpuPowerMode = "LITE_POWER_HIGH";
+        modelPath = "";
+        modelName = "";
+    }
+
+    public Tensor getInput(int idx) {
+        if (!isLoaded()) {
+            return null;
+        }
+        return paddlePredictor.getInput(idx);
+    }
+
+    public Tensor getOutput(int idx) {
+        if (!isLoaded()) {
+            return null;
+        }
+        return paddlePredictor.getOutput(idx);
+    }
+
+    public boolean runModel() {
+        if (!isLoaded()) {
+            return false;
+        }
+        // warm up
+        for (int i = 0; i < warmupIterNum; i++){
+            paddlePredictor.run();
+        }
+        // inference
+        Date start = new Date();
+        for (int i = 0; i < inferIterNum; i++) {
+            paddlePredictor.run();
+        }
+        Date end = new Date();
+        inferenceTime = (end.getTime() - start.getTime()) / (float) inferIterNum;
+        return true;
+    }
+
+    public boolean isLoaded() {
+        return paddlePredictor != null && isLoaded;
+    }
+
+    public String modelPath() {
+        return modelPath;
+    }
+
+    public String modelName() {
+        return modelName;
+    }
+
+    public int cpuThreadNum() {
+        return cpuThreadNum;
+    }
+
+    public String cpuPowerMode() {
+        return cpuPowerMode;
+    }
+
+    public float inferenceTime() {
+        return inferenceTime;
+    }
+}

deploy/lite/humanseg-android-demo/app/src/main/java/com/baidu/paddle/lite/demo/Utils.java

+package com.baidu.paddle.lite.demo;
+
+import android.content.Context;
+import android.os.Environment;
+
+import java.io.*;
+
+public class Utils {
+    private static final String TAG = Utils.class.getSimpleName();
+
+    public static void copyFileFromAssets(Context appCtx, String srcPath, String dstPath) {
+        if (srcPath.isEmpty() || dstPath.isEmpty()) {
+            return;
+        }
+        InputStream is = null;
+        OutputStream os = null;
+        try {
+            is = new BufferedInputStream(appCtx.getAssets().open(srcPath));
+            os = new BufferedOutputStream(new FileOutputStream(new File(dstPath)));
+            byte[] buffer = new byte[1024];
+            int length = 0;
+            while ((length = is.read(buffer)) != -1) {
+                os.write(buffer, 0, length);
+            }
+        } catch (FileNotFoundException e) {
+            e.printStackTrace();
+        } catch (IOException e) {
+            e.printStackTrace();
+        } finally {
+            try {
+                os.close();
+                is.close();
+            } catch (IOException e) {
+                e.printStackTrace();
+            }
+        }
+    }
+
+    public static void copyDirectoryFromAssets(Context appCtx, String srcDir, String dstDir) {
+        if (srcDir.isEmpty() || dstDir.isEmpty()) {
+            return;
+        }
+        try {
+            if (!new File(dstDir).exists()) {
+                new File(dstDir).mkdirs();
+            }
+            for (String fileName : appCtx.getAssets().list(srcDir)) {
+                String srcSubPath = srcDir + File.separator + fileName;
+                String dstSubPath = dstDir + File.separator + fileName;
+                if (new File(srcSubPath).isDirectory()) {
+                    copyDirectoryFromAssets(appCtx, srcSubPath, dstSubPath);
+                } else {
+                    copyFileFromAssets(appCtx, srcSubPath, dstSubPath);
+                }
+            }
+        } catch (Exception e) {
+            e.printStackTrace();
+        }
+    }
+
+    public static float[] parseFloatsFromString(String string, String delimiter) {
+        String[] pieces = string.trim().toLowerCase().split(delimiter);
+        float[] floats = new float[pieces.length];
+        for (int i = 0; i < pieces.length; i++) {
+            floats[i] = Float.parseFloat(pieces[i].trim());
+        }
+        return floats;
+    }
+
+    public static long[] parseLongsFromString(String string, String delimiter) {
+        String[] pieces = string.trim().toLowerCase().split(delimiter);
+        long[] longs = new long[pieces.length];
+        for (int i = 0; i < pieces.length; i++) {
+            longs[i] = Long.parseLong(pieces[i].trim());
+        }
+        return longs;
+    }
+
+    public static String getSDCardDirectory() {
+        return Environment.getExternalStorageDirectory().getAbsolutePath();
+    }
+
+    public static boolean isSupportedNPU() {
+        String hardware = android.os.Build.HARDWARE;
+        return hardware.equalsIgnoreCase("kirin810") || hardware.equalsIgnoreCase("kirin990");
+    }
+}

deploy/lite/humanseg-android-demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/ImgSegActivity.java

+package com.baidu.paddle.lite.demo.segmentation;
+
+import android.content.Intent;
+import android.content.SharedPreferences;
+import android.graphics.Bitmap;
+import android.graphics.BitmapFactory;
+import android.os.Bundle;
+import android.preference.PreferenceManager;
+import android.text.method.ScrollingMovementMethod;
+import android.util.Log;
+import android.view.Menu;
+import android.widget.ImageView;
+import android.widget.TextView;
+import android.widget.Toast;
+
+import com.baidu.paddle.lite.demo.CommonActivity;
+import com.baidu.paddle.lite.demo.R;
+import com.baidu.paddle.lite.demo.Utils;
+import com.baidu.paddle.lite.demo.segmentation.config.Config;
+import com.baidu.paddle.lite.demo.segmentation.preprocess.Preprocess;
+import com.baidu.paddle.lite.demo.segmentation.visual.Visualize;
+
+import java.io.File;
+import java.io.IOException;
+import java.io.InputStream;
+
+public class ImgSegActivity extends CommonActivity {
+    private static final String TAG = ImgSegActivity.class.getSimpleName();
+
+    protected TextView tvInputSetting;
+    protected ImageView ivInputImage;
+    protected TextView tvOutputResult;
+    protected TextView tvInferenceTime;
+
+    // model config
+    Config config = new Config();
+
+    protected ImgSegPredictor predictor = new ImgSegPredictor();
+
+    Preprocess preprocess = new Preprocess();
+
+    Visualize visualize = new Visualize();
+
+    @Override
+    protected void onCreate(Bundle savedInstanceState) {
+
+        super.onCreate(savedInstanceState);
+        setContentView(R.layout.activity_img_seg);
+        tvInputSetting = findViewById(R.id.tv_input_setting);
+        ivInputImage = findViewById(R.id.iv_input_image);
+        tvInferenceTime = findViewById(R.id.tv_inference_time);
+        tvOutputResult = findViewById(R.id.tv_output_result);
+        tvInputSetting.setMovementMethod(ScrollingMovementMethod.getInstance());
+        tvOutputResult.setMovementMethod(ScrollingMovementMethod.getInstance());
+    }
+
+    @Override
+    public boolean onLoadModel() {
+        return super.onLoadModel() && predictor.init(ImgSegActivity.this, config);
+    }
+
+    @Override
+    public boolean onRunModel() {
+        return super.onRunModel() && predictor.isLoaded() && predictor.runModel(preprocess,visualize);
+    }
+
+    @Override
+    public void onLoadModelSuccessed() {
+        super.onLoadModelSuccessed();
+        // load test image from file_paths and run model
+        try {
+            if (config.imagePath.isEmpty()) {
+                return;
+            }
+            Bitmap image = null;
+            // read test image file from custom file_paths if the first character of mode file_paths is '/', otherwise read test
+            // image file from assets
+            if (!config.imagePath.substring(0, 1).equals("/")) {
+                InputStream imageStream = getAssets().open(config.imagePath);
+                image = BitmapFactory.decodeStream(imageStream);
+            } else {
+                if (!new File(config.imagePath).exists()) {
+                    return;
+                }
+                image = BitmapFactory.decodeFile(config.imagePath);
+            }
+            if (image != null && predictor.isLoaded()) {
+                predictor.setInputImage(image);
+                runModel();
+            }
+        } catch (IOException e) {
+            Toast.makeText(ImgSegActivity.this, "Load image failed!", Toast.LENGTH_SHORT).show();
+            e.printStackTrace();
+        }
+    }
+
+    @Override
+    public void onLoadModelFailed() {
+        super.onLoadModelFailed();
+    }
+
+    @Override
+    public void onRunModelSuccessed() {
+        super.onRunModelSuccessed();
+        // obtain results and update UI
+        tvInferenceTime.setText("Inference time: " + predictor.inferenceTime() + " ms");
+        Bitmap outputImage = predictor.outputImage();
+        if (outputImage != null) {
+            ivInputImage.setImageBitmap(outputImage);
+        }
+        tvOutputResult.setText(predictor.outputResult());
+        tvOutputResult.scrollTo(0, 0);
+    }
+
+    @Override
+    public void onRunModelFailed() {
+        super.onRunModelFailed();
+    }
+
+    @Override
+    public void onImageChanged(Bitmap image) {
+        super.onImageChanged(image);
+        // rerun model if users pick test image from gallery or camera
+        if (image != null && predictor.isLoaded()) {
+//            predictor.setConfig(config);
+            predictor.setInputImage(image);
+            runModel();
+        }
+    }
+
+    @Override
+    public void onImageChanged(String path) {
+        super.onImageChanged(path);
+        Bitmap image = BitmapFactory.decodeFile(path);
+        predictor.setInputImage(image);
+            runModel();
+    }
+    public void onSettingsClicked() {
+        super.onSettingsClicked();
+        startActivity(new Intent(ImgSegActivity.this, ImgSegSettingsActivity.class));
+    }
+
+    @Override
+    public boolean onPrepareOptionsMenu(Menu menu) {
+        boolean isLoaded = predictor.isLoaded();
+        menu.findItem(R.id.open_gallery).setEnabled(isLoaded);
+        menu.findItem(R.id.take_photo).setEnabled(isLoaded);
+        return super.onPrepareOptionsMenu(menu);
+    }
+
+    @Override
+    protected void onResume() {
+        Log.i(TAG,"begin onResume");
+        super.onResume();
+
+        SharedPreferences sharedPreferences = PreferenceManager.getDefaultSharedPreferences(this);
+        boolean settingsChanged = false;
+        String model_path = sharedPreferences.getString(getString(R.string.ISG_MODEL_PATH_KEY),
+                getString(R.string.ISG_MODEL_PATH_DEFAULT));
+        String label_path = sharedPreferences.getString(getString(R.string.ISG_LABEL_PATH_KEY),
+                getString(R.string.ISG_LABEL_PATH_DEFAULT));
+        String image_path = sharedPreferences.getString(getString(R.string.ISG_IMAGE_PATH_KEY),
+                getString(R.string.ISG_IMAGE_PATH_DEFAULT));
+        settingsChanged |= !model_path.equalsIgnoreCase(config.modelPath);
+        settingsChanged |= !label_path.equalsIgnoreCase(config.labelPath);
+        settingsChanged |= !image_path.equalsIgnoreCase(config.imagePath);
+        int cpu_thread_num = Integer.parseInt(sharedPreferences.getString(getString(R.string.ISG_CPU_THREAD_NUM_KEY),
+                getString(R.string.ISG_CPU_THREAD_NUM_DEFAULT)));
+        settingsChanged |= cpu_thread_num != config.cpuThreadNum;
+        String cpu_power_mode =
+                sharedPreferences.getString(getString(R.string.ISG_CPU_POWER_MODE_KEY),
+                        getString(R.string.ISG_CPU_POWER_MODE_DEFAULT));
+        settingsChanged |= !cpu_power_mode.equalsIgnoreCase(config.cpuPowerMode);
+        String input_color_format =
+                sharedPreferences.getString(getString(R.string.ISG_INPUT_COLOR_FORMAT_KEY),
+                        getString(R.string.ISG_INPUT_COLOR_FORMAT_DEFAULT));
+        settingsChanged |= !input_color_format.equalsIgnoreCase(config.inputColorFormat);
+        long[] input_shape =
+                Utils.parseLongsFromString(sharedPreferences.getString(getString(R.string.ISG_INPUT_SHAPE_KEY),
+                        getString(R.string.ISG_INPUT_SHAPE_DEFAULT)), ",");
+
+        settingsChanged |= input_shape.length != config.inputShape.length;
+
+        if (!settingsChanged) {
+            for (int i = 0; i < input_shape.length; i++) {
+                settingsChanged |= input_shape[i] != config.inputShape[i];
+            }
+        }
+
+        if (settingsChanged) {
+            config.init(model_path,label_path,image_path,cpu_thread_num,cpu_power_mode,
+                    input_color_format,input_shape);
+            preprocess.init(config);
+            // update UI
+            tvInputSetting.setText("Model: " + config.modelPath.substring(config.modelPath.lastIndexOf("/") + 1) + "\n" + "CPU" +
+                    " Thread Num: " + Integer.toString(config.cpuThreadNum) + "\n" + "CPU Power Mode: " + config.cpuPowerMode);
+            tvInputSetting.scrollTo(0, 0);
+            // reload model if configure has been changed
+            loadModel();
+        }
+    }
+
+    @Override
+    protected void onDestroy() {
+        if (predictor != null) {
+            predictor.releaseModel();
+        }
+        super.onDestroy();
+    }
+}

deploy/lite/humanseg-android-demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/ImgSegPredictor.java

+package com.baidu.paddle.lite.demo.segmentation;
+
+import android.content.Context;
+import android.graphics.Bitmap;
+import android.util.Log;
+
+import com.baidu.paddle.lite.Tensor;
+import com.baidu.paddle.lite.demo.Predictor;
+import com.baidu.paddle.lite.demo.segmentation.config.Config;
+import com.baidu.paddle.lite.demo.segmentation.preprocess.Preprocess;
+import com.baidu.paddle.lite.demo.segmentation.visual.Visualize;
+
+import java.io.InputStream;
+import java.util.Date;
+import java.util.Vector;
+
+import static android.graphics.Color.blue;
+import static android.graphics.Color.green;
+import static android.graphics.Color.red;
+
+public class ImgSegPredictor extends Predictor {
+    private static final String TAG = ImgSegPredictor.class.getSimpleName();
+    protected Vector<String> wordLabels = new Vector<String>();
+
+    Config config;
+
+    protected Bitmap inputImage = null;
+    protected Bitmap scaledImage = null;
+    protected Bitmap outputImage = null;
+    protected String outputResult = "";
+    protected float preprocessTime = 0;
+    protected float postprocessTime = 0;
+
+    public ImgSegPredictor() {
+        super();
+    }
+
+    public boolean init(Context appCtx, Config config) {
+
+        if (config.inputShape.length != 4) {
+            Log.i(TAG, "size of input shape should be: 4");
+            return false;
+        }
+        if (config.inputShape[0] != 1) {
+            Log.i(TAG, "only one batch is supported in the image classification demo, you can use any batch size in " +
+                    "your Apps!");
+            return false;
+        }
+        if (config.inputShape[1] != 1 && config.inputShape[1] != 3) {
+            Log.i(TAG, "only one/three channels are supported in the image classification demo, you can use any " +
+                    "channel size in your Apps!");
+            return false;
+        }
+        if (!config.inputColorFormat.equalsIgnoreCase("RGB") && !config.inputColorFormat.equalsIgnoreCase("BGR")) {
+            Log.i(TAG, "only RGB and BGR color format is supported.");
+            return false;
+        }
+        super.init(appCtx, config.modelPath, config.cpuThreadNum, config.cpuPowerMode);
+        if (!super.isLoaded()) {
+            return false;
+        }
+        this.config = config;
+
+        return isLoaded;
+    }
+
+    protected boolean loadLabel(String labelPath) {
+        wordLabels.clear();
+        // load word labels from file
+        try {
+            InputStream assetsInputStream = appCtx.getAssets().open(labelPath);
+            int available = assetsInputStream.available();
+            byte[] lines = new byte[available];
+            assetsInputStream.read(lines);
+            assetsInputStream.close();
+            String words = new String(lines);
+            String[] contents = words.split("\n");
+            for (String content : contents) {
+                wordLabels.add(content);
+            }
+            Log.i(TAG, "word label size: " + wordLabels.size());
+        } catch (Exception e) {
+            Log.e(TAG, e.getMessage());
+            return false;
+        }
+        return true;
+    }
+
+    public Tensor getInput(int idx) {
+        return super.getInput(idx);
+    }
+
+    public Tensor getOutput(int idx) {
+        return super.getOutput(idx);
+    }
+
+    public boolean runModel(Bitmap image) {
+        setInputImage(image);
+        return runModel();
+    }
+
+    public boolean runModel(Preprocess preprocess, Visualize visualize) {
+        if (inputImage == null) {
+            return false;
+        }
+
+        // set input shape
+        Tensor inputTensor = getInput(0);
+
+        inputTensor.resize(config.inputShape);
+
+        // pre-process image
+        Date start = new Date();
+
+        preprocess.init(config);
+
+        preprocess.to_array(scaledImage);
+
+        // feed input tensor with pre-processed data
+
+        inputTensor.setData(preprocess.inputData);
+
+        Date end = new Date();
+        preprocessTime = (float) (end.getTime() - start.getTime());
+
+        // inference
+        super.runModel();
+
+        Tensor outputTensor = getOutput(0);
+
+        // post-process
+        this.outputImage = visualize.draw(inputImage,outputTensor);
+
+        postprocessTime = (float) (end.getTime() - start.getTime());
+
+        start = new Date();
+        outputResult = new String();
+        end = new Date();
+
+        return true;
+    }
+
+    public void setConfig(Config config){
+        this.config = config;
+    }
+
+    public Bitmap inputImage() {
+        return inputImage;
+    }
+
+    public Bitmap outputImage() {
+        return outputImage;
+    }
+
+    public String outputResult() {
+        return outputResult;
+    }
+
+    public float preprocessTime() {
+        return preprocessTime;
+    }
+
+    public float postprocessTime() {
+        return postprocessTime;
+    }
+
+    public void setInputImage(Bitmap image) {
+        if (image == null) {
+            return;
+        }
+        // scale image to the size of input tensor
+        Bitmap rgbaImage = image.copy(Bitmap.Config.ARGB_8888, true);
+
+        Bitmap scaleImage = Bitmap.createScaledBitmap(rgbaImage, (int) this.config.inputShape[3], (int) this.config.inputShape[2], true);
+        this.inputImage = rgbaImage;
+        this.scaledImage = scaleImage;
+    }
+
+}

deploy/lite/humanseg-android-demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/ImgSegSettingsActivity.java

+package com.baidu.paddle.lite.demo.segmentation;
+
+import android.content.SharedPreferences;
+import android.os.Bundle;
+import android.preference.CheckBoxPreference;
+import android.preference.EditTextPreference;
+import android.preference.ListPreference;
+import android.support.v7.app.ActionBar;
+
+import com.baidu.paddle.lite.demo.AppCompatPreferenceActivity;
+import com.baidu.paddle.lite.demo.R;
+import com.baidu.paddle.lite.demo.Utils;
+
+import java.util.ArrayList;
+import java.util.List;
+
+public class ImgSegSettingsActivity extends AppCompatPreferenceActivity implements SharedPreferences.OnSharedPreferenceChangeListener {
+    ListPreference lpChoosePreInstalledModel = null;
+    CheckBoxPreference cbEnableCustomSettings = null;
+    EditTextPreference etModelPath = null;
+    EditTextPreference etLabelPath = null;
+    EditTextPreference etImagePath = null;
+    ListPreference lpCPUThreadNum = null;
+    ListPreference lpCPUPowerMode = null;
+    ListPreference lpInputColorFormat = null;
+    EditTextPreference etInputShape = null;
+    EditTextPreference etInputMean = null;
+    EditTextPreference etInputStd = null;
+
+    List<String> preInstalledModelPaths = null;
+    List<String> preInstalledLabelPaths = null;
+    List<String> preInstalledImagePaths = null;
+    List<String> preInstalledInputShapes = null;
+    List<String> preInstalledCPUThreadNums = null;
+    List<String> preInstalledCPUPowerModes = null;
+    List<String> preInstalledInputColorFormats = null;
+    List<String> preInstalledInputMeans = null;
+    List<String> preInstalledInputStds = null;
+
+    @Override
+    public void onCreate(Bundle savedInstanceState) {
+        super.onCreate(savedInstanceState);
+        addPreferencesFromResource(R.xml.settings_img_seg);
+        ActionBar supportActionBar = getSupportActionBar();
+        if (supportActionBar != null) {
+            supportActionBar.setDisplayHomeAsUpEnabled(true);
+        }
+
+        // initialized pre-installed models
+        preInstalledModelPaths = new ArrayList<String>();
+        preInstalledLabelPaths = new ArrayList<String>();
+        preInstalledImagePaths = new ArrayList<String>();
+        preInstalledInputShapes = new ArrayList<String>();
+        preInstalledCPUThreadNums = new ArrayList<String>();
+        preInstalledCPUPowerModes = new ArrayList<String>();
+        preInstalledInputColorFormats = new ArrayList<String>();
+        preInstalledInputMeans = new ArrayList<String>();
+        preInstalledInputStds = new ArrayList<String>();
+        // add deeplab_mobilenet_for_cpu
+        preInstalledModelPaths.add(getString(R.string.ISG_MODEL_PATH_DEFAULT));
+        preInstalledLabelPaths.add(getString(R.string.ISG_LABEL_PATH_DEFAULT));
+        preInstalledImagePaths.add(getString(R.string.ISG_IMAGE_PATH_DEFAULT));
+        preInstalledCPUThreadNums.add(getString(R.string.ISG_CPU_THREAD_NUM_DEFAULT));
+        preInstalledCPUPowerModes.add(getString(R.string.ISG_CPU_POWER_MODE_DEFAULT));
+        preInstalledInputColorFormats.add(getString(R.string.ISG_INPUT_COLOR_FORMAT_DEFAULT));
+        preInstalledInputShapes.add(getString(R.string.ISG_INPUT_SHAPE_DEFAULT));
+
+        // initialize UI components
+        lpChoosePreInstalledModel =
+                (ListPreference) findPreference(getString(R.string.ISG_CHOOSE_PRE_INSTALLED_MODEL_KEY));
+        String[] preInstalledModelNames = new String[preInstalledModelPaths.size()];
+        for (int i = 0; i < preInstalledModelPaths.size(); i++) {
+            preInstalledModelNames[i] =
+                    preInstalledModelPaths.get(i).substring(preInstalledModelPaths.get(i).lastIndexOf("/") + 1);
+        }
+        lpChoosePreInstalledModel.setEntries(preInstalledModelNames);
+        lpChoosePreInstalledModel.setEntryValues(preInstalledModelPaths.toArray(new String[preInstalledModelPaths.size()]));
+        cbEnableCustomSettings =
+                (CheckBoxPreference) findPreference(getString(R.string.ISG_ENABLE_CUSTOM_SETTINGS_KEY));
+        etModelPath = (EditTextPreference) findPreference(getString(R.string.ISG_MODEL_PATH_KEY));
+        etModelPath.setTitle("Model Path (SDCard: " + Utils.getSDCardDirectory() + ")");
+        etLabelPath = (EditTextPreference) findPreference(getString(R.string.ISG_LABEL_PATH_KEY));
+        etImagePath = (EditTextPreference) findPreference(getString(R.string.ISG_IMAGE_PATH_KEY));
+        lpCPUThreadNum =
+                (ListPreference) findPreference(getString(R.string.ISG_CPU_THREAD_NUM_KEY));
+        lpCPUPowerMode =
+                (ListPreference) findPreference(getString(R.string.ISG_CPU_POWER_MODE_KEY));
+        lpInputColorFormat =
+                (ListPreference) findPreference(getString(R.string.ISG_INPUT_COLOR_FORMAT_KEY));
+        etInputShape = (EditTextPreference) findPreference(getString(R.string.ISG_INPUT_SHAPE_KEY));
+    }
+
+    private void reloadPreferenceAndUpdateUI() {
+        SharedPreferences sharedPreferences = getPreferenceScreen().getSharedPreferences();
+        boolean enableCustomSettings =
+                sharedPreferences.getBoolean(getString(R.string.ISG_ENABLE_CUSTOM_SETTINGS_KEY), false);
+        String modelPath = sharedPreferences.getString(getString(R.string.ISG_CHOOSE_PRE_INSTALLED_MODEL_KEY),
+                getString(R.string.ISG_MODEL_PATH_DEFAULT));
+        int modelIdx = lpChoosePreInstalledModel.findIndexOfValue(modelPath);
+        if (modelIdx >= 0 && modelIdx < preInstalledModelPaths.size()) {
+            if (!enableCustomSettings) {
+                SharedPreferences.Editor editor = sharedPreferences.edit();
+                editor.putString(getString(R.string.ISG_MODEL_PATH_KEY), preInstalledModelPaths.get(modelIdx));
+                editor.putString(getString(R.string.ISG_LABEL_PATH_KEY), preInstalledLabelPaths.get(modelIdx));
+                editor.putString(getString(R.string.ISG_IMAGE_PATH_KEY), preInstalledImagePaths.get(modelIdx));
+                editor.putString(getString(R.string.ISG_CPU_THREAD_NUM_KEY), preInstalledCPUThreadNums.get(modelIdx));
+                editor.putString(getString(R.string.ISG_CPU_POWER_MODE_KEY), preInstalledCPUPowerModes.get(modelIdx));
+                editor.putString(getString(R.string.ISG_INPUT_COLOR_FORMAT_KEY),
+                        preInstalledInputColorFormats.get(modelIdx));
+                editor.putString(getString(R.string.ISG_INPUT_SHAPE_KEY), preInstalledInputShapes.get(modelIdx));
+                editor.commit();
+            }
+            lpChoosePreInstalledModel.setSummary(modelPath);
+        }
+        cbEnableCustomSettings.setChecked(enableCustomSettings);
+        etModelPath.setEnabled(enableCustomSettings);
+        etLabelPath.setEnabled(enableCustomSettings);
+        etImagePath.setEnabled(enableCustomSettings);
+        lpCPUThreadNum.setEnabled(enableCustomSettings);
+        lpCPUPowerMode.setEnabled(enableCustomSettings);
+        lpInputColorFormat.setEnabled(enableCustomSettings);
+        etInputShape.setEnabled(enableCustomSettings);
+        etInputMean.setEnabled(enableCustomSettings);
+        etInputStd.setEnabled(enableCustomSettings);
+        modelPath = sharedPreferences.getString(getString(R.string.ISG_MODEL_PATH_KEY),
+                getString(R.string.ISG_MODEL_PATH_DEFAULT));
+        String labelPath = sharedPreferences.getString(getString(R.string.ISG_LABEL_PATH_KEY),
+                getString(R.string.ISG_LABEL_PATH_DEFAULT));
+        String imagePath = sharedPreferences.getString(getString(R.string.ISG_IMAGE_PATH_KEY),
+                getString(R.string.ISG_IMAGE_PATH_DEFAULT));
+        String cpuThreadNum = sharedPreferences.getString(getString(R.string.ISG_CPU_THREAD_NUM_KEY),
+                getString(R.string.ISG_CPU_THREAD_NUM_DEFAULT));
+        String cpuPowerMode = sharedPreferences.getString(getString(R.string.ISG_CPU_POWER_MODE_KEY),
+                getString(R.string.ISG_CPU_POWER_MODE_DEFAULT));
+        String inputColorFormat = sharedPreferences.getString(getString(R.string.ISG_INPUT_COLOR_FORMAT_KEY),
+                getString(R.string.ISG_INPUT_COLOR_FORMAT_DEFAULT));
+        String inputShape = sharedPreferences.getString(getString(R.string.ISG_INPUT_SHAPE_KEY),
+                getString(R.string.ISG_INPUT_SHAPE_DEFAULT));
+        etModelPath.setSummary(modelPath);
+        etModelPath.setText(modelPath);
+        etLabelPath.setSummary(labelPath);
+        etLabelPath.setText(labelPath);
+        etImagePath.setSummary(imagePath);
+        etImagePath.setText(imagePath);
+        lpCPUThreadNum.setValue(cpuThreadNum);
+        lpCPUThreadNum.setSummary(cpuThreadNum);
+        lpCPUPowerMode.setValue(cpuPowerMode);
+        lpCPUPowerMode.setSummary(cpuPowerMode);
+        lpInputColorFormat.setValue(inputColorFormat);
+        lpInputColorFormat.setSummary(inputColorFormat);
+        etInputShape.setSummary(inputShape);
+        etInputShape.setText(inputShape);
+    }
+
+    @Override
+    protected void onResume() {
+        super.onResume();
+        getPreferenceScreen().getSharedPreferences().registerOnSharedPreferenceChangeListener(this);
+        reloadPreferenceAndUpdateUI();
+    }
+
+    @Override
+    protected void onPause() {
+        super.onPause();
+        getPreferenceScreen().getSharedPreferences().unregisterOnSharedPreferenceChangeListener(this);
+    }
+
+    @Override
+    public void onSharedPreferenceChanged(SharedPreferences sharedPreferences, String key) {
+        if (key.equals(getString(R.string.ISG_CHOOSE_PRE_INSTALLED_MODEL_KEY))) {
+            SharedPreferences.Editor editor = sharedPreferences.edit();
+            editor.putBoolean(getString(R.string.ISG_ENABLE_CUSTOM_SETTINGS_KEY), false);
+            editor.commit();
+        }
+        reloadPreferenceAndUpdateUI();
+    }
+}

deploy/lite/humanseg-android-demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/config/Config.java

+package com.baidu.paddle.lite.demo.segmentation.config;
+
+import android.graphics.Bitmap;
+
+public class Config {
+
+    public String modelPath = "";
+    public String labelPath = "";
+    public String imagePath = "";
+    public int cpuThreadNum = 1;
+    public String cpuPowerMode = "";
+
+    public String inputColorFormat = "";
+    public long[] inputShape = new long[]{};
+
+
+    public void init(String modelPath, String labelPath, String imagePath, int cpuThreadNum,
+                     String cpuPowerMode, String inputColorFormat,long[] inputShape){
+
+        this.modelPath = modelPath;
+        this.labelPath = labelPath;
+        this.imagePath = imagePath;
+        this.cpuThreadNum = cpuThreadNum;
+        this.cpuPowerMode = cpuPowerMode;
+
+        this.inputColorFormat = inputColorFormat;
+        this.inputShape = inputShape;
+    }
+
+    public void setInputShape(Bitmap inputImage){
+        this.inputShape[0] = 1;
+        this.inputShape[1] = 3;
+
+        this.inputShape[2] = inputImage.getHeight();
+        this.inputShape[3] = inputImage.getWidth();
+
+    }
+
+}

deploy/lite/humanseg-android-demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/preprocess/Preprocess.java

+package com.baidu.paddle.lite.demo.segmentation.preprocess;
+
+import android.graphics.Bitmap;
+import android.util.Log;
+
+import com.baidu.paddle.lite.demo.segmentation.config.Config;
+
+import static android.graphics.Color.blue;
+import static android.graphics.Color.green;
+import static android.graphics.Color.red;
+
+public class Preprocess {
+
+    private static final String TAG = Preprocess.class.getSimpleName();
+
+    Config config;
+    int channels;
+    int width;
+    int height;
+
+    public  float[] inputData;
+
+    public void init(Config config){
+        this.config = config;
+        this.channels = (int) config.inputShape[1];
+        this.height = (int) config.inputShape[2];
+        this.width = (int) config.inputShape[3];
+        this.inputData = new float[channels * width * height];
+    }
+
+    public boolean to_array(Bitmap inputImage){
+
+        if (channels == 3) {
+            int[] channelIdx = null;
+            if (config.inputColorFormat.equalsIgnoreCase("RGB")) {
+                channelIdx = new int[]{0, 1, 2};
+            } else if (config.inputColorFormat.equalsIgnoreCase("BGR")) {
+                channelIdx = new int[]{2, 1, 0};
+            } else {
+                Log.i(TAG, "unknown color format " + config.inputColorFormat + ", only RGB and BGR color format is " +
+                        "supported!");
+                return false;
+            }
+            int[] channelStride = new int[]{width * height, width * height * 2};
+
+            for (int y = 0; y < height; y++) {
+                for (int x = 0; x < width; x++) {
+                    int color = inputImage.getPixel(x, y);
+                    float[] rgb = new float[]{(float) red(color) , (float) green(color) ,
+                            (float) blue(color)};
+                    inputData[y * width + x] = rgb[channelIdx[0]] ;
+                    inputData[y * width + x + channelStride[0]] = rgb[channelIdx[1]] ;
+                    inputData[y * width + x + channelStride[1]] = rgb[channelIdx[2]];
+                }
+            }
+        } else if (channels == 1) {
+            for (int y = 0; y < height; y++) {
+                for (int x = 0; x < width; x++) {
+                    int color = inputImage.getPixel(x, y);
+                    float gray = (float) (red(color) + green(color) + blue(color));
+                    inputData[y * width + x] = gray;
+                }
+            }
+        } else {
+            Log.i(TAG, "unsupported channel size " + Integer.toString(channels) + ",  only channel 1 and 3 is " +
+                    "supported!");
+            return false;
+        }
+        return true;
+
+    }
+
+}

deploy/lite/humanseg-android-demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/visual/Visualize.java

+package com.baidu.paddle.lite.demo.segmentation.visual;
+
+import android.graphics.Bitmap;
+import android.graphics.Canvas;
+import android.graphics.Matrix;
+import android.graphics.Paint;
+import android.util.Log;
+
+import com.baidu.paddle.lite.Tensor;
+
+public class Visualize {
+    private static final String TAG = Visualize.class.getSimpleName();
+
+    public Bitmap draw(Bitmap inputImage, Tensor outputTensor){
+
+        final int[] colors_map = {0xFF000000, 0xFFFFFF00};
+
+        float[] output = outputTensor.getFloatData();
+        long outputShape[] = outputTensor.shape();
+        long outputSize = 1;
+
+        for (long s : outputShape) {
+            outputSize *= s;
+        }
+
+        int[] objectColor = new int[(int)outputSize];
+
+        for(int i=0;i<output.length;i++){
+            objectColor[i] = colors_map[(int)output[i]];
+        }
+
+        Bitmap.Config config = inputImage.getConfig();
+        Bitmap outputImage = null;
+        if(outputShape.length==3){
+            outputImage = Bitmap.createBitmap(objectColor, (int)outputShape[2], (int)outputShape[1], config);
+            outputImage = Bitmap.createScaledBitmap(outputImage, inputImage.getWidth(), inputImage.getHeight(),true);
+        }
+
+        else if (outputShape.length==4){
+            outputImage = Bitmap.createBitmap(objectColor, (int)outputShape[3], (int)outputShape[2], config);
+        }
+        Bitmap bmOverlay = Bitmap.createBitmap(inputImage.getWidth(), inputImage.getHeight() , inputImage.getConfig());
+        Canvas canvas = new Canvas(bmOverlay);
+        canvas.drawBitmap(inputImage, new Matrix(), null);
+
+        Paint paint = new Paint();
+        paint.setAlpha(0x80);
+        canvas.drawBitmap(outputImage, 0, 0, paint);
+
+        return bmOverlay;
+
+    }
+}

deploy/lite/humanseg-android-demo/app/src/main/res/drawable-v24/ic_launcher_foreground.xml

+<vector xmlns:android="http://schemas.android.com/apk/res/android"
+    xmlns:aapt="http://schemas.android.com/aapt"
+    android:width="108dp"
+    android:height="108dp"
+    android:viewportWidth="108"
+    android:viewportHeight="108">
+    <path
+        android:fillType="evenOdd"
+        android:pathData="M32,64C32,64 38.39,52.99 44.13,50.95C51.37,48.37 70.14,49.57 70.14,49.57L108.26,87.69L108,109.01L75.97,107.97L32,64Z"
+        android:strokeWidth="1"
+        android:strokeColor="#00000000">
+        <aapt:attr name="android:fillColor">
+            <gradient
+                android:endX="78.5885"
+                android:endY="90.9159"
+                android:startX="48.7653"
+                android:startY="61.0927"
+                android:type="linear">
+                <item
+                    android:color="#44000000"
+                    android:offset="0.0" />
+                <item
+                    android:color="#00000000"
+                    android:offset="1.0" />
+            </gradient>
+        </aapt:attr>
+    </path>
+    <path
+        android:fillColor="#FFFFFF"
+        android:fillType="nonZero"
+        android:pathData="M66.94,46.02L66.94,46.02C72.44,50.07 76,56.61 76,64L32,64C32,56.61 35.56,50.11 40.98,46.06L36.18,41.19C35.45,40.45 35.45,39.3 36.18,38.56C36.91,37.81 38.05,37.81 38.78,38.56L44.25,44.05C47.18,42.57 50.48,41.71 54,41.71C57.48,41.71 60.78,42.57 63.68,44.05L69.11,38.56C69.84,37.81 70.98,37.81 71.71,38.56C72.44,39.3 72.44,40.45 71.71,41.19L66.94,46.02ZM62.94,56.92C64.08,56.92 65,56.01 65,54.88C65,53.76 64.08,52.85 62.94,52.85C61.8,52.85 60.88,53.76 60.88,54.88C60.88,56.01 61.8,56.92 62.94,56.92ZM45.06,56.92C46.2,56.92 47.13,56.01 47.13,54.88C47.13,53.76 46.2,52.85 45.06,52.85C43.92,52.85 43,53.76 43,54.88C43,56.01 43.92,56.92 45.06,56.92Z"
+        android:strokeWidth="1"
+        android:strokeColor="#00000000" />
+</vector>

deploy/lite/humanseg-android-demo/app/src/main/res/drawable/ic_launcher_background.xml

+<?xml version="1.0" encoding="utf-8"?>
+<vector xmlns:android="http://schemas.android.com/apk/res/android"
+    android:width="108dp"
+    android:height="108dp"
+    android:viewportWidth="108"
+    android:viewportHeight="108">
+    <path
+        android:fillColor="#008577"
+        android:pathData="M0,0h108v108h-108z" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M9,0L9,108"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M19,0L19,108"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M29,0L29,108"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M39,0L39,108"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M49,0L49,108"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M59,0L59,108"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M69,0L69,108"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M79,0L79,108"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M89,0L89,108"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M99,0L99,108"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M0,9L108,9"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M0,19L108,19"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M0,29L108,29"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M0,39L108,39"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M0,49L108,49"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M0,59L108,59"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M0,69L108,69"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M0,79L108,79"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M0,89L108,89"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M0,99L108,99"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M19,29L89,29"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M19,39L89,39"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M19,49L89,49"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M19,59L89,59"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M19,69L89,69"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M19,79L89,79"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M29,19L29,89"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M39,19L39,89"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M49,19L49,89"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M59,19L59,89"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M69,19L69,89"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+    <path
+        android:fillColor="#00000000"
+        android:pathData="M79,19L79,89"
+        android:strokeWidth="0.8"
+        android:strokeColor="#33FFFFFF" />
+</vector>

deploy/lite/humanseg-android-demo/app/src/main/res/layout/activity_img_seg.xml

+<?xml version="1.0" encoding="utf-8"?>
+<android.support.constraint.ConstraintLayout xmlns:android="http://schemas.android.com/apk/res/android"
+                                             xmlns:app="http://schemas.android.com/apk/res-auto"
+                                             xmlns:tools="http://schemas.android.com/tools"
+                                             android:layout_width="match_parent"
+                                             android:layout_height="match_parent"
+                                             tools:context=".segmentation.ImgSegActivity">
+
+    <RelativeLayout
+            android:layout_width="match_parent"
+            android:layout_height="match_parent">
+
+        <LinearLayout
+                android:id="@+id/v_input_info"
+                android:layout_width="fill_parent"
+                android:layout_height="wrap_content"
+                android:layout_alignParentTop="true"
+                android:orientation="vertical">
+            <TextView
+                    android:id="@+id/tv_input_setting"
+                    android:layout_width="wrap_content"
+                    android:layout_height="wrap_content"
+                    android:scrollbars="vertical"
+                    android:layout_marginLeft="12dp"
+                    android:layout_marginRight="12dp"
+                    android:layout_marginTop="10dp"
+                    android:layout_marginBottom="5dp"
+                    android:lineSpacingExtra="4dp"
+                    android:singleLine="false"
+                    android:maxLines="6"
+                    android:text=""/>
+
+        </LinearLayout>
+
+        <RelativeLayout
+                android:layout_width="match_parent"
+                android:layout_height="match_parent"
+                android:layout_above="@+id/v_output_info"
+                android:layout_below="@+id/v_input_info">
+
+            <ImageView
+                    android:id="@+id/iv_input_image"
+                    android:layout_width="400dp"
+                    android:layout_height="400dp"
+                    android:layout_centerHorizontal="true"
+                    android:layout_centerVertical="true"
+                    android:layout_marginLeft="12dp"
+                    android:layout_marginRight="12dp"
+                    android:layout_marginTop="5dp"
+                    android:layout_marginBottom="5dp"
+                    android:adjustViewBounds="true"
+                    android:scaleType="fitCenter"/>
+        </RelativeLayout>
+
+
+        <RelativeLayout
+                android:id="@+id/v_output_info"
+                android:layout_width="wrap_content"
+                android:layout_height="wrap_content"
+                android:layout_alignParentBottom="true"
+                android:layout_centerHorizontal="true">
+
+            <TextView
+                    android:id="@+id/tv_output_result"
+                    android:layout_width="wrap_content"
+                    android:layout_height="wrap_content"
+                    android:layout_alignParentTop="true"
+                    android:layout_centerHorizontal="true"
+                    android:layout_centerVertical="true"
+                    android:scrollbars="vertical"
+                    android:layout_marginLeft="12dp"
+                    android:layout_marginRight="12dp"
+                    android:layout_marginTop="5dp"
+                    android:layout_marginBottom="5dp"
+                    android:textAlignment="center"
+                    android:lineSpacingExtra="5dp"
+                    android:singleLine="false"
+                    android:maxLines="5"
+                    android:text=""/>
+
+            <TextView
+                    android:id="@+id/tv_inference_time"
+                    android:layout_width="wrap_content"
+                    android:layout_height="wrap_content"
+                    android:layout_below="@+id/tv_output_result"
+                    android:layout_centerHorizontal="true"
+                    android:layout_centerVertical="true"
+                    android:textAlignment="center"
+                    android:layout_marginLeft="12dp"
+                    android:layout_marginRight="12dp"
+                    android:layout_marginTop="5dp"
+                    android:layout_marginBottom="10dp"
+                    android:text=""/>
+
+        </RelativeLayout>
+
+    </RelativeLayout>
+
+</android.support.constraint.ConstraintLayout>
\ No newline at end of file

deploy/lite/humanseg-android-demo/app/src/main/res/layout/activity_main.xml

+<?xml version="1.0" encoding="utf-8"?>
+<android.support.constraint.ConstraintLayout xmlns:android="http://schemas.android.com/apk/res/android"
+                                             xmlns:app="http://schemas.android.com/apk/res-auto"
+                                             xmlns:tools="http://schemas.android.com/tools"
+                                             android:layout_width="fill_parent"
+                                             android:layout_height="fill_parent"
+                                             tools:context=".MainActivity">
+
+    <ScrollView
+            android:layout_width="fill_parent"
+            android:layout_height="fill_parent"
+            android:fadingEdge="vertical"
+            android:scrollbars="vertical">
+        <LinearLayout
+                android:layout_width="fill_parent"
+                android:layout_height="fill_parent"
+                android:orientation="vertical">
+
+            <LinearLayout
+                    android:layout_width="fill_parent"
+                    android:layout_height="300dp"
+                    android:orientation="horizontal">
+                <RelativeLayout
+                        android:id="@+id/v_img_seg"
+                        android:layout_width="wrap_content"
+                        android:layout_height="fill_parent"
+                        android:layout_weight="1"
+                        android:clickable="true"
+                        android:onClick="onClick">
+
+                    <ImageView
+                            android:id="@+id/iv_img_seg_image"
+                            android:layout_width="200dp"
+                            android:layout_height="200dp"
+                            android:layout_centerHorizontal="true"
+                            android:layout_centerVertical="true"
+                            android:layout_margin="12dp"
+                            android:adjustViewBounds="true"
+                            android:src="@drawable/image_segementation"
+                            android:scaleType="fitCenter"/>
+
+                    <TextView
+                            android:id="@+id/iv_img_seg_title"
+                            android:layout_below="@id/iv_img_seg_image"
+                            android:layout_width="wrap_content"
+                            android:layout_height="wrap_content"
+                            android:layout_centerHorizontal="true"
+                            android:layout_margin="8dp"
+                            android:text="Image Segmentation"
+                            android:textStyle="bold"
+                            android:textAllCaps="false"
+                            android:singleLine="false"/>
+                </RelativeLayout>
+
+            </LinearLayout>
+        </LinearLayout>
+    </ScrollView>
+</android.support.constraint.ConstraintLayout>
\ No newline at end of file

deploy/lite/humanseg-android-demo/app/src/main/res/menu/menu_action_options.xml

+<menu xmlns:android="http://schemas.android.com/apk/res/android"
+      xmlns:app="http://schemas.android.com/apk/res-auto">
+    <group android:id="@+id/pick_image">
+        <item
+                android:id="@+id/open_gallery"
+                android:title="Open Gallery"
+                app:showAsAction="withText"/>
+
+        <item
+                android:id="@+id/take_photo"
+                android:title="Take Photo"
+                app:showAsAction="withText"/>
+    </group>
+
+    <group>
+        <item
+                android:id="@+id/settings"
+                android:title="Settings..."
+                app:showAsAction="withText"/>
+    </group>
+</menu>

deploy/lite/humanseg-android-demo/app/src/main/res/mipmap-anydpi-v26/ic_launcher.xml

+<?xml version="1.0" encoding="utf-8"?>
+<adaptive-icon xmlns:android="http://schemas.android.com/apk/res/android">
+    <background android:drawable="@drawable/ic_launcher_background" />
+    <foreground android:drawable="@drawable/ic_launcher_foreground" />
+</adaptive-icon>
\ No newline at end of file

deploy/lite/humanseg-android-demo/app/src/main/res/mipmap-anydpi-v26/ic_launcher_round.xml

+<?xml version="1.0" encoding="utf-8"?>
+<adaptive-icon xmlns:android="http://schemas.android.com/apk/res/android">
+    <background android:drawable="@drawable/ic_launcher_background" />
+    <foreground android:drawable="@drawable/ic_launcher_foreground" />
+</adaptive-icon>
\ No newline at end of file

deploy/lite/humanseg-android-demo/app/src/main/res/values/arrays.xml

+<?xml version="1.0" encoding="utf-8"?>
+<resources>
+    <string-array name="cpu_thread_num_entries">
+        <item>1 threads</item>
+        <item>2 threads</item>
+        <item>4 threads</item>
+        <item>8 threads</item>
+    </string-array>
+    <string-array name="cpu_thread_num_values">
+        <item>1</item>
+        <item>2</item>
+        <item>4</item>
+        <item>8</item>
+    </string-array>
+    <string-array name="cpu_power_mode_entries">
+        <item>HIGH(only big cores)</item>
+        <item>LOW(only LITTLE cores)</item>
+        <item>FULL(all cores)</item>
+        <item>NO_BIND(depends on system)</item>
+        <item>RAND_HIGH</item>
+        <item>RAND_LOW</item>
+    </string-array>
+    <string-array name="cpu_power_mode_values">
+        <item>LITE_POWER_HIGH</item>
+        <item>LITE_POWER_LOW</item>
+        <item>LITE_POWER_FULL</item>
+        <item>LITE_POWER_NO_BIND</item>
+        <item>LITE_POWER_RAND_HIGH</item>
+        <item>LITE_POWER_RAND_LOW</item>
+    </string-array>
+    <string-array name="input_color_format_entries">
+        <item>BGR color format</item>
+        <item>RGB color format</item>
+    </string-array>
+    <string-array name="input_color_format_values">
+        <item>BGR</item>
+        <item>RGB</item>
+    </string-array>
+</resources>
\ No newline at end of file

deploy/lite/humanseg-android-demo/app/src/main/res/values/colors.xml

+<?xml version="1.0" encoding="utf-8"?>
+<resources>
+    <color name="colorPrimary">#008577</color>
+    <color name="colorPrimaryDark">#00574B</color>
+    <color name="colorAccent">#D81B60</color>
+</resources>

deploy/lite/humanseg-android-demo/app/src/main/res/values/strings.xml

+<resources>
+<string name="app_name">Segmentation-demo</string>
+<!-- image segmentation settings -->
+<string name="ISG_CHOOSE_PRE_INSTALLED_MODEL_KEY">ISG_CHOOSE_PRE_INSTALLED_MODEL_KEY</string>
+<string name="ISG_ENABLE_CUSTOM_SETTINGS_KEY">ISG_ENABLE_CUSTOM_SETTINGS_KEY</string>
+<string name="ISG_MODEL_PATH_KEY">ISG_MODEL_PATH_KEY</string>
+<string name="ISG_LABEL_PATH_KEY">ISG_LABEL_PATH_KEY</string>
+<string name="ISG_IMAGE_PATH_KEY">ISG_IMAGE_PATH_KEY</string>
+<string name="ISG_CPU_THREAD_NUM_KEY">ISG_CPU_THREAD_NUM_KEY</string>
+<string name="ISG_CPU_POWER_MODE_KEY">ISG_CPU_POWER_MODE_KEY</string>
+<string name="ISG_INPUT_COLOR_FORMAT_KEY">ISG_INPUT_COLOR_FORMAT_KEY</string>
+<string name="ISG_INPUT_SHAPE_KEY">ISG_INPUT_SHAPE_KEY</string>
+<string name="ISG_MODEL_PATH_DEFAULT">image_segmentation/models/deeplab_mobilenet_for_cpu</string>
+<string name="ISG_LABEL_PATH_DEFAULT">image_segmentation/labels/label_list</string>
+<string name="ISG_IMAGE_PATH_DEFAULT">image_segmentation/images/human.jpg</string>
+<string name="ISG_CPU_THREAD_NUM_DEFAULT">1</string>
+<string name="ISG_CPU_POWER_MODE_DEFAULT">LITE_POWER_HIGH</string>
+<string name="ISG_INPUT_COLOR_FORMAT_DEFAULT">RGB</string>
+<string name="ISG_INPUT_SHAPE_DEFAULT">1,3,513,513</string>
+</resources>

deploy/lite/humanseg-android-demo/app/src/main/res/values/styles.xml

+<resources>
+
+    <!-- Base application theme. -->
+    <style name="AppTheme" parent="Theme.AppCompat.Light.DarkActionBar">
+        <!-- Customize your theme here. -->
+        <item name="colorPrimary">@color/colorPrimary</item>
+        <item name="colorPrimaryDark">@color/colorPrimaryDark</item>
+        <item name="colorAccent">@color/colorAccent</item>
+        <item name="actionOverflowMenuStyle">@style/OverflowMenuStyle</item>
+    </style>
+
+    <style name="OverflowMenuStyle" parent="Widget.AppCompat.Light.PopupMenu.Overflow">
+        <item name="overlapAnchor">false</item>
+    </style>
+
+    <style name="AppTheme.NoActionBar">
+        <item name="windowActionBar">false</item>
+        <item name="windowNoTitle">true</item>
+    </style>
+
+    <style name="AppTheme.AppBarOverlay" parent="ThemeOverlay.AppCompat.Dark.ActionBar"/>
+
+    <style name="AppTheme.PopupOverlay" parent="ThemeOverlay.AppCompat.Light"/>
+
+</resources>

deploy/lite/humanseg-android-demo/app/src/main/res/xml/settings_img_seg.xml

+<?xml version="1.0" encoding="utf-8"?>
+<PreferenceScreen xmlns:android="http://schemas.android.com/apk/res/android" >
+    <PreferenceCategory android:title="Model Settings">
+        <ListPreference
+                android:defaultValue="@string/ISG_MODEL_PATH_DEFAULT"
+                android:key="@string/ISG_CHOOSE_PRE_INSTALLED_MODEL_KEY"
+                android:negativeButtonText="@null"
+                android:positiveButtonText="@null"
+                android:title="Choose pre-installed models" />
+        <CheckBoxPreference
+                android:defaultValue="false"
+                android:key="@string/ISG_ENABLE_CUSTOM_SETTINGS_KEY"
+                android:summaryOn="Enable"
+                android:summaryOff="Disable"
+                android:title="Enable custom settings"/>
+        <EditTextPreference
+                android:key="@string/ISG_MODEL_PATH_KEY"
+                android:defaultValue="@string/ISG_MODEL_PATH_DEFAULT"
+                android:title="Model Path" />
+        <EditTextPreference
+                android:key="@string/ISG_LABEL_PATH_KEY"
+                android:defaultValue="@string/ISG_LABEL_PATH_DEFAULT"
+                android:title="Label Path" />
+        <EditTextPreference
+                android:key="@string/ISG_IMAGE_PATH_KEY"
+                android:defaultValue="@string/ISG_IMAGE_PATH_DEFAULT"
+                android:title="Image Path" />
+    </PreferenceCategory>
+    <PreferenceCategory android:title="CPU Settings">
+        <ListPreference
+                android:defaultValue="@string/ISG_CPU_THREAD_NUM_DEFAULT"
+                android:key="@string/ISG_CPU_THREAD_NUM_KEY"
+                android:negativeButtonText="@null"
+                android:positiveButtonText="@null"
+                android:title="CPU Thread Num"
+                android:entries="@array/cpu_thread_num_entries"
+                android:entryValues="@array/cpu_thread_num_values"/>
+        <ListPreference
+                android:defaultValue="@string/ISG_CPU_POWER_MODE_DEFAULT"
+                android:key="@string/ISG_CPU_POWER_MODE_KEY"
+                android:negativeButtonText="@null"
+                android:positiveButtonText="@null"
+                android:title="CPU Power Mode"
+                android:entries="@array/cpu_power_mode_entries"
+                android:entryValues="@array/cpu_power_mode_values"/>
+    </PreferenceCategory>
+    <PreferenceCategory android:title="Input Settings">
+        <ListPreference
+                android:defaultValue="@string/ISG_INPUT_COLOR_FORMAT_DEFAULT"
+                android:key="@string/ISG_INPUT_COLOR_FORMAT_KEY"
+                android:negativeButtonText="@null"
+                android:positiveButtonText="@null"
+                android:title="Input Color Format: BGR or RGB"
+                android:entries="@array/input_color_format_entries"
+                android:entryValues="@array/input_color_format_values"/>
+        <EditTextPreference
+                android:key="@string/ISG_INPUT_SHAPE_KEY"
+                android:defaultValue="@string/ISG_INPUT_SHAPE_DEFAULT"
+                android:title="Input Shape: (1,1,h,w) or (1,3,h,w)" />
+    </PreferenceCategory>
+</PreferenceScreen>
+

deploy/lite/humanseg-android-demo/app/src/test/java/com/baidu/paddle/lite/demo/ExampleUnitTest.java

+package com.baidu.paddle.lite.demo;
+
+import org.junit.Test;
+
+import static org.junit.Assert.*;
+
+/**
+ * Example local unit test, which will execute on the development machine (host).
+ *
+ * @see <a href="http://d.android.com/tools/testing">Testing documentation</a>
+ */
+public class ExampleUnitTest {
+    @Test
+    public void addition_isCorrect() {
+        assertEquals(4, 2 + 2);
+    }
+}
\ No newline at end of file

deploy/lite/humanseg-android-demo/build.gradle

+// Top-level build file where you can add configuration options common to all sub-projects/modules.
+
+buildscript {
+    repositories {
+        google()
+        jcenter()
+        
+    }
+    dependencies {
+        classpath 'com.android.tools.build:gradle:3.4.0'
+        
+        // NOTE: Do not place your application dependencies here; they belong
+        // in the individual module build.gradle files
+    }
+}
+
+allprojects {
+    repositories {
+        google()
+        jcenter()
+        
+    }
+}
+
+task clean(type: Delete) {
+    delete rootProject.buildDir
+}

deploy/lite/humanseg-android-demo/gradle.properties

+# Project-wide Gradle settings.
+# IDE (e.g. Android Studio) users:
+# Gradle settings configured through the IDE *will override*
+# any settings specified in this file.
+# For more details on how to configure your build environment visit
+# http://www.gradle.org/docs/current/userguide/build_environment.html
+# Specifies the JVM arguments used for the daemon process.
+# The setting is particularly useful for tweaking memory settings.
+org.gradle.jvmargs=-Xmx1536m
+# When configured, Gradle will run in incubating parallel mode.
+# This option should only be used with decoupled projects. More details, visit
+# http://www.gradle.org/docs/current/userguide/multi_project_builds.html#sec:decoupled_projects
+# org.gradle.parallel=true
+
+

deploy/lite/humanseg-android-demo/gradle/wrapper/gradle-wrapper.properties

+#Thu Aug 22 15:05:37 CST 2019
+distributionBase=GRADLE_USER_HOME
+distributionPath=wrapper/dists
+zipStoreBase=GRADLE_USER_HOME
+zipStorePath=wrapper/dists
+distributionUrl=https\://services.gradle.org/distributions/gradle-5.1.1-all.zip

deploy/lite/humanseg-android-demo/gradlew

+#!/usr/bin/env sh
+
+##############################################################################
+##
+##  Gradle start up script for UN*X
+##
+##############################################################################
+
+# Attempt to set APP_HOME
+# Resolve links: $0 may be a link
+PRG="$0"
+# Need this for relative symlinks.
+while [ -h "$PRG" ] ; do
+    ls=`ls -ld "$PRG"`
+    link=`expr "$ls" : '.*-> \(.*\)$'`
+    if expr "$link" : '/.*' > /dev/null; then
+        PRG="$link"
+    else
+        PRG=`dirname "$PRG"`"/$link"
+    fi
+done
+SAVED="`pwd`"
+cd "`dirname \"$PRG\"`/" >/dev/null
+APP_HOME="`pwd -P`"
+cd "$SAVED" >/dev/null
+
+APP_NAME="Gradle"
+APP_BASE_NAME=`basename "$0"`
+
+# Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script.
+DEFAULT_JVM_OPTS=""
+
+# Use the maximum available, or set MAX_FD != -1 to use that value.
+MAX_FD="maximum"
+
+warn () {
+    echo "$*"
+}
+
+die () {
+    echo
+    echo "$*"
+    echo
+    exit 1
+}
+
+# OS specific support (must be 'true' or 'false').
+cygwin=false
+msys=false
+darwin=false
+nonstop=false
+case "`uname`" in
+  CYGWIN* )
+    cygwin=true
+    ;;
+  Darwin* )
+    darwin=true
+    ;;
+  MINGW* )
+    msys=true
+    ;;
+  NONSTOP* )
+    nonstop=true
+    ;;
+esac
+
+CLASSPATH=$APP_HOME/gradle/wrapper/gradle-wrapper.jar
+
+# Determine the Java command to use to start the JVM.
+if [ -n "$JAVA_HOME" ] ; then
+    if [ -x "$JAVA_HOME/jre/sh/java" ] ; then
+        # IBM's JDK on AIX uses strange locations for the executables
+        JAVACMD="$JAVA_HOME/jre/sh/java"
+    else
+        JAVACMD="$JAVA_HOME/bin/java"
+    fi
+    if [ ! -x "$JAVACMD" ] ; then
+        die "ERROR: JAVA_HOME is set to an invalid directory: $JAVA_HOME
+
+Please set the JAVA_HOME variable in your environment to match the
+location of your Java installation."
+    fi
+else
+    JAVACMD="java"
+    which java >/dev/null 2>&1 || die "ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH.
+
+Please set the JAVA_HOME variable in your environment to match the
+location of your Java installation."
+fi
+
+# Increase the maximum file descriptors if we can.
+if [ "$cygwin" = "false" -a "$darwin" = "false" -a "$nonstop" = "false" ] ; then
+    MAX_FD_LIMIT=`ulimit -H -n`
+    if [ $? -eq 0 ] ; then
+        if [ "$MAX_FD" = "maximum" -o "$MAX_FD" = "max" ] ; then
+            MAX_FD="$MAX_FD_LIMIT"
+        fi
+        ulimit -n $MAX_FD
+        if [ $? -ne 0 ] ; then
+            warn "Could not set maximum file descriptor limit: $MAX_FD"
+        fi
+    else
+        warn "Could not query maximum file descriptor limit: $MAX_FD_LIMIT"
+    fi
+fi
+
+# For Darwin, add options to specify how the application appears in the dock
+if $darwin; then
+    GRADLE_OPTS="$GRADLE_OPTS \"-Xdock:name=$APP_NAME\" \"-Xdock:icon=$APP_HOME/media/gradle.icns\""
+fi
+
+# For Cygwin, switch paths to Windows format before running java
+if $cygwin ; then
+    APP_HOME=`cygpath --path --mixed "$APP_HOME"`
+    CLASSPATH=`cygpath --path --mixed "$CLASSPATH"`
+    JAVACMD=`cygpath --unix "$JAVACMD"`
+
+    # We build the pattern for arguments to be converted via cygpath
+    ROOTDIRSRAW=`find -L / -maxdepth 1 -mindepth 1 -type d 2>/dev/null`
+    SEP=""
+    for dir in $ROOTDIRSRAW ; do
+        ROOTDIRS="$ROOTDIRS$SEP$dir"
+        SEP="|"
+    done
+    OURCYGPATTERN="(^($ROOTDIRS))"
+    # Add a user-defined pattern to the cygpath arguments
+    if [ "$GRADLE_CYGPATTERN" != "" ] ; then
+        OURCYGPATTERN="$OURCYGPATTERN|($GRADLE_CYGPATTERN)"
+    fi
+    # Now convert the arguments - kludge to limit ourselves to /bin/sh
+    i=0
+    for arg in "$@" ; do
+        CHECK=`echo "$arg"|egrep -c "$OURCYGPATTERN" -`
+        CHECK2=`echo "$arg"|egrep -c "^-"`                                 ### Determine if an option
+
+        if [ $CHECK -ne 0 ] && [ $CHECK2 -eq 0 ] ; then                    ### Added a condition
+            eval `echo args$i`=`cygpath --path --ignore --mixed "$arg"`
+        else
+            eval `echo args$i`="\"$arg\""
+        fi
+        i=$((i+1))
+    done
+    case $i in
+        (0) set -- ;;
+        (1) set -- "$args0" ;;
+        (2) set -- "$args0" "$args1" ;;
+        (3) set -- "$args0" "$args1" "$args2" ;;
+        (4) set -- "$args0" "$args1" "$args2" "$args3" ;;
+        (5) set -- "$args0" "$args1" "$args2" "$args3" "$args4" ;;
+        (6) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" ;;
+        (7) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" ;;
+        (8) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" "$args7" ;;
+        (9) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" "$args7" "$args8" ;;
+    esac
+fi
+
+# Escape application args
+save () {
+    for i do printf %s\\n "$i" | sed "s/'/'\\\\''/g;1s/^/'/;\$s/\$/' \\\\/" ; done
+    echo " "
+}
+APP_ARGS=$(save "$@")
+
+# Collect all arguments for the java command, following the shell quoting and substitution rules
+eval set -- $DEFAULT_JVM_OPTS $JAVA_OPTS $GRADLE_OPTS "\"-Dorg.gradle.appname=$APP_BASE_NAME\"" -classpath "\"$CLASSPATH\"" org.gradle.wrapper.GradleWrapperMain "$APP_ARGS"
+
+# by default we should be in the correct project dir, but when run from Finder on Mac, the cwd is wrong
+if [ "$(uname)" = "Darwin" ] && [ "$HOME" = "$PWD" ]; then
+  cd "$(dirname "$0")"
+fi
+
+exec "$JAVACMD" "$@"

deploy/lite/humanseg-android-demo/gradlew.bat

+@if "%DEBUG%" == "" @echo off
+@rem ##########################################################################
+@rem
+@rem  Gradle startup script for Windows
+@rem
+@rem ##########################################################################
+
+@rem Set local scope for the variables with windows NT shell
+if "%OS%"=="Windows_NT" setlocal
+
+set DIRNAME=%~dp0
+if "%DIRNAME%" == "" set DIRNAME=.
+set APP_BASE_NAME=%~n0
+set APP_HOME=%DIRNAME%
+
+@rem Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script.
+set DEFAULT_JVM_OPTS=
+
+@rem Find java.exe
+if defined JAVA_HOME goto findJavaFromJavaHome
+
+set JAVA_EXE=java.exe
+%JAVA_EXE% -version >NUL 2>&1
+if "%ERRORLEVEL%" == "0" goto init
+
+echo.
+echo ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH.
+echo.
+echo Please set the JAVA_HOME variable in your environment to match the
+echo location of your Java installation.
+
+goto fail
+
+:findJavaFromJavaHome
+set JAVA_HOME=%JAVA_HOME:"=%
+set JAVA_EXE=%JAVA_HOME%/bin/java.exe
+
+if exist "%JAVA_EXE%" goto init
+
+echo.
+echo ERROR: JAVA_HOME is set to an invalid directory: %JAVA_HOME%
+echo.
+echo Please set the JAVA_HOME variable in your environment to match the
+echo location of your Java installation.
+
+goto fail
+
+:init
+@rem Get command-line arguments, handling Windows variants
+
+if not "%OS%" == "Windows_NT" goto win9xME_args
+
+:win9xME_args
+@rem Slurp the command line arguments.
+set CMD_LINE_ARGS=
+set _SKIP=2
+
+:win9xME_args_slurp
+if "x%~1" == "x" goto execute
+
+set CMD_LINE_ARGS=%*
+
+:execute
+@rem Setup the command line
+
+set CLASSPATH=%APP_HOME%\gradle\wrapper\gradle-wrapper.jar
+
+@rem Execute Gradle
+"%JAVA_EXE%" %DEFAULT_JVM_OPTS% %JAVA_OPTS% %GRADLE_OPTS% "-Dorg.gradle.appname=%APP_BASE_NAME%" -classpath "%CLASSPATH%" org.gradle.wrapper.GradleWrapperMain %CMD_LINE_ARGS%
+
+:end
+@rem End local scope for the variables with windows NT shell
+if "%ERRORLEVEL%"=="0" goto mainEnd
+
+:fail
+rem Set variable GRADLE_EXIT_CONSOLE if you need the _script_ return code instead of
+rem the _cmd.exe /c_ return code!
+if  not "" == "%GRADLE_EXIT_CONSOLE%" exit 1
+exit /b 1
+
+:mainEnd
+if "%OS%"=="Windows_NT" endlocal
+
+:omega

deploy/lite/humanseg-android-demo/settings.gradle

+include ':app'

deploy/python/infer.py

@@ -33,12 +33,19 @@ gflags.DEFINE_boolean("use_pr", default=False, help="Use optimized model")
 gflags.DEFINE_string("trt_mode", default="", help="Use optimized model")
 gflags.FLAGS = gflags.FLAGS
 
-# ColorMap for visualization
-color_map = [[128, 64, 128], [244, 35, 231], [69, 69, 69], [102, 102, 156],
-             [190, 153, 153], [153, 153, 153], [250, 170, 29], [219, 219, 0],
-             [106, 142, 35], [152, 250, 152], [69, 129, 180], [219, 19, 60],
-             [255, 0, 0], [0, 0, 142], [0, 0, 69], [0, 60, 100], [0, 79, 100],
-             [0, 0, 230], [119, 10, 32]]
+# Generate ColorMap for visualization
+def generate_colormap(num_classes):
+    color_map = num_classes * [0, 0, 0]
+    for i in range(0, num_classes):
+        j = 0
+        lab = i
+        while lab:
+            color_map[i * 3] |= (((lab >> 0) & 1) << (7 - j))
+            color_map[i * 3 + 1] |= (((lab >> 1) & 1) << (7 - j))
+            color_map[i * 3 + 2] |= (((lab >> 2) & 1) << (7 - j))
+            j += 1
+            lab >>= 3
+    return color_map
 
 # Paddle-TRT Precision Map
 trt_precision_map = {
@@ -202,6 +209,7 @@ class Predictor:
             score_png = mask_png[:, :, np.newaxis]
             score_png = np.concatenate([score_png] * 3, axis=2)
             # visualization score png
+            color_map = generate_colormap(self.config.class_num)
             for i in range(score_png.shape[0]):
                 for j in range(score_png.shape[1]):
                     score_png[i, j] = color_map[score_png[i, j, 0]]
@@ -247,12 +255,12 @@ class Predictor:
             infer_start = time.time()
             output_data = self.predictor.run(input_data)[0]
             infer_end = time.time()
-            reader_time += (reader_end - reader_start)
-            infer_time += (infer_end - infer_start)
             output_data = output_data.as_ndarray()
             post_start = time.time()
             self.output_result(img_datas, output_data, gflags.FLAGS.use_pr)
             post_end = time.time()
+            reader_time += (reader_end - reader_start)
+            infer_time += (infer_end - infer_start)
             post_time += (post_end - post_start)
 
         # finishing process all images

docs/configs/model_group.md

@@ -5,10 +5,11 @@ MODEL Group存放所有和模型相关的配置，该Group还包含三个子Grou
 * [DeepLabv3p](./model_deeplabv3p_group.md)
 * [UNet](./model_unet_group.md)
 * [ICNet](./model_icnet_group.md)
+* [HRNet](./model_hrnet_group.md)
 
 ## `MODEL_NAME`
 
-所选模型，支持`deeplabv3p` `unet` `icnet`三种模型
+所选模型，支持`deeplabv3p` `unet` `icnet` `hrnet`四种模型
 
 ### 默认值
 

docs/configs/model_hrnet_group.md

+# cfg.MODEL.HRNET
+
+MODEL.HRNET 子Group存放所有和HRNet模型相关的配置
+
+## `STAGE2.NUM_MODULES`
+
+HRNet在第二阶段执行modularized block（multi-resolution parallel convolution + multi-resolution fusion)的重复次数
+
+### 默认值
+
+1
+
+<br/>
+<br/>
+
+## `STAGE2.NUM_CHANNELS`
+
+HRNet在第二阶段各个分支的通道数
+
+### 默认值
+
+[40, 80]
+
+<br/>
+<br/>
+
+## `STAGE3.NUM_MODULES`
+
+HRNet在第三阶段执行modularized block的重复次数
+
+### 默认值
+
+4
+
+<br/>
+<br/>
+
+## `STAGE3.NUM_CHANNELS`
+
+HRNet在第三阶段各个分支的通道数
+
+### 默认值
+
+[40, 80, 160]
+
+<br/>
+<br/>
+
+## `STAGE4.NUM_MODULES`
+
+HRNet在第四阶段执行modularized block的重复次数
+
+### 默认值
+
+3
+
+<br/>
+<br/>
+
+## `STAGE4.NUM_CHANNELS`
+
+HRNet在第四阶段各个分支的通道数
+
+### 默认值
+
+[40, 80, 160, 320]
+
+<br/>
+<br/>
\ No newline at end of file

docs/model_zoo.md

@@ -22,6 +22,16 @@ PaddleSeg对所有内置的分割模型都提供了公开数据集下的预训
 | Xception65 | ImageNet | [Xception65_pretrained.tgz](https://paddleseg.bj.bcebos.com/models/Xception65_pretrained.tgz) | 80.32%/94.47% |
 | Xception71 | ImageNet | coming soon | -- |
 
+| 模型 | 数据集合 | 下载地址 | Accuray Top1/5 Error |
+|---|---|---|---|
+| HRNet_W18 | ImageNet | [hrnet_w18_imagenet.tar](https://paddleseg.bj.bcebos.com/models/hrnet_w18_imagenet.tar) | 76.92%/93.39% |
+| HRNet_W30 | ImageNet | [hrnet_w30_imagenet.tar](https://paddleseg.bj.bcebos.com/models/hrnet_w30_imagenet.tar) | 78.04%/94.02% |
+| HRNet_W32 | ImageNet | [hrnet_w32_imagenet.tar](https://paddleseg.bj.bcebos.com/models/hrnet_w32_imagenet.tar) | 78.28%/94.24% |
+| HRNet_W40 | ImageNet | [hrnet_w40_imagenet.tar](https://paddleseg.bj.bcebos.com/models/hrnet_w40_imagenet.tar) | 78.77%/94.47% |
+| HRNet_W44 | ImageNet | [hrnet_w44_imagenet.tar](https://paddleseg.bj.bcebos.com/models/hrnet_w44_imagenet.tar) | 79.00%/94.51% |
+| HRNet_W48 | ImageNet | [hrnet_w48_imagenet.tar](https://paddleseg.bj.bcebos.com/models/hrnet_w48_imagenet.tar) | 78.95%/94.42% |
+| HRNet_W64 | ImageNet | [hrnet_w64_imagenet.tar](https://paddleseg.bj.bcebos.com/models/hrnet_w64_imagenet.tar) | 79.30%/94.61% |
+
 ## COCO预训练模型
 
 数据集为COCO实例分割数据集合转换成的语义分割数据集合
@@ -46,3 +56,4 @@ train数据集合为Cityscapes训练集合，测试为Cityscapes的验证集合
 | ICNet/bn | Cityscapes |[icnet_cityscapes.tgz](https://paddleseg.bj.bcebos.com/models/icnet_cityscapes.tar.gz) |16|false| 0.6831 |
 | PSPNet/bn | Cityscapes |[pspnet50_cityscapes.tgz](https://paddleseg.bj.bcebos.com/models/pspnet50_cityscapes.tgz) |16|false| 0.7013 |
 | PSPNet/bn | Cityscapes |[pspnet101_cityscapes.tgz](https://paddleseg.bj.bcebos.com/models/pspnet101_cityscapes.tgz) |16|false| 0.7734 |
+| HRNet_W18/bn | Cityscapes |[hrnet_w18_bn_cityscapes.tgz](https://paddleseg.bj.bcebos.com/models/hrnet_w18_bn_cityscapes.tgz) | 4 | false | 0.7936 |

pdseg/models/model_builder.py

@@ -112,6 +112,7 @@ def softmax(logit):
     logit = fluid.layers.transpose(logit, [0, 3, 1, 2])
     return logit
 
+
 def sigmoid_to_softmax(logit):
     """
     one channel to two channel
@@ -143,19 +144,23 @@ def build_model(main_prog, start_prog, phase=ModelPhase.TRAIN):
             # 在导出模型的时候，增加图像标准化预处理,减小预测部署时图像的处理流程
             # 预测部署时只须对输入图像增加batch_size维度即可
             if ModelPhase.is_predict(phase):
-                origin_image = fluid.layers.data(name='image', 
-                        shape=[ -1, 1, 1, cfg.DATASET.DATA_DIM], 
-                        dtype='float32', 
-                        append_batch_size=False)
+                origin_image = fluid.layers.data(
+                    name='image',
+                    shape=[-1, 1, 1, cfg.DATASET.DATA_DIM],
+                    dtype='float32',
+                    append_batch_size=False)
                 image = fluid.layers.transpose(origin_image, [0, 3, 1, 2])
                 origin_shape = fluid.layers.shape(image)[-2:]
                 mean = np.array(cfg.MEAN).reshape(1, len(cfg.MEAN), 1, 1)
                 mean = fluid.layers.assign(mean.astype('float32'))
                 std = np.array(cfg.STD).reshape(1, len(cfg.STD), 1, 1)
                 std = fluid.layers.assign(std.astype('float32'))
-                image = (image/255 - mean)/std
-                image = fluid.layers.resize_bilinear(image, 
-                        out_shape=[height, width], align_corners=False, align_mode=0)
+                image = fluid.layers.resize_bilinear(
+                    image,
+                    out_shape=[height, width],
+                    align_corners=False,
+                    align_mode=0)
+                image = (image / 255 - mean) / std
             else:
                 image = fluid.layers.data(
                     name='image', shape=image_shape, dtype='float32')
@@ -180,15 +185,20 @@ def build_model(main_prog, start_prog, phase=ModelPhase.TRAIN):
                 loss_type = list(loss_type)
 
             # dice_loss或bce_loss只适用两类分割中
-            if class_num > 2 and (("dice_loss" in loss_type) or ("bce_loss" in loss_type)):
-                raise Exception("dice loss and bce loss is only applicable to binary classfication")
-            
+            if class_num > 2 and (("dice_loss" in loss_type) or
+                                  ("bce_loss" in loss_type)):
+                raise Exception(
+                    "dice loss and bce loss is only applicable to binary classfication"
+                )
+
             # 在两类分割情况下，当loss函数选择dice_loss或bce_loss的时候，最后logit输出通道数设置为1
             if ("dice_loss" in loss_type) or ("bce_loss" in loss_type):
                 class_num = 1
                 if "softmax_loss" in loss_type:
-                    raise Exception("softmax loss can not combine with dice loss or bce loss")
-            
+                    raise Exception(
+                        "softmax loss can not combine with dice loss or bce loss"
+                    )
+
             logits = model_func(image, class_num)
 
             # 根据选择的loss函数计算相应的损失函数
@@ -196,9 +206,9 @@ def build_model(main_prog, start_prog, phase=ModelPhase.TRAIN):
                 loss_valid = False
                 avg_loss_list = []
                 valid_loss = []
-                if "softmax_loss" in loss_type: 
-                    avg_loss_list.append(multi_softmax_with_loss(logits,
-                        label, mask,class_num))
+                if "softmax_loss" in loss_type:
+                    avg_loss_list.append(
+                        multi_softmax_with_loss(logits, label, mask, class_num))
                     loss_valid = True
                     valid_loss.append("softmax_loss")
                 if "dice_loss" in loss_type:
@@ -210,13 +220,17 @@ def build_model(main_prog, start_prog, phase=ModelPhase.TRAIN):
                     loss_valid = True
                     valid_loss.append("bce_loss")
                 if not loss_valid:
-                    raise Exception("SOLVER.LOSS: {} is set wrong. it should "
-                            "include one of (softmax_loss, bce_loss, dice_loss) at least"
-                            " example: ['softmax_loss'], ['dice_loss'], ['bce_loss', 'dice_loss']".format(cfg.SOLVER.LOSS))
-                
+                    raise Exception(
+                        "SOLVER.LOSS: {} is set wrong. it should "
+                        "include one of (softmax_loss, bce_loss, dice_loss) at least"
+                        " example: ['softmax_loss'], ['dice_loss'], ['bce_loss', 'dice_loss']"
+                        .format(cfg.SOLVER.LOSS))
+
                 invalid_loss = [x for x in loss_type if x not in valid_loss]
                 if len(invalid_loss) > 0:
-                    print("Warning: the loss {} you set is invalid. it will not be included in loss computed.".format(invalid_loss))
+                    print(
+                        "Warning: the loss {} you set is invalid. it will not be included in loss computed."
+                        .format(invalid_loss))
 
                 avg_loss = 0
                 for i in range(0, len(avg_loss_list)):
@@ -238,7 +252,11 @@ def build_model(main_prog, start_prog, phase=ModelPhase.TRAIN):
                     logit = sigmoid_to_softmax(logit)
                 else:
                     logit = softmax(logit)
-                logit = fluid.layers.resize_bilinear(logit, out_shape=origin_shape, align_corners=False, align_mode=0)
+                logit = fluid.layers.resize_bilinear(
+                    logit,
+                    out_shape=origin_shape,
+                    align_corners=False,
+                    align_mode=0)
                 logit = fluid.layers.transpose(logit, [0, 2, 3, 1])
                 logit = fluid.layers.argmax(logit, axis=3)
                 return origin_image, logit

pdseg/models/modeling/hrnet.py

@@ -146,7 +146,7 @@ def layer1(input, name=None):
                                      name=name + '_' + str(i + 1))
     return conv
 
-def highResolutionNet(input, num_classes):
+def high_resolution_net(input, num_classes):
     
     channels_2 = cfg.MODEL.HRNET.STAGE2.NUM_CHANNELS
     channels_3 = cfg.MODEL.HRNET.STAGE3.NUM_CHANNELS
@@ -198,7 +198,7 @@ def highResolutionNet(input, num_classes):
 
 
 def hrnet(input, num_classes):
-    logit = highResolutionNet(input, num_classes)
+    logit = high_resolution_net(input, num_classes)
     return logit
 
 if __name__ == '__main__':

pretrained_model/download_model.py

@@ -37,6 +37,20 @@ model_urls = {
     "https://paddleseg.bj.bcebos.com/models/Xception41_pretrained.tgz",
     "xception65_imagenet":
     "https://paddleseg.bj.bcebos.com/models/Xception65_pretrained.tgz",
+    "hrnet_w18_bn_imagenet":
+    "https://paddleseg.bj.bcebos.com/models/hrnet_w18_imagenet.tar",
+    "hrnet_w30_bn_imagenet":
+    "https://paddleseg.bj.bcebos.com/models/hrnet_w30_imagenet.tar",
+    "hrnet_w32_bn_imagenet":
+    "https://paddleseg.bj.bcebos.com/models/hrnet_w32_imagenet.tar" ,
+    "hrnet_w40_bn_imagenet":
+    "https://paddleseg.bj.bcebos.com/models/hrnet_w40_imagenet.tar",
+    "hrnet_w44_bn_imagenet":
+    "https://paddleseg.bj.bcebos.com/models/hrnet_w44_imagenet.tar",
+    "hrnet_w48_bn_imagenet":
+    "https://paddleseg.bj.bcebos.com/models/hrnet_w48_imagenet.tar",
+    "hrnet_w64_bn_imagenet":
+    "https://paddleseg.bj.bcebos.com/models/hrnet_w64_imagenet.tar",
 
     # COCO pretrained
     "deeplabv3p_mobilenetv2-1-0_bn_coco":
@@ -65,6 +79,8 @@ model_urls = {
     "https://paddleseg.bj.bcebos.com/models/pspnet50_cityscapes.tgz",
     "pspnet101_bn_cityscapes":
     "https://paddleseg.bj.bcebos.com/models/pspnet101_cityscapes.tgz",
+    "hrnet_w18_bn_cityscapes":
+    "https://paddleseg.bj.bcebos.com/models/hrnet_w18_bn_cityscapes.tgz",
 }
 
 if __name__ == "__main__":

turtorial/finetune_hrnet.md

+# HRNet模型训练教程
+
+* 本教程旨在介绍如何通过使用PaddleSeg提供的 ***`HRNet`*** 预训练模型在自定义数据集上进行训练。
+
+* 在阅读本教程前，请确保您已经了解过PaddleSeg的[快速入门](../README.md#快速入门)和[基础功能](../README.md#基础功能)等章节，以便对PaddleSeg有一定的了解
+
+* 本教程的所有命令都基于PaddleSeg主目录进行执行
+
+## 一. 准备待训练数据
+
+我们提前准备好了一份数据集，通过以下代码进行下载
+
+```shell
+python dataset/download_pet.py
+```
+
+## 二. 下载预训练模型
+
+关于PaddleSeg支持的所有预训练模型的列表，我们可以从[模型组合](#模型组合)中查看我们所需模型的名字和配置
+
+接着下载对应的预训练模型
+
+```shell
+python pretrained_model/download_model.py hrnet_w18_bn_cityscapes
+```
+
+## 三. 准备配置
+
+接着我们需要确定相关配置，从本教程的角度，配置分为三部分：
+
+* 数据集
+  * 训练集主目录
+  * 训练集文件列表
+  * 测试集文件列表
+  * 评估集文件列表
+* 预训练模型
+  * 预训练模型名称
+  * 预训练模型各阶段通道数设置
+  * 预训练模型的Normalization类型
+  * 预训练模型路径
+* 其他
+  * 学习率
+  * Batch大小
+  * ...
+
+在三者中，预训练模型的配置尤为重要，如果模型配置错误，会导致预训练的参数没有加载，进而影响收敛速度。预训练模型相关的配置如第二步所展示。
+
+数据集的配置和数据路径有关，在本教程中，数据存放在`dataset/mini_pet`中
+
+其他配置则根据数据集和机器环境的情况进行调节，最终我们保存一个如下内容的yaml配置文件，存放路径为**configs/hrnet_w18_pet.yaml**
+
+```yaml
+# 数据集配置
+DATASET:
+    DATA_DIR: "./dataset/mini_pet/"
+    NUM_CLASSES: 3
+    TEST_FILE_LIST: "./dataset/mini_pet/file_list/test_list.txt"
+    TRAIN_FILE_LIST: "./dataset/mini_pet/file_list/train_list.txt"
+    VAL_FILE_LIST: "./dataset/mini_pet/file_list/val_list.txt"
+    VIS_FILE_LIST: "./dataset/mini_pet/file_list/test_list.txt"
+
+# 预训练模型配置
+MODEL:
+    MODEL_NAME: "hrnet"
+    DEFAULT_NORM_TYPE: "bn"
+    HRNET:
+        STAGE2:
+            NUM_CHANNELS: [18, 36]
+        STAGE3:
+            NUM_CHANNELS: [18, 36, 72]
+        STAGE4:
+            NUM_CHANNELS: [18, 36, 72, 144]
+
+# 其他配置
+TRAIN_CROP_SIZE: (512, 512)
+EVAL_CROP_SIZE: (512, 512)
+AUG:
+    AUG_METHOD: "unpadding"
+    FIX_RESIZE_SIZE: (512, 512)
+BATCH_SIZE: 4
+TRAIN:
+    PRETRAINED_MODEL_DIR: "./pretrained_model/hrnet_w18_bn_cityscapes/"
+    MODEL_SAVE_DIR: "./saved_model/hrnet_w18_bn_pet/"
+    SNAPSHOT_EPOCH: 10
+TEST:
+    TEST_MODEL: "./saved_model/hrnet_w18_bn_pet/final"
+SOLVER:
+    NUM_EPOCHS: 100
+    LR: 0.005
+    LR_POLICY: "poly"
+    OPTIMIZER: "sgd"
+```
+
+## 四. 配置/数据校验
+
+在开始训练和评估之前，我们还需要对配置和数据进行一次校验，确保数据和配置是正确的。使用下述命令启动校验流程
+
+```shell
+python pdseg/check.py --cfg ./configs/hrnet_w18_pet.yaml
+```
+
+
+## 五. 开始训练
+
+校验通过后，使用下述命令启动训练
+
+```shell
+python pdseg/train.py --use_gpu --cfg ./configs/hrnet_w18_pet.yaml
+```
+
+## 六. 进行评估
+
+模型训练完成，使用下述命令启动评估
+
+```shell
+python pdseg/eval.py --use_gpu --cfg ./configs/hrnet_w18_pet.yaml
+```
+
+## 模型组合
+
+|预训练模型名称|BackBone|Norm Type|数据集|配置|
+|-|-|-|-|-|
+|hrnet_w18_bn_cityscapes|-|bn| ImageNet | MODEL.MODEL_NAME: hrnet <br> MODEL.HRNET.STAGE2.NUM_CHANNELS: [18, 36] <br> MODEL.HRNET.STAGE3.NUM_CHANNELS: [18, 36, 72] <br> MODEL.HRNET.STAGE4.NUM_CHANNELS: [18, 36, 72, 144] <br> MODEL.DEFAULT_NORM_TYPE: bn|
+| hrnet_w18_bn_imagenet |-|bn| ImageNet | MODEL.MODEL_NAME: hrnet <br> MODEL.HRNET.STAGE2.NUM_CHANNELS: [18, 36] <br> MODEL.HRNET.STAGE3.NUM_CHANNELS: [18, 36, 72] <br> MODEL.HRNET.STAGE4.NUM_CHANNELS: [18, 36, 72, 144] <br> MODEL.DEFAULT_NORM_TYPE: bn |
+| hrnet_w30_bn_imagenet |-|bn| ImageNet | MODEL.MODEL_NAME: hrnet <br> MODEL.HRNET.STAGE2.NUM_CHANNELS: [30, 60] <br> MODEL.HRNET.STAGE3.NUM_CHANNELS: [30, 60, 120] <br> MODEL.HRNET.STAGE4.NUM_CHANNELS: [30, 60, 120, 240] <br> MODEL.DEFAULT_NORM_TYPE: bn |
+| hrnet_w32_bn_imagenet |-|bn| ImageNet | MODEL.MODEL_NAME: hrnet <br> MODEL.HRNET.STAGE2.NUM_CHANNELS: [32, 64] <br> MODEL.HRNET.STAGE3.NUM_CHANNELS: [32, 64, 128] <br> MODEL.HRNET.STAGE4.NUM_CHANNELS: [32, 64, 128, 256] <br> MODEL.DEFAULT_NORM_TYPE: bn |
+| hrnet_w40_bn_imagenet |-|bn| ImageNet | MODEL.MODEL_NAME: hrnet <br> MODEL.HRNET.STAGE2.NUM_CHANNELS: [40, 80] <br> MODEL.HRNET.STAGE3.NUM_CHANNELS: [40, 80, 160] <br> MODEL.HRNET.STAGE4.NUM_CHANNELS: [40, 80, 160, 320] <br> MODEL.DEFAULT_NORM_TYPE: bn |
+| hrnet_w44_bn_imagenet |-|bn| ImageNet | MODEL.MODEL_NAME: hrnet <br> MODEL.HRNET.STAGE2.NUM_CHANNELS: [44, 88] <br> MODEL.HRNET.STAGE3.NUM_CHANNELS: [44, 88, 176] <br> MODEL.HRNET.STAGE4.NUM_CHANNELS: [44, 88, 176, 352] <br> MODEL.DEFAULT_NORM_TYPE: bn |
+| hrnet_w48_bn_imagenet |-|bn| ImageNet | MODEL.MODEL_NAME: hrnet <br> MODEL.HRNET.STAGE2.NUM_CHANNELS: [48, 96] <br> MODEL.HRNET.STAGE3.NUM_CHANNELS: [48, 96, 192] <br> MODEL.HRNET.STAGE4.NUM_CHANNELS: [48, 96, 192, 384] <br> MODEL.DEFAULT_NORM_TYPE: bn |
+| hrnet_w64_bn_imagenet |-|bn| ImageNet | MODEL.MODEL_NAME: hrnet <br> MODEL.HRNET.STAGE2.NUM_CHANNELS: [64, 128] <br> MODEL.HRNET.STAGE3.NUM_CHANNELS: [64, 128, 256] <br> MODEL.HRNET.STAGE4.NUM_CHANNELS: [64, 128, 256, 512] <br> MODEL.DEFAULT_NORM_TYPE: bn |
+