From 8837d0f9c88065cac6a63c40e9442912a809b0cd Mon Sep 17 00:00:00 2001 From: channings Date: Thu, 26 Dec 2019 15:55:47 +0800 Subject: [PATCH] Update Humanseg Lite demo (#132) * add paddlelite-seg-android.md * add paddlelite-seg-android.md * add paddlelite-seg-android.md * add paddlelite-seg-android.md * modify paddlelite-seg-android.md * modify paddlelite-seg-android.md * modify paddlelite-seg-android.md * modify paddlelite-seg-android.md * modify paddlelite-seg-android.md * modify paddlelite-seg-android.md * modify paddlelite-seg-android.md * modify paddlelite-seg-android.md * modify paddlelite-seg-android.md * modify paddlelite-seg-android.md * modify paddlelite-seg-android.md * modify paddlelite-seg-android.md * modify paddlelite-seg-android.md * Update paddlelite-seg-android.md * modify paddlelite-seg-android.md * modify paddlelite-seg-android.md * add humanseg-android-demo * add humanseg-android-demo * add humanseg-android-demo * add humanseg-android-demo * add humanseg-android-demo * add humanseg-android-demo * add humanseg-android-demo * add humanseg-android-demo * add humanseg-android-demo * add humanseg-android-demo * add humanseg-android-demo * add humanseg-android-demo * add humanseg-android-demo * add humanseg-android-demo * add humanseg-android-demo * add humanseg-android-demo * add humanseg-android-demo * add humanseg-android-demo * add jniLibs * add humanseg-android-demo * add humanseg-android-demo * delete .idea directoy * Fix infer log tips index error (#108) Fix infer log tips index error * Update solver.py * [Lite demo]Download model and library at the same time of building * release/v0.3.0 * modify README.md * modify README.md * modify README.md * modify README.md * modify infer.py * modify infer.py * modify infer.py * [Lite demo]Download model and library at the same time of building * add humanseg lite demo * rm lite * Update Humanseg Lite demo Co-authored-by: Zeyu Chen Co-authored-by: XiaoqingWang Co-authored-by: wuzewu --- deploy/lite/README.md | 69 ++++ deploy/lite/example/human_1.png | Bin 0 -> 620831 bytes deploy/lite/example/human_2.png | Bin 0 -> 1026706 bytes deploy/lite/example/human_3.png | Bin 0 -> 323851 bytes .../lite/human_segmentation_demo/.gitignore | 13 + .../human_segmentation_demo/app/.gitignore | 1 + .../human_segmentation_demo/app/build.gradle | 119 ++++++ .../app/gradle/wrapper/gradle-wrapper.jar | Bin 0 -> 54329 bytes .../gradle/wrapper/gradle-wrapper.properties | 6 + .../lite/human_segmentation_demo/app/gradlew | 172 ++++++++ .../human_segmentation_demo/app/gradlew.bat | 84 ++++ .../app/local.properties | 8 + .../app/proguard-rules.pro | 21 + .../lite/demo/ExampleInstrumentedTest.java | 26 ++ .../app/src/main/AndroidManifest.xml | 29 ++ .../image_segmentation/images/human.jpg | Bin 0 -> 109326 bytes .../image_segmentation/labels/label_list | 2 + .../AppCompatPreferenceActivity.java | 127 ++++++ .../lite/demo/segmentation/MainActivity.java | 388 ++++++++++++++++++ .../lite/demo/segmentation/Predictor.java | 292 +++++++++++++ .../demo/segmentation/SettingsActivity.java | 158 +++++++ .../paddle/lite/demo/segmentation/Utils.java | 87 ++++ .../lite/demo/segmentation/config/Config.java | 36 ++ .../segmentation/preprocess/Preprocess.java | 73 ++++ .../demo/segmentation/visual/Visualize.java | 53 +++ .../drawable-v24/ic_launcher_foreground.xml | 34 ++ .../res/drawable/ic_launcher_background.xml | 170 ++++++++ .../app/src/main/res/layout/activity_main.xml | 99 +++++ .../src/main/res/menu/menu_action_options.xml | 21 + .../res/mipmap-anydpi-v26/ic_launcher.xml | 5 + .../mipmap-anydpi-v26/ic_launcher_round.xml | 5 + .../src/main/res/mipmap-hdpi/ic_launcher.png | Bin 0 -> 2963 bytes .../res/mipmap-hdpi/ic_launcher_round.png | Bin 0 -> 4905 bytes .../src/main/res/mipmap-mdpi/ic_launcher.png | Bin 0 -> 2060 bytes .../res/mipmap-mdpi/ic_launcher_round.png | Bin 0 -> 2783 bytes .../src/main/res/mipmap-xhdpi/ic_launcher.png | Bin 0 -> 4490 bytes .../res/mipmap-xhdpi/ic_launcher_round.png | Bin 0 -> 6895 bytes .../main/res/mipmap-xxhdpi/ic_launcher.png | Bin 0 -> 6387 bytes .../res/mipmap-xxhdpi/ic_launcher_round.png | Bin 0 -> 10413 bytes .../main/res/mipmap-xxxhdpi/ic_launcher.png | Bin 0 -> 9128 bytes .../res/mipmap-xxxhdpi/ic_launcher_round.png | Bin 0 -> 15132 bytes .../app/src/main/res/values/arrays.xml | 39 ++ .../app/src/main/res/values/colors.xml | 6 + .../app/src/main/res/values/strings.xml | 20 + .../app/src/main/res/values/styles.xml | 25 ++ .../app/src/main/res/xml/settings.xml | 59 +++ .../paddle/lite/demo/ExampleUnitTest.java | 17 + .../lite/human_segmentation_demo/build.gradle | 27 ++ .../human_segmentation_demo/gradle.properties | 15 + .../gradle/wrapper/gradle-wrapper.jar | Bin 0 -> 54329 bytes .../gradle/wrapper/gradle-wrapper.properties | 6 + deploy/lite/human_segmentation_demo/gradlew | 172 ++++++++ .../lite/human_segmentation_demo/gradlew.bat | 84 ++++ .../human_segmentation_demo/settings.gradle | 1 + 54 files changed, 2569 insertions(+) create mode 100644 deploy/lite/README.md create mode 100644 deploy/lite/example/human_1.png create mode 100644 deploy/lite/example/human_2.png create mode 100644 deploy/lite/example/human_3.png create mode 100644 deploy/lite/human_segmentation_demo/.gitignore create mode 100644 deploy/lite/human_segmentation_demo/app/.gitignore create mode 100644 deploy/lite/human_segmentation_demo/app/build.gradle create mode 100644 deploy/lite/human_segmentation_demo/app/gradle/wrapper/gradle-wrapper.jar create mode 100644 deploy/lite/human_segmentation_demo/app/gradle/wrapper/gradle-wrapper.properties create mode 100644 deploy/lite/human_segmentation_demo/app/gradlew create mode 100644 deploy/lite/human_segmentation_demo/app/gradlew.bat create mode 100644 deploy/lite/human_segmentation_demo/app/local.properties create mode 100644 deploy/lite/human_segmentation_demo/app/proguard-rules.pro create mode 100644 deploy/lite/human_segmentation_demo/app/src/androidTest/java/com/baidu/paddle/lite/demo/ExampleInstrumentedTest.java create mode 100644 deploy/lite/human_segmentation_demo/app/src/main/AndroidManifest.xml create mode 100644 deploy/lite/human_segmentation_demo/app/src/main/assets/image_segmentation/images/human.jpg create mode 100644 deploy/lite/human_segmentation_demo/app/src/main/assets/image_segmentation/labels/label_list create mode 100644 deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/AppCompatPreferenceActivity.java create mode 100644 deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/MainActivity.java create mode 100644 deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/Predictor.java create mode 100644 deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/SettingsActivity.java create mode 100644 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deploy/lite/human_segmentation_demo/gradle.properties create mode 100644 deploy/lite/human_segmentation_demo/gradle/wrapper/gradle-wrapper.jar create mode 100644 deploy/lite/human_segmentation_demo/gradle/wrapper/gradle-wrapper.properties create mode 100644 deploy/lite/human_segmentation_demo/gradlew create mode 100644 deploy/lite/human_segmentation_demo/gradlew.bat create mode 100644 deploy/lite/human_segmentation_demo/settings.gradle diff --git a/deploy/lite/README.md b/deploy/lite/README.md new file mode 100644 index 00000000..a46dc207 --- /dev/null +++ b/deploy/lite/README.md @@ -0,0 +1,69 @@ +# 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,构建工程的过程中会下载demo需要的模型和Lite预测库; +* 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; +* 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。
+*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 + +## 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。 diff --git a/deploy/lite/example/human_1.png b/deploy/lite/example/human_1.png new file mode 100644 index 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messageDigest.digest()).toString(32) + // Download model file + if (!file("cache/${cacheName}.tar.gz").exists()) { + ant.get(src: model.src, dest: file("cache/${cacheName}.tar.gz")) + } + // Unpack model file + copy { + from tarTree("cache/${cacheName}.tar.gz") + into "cache/${cacheName}" + } + // Copy model file + if (!file("${model.dest}/__model__.nb").exists() || !file("${model.dest}/param.nb").exists()) { + copy { + from "cache/${cacheName}" + into "${model.dest}" + } + } + } + } +} +preBuild.dependsOn downloadAndExtractPaddleLiteModels diff --git a/deploy/lite/human_segmentation_demo/app/gradle/wrapper/gradle-wrapper.jar b/deploy/lite/human_segmentation_demo/app/gradle/wrapper/gradle-wrapper.jar new file mode 100644 index 0000000000000000000000000000000000000000..f6b961fd5a86aa5fbfe90f707c3138408be7c718 GIT binary patch literal 54329 zcmagFV|ZrKvM!pAZQHhO+qP}9lTNj?q^^Y^VFp)SH8qbSJ)2BQ2giqr}t zFG7D6)c?v~^Z#E_K}1nTQbJ9gQ9<%vVRAxVj)8FwL5_iTdUB>&m3fhE=kRWl;g`&m 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b/deploy/lite/human_segmentation_demo/app/gradle/wrapper/gradle-wrapper.properties new file mode 100644 index 00000000..7b5dff50 --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/gradle/wrapper/gradle-wrapper.properties @@ -0,0 +1,6 @@ +#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 diff --git a/deploy/lite/human_segmentation_demo/app/gradlew b/deploy/lite/human_segmentation_demo/app/gradlew new file mode 100644 index 00000000..cccdd3d5 --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/gradlew @@ -0,0 +1,172 @@ +#!/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" "$@" diff --git a/deploy/lite/human_segmentation_demo/app/gradlew.bat b/deploy/lite/human_segmentation_demo/app/gradlew.bat new file mode 100644 index 00000000..f9553162 --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/gradlew.bat @@ -0,0 +1,84 @@ +@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 diff --git a/deploy/lite/human_segmentation_demo/app/local.properties b/deploy/lite/human_segmentation_demo/app/local.properties new file mode 100644 index 00000000..f3bc0d0f --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/local.properties @@ -0,0 +1,8 @@ +## This file must *NOT* be checked into Version Control Systems, +# as it contains information specific to your local configuration. +# +# Location of the SDK. This is only used by Gradle. +# For customization when using a Version Control System, please read the +# header note. +#Mon Nov 25 17:01:52 CST 2019 +sdk.dir=/Users/chenlingchi/Library/Android/sdk diff --git a/deploy/lite/human_segmentation_demo/app/proguard-rules.pro b/deploy/lite/human_segmentation_demo/app/proguard-rules.pro new file mode 100644 index 00000000..f1b42451 --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/proguard-rules.pro @@ -0,0 +1,21 @@ +# 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 diff --git a/deploy/lite/human_segmentation_demo/app/src/androidTest/java/com/baidu/paddle/lite/demo/ExampleInstrumentedTest.java b/deploy/lite/human_segmentation_demo/app/src/androidTest/java/com/baidu/paddle/lite/demo/ExampleInstrumentedTest.java new file mode 100644 index 00000000..353c3677 --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/src/androidTest/java/com/baidu/paddle/lite/demo/ExampleInstrumentedTest.java @@ -0,0 +1,26 @@ +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 Testing documentation + */ +@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()); + } +} diff --git a/deploy/lite/human_segmentation_demo/app/src/main/AndroidManifest.xml b/deploy/lite/human_segmentation_demo/app/src/main/AndroidManifest.xml new file mode 100644 index 00000000..39789e03 --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/src/main/AndroidManifest.xml @@ -0,0 +1,29 @@ + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/deploy/lite/human_segmentation_demo/app/src/main/assets/image_segmentation/images/human.jpg b/deploy/lite/human_segmentation_demo/app/src/main/assets/image_segmentation/images/human.jpg new file mode 100644 index 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z^e@s3%lOc;H@qLdmJKXG?L*5iFIPDW;EThCSdue`Ng`GiOO<3(X zu!L%D=j={s;STI@KFqN`MRA51-Bfp`Hz`Relm~e$q^xph(6b>W%(ba|vDrK=FPxF- zJB#~t?Ldf@3Y-G8Zjokuv)tCRlY*0U_ndN?ZP#46A+9QE@Q!z0Fp61_9jODn zx8E;}8!Rd#%SdZOY#?38@*Cj(;upcxn81BelHUB=@hd-;`!jD_CAbY97*xPIv^T%JCRO^$>eq{~mq0aT^D+#x}zO0W4RVs83VAKW^vf k$R`W0T?-9o9KcJh4c@QOv1+S_*x>LTF*L`-w||fRKa}}(_W%F@ literal 0 HcmV?d00001 diff --git a/deploy/lite/human_segmentation_demo/app/src/main/assets/image_segmentation/labels/label_list b/deploy/lite/human_segmentation_demo/app/src/main/assets/image_segmentation/labels/label_list new file mode 100644 index 00000000..b043d376 --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/src/main/assets/image_segmentation/labels/label_list @@ -0,0 +1,2 @@ +background +human diff --git a/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/AppCompatPreferenceActivity.java b/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/AppCompatPreferenceActivity.java new file mode 100644 index 00000000..314c0456 --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/AppCompatPreferenceActivity.java @@ -0,0 +1,127 @@ +/* + * 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.segmentation; + +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. + *

    + * 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; + } +} diff --git a/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/MainActivity.java b/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/MainActivity.java new file mode 100644 index 00000000..aab9f54c --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/MainActivity.java @@ -0,0 +1,388 @@ +package com.baidu.paddle.lite.demo.segmentation; + +import android.Manifest; +import android.app.ProgressDialog; +import android.content.ContentResolver; +import android.content.Intent; +import android.content.SharedPreferences; +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.Handler; +import android.os.HandlerThread; +import android.os.Message; +import android.preference.PreferenceManager; +import android.provider.MediaStore; +import android.support.annotation.NonNull; +import android.support.v4.app.ActivityCompat; +import android.support.v4.content.ContextCompat; +import android.support.v7.app.AppCompatActivity; +import android.text.method.ScrollingMovementMethod; +import android.util.Log; +import android.view.Menu; +import android.view.MenuInflater; +import android.view.MenuItem; +import android.widget.ImageView; +import android.widget.TextView; +import android.widget.Toast; + +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 MainActivity extends AppCompatActivity { + + private static final String TAG = MainActivity.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 + + + protected TextView tvInputSetting; + protected ImageView ivInputImage; + protected TextView tvOutputResult; + protected TextView tvInferenceTime; + + // model config + Config config = new Config(); + + protected Predictor predictor = new Predictor(); + + Preprocess preprocess = new Preprocess(); + + Visualize visualize = new Visualize(); + + @Override + protected void onCreate(Bundle savedInstanceState) { + super.onCreate(savedInstanceState); + setContentView(R.layout.activity_main); + 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(MainActivity.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(MainActivity.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; + } + } + }; + + 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()); + } + + + public boolean onLoadModel() { + return predictor.init(MainActivity.this, config); + } + + + public boolean onRunModel() { + return predictor.isLoaded() && predictor.runModel(preprocess,visualize); + } + + public void onLoadModelFailed() { + + } + public void onRunModelFailed() { + } + + 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 void 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(MainActivity.this, "Load image failed!", Toast.LENGTH_SHORT).show(); + e.printStackTrace(); + } + } + + public void 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); + } + + + public void onImageChanged(Bitmap image) { + // rerun model if users pick test image from gallery or camera + if (image != null && predictor.isLoaded()) { + predictor.setInputImage(image); + runModel(); + } + } + + public void onImageChanged(String path) { + Bitmap image = BitmapFactory.decodeFile(path); + predictor.setInputImage(image); + runModel(); + } + public void onSettingsClicked() { + startActivity(new Intent(MainActivity.this, SettingsActivity.class)); + } + + @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(); + } + } + @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; + } + } + } + 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 + 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.MODEL_PATH_KEY), + getString(R.string.MODEL_PATH_DEFAULT)); + String label_path = sharedPreferences.getString(getString(R.string.LABEL_PATH_KEY), + getString(R.string.LABEL_PATH_DEFAULT)); + String image_path = sharedPreferences.getString(getString(R.string.IMAGE_PATH_KEY), + getString(R.string.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.CPU_THREAD_NUM_KEY), + getString(R.string.CPU_THREAD_NUM_DEFAULT))); + settingsChanged |= cpu_thread_num != config.cpuThreadNum; + String cpu_power_mode = + sharedPreferences.getString(getString(R.string.CPU_POWER_MODE_KEY), + getString(R.string.CPU_POWER_MODE_DEFAULT)); + settingsChanged |= !cpu_power_mode.equalsIgnoreCase(config.cpuPowerMode); + String input_color_format = + sharedPreferences.getString(getString(R.string.INPUT_COLOR_FORMAT_KEY), + getString(R.string.INPUT_COLOR_FORMAT_DEFAULT)); + settingsChanged |= !input_color_format.equalsIgnoreCase(config.inputColorFormat); + long[] input_shape = + Utils.parseLongsFromString(sharedPreferences.getString(getString(R.string.INPUT_SHAPE_KEY), + getString(R.string.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(); + } + worker.quit(); + super.onDestroy(); + } +} diff --git a/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/Predictor.java b/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/Predictor.java new file mode 100644 index 00000000..27bfe354 --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/Predictor.java @@ -0,0 +1,292 @@ +package com.baidu.paddle.lite.demo.segmentation; + +import android.content.Context; +import android.graphics.Bitmap; +import android.util.Log; + +import com.baidu.paddle.lite.MobileConfig; +import com.baidu.paddle.lite.PaddlePredictor; +import com.baidu.paddle.lite.PowerMode; +import com.baidu.paddle.lite.Tensor; +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; + +public class Predictor { + private static final String TAG = Predictor.class.getSimpleName(); + protected Vector wordLabels = new Vector(); + + Config config = new 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 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() { + super(); + } + + public boolean init(Context appCtx, String modelPath, int cpuThreadNum, String cpuPowerMode) { + this.appCtx = appCtx; + isLoaded = loadModel(modelPath, cpuThreadNum, cpuPowerMode); + return isLoaded; + } + + 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; + } + init(appCtx, config.modelPath, config.cpuThreadNum, config.cpuPowerMode); + + if (!isLoaded()) { + return false; + } + this.config = config; + + return isLoaded; + } + + + public boolean isLoaded() { + return paddlePredictor != null && 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) { + if (!isLoaded()) { + return null; + } + return paddlePredictor.getInput(idx); + } + + public Tensor getOutput(int idx) { + if (!isLoaded()) { + return null; + } + return paddlePredictor.getOutput(idx); + } + + 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 modelConfig = new MobileConfig(); + modelConfig.setModelDir(realPath); + modelConfig.setThreads(cpuThreadNum); + if (cpuPowerMode.equalsIgnoreCase("LITE_POWER_HIGH")) { + modelConfig.setPowerMode(PowerMode.LITE_POWER_HIGH); + } else if (cpuPowerMode.equalsIgnoreCase("LITE_POWER_LOW")) { + modelConfig.setPowerMode(PowerMode.LITE_POWER_LOW); + } else if (cpuPowerMode.equalsIgnoreCase("LITE_POWER_FULL")) { + modelConfig.setPowerMode(PowerMode.LITE_POWER_FULL); + } else if (cpuPowerMode.equalsIgnoreCase("LITE_POWER_NO_BIND")) { + modelConfig.setPowerMode(PowerMode.LITE_POWER_NO_BIND); + } else if (cpuPowerMode.equalsIgnoreCase("LITE_POWER_RAND_HIGH")) { + modelConfig.setPowerMode(PowerMode.LITE_POWER_RAND_HIGH); + } else if (cpuPowerMode.equalsIgnoreCase("LITE_POWER_RAND_LOW")) { + modelConfig.setPowerMode(PowerMode.LITE_POWER_RAND_LOW); + } else { + Log.e(TAG, "unknown cpu power mode!"); + return false; + } + paddlePredictor = PaddlePredictor.createPaddlePredictor(modelConfig); + this.cpuThreadNum = cpuThreadNum; + this.cpuPowerMode = cpuPowerMode; + this.modelPath = realPath; + this.modelName = realPath.substring(realPath.lastIndexOf("/") + 1); + return true; + } + + 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 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 + runModel(); + + start = new Date(); + Tensor outputTensor = getOutput(0); + + // post-process + this.outputImage = visualize.draw(inputImage, outputTensor); + postprocessTime = (float) (end.getTime() - start.getTime()); + + outputResult = new String(); + + return true; + } + public void releaseModel() { + paddlePredictor = null; + isLoaded = false; + cpuThreadNum = 1; + cpuPowerMode = "LITE_POWER_HIGH"; + modelPath = ""; + modelName = ""; + } + + 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 String modelPath() { + return modelPath; + } + + public String modelName() { + return modelName; + } + + public int cpuThreadNum() { + return cpuThreadNum; + } + + public String cpuPowerMode() { + return cpuPowerMode; + } + + public float inferenceTime() { + return inferenceTime; + } + + 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; + } + +} diff --git a/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/SettingsActivity.java b/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/SettingsActivity.java new file mode 100644 index 00000000..8f53974d --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/SettingsActivity.java @@ -0,0 +1,158 @@ +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 java.util.ArrayList; +import java.util.List; + +public class SettingsActivity 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; + + + + List preInstalledModelPaths = null; + List preInstalledLabelPaths = null; + List preInstalledImagePaths = null; + List preInstalledCPUThreadNums = null; + List preInstalledCPUPowerModes = null; + List preInstalledInputColorFormats = null; + + + @Override + public void onCreate(Bundle savedInstanceState) { + super.onCreate(savedInstanceState); + addPreferencesFromResource(R.xml.settings); + ActionBar supportActionBar = getSupportActionBar(); + if (supportActionBar != null) { + supportActionBar.setDisplayHomeAsUpEnabled(true); + } + + // initialized pre-installed models + preInstalledModelPaths = new ArrayList(); + preInstalledLabelPaths = new ArrayList(); + preInstalledImagePaths = new ArrayList(); + + preInstalledCPUThreadNums = new ArrayList(); + preInstalledCPUPowerModes = new ArrayList(); + preInstalledInputColorFormats = new ArrayList(); + // add deeplab_mobilenet_for_cpu + preInstalledModelPaths.add(getString(R.string.MODEL_PATH_DEFAULT)); + preInstalledLabelPaths.add(getString(R.string.LABEL_PATH_DEFAULT)); + preInstalledImagePaths.add(getString(R.string.IMAGE_PATH_DEFAULT)); + preInstalledCPUThreadNums.add(getString(R.string.CPU_THREAD_NUM_DEFAULT)); + preInstalledCPUPowerModes.add(getString(R.string.CPU_POWER_MODE_DEFAULT)); + preInstalledInputColorFormats.add(getString(R.string.INPUT_COLOR_FORMAT_DEFAULT)); + // initialize UI components + lpChoosePreInstalledModel = + (ListPreference) findPreference(getString(R.string.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.ENABLE_CUSTOM_SETTINGS_KEY)); + etModelPath = (EditTextPreference) findPreference(getString(R.string.MODEL_PATH_KEY)); + etModelPath.setTitle("Model Path (SDCard: " + Utils.getSDCardDirectory() + ")"); + etLabelPath = (EditTextPreference) findPreference(getString(R.string.LABEL_PATH_KEY)); + etImagePath = (EditTextPreference) findPreference(getString(R.string.IMAGE_PATH_KEY)); + lpCPUThreadNum = + (ListPreference) findPreference(getString(R.string.CPU_THREAD_NUM_KEY)); + lpCPUPowerMode = + (ListPreference) findPreference(getString(R.string.CPU_POWER_MODE_KEY)); + lpInputColorFormat = + (ListPreference) findPreference(getString(R.string.INPUT_COLOR_FORMAT_KEY)); + } + + private void reloadPreferenceAndUpdateUI() { + SharedPreferences sharedPreferences = getPreferenceScreen().getSharedPreferences(); + boolean enableCustomSettings = + sharedPreferences.getBoolean(getString(R.string.ENABLE_CUSTOM_SETTINGS_KEY), false); + String modelPath = sharedPreferences.getString(getString(R.string.CHOOSE_PRE_INSTALLED_MODEL_KEY), + getString(R.string.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.MODEL_PATH_KEY), preInstalledModelPaths.get(modelIdx)); + editor.putString(getString(R.string.LABEL_PATH_KEY), preInstalledLabelPaths.get(modelIdx)); + editor.putString(getString(R.string.IMAGE_PATH_KEY), preInstalledImagePaths.get(modelIdx)); + editor.putString(getString(R.string.CPU_THREAD_NUM_KEY), preInstalledCPUThreadNums.get(modelIdx)); + editor.putString(getString(R.string.CPU_POWER_MODE_KEY), preInstalledCPUPowerModes.get(modelIdx)); + editor.putString(getString(R.string.INPUT_COLOR_FORMAT_KEY), + preInstalledInputColorFormats.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); + modelPath = sharedPreferences.getString(getString(R.string.MODEL_PATH_KEY), + getString(R.string.MODEL_PATH_DEFAULT)); + String labelPath = sharedPreferences.getString(getString(R.string.LABEL_PATH_KEY), + getString(R.string.LABEL_PATH_DEFAULT)); + String imagePath = sharedPreferences.getString(getString(R.string.IMAGE_PATH_KEY), + getString(R.string.IMAGE_PATH_DEFAULT)); + String cpuThreadNum = sharedPreferences.getString(getString(R.string.CPU_THREAD_NUM_KEY), + getString(R.string.CPU_THREAD_NUM_DEFAULT)); + String cpuPowerMode = sharedPreferences.getString(getString(R.string.CPU_POWER_MODE_KEY), + getString(R.string.CPU_POWER_MODE_DEFAULT)); + String inputColorFormat = sharedPreferences.getString(getString(R.string.INPUT_COLOR_FORMAT_KEY), + getString(R.string.INPUT_COLOR_FORMAT_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); + + } + + @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.CHOOSE_PRE_INSTALLED_MODEL_KEY))) { + SharedPreferences.Editor editor = sharedPreferences.edit(); + editor.putBoolean(getString(R.string.ENABLE_CUSTOM_SETTINGS_KEY), false); + editor.commit(); + } + reloadPreferenceAndUpdateUI(); + } +} diff --git a/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/Utils.java b/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/Utils.java new file mode 100644 index 00000000..3d581592 --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/Utils.java @@ -0,0 +1,87 @@ +package com.baidu.paddle.lite.demo.segmentation; + +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"); + } +} diff --git a/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/config/Config.java b/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/config/Config.java new file mode 100644 index 00000000..4f09eb53 --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/config/Config.java @@ -0,0 +1,36 @@ +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(); + + } + +} diff --git a/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/preprocess/Preprocess.java b/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/preprocess/Preprocess.java new file mode 100644 index 00000000..d1ce2b02 --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/preprocess/Preprocess.java @@ -0,0 +1,73 @@ +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; + + } + +} diff --git a/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/visual/Visualize.java b/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/visual/Visualize.java new file mode 100644 index 00000000..56a2dd24 --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/src/main/java/com/baidu/paddle/lite/demo/segmentation/visual/Visualize.java @@ -0,0 +1,53 @@ +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 + + + + + + + + + + diff --git a/deploy/lite/human_segmentation_demo/app/src/main/res/drawable/ic_launcher_background.xml b/deploy/lite/human_segmentation_demo/app/src/main/res/drawable/ic_launcher_background.xml new file mode 100644 index 00000000..0d025f9b --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/src/main/res/drawable/ic_launcher_background.xml @@ -0,0 +1,170 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/deploy/lite/human_segmentation_demo/app/src/main/res/layout/activity_main.xml b/deploy/lite/human_segmentation_demo/app/src/main/res/layout/activity_main.xml new file mode 100644 index 00000000..356b0069 --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/src/main/res/layout/activity_main.xml @@ -0,0 +1,99 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/deploy/lite/human_segmentation_demo/app/src/main/res/menu/menu_action_options.xml b/deploy/lite/human_segmentation_demo/app/src/main/res/menu/menu_action_options.xml new file mode 100644 index 00000000..fe74758a --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/src/main/res/menu/menu_action_options.xml @@ -0,0 +1,21 @@ +

    + + + + + + + + + + diff --git a/deploy/lite/human_segmentation_demo/app/src/main/res/mipmap-anydpi-v26/ic_launcher.xml b/deploy/lite/human_segmentation_demo/app/src/main/res/mipmap-anydpi-v26/ic_launcher.xml new file mode 100644 index 00000000..eca70cfe --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/src/main/res/mipmap-anydpi-v26/ic_launcher.xml @@ -0,0 +1,5 @@ + + + + + \ No newline at end of file diff --git a/deploy/lite/human_segmentation_demo/app/src/main/res/mipmap-anydpi-v26/ic_launcher_round.xml b/deploy/lite/human_segmentation_demo/app/src/main/res/mipmap-anydpi-v26/ic_launcher_round.xml new file mode 100644 index 00000000..eca70cfe --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/src/main/res/mipmap-anydpi-v26/ic_launcher_round.xml @@ -0,0 +1,5 @@ + + + + + \ No newline at end of file diff --git a/deploy/lite/human_segmentation_demo/app/src/main/res/mipmap-hdpi/ic_launcher.png 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+ LITE_POWER_RAND_HIGH + LITE_POWER_RAND_LOW + + + BGR color format + RGB color format + + + BGR + RGB + + \ No newline at end of file diff --git a/deploy/lite/human_segmentation_demo/app/src/main/res/values/colors.xml b/deploy/lite/human_segmentation_demo/app/src/main/res/values/colors.xml new file mode 100644 index 00000000..69b22338 --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/src/main/res/values/colors.xml @@ -0,0 +1,6 @@ + + + #008577 + #00574B + #D81B60 + diff --git a/deploy/lite/human_segmentation_demo/app/src/main/res/values/strings.xml b/deploy/lite/human_segmentation_demo/app/src/main/res/values/strings.xml new file mode 100644 index 00000000..d3ad4ecf --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/src/main/res/values/strings.xml @@ -0,0 +1,20 @@ + +Human Segmentation + +CHOOSE_PRE_INSTALLED_MODEL_KEY +ENABLE_CUSTOM_SETTINGS_KEY +MODEL_PATH_KEY +LABEL_PATH_KEY +IMAGE_PATH_KEY +CPU_THREAD_NUM_KEY +CPU_POWER_MODE_KEY +INPUT_COLOR_FORMAT_KEY +INPUT_SHAPE_KEY +image_segmentation/models/deeplab_mobilenet_for_cpu +image_segmentation/labels/label_list +image_segmentation/images/human.jpg +1 +LITE_POWER_HIGH +RGB +1,3,513,513 + diff --git a/deploy/lite/human_segmentation_demo/app/src/main/res/values/styles.xml b/deploy/lite/human_segmentation_demo/app/src/main/res/values/styles.xml new file mode 100644 index 00000000..85326201 --- /dev/null +++ b/deploy/lite/human_segmentation_demo/app/src/main/res/values/styles.xml @@ -0,0 +1,25 @@ + + + + + + + + + +

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