添加android ocr demo
Signed-off-by: authorfu <fujiayi2012@gmail.com>
This commit is contained in:
authorfu
parent
a5eeb722a7
commit
dd280ec86a
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*.iml
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.gradle
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/local.properties
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/.idea/*
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.DS_Store
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/build
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/captures
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.externalNativeBuild
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# 如何快速测试
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### 1. 安装最新版本的Android Studio
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可以从https://developer.android.com/studio下载。本Demo使用是4.0版本Android Studio编写。
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### 2. 按照NDK 20 以上版本
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Demo测试的时候使用的是NDK 20b版本，20版本以上均可以支持编译成功。
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如果您是初学者，可以用以下方式安装和测试NDK编译环境。
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点击 File -> New ->New Project， 新建 "Native C++" project
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### 3. 导入项目
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点击 File->New->Import Project...， 然后跟着Android Studio的引导导入
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# 获得更多支持
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前往[端计算模型生成平台EasyEdge](https://ai.baidu.com/easyedge/app/open_source_demo?referrerUrl=paddlelite)，获得更多开发支持：
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- Demo APP：可使用手机扫码安装，方便手机端快速体验文字识别
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- SDK：模型被封装为适配不同芯片硬件和操作系统SDK，包括完善的接口，方便进行二次开发
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/build
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import java.security.MessageDigest
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apply plugin: 'com.android.application'
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android {
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compileSdkVersion 28
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defaultConfig {
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applicationId "com.baidu.paddle.lite.demo.ocr"
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minSdkVersion 15
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targetSdkVersion 28
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versionCode 1
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versionName "1.0"
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testInstrumentationRunner "android.support.test.runner.AndroidJUnitRunner"
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externalNativeBuild {
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cmake {
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cppFlags "-std=c++11 -frtti -fexceptions -Wno-format"
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arguments '-DANDROID_PLATFORM=android-23', '-DANDROID_STL=c++_shared' ,"-DANDROID_ARM_NEON=TRUE"
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}
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}
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ndk {
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// abiFilters "arm64-v8a", "armeabi-v7a"
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abiFilters "arm64-v8a", "armeabi-v7a"
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ldLibs "jnigraphics"
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}
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}
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buildTypes {
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release {
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minifyEnabled false
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proguardFiles getDefaultProguardFile('proguard-android-optimize.txt'), 'proguard-rules.pro'
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}
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}
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externalNativeBuild {
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cmake {
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path "src/main/cpp/CMakeLists.txt"
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version "3.10.2"
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}
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}
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}
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dependencies {
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implementation fileTree(include: ['*.jar'], dir: 'libs')
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implementation 'com.android.support:appcompat-v7:28.0.0'
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implementation 'com.android.support.constraint:constraint-layout:1.1.3'
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implementation 'com.android.support:design:28.0.0'
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testImplementation 'junit:junit:4.12'
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androidTestImplementation 'com.android.support.test:runner:1.0.2'
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androidTestImplementation 'com.android.support.test.espresso:espresso-core:3.0.2'
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}
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def archives = [
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[
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'src' : 'https://paddlelite-demo.bj.bcebos.com/libs/android/paddle_lite_libs_v2_6_1.tar.gz',
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'dest': 'PaddleLite'
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],
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[
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'src' : 'https://paddlelite-demo.bj.bcebos.com/libs/android/opencv-4.2.0-android-sdk.tar.gz',
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'dest': 'OpenCV'
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],
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[
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'src' : 'https://paddleocr.bj.bcebos.com/deploy/lite/ocr_v1_for_cpu.tar.gz',
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'dest' : 'src/main/assets/models/ocr_v1_for_cpu'
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]
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]
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task downloadAndExtractArchives(type: DefaultTask) {
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doFirst {
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println "Downloading and extracting archives including libs and models"
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}
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doLast {
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// Prepare cache folder for archives
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String cachePath = "cache"
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if (!file("${cachePath}").exists()) {
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mkdir "${cachePath}"
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}
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archives.eachWithIndex { archive, index ->
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MessageDigest messageDigest = MessageDigest.getInstance('MD5')
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messageDigest.update(archive.src.bytes)
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String cacheName = new BigInteger(1, messageDigest.digest()).toString(32)
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// Download the target archive if not exists
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boolean copyFiles = !file("${archive.dest}").exists()
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if (!file("${cachePath}/${cacheName}.tar.gz").exists()) {
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ant.get(src: archive.src, dest: file("${cachePath}/${cacheName}.tar.gz"))
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copyFiles = true; // force to copy files from the latest archive files
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}
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// Extract the target archive if its dest path does not exists
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if (copyFiles) {
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copy {
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from tarTree("${cachePath}/${cacheName}.tar.gz")
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into "${archive.dest}"
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}
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}
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}
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}
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}
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preBuild.dependsOn downloadAndExtractArchives
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# Add project specific ProGuard rules here.
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# You can control the set of applied configuration files using the
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# proguardFiles setting in build.gradle.
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#
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# For more details, see
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# http://developer.android.com/guide/developing/tools/proguard.html
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# If your project uses WebView with JS, uncomment the following
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# and specify the fully qualified class name to the JavaScript interface
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# class:
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#-keepclassmembers class fqcn.of.javascript.interface.for.webview {
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# public *;
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#}
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# Uncomment this to preserve the line number information for
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# debugging stack traces.
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#-keepattributes SourceFile,LineNumberTable
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# If you keep the line number information, uncomment this to
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# hide the original source file name.
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#-renamesourcefileattribute SourceFile
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package com.baidu.paddle.lite.demo.ocr;
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import android.content.Context;
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import android.support.test.InstrumentationRegistry;
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import android.support.test.runner.AndroidJUnit4;
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import org.junit.Test;
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import org.junit.runner.RunWith;
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import static org.junit.Assert.*;
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/**
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* Instrumented test, which will execute on an Android device.
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*
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* @see <a href="http://d.android.com/tools/testing">Testing documentation</a>
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*/
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@RunWith(AndroidJUnit4.class)
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public class ExampleInstrumentedTest {
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@Test
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public void useAppContext() {
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// Context of the app under test.
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Context appContext = InstrumentationRegistry.getTargetContext();
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assertEquals("com.baidu.paddle.lite.demo", appContext.getPackageName());
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}
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}
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<?xml version="1.0" encoding="utf-8"?>
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<manifest xmlns:android="http://schemas.android.com/apk/res/android"
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package="com.baidu.paddle.lite.demo.ocr">
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<uses-permission android:name="android.permission.WRITE_EXTERNAL_STORAGE"/>
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<uses-permission android:name="android.permission.READ_EXTERNAL_STORAGE"/>
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<uses-permission android:name="android.permission.CAMERA"/>
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<application
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android:allowBackup="true"
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android:icon="@mipmap/ic_launcher"
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android:label="@string/app_name"
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android:roundIcon="@mipmap/ic_launcher_round"
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android:supportsRtl="true"
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android:theme="@style/AppTheme">
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<activity android:name="com.baidu.paddle.lite.demo.ocr.MainActivity">
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<intent-filter>
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<action android:name="android.intent.action.MAIN"/>
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<category android:name="android.intent.category.LAUNCHER"/>
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</intent-filter>
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</activity>
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<activity
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android:name="com.baidu.paddle.lite.demo.ocr.SettingsActivity"
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android:label="Settings">
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</activity>
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</application>
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</manifest>
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Load Diff
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# For more information about using CMake with Android Studio, read the
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# documentation: https://d.android.com/studio/projects/add-native-code.html
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# Sets the minimum version of CMake required to build the native library.
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cmake_minimum_required(VERSION 3.4.1)
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# Creates and names a library, sets it as either STATIC or SHARED, and provides
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# the relative paths to its source code. You can define multiple libraries, and
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# CMake builds them for you. Gradle automatically packages shared libraries with
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# your APK.
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set(PaddleLite_DIR "${CMAKE_CURRENT_SOURCE_DIR}/../../../PaddleLite")
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include_directories(${PaddleLite_DIR}/cxx/include)
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set(OpenCV_DIR "${CMAKE_CURRENT_SOURCE_DIR}/../../../OpenCV/sdk/native/jni")
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message(STATUS "opencv dir: ${OpenCV_DIR}")
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find_package(OpenCV REQUIRED)
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message(STATUS "OpenCV libraries: ${OpenCV_LIBS}")
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include_directories(${OpenCV_INCLUDE_DIRS})
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aux_source_directory(. SOURCES)
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set(CMAKE_CXX_FLAGS
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"${CMAKE_CXX_FLAGS} -ffast-math -Ofast -Os"
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)
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set(CMAKE_CXX_FLAGS
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"${CMAKE_CXX_FLAGS} -fvisibility=hidden -fvisibility-inlines-hidden -fdata-sections -ffunction-sections"
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)
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set(CMAKE_SHARED_LINKER_FLAGS
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"${CMAKE_SHARED_LINKER_FLAGS} -Wl,--gc-sections -Wl,-z,nocopyreloc")
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add_library(
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# Sets the name of the library.
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Native
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# Sets the library as a shared library.
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SHARED
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# Provides a relative path to your source file(s).
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${SOURCES})
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find_library(
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# Sets the name of the path variable.
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log-lib
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# Specifies the name of the NDK library that you want CMake to locate.
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log)
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add_library(
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# Sets the name of the library.
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paddle_light_api_shared
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# Sets the library as a shared library.
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SHARED
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# Provides a relative path to your source file(s).
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IMPORTED)
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set_target_properties(
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# Specifies the target library.
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paddle_light_api_shared
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# Specifies the parameter you want to define.
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PROPERTIES
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IMPORTED_LOCATION
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${PaddleLite_DIR}/cxx/libs/${ANDROID_ABI}/libpaddle_light_api_shared.so
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# Provides the path to the library you want to import.
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)
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# Specifies libraries CMake should link to your target library. You can link
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# multiple libraries, such as libraries you define in this build script,
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# prebuilt third-party libraries, or system libraries.
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target_link_libraries(
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# Specifies the target library.
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Native
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paddle_light_api_shared
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${OpenCV_LIBS}
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GLESv2
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EGL
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jnigraphics
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${log-lib}
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)
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add_custom_command(
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TARGET Native
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POST_BUILD
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COMMAND
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${CMAKE_COMMAND} -E copy
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${PaddleLite_DIR}/cxx/libs/${ANDROID_ABI}/libc++_shared.so
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${CMAKE_LIBRARY_OUTPUT_DIRECTORY}/libc++_shared.so)
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add_custom_command(
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TARGET Native
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POST_BUILD
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COMMAND
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${CMAKE_COMMAND} -E copy
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${PaddleLite_DIR}/cxx/libs/${ANDROID_ABI}/libpaddle_light_api_shared.so
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${CMAKE_LIBRARY_OUTPUT_DIRECTORY}/libpaddle_light_api_shared.so)
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add_custom_command(
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TARGET Native
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POST_BUILD
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COMMAND
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${CMAKE_COMMAND} -E copy
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${PaddleLite_DIR}/cxx/libs/${ANDROID_ABI}/libhiai.so
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${CMAKE_LIBRARY_OUTPUT_DIRECTORY}/libhiai.so)
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add_custom_command(
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TARGET Native
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POST_BUILD
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COMMAND
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${CMAKE_COMMAND} -E copy
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${PaddleLite_DIR}/cxx/libs/${ANDROID_ABI}/libhiai_ir.so
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${CMAKE_LIBRARY_OUTPUT_DIRECTORY}/libhiai_ir.so)
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add_custom_command(
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TARGET Native
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POST_BUILD
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COMMAND
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${CMAKE_COMMAND} -E copy
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${PaddleLite_DIR}/cxx/libs/${ANDROID_ABI}/libhiai_ir_build.so
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${CMAKE_LIBRARY_OUTPUT_DIRECTORY}/libhiai_ir_build.so)
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//
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// Created by fu on 4/25/18.
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//
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#pragma once
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#import <vector>
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#import <numeric>
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#ifdef __ANDROID__
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#include <android/log.h>
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#define LOG_TAG "OCR_NDK"
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#define LOGI(...) \
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__android_log_print(ANDROID_LOG_INFO, LOG_TAG, __VA_ARGS__)
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#define LOGW(...) \
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__android_log_print(ANDROID_LOG_WARN, LOG_TAG, __VA_ARGS__)
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#define LOGE(...) \
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__android_log_print(ANDROID_LOG_ERROR, LOG_TAG, __VA_ARGS__)
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#else
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#include <stdio.h>
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#define LOGI(format, ...) \
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fprintf(stdout, "[" LOG_TAG "]" format "\n", ##__VA_ARGS__)
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#define LOGW(format, ...) \
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fprintf(stdout, "[" LOG_TAG "]" format "\n", ##__VA_ARGS__)
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#define LOGE(format, ...) \
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fprintf(stderr, "[" LOG_TAG "]Error: " format "\n", ##__VA_ARGS__)
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#endif
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enum RETURN_CODE {
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RETURN_OK = 0
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};
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enum NET_TYPE{
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NET_OCR = 900100,
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NET_OCR_INTERNAL = 991008
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};
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template <typename T>
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inline T product(const std::vector<T> &vec) {
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if (vec.empty()){
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return 0;
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}
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return std::accumulate(vec.begin(), vec.end(), 1, std::multiplies<T>());
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}
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//
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// Created by fujiayi on 2020/7/5.
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//
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#include "native.h"
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#include "ocr_ppredictor.h"
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#include <string>
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#include <algorithm>
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#include <paddle_api.h>
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static paddle::lite_api::PowerMode str_to_cpu_mode(const std::string &cpu_mode);
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extern "C"
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JNIEXPORT jlong JNICALL
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Java_com_baidu_paddle_lite_demo_ocr_OCRPredictorNative_init(JNIEnv *env, jobject thiz,
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jstring j_det_model_path,
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jstring j_rec_model_path,
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jint j_thread_num,
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jstring j_cpu_mode) {
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std::string det_model_path = jstring_to_cpp_string(env, j_det_model_path);
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std::string rec_model_path = jstring_to_cpp_string(env, j_rec_model_path);
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int thread_num = j_thread_num;
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std::string cpu_mode = jstring_to_cpp_string(env, j_cpu_mode);
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ppredictor::OCR_Config conf;
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conf.thread_num = thread_num;
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conf.mode = str_to_cpu_mode(cpu_mode);
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ppredictor::OCR_PPredictor *orc_predictor = new ppredictor::OCR_PPredictor{conf};
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orc_predictor->init_from_file(det_model_path, rec_model_path);
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return reinterpret_cast<jlong>(orc_predictor);
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}
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/**
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* "LITE_POWER_HIGH" 转为 paddle::lite_api::LITE_POWER_HIGH
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* @param cpu_mode
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* @return
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*/
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static paddle::lite_api::PowerMode str_to_cpu_mode(const std::string &cpu_mode) {
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static std::map<std::string, paddle::lite_api::PowerMode> cpu_mode_map{
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{"LITE_POWER_HIGH", paddle::lite_api::LITE_POWER_HIGH},
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{"LITE_POWER_LOW", paddle::lite_api::LITE_POWER_HIGH},
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{"LITE_POWER_FULL", paddle::lite_api::LITE_POWER_FULL},
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{"LITE_POWER_NO_BIND", paddle::lite_api::LITE_POWER_NO_BIND},
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{"LITE_POWER_RAND_HIGH", paddle::lite_api::LITE_POWER_RAND_HIGH},
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{"LITE_POWER_RAND_LOW", paddle::lite_api::LITE_POWER_RAND_LOW}
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};
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std::string upper_key;
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std::transform(cpu_mode.cbegin(), cpu_mode.cend(), upper_key.begin(), ::toupper);
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auto index = cpu_mode_map.find(upper_key);
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||||
if (index == cpu_mode_map.end()) {
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LOGE("cpu_mode not found %s", upper_key.c_str());
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return paddle::lite_api::LITE_POWER_HIGH;
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||||
} else {
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||||
return index->second;
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||||
}
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||||
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||||
}
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||||
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||||
extern "C"
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||||
JNIEXPORT jfloatArray JNICALL
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||||
Java_com_baidu_paddle_lite_demo_ocr_OCRPredictorNative_forward(JNIEnv *env, jobject thiz,
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jlong java_pointer, jfloatArray buf,
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||||
jfloatArray ddims,
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jobject original_image) {
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LOGI("begin to run native forward");
|
||||
if (java_pointer == 0) {
|
||||
LOGE("JAVA pointer is NULL");
|
||||
return cpp_array_to_jfloatarray(env, nullptr, 0);
|
||||
}
|
||||
cv::Mat origin = bitmap_to_cv_mat(env, original_image);
|
||||
if (origin.size == 0) {
|
||||
LOGE("origin bitmap cannot convert to CV Mat");
|
||||
return cpp_array_to_jfloatarray(env, nullptr, 0);
|
||||
}
|
||||
ppredictor::OCR_PPredictor *ppredictor = (ppredictor::OCR_PPredictor *) java_pointer;
|
||||
std::vector<float> dims_float_arr = jfloatarray_to_float_vector(env, ddims);
|
||||
std::vector<int64_t> dims_arr;
|
||||
dims_arr.resize(dims_float_arr.size());
|
||||
std::copy(dims_float_arr.cbegin(), dims_float_arr.cend(), dims_arr.begin());
|
||||
|
||||
// 这里值有点大，就不调用jfloatarray_to_float_vector了
|
||||
int64_t buf_len = (int64_t) env->GetArrayLength(buf);
|
||||
jfloat *buf_data = env->GetFloatArrayElements(buf, JNI_FALSE);
|
||||
float *data = (jfloat *) buf_data;
|
||||
std::vector<ppredictor::OCRPredictResult> results = ppredictor->infer_ocr(dims_arr, data,
|
||||
buf_len,
|
||||
NET_OCR, origin);
|
||||
LOGI("infer_ocr finished with boxes %ld", results.size());
|
||||
// 这里将std::vector<ppredictor::OCRPredictResult> 序列化成 float数组，传输到java层再反序列化
|
||||
std::vector<float> float_arr;
|
||||
for (const ppredictor::OCRPredictResult &r :results) {
|
||||
float_arr.push_back(r.points.size());
|
||||
float_arr.push_back(r.word_index.size());
|
||||
float_arr.push_back(r.score);
|
||||
for (const std::vector<int> &point : r.points) {
|
||||
float_arr.push_back(point.at(0));
|
||||
float_arr.push_back(point.at(1));
|
||||
}
|
||||
for (int index: r.word_index) {
|
||||
float_arr.push_back(index);
|
||||
}
|
||||
}
|
||||
return cpp_array_to_jfloatarray(env, float_arr.data(), float_arr.size());
|
||||
}
|
||||
|
||||
extern "C"
|
||||
JNIEXPORT void JNICALL
|
||||
Java_com_baidu_paddle_lite_demo_ocr_OCRPredictorNative_release(JNIEnv *env, jobject thiz,
|
||||
jlong java_pointer){
|
||||
if (java_pointer == 0) {
|
||||
LOGE("JAVA pointer is NULL");
|
||||
return;
|
||||
}
|
||||
ppredictor::OCR_PPredictor *ppredictor = (ppredictor::OCR_PPredictor *) java_pointer;
|
||||
delete ppredictor;
|
||||
}
|
||||
|
|
@ -0,0 +1,138 @@
|
|||
//
|
||||
// Created by fujiayi on 2020/7/5.
|
||||
//
|
||||
|
||||
#pragma once
|
||||
|
||||
|
||||
#include <jni.h>
|
||||
#include <string>
|
||||
#include <vector>
|
||||
#include <android/bitmap.h>
|
||||
#include <opencv2/opencv.hpp>
|
||||
#include "common.h"
|
||||
|
||||
inline std::string jstring_to_cpp_string(JNIEnv *env, jstring jstr) {
|
||||
// In java, a unicode char will be encoded using 2 bytes (utf16).
|
||||
// so jstring will contain characters utf16. std::string in c++ is
|
||||
// essentially a string of bytes, not characters, so if we want to
|
||||
// pass jstring from JNI to c++, we have convert utf16 to bytes.
|
||||
if (!jstr) {
|
||||
return "";
|
||||
}
|
||||
const jclass stringClass = env->GetObjectClass(jstr);
|
||||
const jmethodID getBytes =
|
||||
env->GetMethodID(stringClass, "getBytes", "(Ljava/lang/String;)[B");
|
||||
const jbyteArray stringJbytes = (jbyteArray) env->CallObjectMethod(
|
||||
jstr, getBytes, env->NewStringUTF("UTF-8"));
|
||||
|
||||
size_t length = (size_t) env->GetArrayLength(stringJbytes);
|
||||
jbyte *pBytes = env->GetByteArrayElements(stringJbytes, NULL);
|
||||
|
||||
std::string ret = std::string(reinterpret_cast<char *>(pBytes), length);
|
||||
env->ReleaseByteArrayElements(stringJbytes, pBytes, JNI_ABORT);
|
||||
|
||||
env->DeleteLocalRef(stringJbytes);
|
||||
env->DeleteLocalRef(stringClass);
|
||||
return ret;
|
||||
}
|
||||
|
||||
inline jstring cpp_string_to_jstring(JNIEnv *env, std::string str) {
|
||||
auto *data = str.c_str();
|
||||
jclass strClass = env->FindClass("java/lang/String");
|
||||
jmethodID strClassInitMethodID =
|
||||
env->GetMethodID(strClass, "<init>", "([BLjava/lang/String;)V");
|
||||
|
||||
jbyteArray bytes = env->NewByteArray(strlen(data));
|
||||
env->SetByteArrayRegion(bytes, 0, strlen(data),
|
||||
reinterpret_cast<const jbyte *>(data));
|
||||
|
||||
jstring encoding = env->NewStringUTF("UTF-8");
|
||||
jstring res = (jstring) (
|
||||
env->NewObject(strClass, strClassInitMethodID, bytes, encoding));
|
||||
|
||||
env->DeleteLocalRef(strClass);
|
||||
env->DeleteLocalRef(encoding);
|
||||
env->DeleteLocalRef(bytes);
|
||||
|
||||
return res;
|
||||
}
|
||||
|
||||
inline jfloatArray cpp_array_to_jfloatarray(JNIEnv *env, const float *buf,
|
||||
int64_t len) {
|
||||
if (len == 0) {
|
||||
return env->NewFloatArray(0);
|
||||
}
|
||||
jfloatArray result = env->NewFloatArray(len);
|
||||
env->SetFloatArrayRegion(result, 0, len, buf);
|
||||
return result;
|
||||
}
|
||||
|
||||
inline jintArray cpp_array_to_jintarray(JNIEnv *env, const int *buf,
|
||||
int64_t len) {
|
||||
jintArray result = env->NewIntArray(len);
|
||||
env->SetIntArrayRegion(result, 0, len, buf);
|
||||
return result;
|
||||
}
|
||||
|
||||
inline jbyteArray cpp_array_to_jbytearray(JNIEnv *env, const int8_t *buf,
|
||||
int64_t len) {
|
||||
jbyteArray result = env->NewByteArray(len);
|
||||
env->SetByteArrayRegion(result, 0, len, buf);
|
||||
return result;
|
||||
}
|
||||
|
||||
inline jlongArray int64_vector_to_jlongarray(JNIEnv *env,
|
||||
const std::vector<int64_t> &vec) {
|
||||
jlongArray result = env->NewLongArray(vec.size());
|
||||
jlong *buf = new jlong[vec.size()];
|
||||
for (size_t i = 0; i < vec.size(); ++i) {
|
||||
buf[i] = (jlong) vec[i];
|
||||
}
|
||||
env->SetLongArrayRegion(result, 0, vec.size(), buf);
|
||||
delete[] buf;
|
||||
return result;
|
||||
}
|
||||
|
||||
inline std::vector<int64_t> jlongarray_to_int64_vector(JNIEnv *env,
|
||||
jlongArray data) {
|
||||
int data_size = env->GetArrayLength(data);
|
||||
jlong *data_ptr = env->GetLongArrayElements(data, nullptr);
|
||||
std::vector<int64_t> data_vec(data_ptr, data_ptr + data_size);
|
||||
env->ReleaseLongArrayElements(data, data_ptr, 0);
|
||||
return data_vec;
|
||||
}
|
||||
|
||||
inline std::vector<float> jfloatarray_to_float_vector(JNIEnv *env,
|
||||
jfloatArray data) {
|
||||
int data_size = env->GetArrayLength(data);
|
||||
jfloat *data_ptr = env->GetFloatArrayElements(data, nullptr);
|
||||
std::vector<float> data_vec(data_ptr, data_ptr + data_size);
|
||||
env->ReleaseFloatArrayElements(data, data_ptr, 0);
|
||||
return data_vec;
|
||||
}
|
||||
|
||||
inline cv::Mat bitmap_to_cv_mat(JNIEnv *env, jobject bitmap) {
|
||||
AndroidBitmapInfo info;
|
||||
int result = AndroidBitmap_getInfo(env, bitmap, &info);
|
||||
if (result != ANDROID_BITMAP_RESULT_SUCCESS) {
|
||||
LOGE("AndroidBitmap_getInfo failed, result: %d", result);
|
||||
return cv::Mat{};
|
||||
}
|
||||
if (info.format != ANDROID_BITMAP_FORMAT_RGBA_8888) {
|
||||
LOGE("Bitmap format is not RGBA_8888 !");
|
||||
return cv::Mat{};
|
||||
}
|
||||
unsigned char *srcData = NULL;
|
||||
AndroidBitmap_lockPixels(env, bitmap, (void **) &srcData);
|
||||
cv::Mat mat = cv::Mat::zeros(info.height, info.width, CV_8UC4);
|
||||
memcpy(mat.data, srcData, info.height * info.width * 4);
|
||||
AndroidBitmap_unlockPixels(env, bitmap);
|
||||
cv::cvtColor(mat, mat, cv::COLOR_RGBA2BGR);
|
||||
/**
|
||||
if (!cv::imwrite("/sdcard/1/copy.jpg", mat)){
|
||||
LOGE("Write image failed " );
|
||||
}
|
||||
*/
|
||||
return mat;
|
||||
}
|
||||
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,547 @@
|
|||
/*******************************************************************************
|
||||
* *
|
||||
* Author : Angus Johnson *
|
||||
* Version : 6.4.2 *
|
||||
* Date : 27 February 2017 *
|
||||
* Website : http://www.angusj.com *
|
||||
* Copyright : Angus Johnson 2010-2017 *
|
||||
* *
|
||||
* License: *
|
||||
* Use, modification & distribution is subject to Boost Software License Ver 1. *
|
||||
* http://www.boost.org/LICENSE_1_0.txt *
|
||||
* *
|
||||
* Attributions: *
|
||||
* The code in this library is an extension of Bala Vatti's clipping algorithm: *
|
||||
* "A generic solution to polygon clipping" *
|
||||
* Communications of the ACM, Vol 35, Issue 7 (July 1992) pp 56-63. *
|
||||
* http://portal.acm.org/citation.cfm?id=129906 *
|
||||
* *
|
||||
* Computer graphics and geometric modeling: implementation and algorithms *
|
||||
* By Max K. Agoston *
|
||||
* Springer; 1 edition (January 4, 2005) *
|
||||
* http://books.google.com/books?q=vatti+clipping+agoston *
|
||||
* *
|
||||
* See also: *
|
||||
* "Polygon Offsetting by Computing Winding Numbers" *
|
||||
* Paper no. DETC2005-85513 pp. 565-575 *
|
||||
* ASME 2005 International Design Engineering Technical Conferences *
|
||||
* and Computers and Information in Engineering Conference (IDETC/CIE2005) *
|
||||
* September 24-28, 2005 , Long Beach, California, USA *
|
||||
* http://www.me.berkeley.edu/~mcmains/pubs/DAC05OffsetPolygon.pdf *
|
||||
* *
|
||||
*******************************************************************************/
|
||||
|
||||
#ifndef clipper_hpp
|
||||
#define clipper_hpp
|
||||
|
||||
#define CLIPPER_VERSION "6.4.2"
|
||||
|
||||
//use_int32: When enabled 32bit ints are used instead of 64bit ints. This
|
||||
//improve performance but coordinate values are limited to the range +/- 46340
|
||||
//#define use_int32
|
||||
|
||||
//use_xyz: adds a Z member to IntPoint. Adds a minor cost to perfomance.
|
||||
//#define use_xyz
|
||||
|
||||
//use_lines: Enables line clipping. Adds a very minor cost to performance.
|
||||
#define use_lines
|
||||
|
||||
//use_deprecated: Enables temporary support for the obsolete functions
|
||||
//#define use_deprecated
|
||||
|
||||
#include <vector>
|
||||
#include <list>
|
||||
#include <set>
|
||||
#include <stdexcept>
|
||||
#include <cstring>
|
||||
#include <cstdlib>
|
||||
#include <ostream>
|
||||
#include <functional>
|
||||
#include <queue>
|
||||
|
||||
namespace ClipperLib {
|
||||
|
||||
enum ClipType {
|
||||
ctIntersection, ctUnion, ctDifference, ctXor
|
||||
};
|
||||
enum PolyType {
|
||||
ptSubject, ptClip
|
||||
};
|
||||
//By far the most widely used winding rules for polygon filling are
|
||||
//EvenOdd & NonZero (GDI, GDI+, XLib, OpenGL, Cairo, AGG, Quartz, SVG, Gr32)
|
||||
//Others rules include Positive, Negative and ABS_GTR_EQ_TWO (only in OpenGL)
|
||||
//see http://glprogramming.com/red/chapter11.html
|
||||
enum PolyFillType {
|
||||
pftEvenOdd, pftNonZero, pftPositive, pftNegative
|
||||
};
|
||||
|
||||
#ifdef use_int32
|
||||
typedef int cInt;
|
||||
static cInt const loRange = 0x7FFF;
|
||||
static cInt const hiRange = 0x7FFF;
|
||||
#else
|
||||
typedef signed long long cInt;
|
||||
static cInt const loRange = 0x3FFFFFFF;
|
||||
static cInt const hiRange = 0x3FFFFFFFFFFFFFFFLL;
|
||||
typedef signed long long long64; //used by Int128 class
|
||||
typedef unsigned long long ulong64;
|
||||
|
||||
#endif
|
||||
|
||||
struct IntPoint {
|
||||
cInt X;
|
||||
cInt Y;
|
||||
#ifdef use_xyz
|
||||
cInt Z;
|
||||
IntPoint(cInt x = 0, cInt y = 0, cInt z = 0): X(x), Y(y), Z(z) {};
|
||||
#else
|
||||
|
||||
IntPoint(cInt x = 0, cInt y = 0) : X(x), Y(y) {};
|
||||
#endif
|
||||
|
||||
friend inline bool operator==(const IntPoint &a, const IntPoint &b) {
|
||||
return a.X == b.X && a.Y == b.Y;
|
||||
}
|
||||
|
||||
friend inline bool operator!=(const IntPoint &a, const IntPoint &b) {
|
||||
return a.X != b.X || a.Y != b.Y;
|
||||
}
|
||||
};
|
||||
//------------------------------------------------------------------------------
|
||||
|
||||
typedef std::vector <IntPoint> Path;
|
||||
typedef std::vector <Path> Paths;
|
||||
|
||||
inline Path &operator<<(Path &poly, const IntPoint &p) {
|
||||
poly.push_back(p);
|
||||
return poly;
|
||||
}
|
||||
|
||||
inline Paths &operator<<(Paths &polys, const Path &p) {
|
||||
polys.push_back(p);
|
||||
return polys;
|
||||
}
|
||||
|
||||
std::ostream &operator<<(std::ostream &s, const IntPoint &p);
|
||||
|
||||
std::ostream &operator<<(std::ostream &s, const Path &p);
|
||||
|
||||
std::ostream &operator<<(std::ostream &s, const Paths &p);
|
||||
|
||||
struct DoublePoint {
|
||||
double X;
|
||||
double Y;
|
||||
|
||||
DoublePoint(double x = 0, double y = 0) : X(x), Y(y) {}
|
||||
|
||||
DoublePoint(IntPoint ip) : X((double) ip.X), Y((double) ip.Y) {}
|
||||
};
|
||||
//------------------------------------------------------------------------------
|
||||
|
||||
#ifdef use_xyz
|
||||
typedef void (*ZFillCallback)(IntPoint& e1bot, IntPoint& e1top, IntPoint& e2bot, IntPoint& e2top, IntPoint& pt);
|
||||
#endif
|
||||
|
||||
enum InitOptions {
|
||||
ioReverseSolution = 1, ioStrictlySimple = 2, ioPreserveCollinear = 4
|
||||
};
|
||||
enum JoinType {
|
||||
jtSquare, jtRound, jtMiter
|
||||
};
|
||||
enum EndType {
|
||||
etClosedPolygon, etClosedLine, etOpenButt, etOpenSquare, etOpenRound
|
||||
};
|
||||
|
||||
class PolyNode;
|
||||
|
||||
typedef std::vector<PolyNode *> PolyNodes;
|
||||
|
||||
class PolyNode {
|
||||
public:
|
||||
PolyNode();
|
||||
|
||||
virtual ~PolyNode() {};
|
||||
Path Contour;
|
||||
PolyNodes Childs;
|
||||
PolyNode *Parent;
|
||||
|
||||
PolyNode *GetNext() const;
|
||||
|
||||
bool IsHole() const;
|
||||
|
||||
bool IsOpen() const;
|
||||
|
||||
int ChildCount() const;
|
||||
|
||||
private:
|
||||
//PolyNode& operator =(PolyNode& other);
|
||||
unsigned Index; //node index in Parent.Childs
|
||||
bool m_IsOpen;
|
||||
JoinType m_jointype;
|
||||
EndType m_endtype;
|
||||
|
||||
PolyNode *GetNextSiblingUp() const;
|
||||
|
||||
void AddChild(PolyNode &child);
|
||||
|
||||
friend class Clipper; //to access Index
|
||||
friend class ClipperOffset;
|
||||
};
|
||||
|
||||
class PolyTree : public PolyNode {
|
||||
public:
|
||||
~PolyTree() { Clear(); };
|
||||
|
||||
PolyNode *GetFirst() const;
|
||||
|
||||
void Clear();
|
||||
|
||||
int Total() const;
|
||||
|
||||
private:
|
||||
//PolyTree& operator =(PolyTree& other);
|
||||
PolyNodes AllNodes;
|
||||
|
||||
friend class Clipper; //to access AllNodes
|
||||
};
|
||||
|
||||
bool Orientation(const Path &poly);
|
||||
|
||||
double Area(const Path &poly);
|
||||
|
||||
int PointInPolygon(const IntPoint &pt, const Path &path);
|
||||
|
||||
void SimplifyPolygon(const Path &in_poly, Paths &out_polys, PolyFillType fillType = pftEvenOdd);
|
||||
|
||||
void SimplifyPolygons(const Paths &in_polys, Paths &out_polys, PolyFillType fillType = pftEvenOdd);
|
||||
|
||||
void SimplifyPolygons(Paths &polys, PolyFillType fillType = pftEvenOdd);
|
||||
|
||||
void CleanPolygon(const Path &in_poly, Path &out_poly, double distance = 1.415);
|
||||
|
||||
void CleanPolygon(Path &poly, double distance = 1.415);
|
||||
|
||||
void CleanPolygons(const Paths &in_polys, Paths &out_polys, double distance = 1.415);
|
||||
|
||||
void CleanPolygons(Paths &polys, double distance = 1.415);
|
||||
|
||||
void MinkowskiSum(const Path &pattern, const Path &path, Paths &solution, bool pathIsClosed);
|
||||
|
||||
void MinkowskiSum(const Path &pattern, const Paths &paths, Paths &solution, bool pathIsClosed);
|
||||
|
||||
void MinkowskiDiff(const Path &poly1, const Path &poly2, Paths &solution);
|
||||
|
||||
void PolyTreeToPaths(const PolyTree &polytree, Paths &paths);
|
||||
|
||||
void ClosedPathsFromPolyTree(const PolyTree &polytree, Paths &paths);
|
||||
|
||||
void OpenPathsFromPolyTree(PolyTree &polytree, Paths &paths);
|
||||
|
||||
void ReversePath(Path &p);
|
||||
|
||||
void ReversePaths(Paths &p);
|
||||
|
||||
struct IntRect {
|
||||
cInt left;
|
||||
cInt top;
|
||||
cInt right;
|
||||
cInt bottom;
|
||||
};
|
||||
|
||||
//enums that are used internally ...
|
||||
enum EdgeSide {
|
||||
esLeft = 1, esRight = 2
|
||||
};
|
||||
|
||||
//forward declarations (for stuff used internally) ...
|
||||
struct TEdge;
|
||||
struct IntersectNode;
|
||||
struct LocalMinimum;
|
||||
struct OutPt;
|
||||
struct OutRec;
|
||||
struct Join;
|
||||
|
||||
typedef std::vector<OutRec *> PolyOutList;
|
||||
typedef std::vector<TEdge *> EdgeList;
|
||||
typedef std::vector<Join *> JoinList;
|
||||
typedef std::vector<IntersectNode *> IntersectList;
|
||||
|
||||
//------------------------------------------------------------------------------
|
||||
|
||||
//ClipperBase is the ancestor to the Clipper class. It should not be
|
||||
//instantiated directly. This class simply abstracts the conversion of sets of
|
||||
//polygon coordinates into edge objects that are stored in a LocalMinima list.
|
||||
class ClipperBase {
|
||||
public:
|
||||
ClipperBase();
|
||||
|
||||
virtual ~ClipperBase();
|
||||
|
||||
virtual bool AddPath(const Path &pg, PolyType PolyTyp, bool Closed);
|
||||
|
||||
bool AddPaths(const Paths &ppg, PolyType PolyTyp, bool Closed);
|
||||
|
||||
virtual void Clear();
|
||||
|
||||
IntRect GetBounds();
|
||||
|
||||
bool PreserveCollinear() { return m_PreserveCollinear; };
|
||||
|
||||
void PreserveCollinear(bool value) { m_PreserveCollinear = value; };
|
||||
protected:
|
||||
void DisposeLocalMinimaList();
|
||||
|
||||
TEdge *AddBoundsToLML(TEdge *e, bool IsClosed);
|
||||
|
||||
virtual void Reset();
|
||||
|
||||
TEdge *ProcessBound(TEdge *E, bool IsClockwise);
|
||||
|
||||
void InsertScanbeam(const cInt Y);
|
||||
|
||||
bool PopScanbeam(cInt &Y);
|
||||
|
||||
bool LocalMinimaPending();
|
||||
|
||||
bool PopLocalMinima(cInt Y, const LocalMinimum *&locMin);
|
||||
|
||||
OutRec *CreateOutRec();
|
||||
|
||||
void DisposeAllOutRecs();
|
||||
|
||||
void DisposeOutRec(PolyOutList::size_type index);
|
||||
|
||||
void SwapPositionsInAEL(TEdge *edge1, TEdge *edge2);
|
||||
|
||||
void DeleteFromAEL(TEdge *e);
|
||||
|
||||
void UpdateEdgeIntoAEL(TEdge *&e);
|
||||
|
||||
typedef std::vector <LocalMinimum> MinimaList;
|
||||
MinimaList::iterator m_CurrentLM;
|
||||
MinimaList m_MinimaList;
|
||||
|
||||
bool m_UseFullRange;
|
||||
EdgeList m_edges;
|
||||
bool m_PreserveCollinear;
|
||||
bool m_HasOpenPaths;
|
||||
PolyOutList m_PolyOuts;
|
||||
TEdge *m_ActiveEdges;
|
||||
|
||||
typedef std::priority_queue <cInt> ScanbeamList;
|
||||
ScanbeamList m_Scanbeam;
|
||||
};
|
||||
//------------------------------------------------------------------------------
|
||||
|
||||
class Clipper : public virtual ClipperBase {
|
||||
public:
|
||||
Clipper(int initOptions = 0);
|
||||
|
||||
bool Execute(ClipType clipType,
|
||||
Paths &solution,
|
||||
PolyFillType fillType = pftEvenOdd);
|
||||
|
||||
bool Execute(ClipType clipType,
|
||||
Paths &solution,
|
||||
PolyFillType subjFillType,
|
||||
PolyFillType clipFillType);
|
||||
|
||||
bool Execute(ClipType clipType,
|
||||
PolyTree &polytree,
|
||||
PolyFillType fillType = pftEvenOdd);
|
||||
|
||||
bool Execute(ClipType clipType,
|
||||
PolyTree &polytree,
|
||||
PolyFillType subjFillType,
|
||||
PolyFillType clipFillType);
|
||||
|
||||
bool ReverseSolution() { return m_ReverseOutput; };
|
||||
|
||||
void ReverseSolution(bool value) { m_ReverseOutput = value; };
|
||||
|
||||
bool StrictlySimple() { return m_StrictSimple; };
|
||||
|
||||
void StrictlySimple(bool value) { m_StrictSimple = value; };
|
||||
//set the callback function for z value filling on intersections (otherwise Z is 0)
|
||||
#ifdef use_xyz
|
||||
void ZFillFunction(ZFillCallback zFillFunc);
|
||||
#endif
|
||||
protected:
|
||||
virtual bool ExecuteInternal();
|
||||
|
||||
private:
|
||||
JoinList m_Joins;
|
||||
JoinList m_GhostJoins;
|
||||
IntersectList m_IntersectList;
|
||||
ClipType m_ClipType;
|
||||
typedef std::list <cInt> MaximaList;
|
||||
MaximaList m_Maxima;
|
||||
TEdge *m_SortedEdges;
|
||||
bool m_ExecuteLocked;
|
||||
PolyFillType m_ClipFillType;
|
||||
PolyFillType m_SubjFillType;
|
||||
bool m_ReverseOutput;
|
||||
bool m_UsingPolyTree;
|
||||
bool m_StrictSimple;
|
||||
#ifdef use_xyz
|
||||
ZFillCallback m_ZFill; //custom callback
|
||||
#endif
|
||||
|
||||
void SetWindingCount(TEdge &edge);
|
||||
|
||||
bool IsEvenOddFillType(const TEdge &edge) const;
|
||||
|
||||
bool IsEvenOddAltFillType(const TEdge &edge) const;
|
||||
|
||||
void InsertLocalMinimaIntoAEL(const cInt botY);
|
||||
|
||||
void InsertEdgeIntoAEL(TEdge *edge, TEdge *startEdge);
|
||||
|
||||
void AddEdgeToSEL(TEdge *edge);
|
||||
|
||||
bool PopEdgeFromSEL(TEdge *&edge);
|
||||
|
||||
void CopyAELToSEL();
|
||||
|
||||
void DeleteFromSEL(TEdge *e);
|
||||
|
||||
void SwapPositionsInSEL(TEdge *edge1, TEdge *edge2);
|
||||
|
||||
bool IsContributing(const TEdge &edge) const;
|
||||
|
||||
bool IsTopHorz(const cInt XPos);
|
||||
|
||||
void DoMaxima(TEdge *e);
|
||||
|
||||
void ProcessHorizontals();
|
||||
|
||||
void ProcessHorizontal(TEdge *horzEdge);
|
||||
|
||||
void AddLocalMaxPoly(TEdge *e1, TEdge *e2, const IntPoint &pt);
|
||||
|
||||
OutPt *AddLocalMinPoly(TEdge *e1, TEdge *e2, const IntPoint &pt);
|
||||
|
||||
OutRec *GetOutRec(int idx);
|
||||
|
||||
void AppendPolygon(TEdge *e1, TEdge *e2);
|
||||
|
||||
void IntersectEdges(TEdge *e1, TEdge *e2, IntPoint &pt);
|
||||
|
||||
OutPt *AddOutPt(TEdge *e, const IntPoint &pt);
|
||||
|
||||
OutPt *GetLastOutPt(TEdge *e);
|
||||
|
||||
bool ProcessIntersections(const cInt topY);
|
||||
|
||||
void BuildIntersectList(const cInt topY);
|
||||
|
||||
void ProcessIntersectList();
|
||||
|
||||
void ProcessEdgesAtTopOfScanbeam(const cInt topY);
|
||||
|
||||
void BuildResult(Paths &polys);
|
||||
|
||||
void BuildResult2(PolyTree &polytree);
|
||||
|
||||
void SetHoleState(TEdge *e, OutRec *outrec);
|
||||
|
||||
void DisposeIntersectNodes();
|
||||
|
||||
bool FixupIntersectionOrder();
|
||||
|
||||
void FixupOutPolygon(OutRec &outrec);
|
||||
|
||||
void FixupOutPolyline(OutRec &outrec);
|
||||
|
||||
bool IsHole(TEdge *e);
|
||||
|
||||
bool FindOwnerFromSplitRecs(OutRec &outRec, OutRec *&currOrfl);
|
||||
|
||||
void FixHoleLinkage(OutRec &outrec);
|
||||
|
||||
void AddJoin(OutPt *op1, OutPt *op2, const IntPoint offPt);
|
||||
|
||||
void ClearJoins();
|
||||
|
||||
void ClearGhostJoins();
|
||||
|
||||
void AddGhostJoin(OutPt *op, const IntPoint offPt);
|
||||
|
||||
bool JoinPoints(Join *j, OutRec *outRec1, OutRec *outRec2);
|
||||
|
||||
void JoinCommonEdges();
|
||||
|
||||
void DoSimplePolygons();
|
||||
|
||||
void FixupFirstLefts1(OutRec *OldOutRec, OutRec *NewOutRec);
|
||||
|
||||
void FixupFirstLefts2(OutRec *InnerOutRec, OutRec *OuterOutRec);
|
||||
|
||||
void FixupFirstLefts3(OutRec *OldOutRec, OutRec *NewOutRec);
|
||||
|
||||
#ifdef use_xyz
|
||||
void SetZ(IntPoint& pt, TEdge& e1, TEdge& e2);
|
||||
#endif
|
||||
};
|
||||
//------------------------------------------------------------------------------
|
||||
|
||||
class ClipperOffset {
|
||||
public:
|
||||
ClipperOffset(double miterLimit = 2.0, double roundPrecision = 0.25);
|
||||
|
||||
~ClipperOffset();
|
||||
|
||||
void AddPath(const Path &path, JoinType joinType, EndType endType);
|
||||
|
||||
void AddPaths(const Paths &paths, JoinType joinType, EndType endType);
|
||||
|
||||
void Execute(Paths &solution, double delta);
|
||||
|
||||
void Execute(PolyTree &solution, double delta);
|
||||
|
||||
void Clear();
|
||||
|
||||
double MiterLimit;
|
||||
double ArcTolerance;
|
||||
private:
|
||||
Paths m_destPolys;
|
||||
Path m_srcPoly;
|
||||
Path m_destPoly;
|
||||
std::vector <DoublePoint> m_normals;
|
||||
double m_delta, m_sinA, m_sin, m_cos;
|
||||
double m_miterLim, m_StepsPerRad;
|
||||
IntPoint m_lowest;
|
||||
PolyNode m_polyNodes;
|
||||
|
||||
void FixOrientations();
|
||||
|
||||
void DoOffset(double delta);
|
||||
|
||||
void OffsetPoint(int j, int &k, JoinType jointype);
|
||||
|
||||
void DoSquare(int j, int k);
|
||||
|
||||
void DoMiter(int j, int k, double r);
|
||||
|
||||
void DoRound(int j, int k);
|
||||
};
|
||||
//------------------------------------------------------------------------------
|
||||
|
||||
class clipperException : public std::exception {
|
||||
public:
|
||||
clipperException(const char *description) : m_descr(description) {}
|
||||
|
||||
virtual ~clipperException() throw() {}
|
||||
|
||||
virtual const char *what() const throw() { return m_descr.c_str(); }
|
||||
|
||||
private:
|
||||
std::string m_descr;
|
||||
};
|
||||
//------------------------------------------------------------------------------
|
||||
|
||||
} //ClipperLib namespace
|
||||
|
||||
#endif //clipper_hpp
|
||||
|
||||
|
||||
|
|
@ -0,0 +1,140 @@
|
|||
// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
|
||||
//
|
||||
// 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.
|
||||
|
||||
#include "ocr_crnn_process.h"
|
||||
#include <iostream>
|
||||
#include <vector>
|
||||
#include <iostream>
|
||||
#include <cstring>
|
||||
#include <fstream>
|
||||
#include <cmath>
|
||||
|
||||
const std::string CHARACTER_TYPE = "ch";
|
||||
const int MAX_DICT_LENGTH = 6624;
|
||||
const std::vector<int> REC_IMAGE_SHAPE = {3, 32, 320};
|
||||
|
||||
static cv::Mat crnn_resize_norm_img(cv::Mat img, float wh_ratio) {
|
||||
int imgC = REC_IMAGE_SHAPE[0];
|
||||
int imgW = REC_IMAGE_SHAPE[2];
|
||||
int imgH = REC_IMAGE_SHAPE[1];
|
||||
|
||||
if (CHARACTER_TYPE == "ch")
|
||||
imgW = int(32 * wh_ratio);
|
||||
|
||||
float ratio = float(img.cols) / float(img.rows);
|
||||
int resize_w = 0;
|
||||
if (ceilf(imgH * ratio) > imgW)
|
||||
resize_w = imgW;
|
||||
else
|
||||
resize_w = int(ceilf(imgH * ratio));
|
||||
cv::Mat resize_img;
|
||||
cv::resize(img, resize_img, cv::Size(resize_w, imgH), 0.f, 0.f, cv::INTER_CUBIC);
|
||||
|
||||
resize_img.convertTo(resize_img, CV_32FC3, 1 / 255.f);
|
||||
|
||||
for (int h = 0; h < resize_img.rows; h++) {
|
||||
for (int w = 0; w < resize_img.cols; w++) {
|
||||
resize_img.at<cv::Vec3f>(h, w)[0] = (resize_img.at<cv::Vec3f>(h, w)[0] - 0.5) * 2;
|
||||
resize_img.at<cv::Vec3f>(h, w)[1] = (resize_img.at<cv::Vec3f>(h, w)[1] - 0.5) * 2;
|
||||
resize_img.at<cv::Vec3f>(h, w)[2] = (resize_img.at<cv::Vec3f>(h, w)[2] - 0.5) * 2;
|
||||
}
|
||||
}
|
||||
|
||||
cv::Mat dist;
|
||||
cv::copyMakeBorder(resize_img, dist, 0, 0, 0, int(imgW - resize_w), cv::BORDER_CONSTANT,
|
||||
{0, 0, 0});
|
||||
|
||||
return dist;
|
||||
|
||||
}
|
||||
|
||||
cv::Mat crnn_resize_img(const cv::Mat &img, float wh_ratio) {
|
||||
int imgC = REC_IMAGE_SHAPE[0];
|
||||
int imgW = REC_IMAGE_SHAPE[2];
|
||||
int imgH = REC_IMAGE_SHAPE[1];
|
||||
|
||||
if (CHARACTER_TYPE == "ch") {
|
||||
imgW = int(32 * wh_ratio);
|
||||
}
|
||||
|
||||
float ratio = float(img.cols) / float(img.rows);
|
||||
int resize_w = 0;
|
||||
if (ceilf(imgH * ratio) > imgW)
|
||||
resize_w = imgW;
|
||||
else
|
||||
resize_w = int(ceilf(imgH * ratio));
|
||||
cv::Mat resize_img;
|
||||
cv::resize(img, resize_img, cv::Size(resize_w, imgH));
|
||||
return resize_img;
|
||||
}
|
||||
|
||||
|
||||
cv::Mat get_rotate_crop_image(const cv::Mat &srcimage, const std::vector<std::vector<int>> &box) {
|
||||
|
||||
std::vector<std::vector<int>> points = box;
|
||||
|
||||
int x_collect[4] = {box[0][0], box[1][0], box[2][0], box[3][0]};
|
||||
int y_collect[4] = {box[0][1], box[1][1], box[2][1], box[3][1]};
|
||||
int left = int(*std::min_element(x_collect, x_collect + 4));
|
||||
int right = int(*std::max_element(x_collect, x_collect + 4));
|
||||
int top = int(*std::min_element(y_collect, y_collect + 4));
|
||||
int bottom = int(*std::max_element(y_collect, y_collect + 4));
|
||||
|
||||
cv::Mat img_crop;
|
||||
srcimage(cv::Rect(left, top, right - left, bottom - top)).copyTo(img_crop);
|
||||
|
||||
for (int i = 0; i < points.size(); i++) {
|
||||
points[i][0] -= left;
|
||||
points[i][1] -= top;
|
||||
}
|
||||
|
||||
int img_crop_width = int(sqrt(pow(points[0][0] - points[1][0], 2) +
|
||||
pow(points[0][1] - points[1][1], 2)));
|
||||
int img_crop_height = int(sqrt(pow(points[0][0] - points[3][0], 2) +
|
||||
pow(points[0][1] - points[3][1], 2)));
|
||||
|
||||
cv::Point2f pts_std[4];
|
||||
pts_std[0] = cv::Point2f(0., 0.);
|
||||
pts_std[1] = cv::Point2f(img_crop_width, 0.);
|
||||
pts_std[2] = cv::Point2f(img_crop_width, img_crop_height);
|
||||
pts_std[3] = cv::Point2f(0.f, img_crop_height);
|
||||
|
||||
cv::Point2f pointsf[4];
|
||||
pointsf[0] = cv::Point2f(points[0][0], points[0][1]);
|
||||
pointsf[1] = cv::Point2f(points[1][0], points[1][1]);
|
||||
pointsf[2] = cv::Point2f(points[2][0], points[2][1]);
|
||||
pointsf[3] = cv::Point2f(points[3][0], points[3][1]);
|
||||
|
||||
cv::Mat M = cv::getPerspectiveTransform(pointsf, pts_std);
|
||||
|
||||
cv::Mat dst_img;
|
||||
cv::warpPerspective(img_crop, dst_img, M, cv::Size(img_crop_width, img_crop_height),
|
||||
cv::BORDER_REPLICATE);
|
||||
|
||||
if (float(dst_img.rows) >= float(dst_img.cols) * 1.5) {
|
||||
/*
|
||||
cv::Mat srcCopy = cv::Mat(dst_img.rows, dst_img.cols, dst_img.depth());
|
||||
cv::transpose(dst_img, srcCopy);
|
||||
cv::flip(srcCopy, srcCopy, 0);
|
||||
return srcCopy;
|
||||
*/
|
||||
cv::transpose(dst_img, dst_img);
|
||||
cv::flip(dst_img, dst_img, 0);
|
||||
return dst_img;
|
||||
} else {
|
||||
return dst_img;
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
|
|
@ -0,0 +1,19 @@
|
|||
//
|
||||
// Created by fujiayi on 2020/7/3.
|
||||
//
|
||||
#pragma once
|
||||
|
||||
#include <vector>
|
||||
#include <opencv2/opencv.hpp>
|
||||
#include "common.h"
|
||||
|
||||
extern const std::vector<int> REC_IMAGE_SHAPE;
|
||||
|
||||
cv::Mat get_rotate_crop_image(const cv::Mat &srcimage, const std::vector<std::vector<int>> &box);
|
||||
|
||||
cv::Mat crnn_resize_img(const cv::Mat &img, float wh_ratio);
|
||||
|
||||
template<class ForwardIterator>
|
||||
inline size_t argmax(ForwardIterator first, ForwardIterator last) {
|
||||
return std::distance(first, std::max_element(first, last));
|
||||
}
|
||||
|
|
@ -0,0 +1,336 @@
|
|||
// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
|
||||
//
|
||||
// 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.
|
||||
|
||||
#include <iostream>
|
||||
#include <vector>
|
||||
#include <math.h>
|
||||
#include "opencv2/core.hpp"
|
||||
#include "opencv2/imgcodecs.hpp"
|
||||
#include "opencv2/imgproc.hpp"
|
||||
#include "ocr_clipper.hpp"
|
||||
|
||||
static void getcontourarea(float **box, float unclip_ratio, float &distance) {
|
||||
int pts_num = 4;
|
||||
float area = 0.0f;
|
||||
float dist = 0.0f;
|
||||
for (int i = 0; i < pts_num; i++) {
|
||||
area += box[i][0] * box[(i + 1) % pts_num][1] - box[i][1] * box[(i + 1) % pts_num][0];
|
||||
dist += sqrtf(
|
||||
(box[i][0] - box[(i + 1) % pts_num][0]) * (box[i][0] - box[(i + 1) % pts_num][0]) +
|
||||
(box[i][1] - box[(i + 1) % pts_num][1]) * (box[i][1] - box[(i + 1) % pts_num][1]));
|
||||
}
|
||||
area = fabs(float(area / 2.0));
|
||||
|
||||
distance = area * unclip_ratio / dist;
|
||||
|
||||
}
|
||||
|
||||
static cv::RotatedRect unclip(float **box) {
|
||||
float unclip_ratio = 2.0;
|
||||
float distance = 1.0;
|
||||
|
||||
getcontourarea(box, unclip_ratio, distance);
|
||||
|
||||
ClipperLib::ClipperOffset offset;
|
||||
ClipperLib::Path p;
|
||||
p << ClipperLib::IntPoint(int(box[0][0]), int(box[0][1]))
|
||||
<< ClipperLib::IntPoint(int(box[1][0]), int(box[1][1])) <<
|
||||
ClipperLib::IntPoint(int(box[2][0]), int(box[2][1]))
|
||||
<< ClipperLib::IntPoint(int(box[3][0]), int(box[3][1]));
|
||||
offset.AddPath(p, ClipperLib::jtRound, ClipperLib::etClosedPolygon);
|
||||
|
||||
ClipperLib::Paths soln;
|
||||
offset.Execute(soln, distance);
|
||||
std::vector<cv::Point2f> points;
|
||||
|
||||
for (int j = 0; j < soln.size(); j++) {
|
||||
for (int i = 0; i < soln[soln.size() - 1].size(); i++) {
|
||||
points.emplace_back(soln[j][i].X, soln[j][i].Y);
|
||||
}
|
||||
}
|
||||
cv::RotatedRect res = cv::minAreaRect(points);
|
||||
|
||||
return res;
|
||||
}
|
||||
|
||||
static float **Mat2Vec(cv::Mat mat) {
|
||||
auto **array = new float *[mat.rows];
|
||||
for (int i = 0; i < mat.rows; ++i){
|
||||
array[i] = new float[mat.cols];
|
||||
}
|
||||
for (int i = 0; i < mat.rows; ++i) {
|
||||
for (int j = 0; j < mat.cols; ++j) {
|
||||
array[i][j] = mat.at<float>(i, j);
|
||||
}
|
||||
}
|
||||
|
||||
return array;
|
||||
}
|
||||
|
||||
static void quickSort(float **s, int l, int r) {
|
||||
if (l < r) {
|
||||
int i = l, j = r;
|
||||
float x = s[l][0];
|
||||
float *xp = s[l];
|
||||
while (i < j) {
|
||||
while (i < j && s[j][0] >= x){
|
||||
j--;
|
||||
}
|
||||
if (i < j){
|
||||
std::swap(s[i++], s[j]);
|
||||
}
|
||||
while (i < j && s[i][0] < x){
|
||||
i++;
|
||||
}
|
||||
if (i < j){
|
||||
std::swap(s[j--], s[i]);
|
||||
}
|
||||
}
|
||||
s[i] = xp;
|
||||
quickSort(s, l, i - 1);
|
||||
quickSort(s, i + 1, r);
|
||||
}
|
||||
}
|
||||
|
||||
static void quickSort_vector(std::vector<std::vector<int>> &box, int l, int r, int axis) {
|
||||
if (l < r) {
|
||||
int i = l, j = r;
|
||||
int x = box[l][axis];
|
||||
std::vector<int> xp(box[l]);
|
||||
while (i < j) {
|
||||
while (i < j && box[j][axis] >= x){
|
||||
j--;
|
||||
}
|
||||
if (i < j){
|
||||
std::swap(box[i++], box[j]);
|
||||
}
|
||||
while (i < j && box[i][axis] < x){
|
||||
i++;
|
||||
}
|
||||
if (i < j){
|
||||
std::swap(box[j--], box[i]);
|
||||
}
|
||||
}
|
||||
box[i] = xp;
|
||||
quickSort_vector(box, l, i - 1, axis);
|
||||
quickSort_vector(box, i + 1, r, axis);
|
||||
}
|
||||
}
|
||||
|
||||
static std::vector<std::vector<int>> order_points_clockwise(std::vector<std::vector<int>> pts) {
|
||||
std::vector<std::vector<int>> box = pts;
|
||||
quickSort_vector(box, 0, int(box.size() - 1), 0);
|
||||
std::vector<std::vector<int>> leftmost = {box[0], box[1]};
|
||||
std::vector<std::vector<int>> rightmost = {box[2], box[3]};
|
||||
|
||||
if (leftmost[0][1] > leftmost[1][1]){
|
||||
std::swap(leftmost[0], leftmost[1]);
|
||||
}
|
||||
|
||||
if (rightmost[0][1] > rightmost[1][1]){
|
||||
std::swap(rightmost[0], rightmost[1]);
|
||||
}
|
||||
|
||||
std::vector<std::vector<int>> rect = {leftmost[0], rightmost[0], rightmost[1], leftmost[1]};
|
||||
return rect;
|
||||
}
|
||||
|
||||
static float **get_mini_boxes(cv::RotatedRect box, float &ssid) {
|
||||
ssid = box.size.width >= box.size.height ? box.size.height : box.size.width;
|
||||
|
||||
cv::Mat points;
|
||||
cv::boxPoints(box, points);
|
||||
// sorted box points
|
||||
auto array = Mat2Vec(points);
|
||||
quickSort(array, 0, 3);
|
||||
|
||||
float *idx1 = array[0], *idx2 = array[1], *idx3 = array[2], *idx4 = array[3];
|
||||
if (array[3][1] <= array[2][1]) {
|
||||
idx2 = array[3];
|
||||
idx3 = array[2];
|
||||
} else {
|
||||
idx2 = array[2];
|
||||
idx3 = array[3];
|
||||
}
|
||||
if (array[1][1] <= array[0][1]) {
|
||||
idx1 = array[1];
|
||||
idx4 = array[0];
|
||||
} else {
|
||||
idx1 = array[0];
|
||||
idx4 = array[1];
|
||||
}
|
||||
|
||||
array[0] = idx1;
|
||||
array[1] = idx2;
|
||||
array[2] = idx3;
|
||||
array[3] = idx4;
|
||||
|
||||
return array;
|
||||
}
|
||||
|
||||
template <class T> T clamp(T x, T min, T max) {
|
||||
if (x > max){
|
||||
return max;
|
||||
}
|
||||
if (x < min){
|
||||
return min;
|
||||
}
|
||||
return x;
|
||||
}
|
||||
|
||||
static float clampf(float x, float min, float max) {
|
||||
if (x > max)
|
||||
return max;
|
||||
if (x < min)
|
||||
return min;
|
||||
return x;
|
||||
}
|
||||
|
||||
|
||||
float box_score_fast(float **box_array, cv::Mat pred) {
|
||||
auto array = box_array;
|
||||
int width = pred.cols;
|
||||
int height = pred.rows;
|
||||
|
||||
float box_x[4] = {array[0][0], array[1][0], array[2][0], array[3][0]};
|
||||
float box_y[4] = {array[0][1], array[1][1], array[2][1], array[3][1]};
|
||||
|
||||
int xmin = clamp(int(std::floorf(*(std::min_element(box_x, box_x + 4)))), 0, width - 1);
|
||||
int xmax = clamp(int(std::ceilf(*(std::max_element(box_x, box_x + 4)))), 0, width - 1);
|
||||
int ymin = clamp(int(std::floorf(*(std::min_element(box_y, box_y + 4)))), 0, height - 1);
|
||||
int ymax = clamp(int(std::ceilf(*(std::max_element(box_y, box_y + 4)))), 0, height - 1);
|
||||
|
||||
cv::Mat mask;
|
||||
mask = cv::Mat::zeros(ymax - ymin + 1, xmax - xmin + 1, CV_8UC1);
|
||||
|
||||
cv::Point root_point[4];
|
||||
root_point[0] = cv::Point(int(array[0][0]) - xmin, int(array[0][1]) - ymin);
|
||||
root_point[1] = cv::Point(int(array[1][0]) - xmin, int(array[1][1]) - ymin);
|
||||
root_point[2] = cv::Point(int(array[2][0]) - xmin, int(array[2][1]) - ymin);
|
||||
root_point[3] = cv::Point(int(array[3][0]) - xmin, int(array[3][1]) - ymin);
|
||||
const cv::Point *ppt[1] = {root_point};
|
||||
int npt[] = {4};
|
||||
cv::fillPoly(mask, ppt, npt, 1, cv::Scalar(1));
|
||||
|
||||
cv::Mat croppedImg;
|
||||
pred(cv::Rect(xmin, ymin, xmax - xmin + 1, ymax - ymin + 1)).copyTo(croppedImg);
|
||||
|
||||
auto score = cv::mean(croppedImg, mask)[0];
|
||||
return score;
|
||||
}
|
||||
|
||||
|
||||
std::vector<std::vector<std::vector<int>>>
|
||||
boxes_from_bitmap(const cv::Mat& pred, const cv::Mat& bitmap) {
|
||||
const int min_size = 3;
|
||||
const int max_candidates = 1000;
|
||||
const float box_thresh = 0.5;
|
||||
|
||||
int width = bitmap.cols;
|
||||
int height = bitmap.rows;
|
||||
|
||||
std::vector<std::vector<cv::Point>> contours;
|
||||
std::vector<cv::Vec4i> hierarchy;
|
||||
|
||||
cv::findContours(bitmap, contours, hierarchy, cv::RETR_LIST, cv::CHAIN_APPROX_SIMPLE);
|
||||
|
||||
int num_contours = contours.size() >= max_candidates ? max_candidates : contours.size();
|
||||
|
||||
std::vector<std::vector<std::vector<int>>> boxes;
|
||||
|
||||
for (int _i = 0; _i < num_contours; _i++) {
|
||||
float ssid;
|
||||
cv::RotatedRect box = cv::minAreaRect(contours[_i]);
|
||||
auto array = get_mini_boxes(box, ssid);
|
||||
|
||||
auto box_for_unclip = array;
|
||||
//end get_mini_box
|
||||
|
||||
if (ssid < min_size) {
|
||||
continue;
|
||||
}
|
||||
|
||||
float score;
|
||||
score = box_score_fast(array, pred);
|
||||
//end box_score_fast
|
||||
if (score < box_thresh){
|
||||
continue;
|
||||
}
|
||||
|
||||
|
||||
// start for unclip
|
||||
cv::RotatedRect points = unclip(box_for_unclip);
|
||||
// end for unclip
|
||||
|
||||
cv::RotatedRect clipbox = points;
|
||||
auto cliparray = get_mini_boxes(clipbox, ssid);
|
||||
|
||||
if (ssid < min_size + 2) continue;
|
||||
|
||||
int dest_width = pred.cols;
|
||||
int dest_height = pred.rows;
|
||||
std::vector<std::vector<int>> intcliparray;
|
||||
|
||||
for (int num_pt = 0; num_pt < 4; num_pt++) {
|
||||
std::vector<int> a{
|
||||
int(clampf(roundf(cliparray[num_pt][0] / float(width) * float(dest_width)), 0,
|
||||
float(dest_width))),
|
||||
int(clampf(roundf(cliparray[num_pt][1] / float(height) * float(dest_height)), 0,
|
||||
float(dest_height)))};
|
||||
intcliparray.emplace_back(std::move(a));
|
||||
}
|
||||
boxes.emplace_back(std::move(intcliparray));
|
||||
|
||||
}//end for
|
||||
return boxes;
|
||||
}
|
||||
|
||||
int _max(int a, int b) {
|
||||
return a >= b ? a : b;
|
||||
}
|
||||
|
||||
int _min(int a, int b) {
|
||||
return a >= b ? b : a;
|
||||
}
|
||||
|
||||
std::vector<std::vector<std::vector<int>>>
|
||||
filter_tag_det_res(const std::vector<std::vector<std::vector<int>>>& o_boxes,
|
||||
float ratio_h, float ratio_w,const cv::Mat& srcimg) {
|
||||
int oriimg_h = srcimg.rows;
|
||||
int oriimg_w = srcimg.cols;
|
||||
std::vector<std::vector<std::vector<int>>> boxes{o_boxes};
|
||||
std::vector<std::vector<std::vector<int>>> root_points;
|
||||
for (int n = 0; n < boxes.size(); n++) {
|
||||
boxes[n] = order_points_clockwise(boxes[n]);
|
||||
for (int m = 0; m < boxes[0].size(); m++) {
|
||||
boxes[n][m][0] /= ratio_w;
|
||||
boxes[n][m][1] /= ratio_h;
|
||||
|
||||
boxes[n][m][0] = int(_min(_max(boxes[n][m][0], 0), oriimg_w - 1));
|
||||
boxes[n][m][1] = int(_min(_max(boxes[n][m][1], 0), oriimg_h - 1));
|
||||
}
|
||||
}
|
||||
|
||||
for (int n = 0; n < boxes.size(); n++) {
|
||||
int rect_width, rect_height;
|
||||
rect_width = int(sqrt(
|
||||
pow(boxes[n][0][0] - boxes[n][1][0], 2) + pow(boxes[n][0][1] - boxes[n][1][1], 2)));
|
||||
rect_height = int(sqrt(
|
||||
pow(boxes[n][0][0] - boxes[n][3][0], 2) + pow(boxes[n][0][1] - boxes[n][3][1], 2)));
|
||||
if (rect_width <= 10 || rect_height <= 10)
|
||||
continue;
|
||||
root_points.push_back(boxes[n]);
|
||||
}
|
||||
return root_points;
|
||||
}
|
||||
|
|
@ -0,0 +1,17 @@
|
|||
//
|
||||
// Created by fujiayi on 2020/7/2.
|
||||
//
|
||||
#pragma once
|
||||
#include <vector>
|
||||
#include <opencv2/opencv.hpp>
|
||||
|
||||
std::vector<std::vector<std::vector<int>>>
|
||||
boxes_from_bitmap(const cv::Mat &pred, const cv::Mat &bitmap);
|
||||
|
||||
std::vector<std::vector<std::vector<int>>>
|
||||
filter_tag_det_res(
|
||||
const std::vector<std::vector<std::vector<int>>> &o_boxes,
|
||||
float ratio_h,
|
||||
float ratio_w,
|
||||
const cv::Mat &srcimg
|
||||
);
|
||||
|
|
@ -0,0 +1,186 @@
|
|||
//
|
||||
// Created by fujiayi on 2020/7/1.
|
||||
//
|
||||
|
||||
#include "ocr_ppredictor.h"
|
||||
#include "preprocess.h"
|
||||
#include "common.h"
|
||||
#include "ocr_db_post_process.h"
|
||||
#include "ocr_crnn_process.h"
|
||||
|
||||
namespace ppredictor {
|
||||
|
||||
OCR_PPredictor::OCR_PPredictor(const OCR_Config &config) : _config(config) {
|
||||
|
||||
}
|
||||
|
||||
int
|
||||
OCR_PPredictor::init(const std::string &det_model_content, const std::string &rec_model_content) {
|
||||
_det_predictor = std::unique_ptr<PPredictor>(
|
||||
new PPredictor{_config.thread_num, NET_OCR, _config.mode});
|
||||
_det_predictor->init_nb(det_model_content);
|
||||
|
||||
_rec_predictor = std::unique_ptr<PPredictor>(
|
||||
new PPredictor{_config.thread_num, NET_OCR_INTERNAL, _config.mode});
|
||||
_rec_predictor->init_nb(rec_model_content);
|
||||
return RETURN_OK;
|
||||
}
|
||||
|
||||
int OCR_PPredictor::init_from_file(const std::string &det_model_path, const std::string &rec_model_path){
|
||||
_det_predictor = std::unique_ptr<PPredictor>(
|
||||
new PPredictor{_config.thread_num, NET_OCR, _config.mode});
|
||||
_det_predictor->init_from_file(det_model_path);
|
||||
|
||||
_rec_predictor = std::unique_ptr<PPredictor>(
|
||||
new PPredictor{_config.thread_num, NET_OCR_INTERNAL, _config.mode});
|
||||
_rec_predictor->init_from_file(rec_model_path);
|
||||
return RETURN_OK;
|
||||
}
|
||||
/**
|
||||
* 调试用，保存第一步的框选结果
|
||||
* @param filter_boxes
|
||||
* @param boxes
|
||||
* @param srcimg
|
||||
*/
|
||||
static void visual_img(const std::vector<std::vector<std::vector<int>>> &filter_boxes,
|
||||
const std::vector<std::vector<std::vector<int>>> &boxes,
|
||||
const cv::Mat &srcimg) {
|
||||
// visualization
|
||||
cv::Point rook_points[filter_boxes.size()][4];
|
||||
for (int n = 0; n < filter_boxes.size(); n++) {
|
||||
for (int m = 0; m < filter_boxes[0].size(); m++) {
|
||||
rook_points[n][m] = cv::Point(int(filter_boxes[n][m][0]), int(filter_boxes[n][m][1]));
|
||||
}
|
||||
}
|
||||
|
||||
cv::Mat img_vis;
|
||||
srcimg.copyTo(img_vis);
|
||||
for (int n = 0; n < boxes.size(); n++) {
|
||||
const cv::Point *ppt[1] = {rook_points[n]};
|
||||
int npt[] = {4};
|
||||
cv::polylines(img_vis, ppt, npt, 1, 1, CV_RGB(0, 255, 0), 2, 8, 0);
|
||||
}
|
||||
// 调试用，自行替换需要修改的路径
|
||||
cv::imwrite("/sdcard/1/vis.png", img_vis);
|
||||
}
|
||||
|
||||
std::vector<OCRPredictResult>
|
||||
OCR_PPredictor::infer_ocr(const std::vector<int64_t> &dims, const float *input_data, int input_len,
|
||||
int net_flag, cv::Mat &origin) {
|
||||
|
||||
PredictorInput input = _det_predictor->get_first_input();
|
||||
input.set_dims(dims);
|
||||
input.set_data(input_data, input_len);
|
||||
std::vector<PredictorOutput> results = _det_predictor->infer();
|
||||
PredictorOutput &res = results.at(0);
|
||||
std::vector<std::vector<std::vector<int>>> filtered_box
|
||||
= calc_filtered_boxes(res.get_float_data(), res.get_size(), (int) dims[2], (int) dims[3],
|
||||
origin);
|
||||
LOGI("Filter_box size %ld", filtered_box.size());
|
||||
return infer_rec(filtered_box, origin);
|
||||
}
|
||||
|
||||
std::vector<OCRPredictResult>
|
||||
OCR_PPredictor::infer_rec(const std::vector<std::vector<std::vector<int>>> &boxes,
|
||||
const cv::Mat &origin_img) {
|
||||
std::vector<float> mean = {0.5f, 0.5f, 0.5f};
|
||||
std::vector<float> scale = {1 / 0.5f, 1 / 0.5f, 1 / 0.5f};
|
||||
std::vector<int64_t> dims = {1, 3, 0, 0};
|
||||
std::vector<OCRPredictResult> ocr_results;
|
||||
|
||||
PredictorInput input = _rec_predictor->get_first_input();
|
||||
for (auto bp = boxes.crbegin(); bp != boxes.crend(); ++bp) {
|
||||
const std::vector<std::vector<int>> &box = *bp;
|
||||
cv::Mat crop_img = get_rotate_crop_image(origin_img, box);
|
||||
float wh_ratio = float(crop_img.cols) / float(crop_img.rows);
|
||||
cv::Mat input_image = crnn_resize_img(crop_img, wh_ratio);
|
||||
input_image.convertTo(input_image, CV_32FC3, 1 / 255.0f);
|
||||
const float *dimg = reinterpret_cast<const float *>(input_image.data);
|
||||
int input_size = input_image.rows * input_image.cols;
|
||||
|
||||
dims[2] = input_image.rows;
|
||||
dims[3] = input_image.cols;
|
||||
input.set_dims(dims);
|
||||
|
||||
neon_mean_scale(dimg, input.get_mutable_float_data(), input_size, mean, scale);
|
||||
|
||||
std::vector<PredictorOutput> results = _rec_predictor->infer();
|
||||
|
||||
OCRPredictResult res;
|
||||
res.word_index = postprocess_rec_word_index(results.at(0));
|
||||
if (res.word_index.empty()) {
|
||||
continue;
|
||||
}
|
||||
res.score = postprocess_rec_score(results.at(1));
|
||||
res.points = box;
|
||||
ocr_results.emplace_back(std::move(res));
|
||||
}
|
||||
LOGI("ocr_results finished %lu", ocr_results.size());
|
||||
return ocr_results;
|
||||
}
|
||||
|
||||
std::vector<std::vector<std::vector<int>>>
|
||||
OCR_PPredictor::calc_filtered_boxes(const float *pred, int pred_size, int output_height,
|
||||
int output_width, const cv::Mat &origin) {
|
||||
const double threshold = 0.3;
|
||||
const double maxvalue = 1;
|
||||
|
||||
cv::Mat pred_map = cv::Mat::zeros(output_height, output_width, CV_32F);
|
||||
memcpy(pred_map.data, pred, pred_size * sizeof(float));
|
||||
cv::Mat cbuf_map;
|
||||
pred_map.convertTo(cbuf_map, CV_8UC1);
|
||||
|
||||
cv::Mat bit_map;
|
||||
cv::threshold(cbuf_map, bit_map, threshold, maxvalue, cv::THRESH_BINARY);
|
||||
|
||||
std::vector<std::vector<std::vector<int>>> boxes = boxes_from_bitmap(pred_map, bit_map);
|
||||
float ratio_h = output_height * 1.0f / origin.rows;
|
||||
float ratio_w = output_width * 1.0f / origin.cols;
|
||||
std::vector<std::vector<std::vector<int>>> filter_boxes = filter_tag_det_res(boxes, ratio_h,
|
||||
ratio_w, origin);
|
||||
return filter_boxes;
|
||||
}
|
||||
|
||||
std::vector<int> OCR_PPredictor::postprocess_rec_word_index(const PredictorOutput &res) {
|
||||
const int *rec_idx = res.get_int_data();
|
||||
const std::vector<std::vector<uint64_t>> rec_idx_lod = res.get_lod();
|
||||
|
||||
std::vector<int> pred_idx;
|
||||
for (int n = int(rec_idx_lod[0][0]); n < int(rec_idx_lod[0][1] * 2); n += 2) {
|
||||
pred_idx.emplace_back(rec_idx[n]);
|
||||
}
|
||||
return pred_idx;
|
||||
}
|
||||
|
||||
float OCR_PPredictor::postprocess_rec_score(const PredictorOutput &res) {
|
||||
const float *predict_batch = res.get_float_data();
|
||||
const std::vector<int64_t> predict_shape = res.get_shape();
|
||||
const std::vector<std::vector<uint64_t>> predict_lod = res.get_lod();
|
||||
int blank = predict_shape[1];
|
||||
float score = 0.f;
|
||||
int count = 0;
|
||||
for (int n = predict_lod[0][0]; n < predict_lod[0][1] - 1; n++) {
|
||||
int argmax_idx = argmax(predict_batch + n * predict_shape[1],
|
||||
predict_batch + (n + 1) * predict_shape[1]);
|
||||
float max_value = predict_batch[n * predict_shape[1] + argmax_idx];
|
||||
if (blank - 1 - argmax_idx > 1e-5) {
|
||||
score += max_value;
|
||||
count += 1;
|
||||
}
|
||||
|
||||
}
|
||||
if (count == 0) {
|
||||
LOGE("calc score count 0");
|
||||
} else {
|
||||
score /= count;
|
||||
}
|
||||
LOGI("calc score: %f", score);
|
||||
return score;
|
||||
|
||||
}
|
||||
|
||||
|
||||
NET_TYPE OCR_PPredictor::get_net_flag() const {
|
||||
return NET_OCR;
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,112 @@
|
|||
//
|
||||
// Created by fujiayi on 2020/7/1.
|
||||
//
|
||||
|
||||
#pragma once
|
||||
|
||||
#include <string>
|
||||
#include <opencv2/opencv.hpp>
|
||||
#include <paddle_api.h>
|
||||
#include "ppredictor.h"
|
||||
|
||||
namespace ppredictor {
|
||||
|
||||
/**
|
||||
* 配置
|
||||
*/
|
||||
struct OCR_Config {
|
||||
int thread_num = 4; // 线程数
|
||||
paddle::lite_api::PowerMode mode = paddle::lite_api::LITE_POWER_HIGH; // PaddleLite Mode
|
||||
};
|
||||
|
||||
/**
|
||||
* 一个四边形内图片的推理结果,
|
||||
*/
|
||||
struct OCRPredictResult {
|
||||
std::vector<int> word_index; //
|
||||
std::vector<std::vector<int>> points;
|
||||
float score;
|
||||
};
|
||||
|
||||
/**
|
||||
* OCR 一共有2个模型进行推理，
|
||||
* 1. 使用第一个模型（det），框选出多个四边形
|
||||
* 2. 从原图从抠出这些多边形，使用第二个模型（rec），获取文本
|
||||
*/
|
||||
class OCR_PPredictor : public PPredictor_Interface {
|
||||
public:
|
||||
OCR_PPredictor(const OCR_Config &config);
|
||||
|
||||
virtual ~OCR_PPredictor() {
|
||||
|
||||
}
|
||||
|
||||
/**
|
||||
* 初始化二个模型的Predictor
|
||||
* @param det_model_content
|
||||
* @param rec_model_content
|
||||
* @return
|
||||
*/
|
||||
int init(const std::string &det_model_content, const std::string &rec_model_content);
|
||||
int init_from_file(const std::string &det_model_path, const std::string &rec_model_path);
|
||||
/**
|
||||
* 返回OCR结果
|
||||
* @param dims
|
||||
* @param input_data
|
||||
* @param input_len
|
||||
* @param net_flag
|
||||
* @param origin
|
||||
* @return
|
||||
*/
|
||||
virtual std::vector<OCRPredictResult>
|
||||
infer_ocr(const std::vector<int64_t> &dims, const float *input_data, int input_len,
|
||||
int net_flag, cv::Mat &origin);
|
||||
|
||||
|
||||
virtual NET_TYPE get_net_flag() const;
|
||||
|
||||
|
||||
private:
|
||||
|
||||
/**
|
||||
* 从第一个模型的结果中计算有文字的四边形
|
||||
* @param pred
|
||||
* @param output_height
|
||||
* @param output_width
|
||||
* @param origin
|
||||
* @return
|
||||
*/
|
||||
std::vector<std::vector<std::vector<int>>>
|
||||
calc_filtered_boxes(const float *pred, int pred_size, int output_height, int output_width,
|
||||
const cv::Mat &origin);
|
||||
|
||||
/**
|
||||
* 第二个模型的推理
|
||||
*
|
||||
* @param boxes
|
||||
* @param origin
|
||||
* @return
|
||||
*/
|
||||
std::vector<OCRPredictResult>
|
||||
infer_rec(const std::vector<std::vector<std::vector<int>>> &boxes, const cv::Mat &origin);
|
||||
|
||||
/**
|
||||
* 第二个模型提取文字的后处理
|
||||
* @param res
|
||||
* @return
|
||||
*/
|
||||
std::vector<int> postprocess_rec_word_index(const PredictorOutput &res);
|
||||
|
||||
/**
|
||||
* 计算第二个模型的文字的置信度
|
||||
* @param res
|
||||
* @return
|
||||
*/
|
||||
float postprocess_rec_score(const PredictorOutput &res);
|
||||
|
||||
std::unique_ptr<PPredictor> _det_predictor;
|
||||
std::unique_ptr<PPredictor> _rec_predictor;
|
||||
OCR_Config _config;
|
||||
|
||||
};
|
||||
}
|
||||
|
|
@ -0,0 +1,70 @@
|
|||
#include "ppredictor.h"
|
||||
#include "common.h"
|
||||
|
||||
namespace ppredictor {
|
||||
PPredictor::PPredictor(int thread_num, int net_flag, paddle::lite_api::PowerMode mode) :
|
||||
_thread_num(thread_num), _net_flag(net_flag), _mode(mode) {
|
||||
}
|
||||
|
||||
int PPredictor::init_nb(const std::string &model_content) {
|
||||
paddle::lite_api::MobileConfig config;
|
||||
config.set_model_from_buffer(model_content);
|
||||
return _init(config);
|
||||
}
|
||||
|
||||
int PPredictor::init_from_file(const std::string &model_content){
|
||||
paddle::lite_api::MobileConfig config;
|
||||
config.set_model_from_file(model_content);
|
||||
return _init(config);
|
||||
}
|
||||
|
||||
template<typename ConfigT>
|
||||
int PPredictor::_init(ConfigT &config) {
|
||||
config.set_threads(_thread_num);
|
||||
config.set_power_mode(_mode);
|
||||
_predictor = paddle::lite_api::CreatePaddlePredictor(config);
|
||||
LOGI("paddle instance created");
|
||||
return RETURN_OK;
|
||||
}
|
||||
|
||||
PredictorInput PPredictor::get_input(int index) {
|
||||
PredictorInput input{_predictor->GetInput(index), index, _net_flag};
|
||||
_is_input_get = true;
|
||||
return input;
|
||||
}
|
||||
|
||||
std::vector<PredictorInput> PPredictor::get_inputs(int num) {
|
||||
std::vector<PredictorInput> results;
|
||||
for (int i = 0; i < num; i++) {
|
||||
results.emplace_back(get_input(i));
|
||||
}
|
||||
return results;
|
||||
}
|
||||
|
||||
PredictorInput PPredictor::get_first_input() {
|
||||
return get_input(0);
|
||||
}
|
||||
|
||||
std::vector<PredictorOutput> PPredictor::infer() {
|
||||
LOGI("infer Run start %d", _net_flag);
|
||||
std::vector<PredictorOutput> results;
|
||||
if (!_is_input_get) {
|
||||
return results;
|
||||
}
|
||||
_predictor->Run();
|
||||
LOGI("infer Run end");
|
||||
|
||||
for (int i = 0; i < _predictor->GetOutputNames().size(); i++) {
|
||||
std::unique_ptr<const paddle::lite_api::Tensor> output_tensor = _predictor->GetOutput(i);
|
||||
LOGI("output tensor[%d] size %ld", i, product(output_tensor->shape()));
|
||||
PredictorOutput result{std::move(output_tensor), i, _net_flag};
|
||||
results.emplace_back(std::move(result));
|
||||
}
|
||||
return results;
|
||||
}
|
||||
|
||||
NET_TYPE PPredictor::get_net_flag() const {
|
||||
return (NET_TYPE) _net_flag;
|
||||
}
|
||||
|
||||
}
|
||||
|
|
@ -0,0 +1,74 @@
|
|||
#pragma once
|
||||
|
||||
#include "paddle_api.h"
|
||||
#include "predictor_input.h"
|
||||
#include "predictor_output.h"
|
||||
|
||||
namespace ppredictor {
|
||||
|
||||
/**
|
||||
* PaddleLite Preditor 通用接口
|
||||
*/
|
||||
class PPredictor_Interface {
|
||||
public:
|
||||
virtual ~PPredictor_Interface() {
|
||||
|
||||
}
|
||||
|
||||
|
||||
virtual NET_TYPE get_net_flag() const = 0;
|
||||
|
||||
};
|
||||
|
||||
/**
|
||||
* 通用推理
|
||||
*/
|
||||
class PPredictor : public PPredictor_Interface {
|
||||
public:
|
||||
PPredictor(int thread_num, int net_flag = 0,
|
||||
paddle::lite_api::PowerMode mode = paddle::lite_api::LITE_POWER_HIGH);
|
||||
|
||||
virtual ~PPredictor() {
|
||||
|
||||
}
|
||||
|
||||
/**
|
||||
* 初始化paddlitelite的opt模型，nb格式，与init_paddle二选一
|
||||
* @param model_content
|
||||
* @return 0 目前是固定值0， 之后其他值表示失败
|
||||
*/
|
||||
virtual int init_nb(const std::string &model_content);
|
||||
|
||||
virtual int init_from_file(const std::string &model_content);
|
||||
|
||||
std::vector<PredictorOutput> infer();
|
||||
|
||||
std::shared_ptr<paddle::lite_api::PaddlePredictor> get_predictor() {
|
||||
return _predictor;
|
||||
}
|
||||
|
||||
virtual std::vector<PredictorInput> get_inputs(int num);
|
||||
|
||||
virtual PredictorInput get_input(int index);
|
||||
|
||||
virtual PredictorInput get_first_input();
|
||||
|
||||
virtual NET_TYPE get_net_flag() const;
|
||||
|
||||
protected:
|
||||
template<typename ConfigT>
|
||||
int _init(ConfigT &config);
|
||||
|
||||
private:
|
||||
int _thread_num;
|
||||
paddle::lite_api::PowerMode _mode;
|
||||
std::shared_ptr<paddle::lite_api::PaddlePredictor> _predictor;
|
||||
bool _is_input_get = false;
|
||||
int _net_flag;
|
||||
|
||||
};
|
||||
|
||||
|
||||
}
|
||||
|
||||
|
||||
|
|
@ -0,0 +1,29 @@
|
|||
#include "predictor_input.h"
|
||||
|
||||
namespace ppredictor {
|
||||
|
||||
|
||||
void PredictorInput::set_dims(std::vector<int64_t> dims) {
|
||||
// yolov3
|
||||
if (_net_flag == 101 && _index == 1) {
|
||||
_tensor->Resize({1, 2});
|
||||
_tensor->mutable_data<int>()[0] = (int) dims.at(2);
|
||||
_tensor->mutable_data<int>()[1] = (int) dims.at(3);
|
||||
} else {
|
||||
_tensor->Resize(dims);
|
||||
}
|
||||
_is_dims_set = true;
|
||||
}
|
||||
|
||||
float *PredictorInput::get_mutable_float_data() {
|
||||
if (!_is_dims_set) {
|
||||
LOGE("PredictorInput::set_dims is not called");
|
||||
}
|
||||
return _tensor->mutable_data<float>();
|
||||
}
|
||||
|
||||
void PredictorInput::set_data(const float *input_data, int input_float_len) {
|
||||
float *input_raw_data = get_mutable_float_data();
|
||||
memcpy(input_raw_data, input_data, input_float_len * sizeof(float));
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,28 @@
|
|||
#pragma once
|
||||
|
||||
#include <paddle_api.h>
|
||||
#include <vector>
|
||||
#include "common.h"
|
||||
|
||||
namespace ppredictor {
|
||||
class PredictorInput {
|
||||
public:
|
||||
PredictorInput(std::unique_ptr<paddle::lite_api::Tensor> &&tensor, int index, int net_flag) :
|
||||
_tensor(std::move(tensor)), _index(index),_net_flag(net_flag) {
|
||||
|
||||
}
|
||||
|
||||
|
||||
void set_dims(std::vector<int64_t> dims);
|
||||
|
||||
float *get_mutable_float_data();
|
||||
|
||||
void set_data(const float *input_data, int input_float_len);
|
||||
|
||||
private:
|
||||
std::unique_ptr<paddle::lite_api::Tensor> _tensor;
|
||||
bool _is_dims_set = false;
|
||||
int _index;
|
||||
int _net_flag;
|
||||
};
|
||||
}
|
||||
|
|
@ -0,0 +1,27 @@
|
|||
#include "predictor_output.h"
|
||||
namespace ppredictor {
|
||||
const float* PredictorOutput::get_float_data() const{
|
||||
return _tensor->data<float>();
|
||||
}
|
||||
|
||||
const int* PredictorOutput::get_int_data() const{
|
||||
return _tensor->data<int>();
|
||||
}
|
||||
|
||||
const std::vector<std::vector<uint64_t>> PredictorOutput::get_lod() const{
|
||||
return _tensor->lod();
|
||||
}
|
||||
|
||||
int64_t PredictorOutput::get_size() const{
|
||||
if (_net_flag == NET_OCR) {
|
||||
return _tensor->shape().at(2) * _tensor->shape().at(3);
|
||||
} else {
|
||||
return product(_tensor->shape());
|
||||
}
|
||||
}
|
||||
|
||||
const std::vector<int64_t> PredictorOutput::get_shape() const{
|
||||
return _tensor->shape();
|
||||
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,35 @@
|
|||
#pragma once
|
||||
|
||||
#include <paddle_api.h>
|
||||
#include <vector>
|
||||
#include "common.h"
|
||||
|
||||
namespace ppredictor {
|
||||
class PredictorOutput {
|
||||
public:
|
||||
PredictorOutput(){
|
||||
|
||||
}
|
||||
PredictorOutput(std::unique_ptr<const paddle::lite_api::Tensor> &&tensor, int index, int net_flag) :
|
||||
_tensor(std::move(tensor)), _index(index), _net_flag(net_flag) {
|
||||
|
||||
}
|
||||
|
||||
const float* get_float_data() const;
|
||||
const int* get_int_data() const;
|
||||
int64_t get_size() const;
|
||||
const std::vector<std::vector<uint64_t>> get_lod() const;
|
||||
const std::vector<int64_t> get_shape() const;
|
||||
|
||||
std::vector<float> data; // 通常是float返回，与下面的data_int二选一
|
||||
std::vector<int> data_int; // 少数层是int返回，与 data二选一
|
||||
std::vector<int64_t> shape; // PaddleLite输出层的shape
|
||||
std::vector<std::vector<uint64_t>> lod; // PaddleLite输出层的lod
|
||||
|
||||
private:
|
||||
std::unique_ptr<const paddle::lite_api::Tensor> _tensor;
|
||||
int _index;
|
||||
int _net_flag;
|
||||
};
|
||||
}
|
||||
|
||||
|
|
@ -0,0 +1,84 @@
|
|||
#include "preprocess.h"
|
||||
#include <android/bitmap.h>
|
||||
|
||||
cv::Mat bitmap_to_cv_mat(JNIEnv *env, jobject bitmap) {
|
||||
AndroidBitmapInfo info;
|
||||
int result = AndroidBitmap_getInfo(env, bitmap, &info);
|
||||
if (result != ANDROID_BITMAP_RESULT_SUCCESS) {
|
||||
LOGE("AndroidBitmap_getInfo failed, result: %d", result);
|
||||
return cv::Mat{};
|
||||
}
|
||||
if (info.format != ANDROID_BITMAP_FORMAT_RGBA_8888) {
|
||||
LOGE("Bitmap format is not RGBA_8888 !");
|
||||
return cv::Mat{};
|
||||
}
|
||||
unsigned char *srcData = NULL;
|
||||
AndroidBitmap_lockPixels(env, bitmap, (void **) &srcData);
|
||||
cv::Mat mat = cv::Mat::zeros(info.height, info.width, CV_8UC4);
|
||||
memcpy(mat.data, srcData, info.height * info.width * 4);
|
||||
AndroidBitmap_unlockPixels(env, bitmap);
|
||||
cv::cvtColor(mat, mat, cv::COLOR_RGBA2BGR);
|
||||
/**
|
||||
if (!cv::imwrite("/sdcard/1/copy.jpg", mat)){
|
||||
LOGE("Write image failed " );
|
||||
}
|
||||
*/
|
||||
|
||||
return mat;
|
||||
}
|
||||
|
||||
cv::Mat resize_img(const cv::Mat& img, int height, int width){
|
||||
if (img.rows == height && img.cols == width){
|
||||
return img;
|
||||
}
|
||||
cv::Mat new_img;
|
||||
cv::resize(img, new_img, cv::Size(height, width));
|
||||
return new_img;
|
||||
}
|
||||
|
||||
// fill tensor with mean and scale and trans layout: nhwc -> nchw, neon speed up
|
||||
void neon_mean_scale(const float* din,
|
||||
float* dout,
|
||||
int size,
|
||||
const std::vector<float>& mean,
|
||||
const std::vector<float>& scale) {
|
||||
if (mean.size() != 3 || scale.size() != 3) {
|
||||
LOGE("[ERROR] mean or scale size must equal to 3");
|
||||
return;
|
||||
}
|
||||
|
||||
float32x4_t vmean0 = vdupq_n_f32(mean[0]);
|
||||
float32x4_t vmean1 = vdupq_n_f32(mean[1]);
|
||||
float32x4_t vmean2 = vdupq_n_f32(mean[2]);
|
||||
float32x4_t vscale0 = vdupq_n_f32(scale[0]);
|
||||
float32x4_t vscale1 = vdupq_n_f32(scale[1]);
|
||||
float32x4_t vscale2 = vdupq_n_f32(scale[2]);
|
||||
|
||||
float* dout_c0 = dout;
|
||||
float* dout_c1 = dout + size;
|
||||
float* dout_c2 = dout + size * 2;
|
||||
|
||||
int i = 0;
|
||||
for (; i < size - 3; i += 4) {
|
||||
float32x4x3_t vin3 = vld3q_f32(din);
|
||||
float32x4_t vsub0 = vsubq_f32(vin3.val[0], vmean0);
|
||||
float32x4_t vsub1 = vsubq_f32(vin3.val[1], vmean1);
|
||||
float32x4_t vsub2 = vsubq_f32(vin3.val[2], vmean2);
|
||||
float32x4_t vs0 = vmulq_f32(vsub0, vscale0);
|
||||
float32x4_t vs1 = vmulq_f32(vsub1, vscale1);
|
||||
float32x4_t vs2 = vmulq_f32(vsub2, vscale2);
|
||||
vst1q_f32(dout_c0, vs0);
|
||||
vst1q_f32(dout_c1, vs1);
|
||||
vst1q_f32(dout_c2, vs2);
|
||||
|
||||
din += 12;
|
||||
dout_c0 += 4;
|
||||
dout_c1 += 4;
|
||||
dout_c2 += 4;
|
||||
}
|
||||
for (; i < size; i++) {
|
||||
*(dout_c0++) = (*(din++) - mean[0]) * scale[0];
|
||||
*(dout_c1++) = (*(din++) - mean[1]) * scale[1];
|
||||
*(dout_c2++) = (*(din++) - mean[2]) * scale[2];
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,14 @@
|
|||
#pragma once
|
||||
|
||||
#include <jni.h>
|
||||
#include <opencv2/opencv.hpp>
|
||||
#include "common.h"
|
||||
cv::Mat bitmap_to_cv_mat(JNIEnv *env, jobject bitmap);
|
||||
|
||||
cv::Mat resize_img(const cv::Mat& img, int height, int width);
|
||||
|
||||
void neon_mean_scale(const float* din,
|
||||
float* dout,
|
||||
int size,
|
||||
const std::vector<float>& mean,
|
||||
const std::vector<float>& scale);
|
||||
|
|
@ -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.ocr;
|
||||
|
||||
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 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 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;
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,414 @@
|
|||
package com.baidu.paddle.lite.demo.ocr;
|
||||
|
||||
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 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
|
||||
|
||||
// UI components of object detection
|
||||
protected TextView tvInputSetting;
|
||||
protected ImageView ivInputImage;
|
||||
protected TextView tvOutputResult;
|
||||
protected TextView tvInferenceTime;
|
||||
|
||||
// Model settings of object detection
|
||||
protected String modelPath = "";
|
||||
protected String labelPath = "";
|
||||
protected String imagePath = "";
|
||||
protected int cpuThreadNum = 1;
|
||||
protected String cpuPowerMode = "";
|
||||
protected String inputColorFormat = "";
|
||||
protected long[] inputShape = new long[]{};
|
||||
protected float[] inputMean = new float[]{};
|
||||
protected float[] inputStd = new float[]{};
|
||||
protected float scoreThreshold = 0.1f;
|
||||
|
||||
protected Predictor predictor = new Predictor();
|
||||
|
||||
@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();
|
||||
|
||||
// Prepare the worker thread for mode loading and inference
|
||||
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;
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
// Setup the UI components
|
||||
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
|
||||
protected void 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(modelPath);
|
||||
settingsChanged |= !label_path.equalsIgnoreCase(labelPath);
|
||||
settingsChanged |= !image_path.equalsIgnoreCase(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 != 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(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(inputColorFormat);
|
||||
long[] input_shape =
|
||||
Utils.parseLongsFromString(sharedPreferences.getString(getString(R.string.INPUT_SHAPE_KEY),
|
||||
getString(R.string.INPUT_SHAPE_DEFAULT)), ",");
|
||||
float[] input_mean =
|
||||
Utils.parseFloatsFromString(sharedPreferences.getString(getString(R.string.INPUT_MEAN_KEY),
|
||||
getString(R.string.INPUT_MEAN_DEFAULT)), ",");
|
||||
float[] input_std =
|
||||
Utils.parseFloatsFromString(sharedPreferences.getString(getString(R.string.INPUT_STD_KEY)
|
||||
, getString(R.string.INPUT_STD_DEFAULT)), ",");
|
||||
settingsChanged |= input_shape.length != inputShape.length;
|
||||
settingsChanged |= input_mean.length != inputMean.length;
|
||||
settingsChanged |= input_std.length != inputStd.length;
|
||||
if (!settingsChanged) {
|
||||
for (int i = 0; i < input_shape.length; i++) {
|
||||
settingsChanged |= input_shape[i] != inputShape[i];
|
||||
}
|
||||
for (int i = 0; i < input_mean.length; i++) {
|
||||
settingsChanged |= input_mean[i] != inputMean[i];
|
||||
}
|
||||
for (int i = 0; i < input_std.length; i++) {
|
||||
settingsChanged |= input_std[i] != inputStd[i];
|
||||
}
|
||||
}
|
||||
float score_threshold =
|
||||
Float.parseFloat(sharedPreferences.getString(getString(R.string.SCORE_THRESHOLD_KEY),
|
||||
getString(R.string.SCORE_THRESHOLD_DEFAULT)));
|
||||
settingsChanged |= scoreThreshold != score_threshold;
|
||||
if (settingsChanged) {
|
||||
modelPath = model_path;
|
||||
labelPath = label_path;
|
||||
imagePath = image_path;
|
||||
cpuThreadNum = cpu_thread_num;
|
||||
cpuPowerMode = cpu_power_mode;
|
||||
inputColorFormat = input_color_format;
|
||||
inputShape = input_shape;
|
||||
inputMean = input_mean;
|
||||
inputStd = input_std;
|
||||
scoreThreshold = score_threshold;
|
||||
// Update UI
|
||||
tvInputSetting.setText("Model: " + modelPath.substring(modelPath.lastIndexOf("/") + 1) + "\n" + "CPU" +
|
||||
" Thread Num: " + Integer.toString(cpuThreadNum) + "\n" + "CPU Power Mode: " + cpuPowerMode);
|
||||
tvInputSetting.scrollTo(0, 0);
|
||||
// Reload model if configure has been changed
|
||||
loadModel();
|
||||
}
|
||||
}
|
||||
|
||||
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 predictor.init(MainActivity.this, modelPath, labelPath, cpuThreadNum,
|
||||
cpuPowerMode,
|
||||
inputColorFormat,
|
||||
inputShape, inputMean,
|
||||
inputStd, scoreThreshold);
|
||||
}
|
||||
|
||||
public boolean onRunModel() {
|
||||
return predictor.isLoaded() && predictor.runModel();
|
||||
}
|
||||
|
||||
public void onLoadModelSuccessed() {
|
||||
// Load test image from path and run model
|
||||
try {
|
||||
if (imagePath.isEmpty()) {
|
||||
return;
|
||||
}
|
||||
Bitmap image = null;
|
||||
// Read test image file from custom path if the first character of mode path is '/', otherwise read test
|
||||
// image file from assets
|
||||
if (!imagePath.substring(0, 1).equals("/")) {
|
||||
InputStream imageStream = getAssets().open(imagePath);
|
||||
image = BitmapFactory.decodeStream(imageStream);
|
||||
} else {
|
||||
if (!new File(imagePath).exists()) {
|
||||
return;
|
||||
}
|
||||
image = BitmapFactory.decodeFile(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 onLoadModelFailed() {
|
||||
}
|
||||
|
||||
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 onRunModelFailed() {
|
||||
}
|
||||
|
||||
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 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;
|
||||
}
|
||||
|
||||
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
|
||||
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:
|
||||
Bundle extras = data.getExtras();
|
||||
Bitmap image = (Bitmap) extras.get("data");
|
||||
onImageChanged(image);
|
||||
break;
|
||||
default:
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@Override
|
||||
protected void onDestroy() {
|
||||
if (predictor != null) {
|
||||
predictor.releaseModel();
|
||||
}
|
||||
worker.quit();
|
||||
super.onDestroy();
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,100 @@
|
|||
package com.baidu.paddle.lite.demo.ocr;
|
||||
|
||||
import android.graphics.Bitmap;
|
||||
import android.util.Log;
|
||||
|
||||
import java.util.ArrayList;
|
||||
import java.util.concurrent.atomic.AtomicBoolean;
|
||||
|
||||
public class OCRPredictorNative {
|
||||
|
||||
private static final AtomicBoolean isSOLoaded = new AtomicBoolean();
|
||||
|
||||
public static void loadLibrary() throws RuntimeException {
|
||||
if (!isSOLoaded.get() && isSOLoaded.compareAndSet(false, true)) {
|
||||
try {
|
||||
System.loadLibrary("Native");
|
||||
} catch (Throwable e) {
|
||||
RuntimeException exception = new RuntimeException(
|
||||
"Load libNative.so failed, please check it exists in apk file.", e);
|
||||
throw exception;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private Config config;
|
||||
|
||||
private long nativePointer = 0;
|
||||
|
||||
public OCRPredictorNative(Config config) {
|
||||
this.config = config;
|
||||
loadLibrary();
|
||||
nativePointer = init(config.detModelFilename, config.recModelFilename,
|
||||
config.cpuThreadNum, config.cpuPower);
|
||||
Log.i("OCRPredictorNative", "load success " + nativePointer);
|
||||
|
||||
}
|
||||
|
||||
public void release(){
|
||||
if (nativePointer != 0){
|
||||
nativePointer = 0;
|
||||
destory(nativePointer);
|
||||
}
|
||||
}
|
||||
|
||||
public ArrayList<OcrResultModel> runImage(float[] inputData, int width, int height, int channels, Bitmap originalImage) {
|
||||
Log.i("OCRPredictorNative", "begin to run image " + inputData.length + " " + width + " " + height);
|
||||
float[] dims = new float[]{1, channels, height, width};
|
||||
float[] rawResults = forward(nativePointer, inputData, dims, originalImage);
|
||||
ArrayList<OcrResultModel> results = postprocess(rawResults);
|
||||
return results;
|
||||
}
|
||||
|
||||
public static class Config {
|
||||
public int cpuThreadNum;
|
||||
public String cpuPower;
|
||||
public String detModelFilename;
|
||||
public String recModelFilename;
|
||||
|
||||
}
|
||||
|
||||
protected native long init(String detModelPath, String recModelPath, int threadNum, String cpuMode);
|
||||
|
||||
protected native float[] forward(long pointer, float[] buf, float[] ddims, Bitmap originalImage);
|
||||
|
||||
protected native void destory(long pointer);
|
||||
|
||||
private ArrayList<OcrResultModel> postprocess(float[] raw) {
|
||||
ArrayList<OcrResultModel> results = new ArrayList<OcrResultModel>();
|
||||
int begin = 0;
|
||||
|
||||
while (begin < raw.length) {
|
||||
int point_num = Math.round(raw[begin]);
|
||||
int word_num = Math.round(raw[begin + 1]);
|
||||
OcrResultModel model = parse(raw, begin + 2, point_num, word_num);
|
||||
begin += 2 + 1 + point_num * 2 + word_num;
|
||||
results.add(model);
|
||||
}
|
||||
|
||||
return results;
|
||||
}
|
||||
|
||||
private OcrResultModel parse(float[] raw, int begin, int pointNum, int wordNum) {
|
||||
int current = begin;
|
||||
OcrResultModel model = new OcrResultModel();
|
||||
model.setConfidence(raw[current]);
|
||||
current++;
|
||||
for (int i = 0; i < pointNum; i++) {
|
||||
model.addPoints(Math.round(raw[current + i * 2]), Math.round(raw[current + i * 2 + 1]));
|
||||
}
|
||||
current += (pointNum * 2);
|
||||
for (int i = 0; i < wordNum; i++) {
|
||||
int index = Math.round(raw[current + i]);
|
||||
model.addWordIndex(index);
|
||||
}
|
||||
Log.i("OCRPredictorNative", "word finished " + wordNum);
|
||||
return model;
|
||||
}
|
||||
|
||||
|
||||
}
|
||||
|
|
@ -0,0 +1,52 @@
|
|||
package com.baidu.paddle.lite.demo.ocr;
|
||||
|
||||
import android.graphics.Point;
|
||||
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
|
||||
public class OcrResultModel {
|
||||
private List<Point> points;
|
||||
private List<Integer> wordIndex;
|
||||
private String label;
|
||||
private float confidence;
|
||||
|
||||
public OcrResultModel() {
|
||||
super();
|
||||
points = new ArrayList<>();
|
||||
wordIndex = new ArrayList<>();
|
||||
}
|
||||
|
||||
public void addPoints(int x, int y) {
|
||||
Point point = new Point(x, y);
|
||||
points.add(point);
|
||||
}
|
||||
|
||||
public void addWordIndex(int index) {
|
||||
wordIndex.add(index);
|
||||
}
|
||||
|
||||
public List<Point> getPoints() {
|
||||
return points;
|
||||
}
|
||||
|
||||
public List<Integer> getWordIndex() {
|
||||
return wordIndex;
|
||||
}
|
||||
|
||||
public String getLabel() {
|
||||
return label;
|
||||
}
|
||||
|
||||
public void setLabel(String label) {
|
||||
this.label = label;
|
||||
}
|
||||
|
||||
public float getConfidence() {
|
||||
return confidence;
|
||||
}
|
||||
|
||||
public void setConfidence(float confidence) {
|
||||
this.confidence = confidence;
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,351 @@
|
|||
package com.baidu.paddle.lite.demo.ocr;
|
||||
|
||||
import android.content.Context;
|
||||
import android.graphics.Bitmap;
|
||||
import android.graphics.Canvas;
|
||||
import android.graphics.Color;
|
||||
import android.graphics.Paint;
|
||||
import android.graphics.Path;
|
||||
import android.graphics.Point;
|
||||
import android.util.Log;
|
||||
|
||||
import java.io.File;
|
||||
import java.io.InputStream;
|
||||
import java.util.ArrayList;
|
||||
import java.util.Date;
|
||||
import java.util.List;
|
||||
import java.util.Vector;
|
||||
|
||||
import static android.graphics.Color.*;
|
||||
|
||||
public class Predictor {
|
||||
private static final String TAG = Predictor.class.getSimpleName();
|
||||
public boolean isLoaded = false;
|
||||
public int warmupIterNum = 1;
|
||||
public int inferIterNum = 1;
|
||||
public int cpuThreadNum = 4;
|
||||
public String cpuPowerMode = "LITE_POWER_HIGH";
|
||||
public String modelPath = "";
|
||||
public String modelName = "";
|
||||
protected OCRPredictorNative paddlePredictor = null;
|
||||
protected float inferenceTime = 0;
|
||||
// Only for object detection
|
||||
protected Vector<String> wordLabels = new Vector<String>();
|
||||
protected String inputColorFormat = "BGR";
|
||||
protected long[] inputShape = new long[]{1, 3, 960};
|
||||
protected float[] inputMean = new float[]{0.485f, 0.456f, 0.406f};
|
||||
protected float[] inputStd = new float[]{1.0f / 0.229f, 1.0f / 0.224f, 1.0f / 0.225f};
|
||||
protected float scoreThreshold = 0.1f;
|
||||
protected Bitmap inputImage = null;
|
||||
protected Bitmap outputImage = null;
|
||||
protected String outputResult = "";
|
||||
protected float preprocessTime = 0;
|
||||
protected float postprocessTime = 0;
|
||||
|
||||
|
||||
public Predictor() {
|
||||
}
|
||||
|
||||
public boolean init(Context appCtx, String modelPath, String labelPath, int cpuThreadNum, String cpuPowerMode,
|
||||
String inputColorFormat,
|
||||
long[] inputShape, float[] inputMean,
|
||||
float[] inputStd, float scoreThreshold) {
|
||||
if (inputShape.length != 3) {
|
||||
Log.e(TAG, "Size of input shape should be: 3");
|
||||
return false;
|
||||
}
|
||||
if (inputMean.length != inputShape[1]) {
|
||||
Log.e(TAG, "Size of input mean should be: " + Long.toString(inputShape[1]));
|
||||
return false;
|
||||
}
|
||||
if (inputStd.length != inputShape[1]) {
|
||||
Log.e(TAG, "Size of input std should be: " + Long.toString(inputShape[1]));
|
||||
return false;
|
||||
}
|
||||
if (inputShape[0] != 1) {
|
||||
Log.e(TAG, "Only one batch is supported in the image classification demo, you can use any batch size in " +
|
||||
"your Apps!");
|
||||
return false;
|
||||
}
|
||||
if (inputShape[1] != 1 && inputShape[1] != 3) {
|
||||
Log.e(TAG, "Only one/three channels are supported in the image classification demo, you can use any " +
|
||||
"channel size in your Apps!");
|
||||
return false;
|
||||
}
|
||||
if (!inputColorFormat.equalsIgnoreCase("BGR")) {
|
||||
Log.e(TAG, "Only BGR color format is supported.");
|
||||
return false;
|
||||
}
|
||||
isLoaded = loadModel(appCtx, modelPath, cpuThreadNum, cpuPowerMode);
|
||||
if (!isLoaded) {
|
||||
return false;
|
||||
}
|
||||
isLoaded = loadLabel(appCtx, labelPath);
|
||||
if (!isLoaded) {
|
||||
return false;
|
||||
}
|
||||
this.inputColorFormat = inputColorFormat;
|
||||
this.inputShape = inputShape;
|
||||
this.inputMean = inputMean;
|
||||
this.inputStd = inputStd;
|
||||
this.scoreThreshold = scoreThreshold;
|
||||
return true;
|
||||
}
|
||||
|
||||
protected boolean loadModel(Context appCtx, 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 path if the first character of mode path is '/'
|
||||
// otherwise copy model to cache from assets
|
||||
realPath = appCtx.getCacheDir() + "/" + modelPath;
|
||||
Utils.copyDirectoryFromAssets(appCtx, modelPath, realPath);
|
||||
}
|
||||
if (realPath.isEmpty()) {
|
||||
return false;
|
||||
}
|
||||
|
||||
OCRPredictorNative.Config config = new OCRPredictorNative.Config();
|
||||
config.cpuThreadNum = cpuThreadNum;
|
||||
config.detModelFilename = realPath + File.separator + "ch_det_mv3_db_opt.nb";
|
||||
config.recModelFilename = realPath + File.separator + "ch_rec_mv3_crnn_opt.nb";
|
||||
Log.e("Predictor", "model path" + config.detModelFilename + " ; " + config.recModelFilename);
|
||||
config.cpuPower = cpuPowerMode;
|
||||
paddlePredictor = new OCRPredictorNative(config);
|
||||
|
||||
this.cpuThreadNum = cpuThreadNum;
|
||||
this.cpuPowerMode = cpuPowerMode;
|
||||
this.modelPath = realPath;
|
||||
this.modelName = realPath.substring(realPath.lastIndexOf("/") + 1);
|
||||
return true;
|
||||
}
|
||||
|
||||
public void releaseModel() {
|
||||
if (paddlePredictor != null){
|
||||
paddlePredictor.release();
|
||||
paddlePredictor = null;
|
||||
}
|
||||
isLoaded = false;
|
||||
cpuThreadNum = 4;
|
||||
cpuPowerMode = "LITE_POWER_HIGH";
|
||||
modelPath = "";
|
||||
modelName = "";
|
||||
}
|
||||
|
||||
protected boolean loadLabel(Context appCtx, 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 boolean runModel() {
|
||||
if (inputImage == null || !isLoaded()) {
|
||||
return false;
|
||||
}
|
||||
|
||||
// Pre-process image, and feed input tensor with pre-processed data
|
||||
|
||||
Bitmap scaleImage = Utils.resizeWithStep(inputImage, Long.valueOf(inputShape[2]).intValue(), 32);
|
||||
|
||||
Date start = new Date();
|
||||
int channels = (int) inputShape[1];
|
||||
int width = scaleImage.getWidth();
|
||||
int height = scaleImage.getHeight();
|
||||
float[] inputData = new float[channels * width * height];
|
||||
if (channels == 3) {
|
||||
int[] channelIdx = null;
|
||||
if (inputColorFormat.equalsIgnoreCase("RGB")) {
|
||||
channelIdx = new int[]{0, 1, 2};
|
||||
} else if (inputColorFormat.equalsIgnoreCase("BGR")) {
|
||||
channelIdx = new int[]{2, 1, 0};
|
||||
} else {
|
||||
Log.i(TAG, "Unknown color format " + inputColorFormat + ", only RGB and BGR color format is " +
|
||||
"supported!");
|
||||
return false;
|
||||
}
|
||||
int[] channelStride = new int[]{width * height, width * height * 2};
|
||||
int p = scaleImage.getPixel(scaleImage.getWidth() - 1, scaleImage.getHeight() - 1);
|
||||
for (int y = 0; y < height; y++) {
|
||||
for (int x = 0; x < width; x++) {
|
||||
int color = scaleImage.getPixel(x, y);
|
||||
float[] rgb = new float[]{(float) red(color) / 255.0f, (float) green(color) / 255.0f,
|
||||
(float) blue(color) / 255.0f};
|
||||
inputData[y * width + x] = (rgb[channelIdx[0]] - inputMean[0]) / inputStd[0];
|
||||
inputData[y * width + x + channelStride[0]] = (rgb[channelIdx[1]] - inputMean[1]) / inputStd[1];
|
||||
inputData[y * width + x + channelStride[1]] = (rgb[channelIdx[2]] - inputMean[2]) / inputStd[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)) / 3.0f / 255.0f;
|
||||
inputData[y * width + x] = (gray - inputMean[0]) / inputStd[0];
|
||||
}
|
||||
}
|
||||
} else {
|
||||
Log.i(TAG, "Unsupported channel size " + Integer.toString(channels) + ", only channel 1 and 3 is " +
|
||||
"supported!");
|
||||
return false;
|
||||
}
|
||||
float[] pixels = inputData;
|
||||
Log.i(TAG, "pixels " + pixels[0] + " " + pixels[1] + " " + pixels[2] + " " + pixels[3]
|
||||
+ " " + pixels[pixels.length / 2] + " " + pixels[pixels.length / 2 + 1] + " " + pixels[pixels.length - 2] + " " + pixels[pixels.length - 1]);
|
||||
Date end = new Date();
|
||||
preprocessTime = (float) (end.getTime() - start.getTime());
|
||||
|
||||
// Warm up
|
||||
for (int i = 0; i < warmupIterNum; i++) {
|
||||
paddlePredictor.runImage(inputData, width, height, channels, inputImage);
|
||||
}
|
||||
warmupIterNum = 0; // 之后不要再warm了
|
||||
// Run inference
|
||||
start = new Date();
|
||||
ArrayList<OcrResultModel> results = paddlePredictor.runImage(inputData, width, height, channels, inputImage);
|
||||
end = new Date();
|
||||
inferenceTime = (end.getTime() - start.getTime()) / (float) inferIterNum;
|
||||
|
||||
results = postprocess(results);
|
||||
Log.i(TAG, "[stat] Preprocess Time: " + preprocessTime
|
||||
+ " ; Inference Time: " + inferenceTime + " ;Box Size " + results.size());
|
||||
drawResults(results);
|
||||
|
||||
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;
|
||||
}
|
||||
|
||||
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);
|
||||
this.inputImage = rgbaImage;
|
||||
}
|
||||
|
||||
private ArrayList<OcrResultModel> postprocess(ArrayList<OcrResultModel> results) {
|
||||
for (OcrResultModel r : results) {
|
||||
StringBuffer word = new StringBuffer();
|
||||
for (int index : r.getWordIndex()) {
|
||||
if (index >= 0 && index < wordLabels.size()) {
|
||||
word.append(wordLabels.get(index));
|
||||
} else {
|
||||
Log.e(TAG, "Word index is not in label list:" + index);
|
||||
word.append("×");
|
||||
}
|
||||
}
|
||||
r.setLabel(word.toString());
|
||||
}
|
||||
return results;
|
||||
}
|
||||
|
||||
private void drawResults(ArrayList<OcrResultModel> results) {
|
||||
StringBuffer outputResultSb = new StringBuffer("");
|
||||
for (int i=0;i<results.size();i++) {
|
||||
OcrResultModel result = results.get(i);
|
||||
StringBuilder sb = new StringBuilder("");
|
||||
sb.append(result.getLabel());
|
||||
sb.append(" ").append(result.getConfidence());
|
||||
sb.append("; Points: ");
|
||||
for (Point p : result.getPoints()) {
|
||||
sb.append("(").append(p.x).append(",").append(p.y).append(") ");
|
||||
}
|
||||
Log.i(TAG, sb.toString());
|
||||
outputResultSb.append(i+1).append(": ").append(result.getLabel()).append("\n");
|
||||
}
|
||||
outputResult = outputResultSb.toString();
|
||||
outputImage = inputImage;
|
||||
Canvas canvas = new Canvas(outputImage);
|
||||
Paint paintFillAlpha = new Paint();
|
||||
paintFillAlpha.setStyle(Paint.Style.FILL);
|
||||
paintFillAlpha.setColor(Color.parseColor("#3B85F5"));
|
||||
paintFillAlpha.setAlpha(50);
|
||||
|
||||
Paint paint = new Paint();
|
||||
paint.setColor(Color.parseColor("#3B85F5"));
|
||||
paint.setStrokeWidth(5);
|
||||
paint.setStyle(Paint.Style.STROKE);
|
||||
|
||||
for (OcrResultModel result : results) {
|
||||
Path path = new Path();
|
||||
List<Point> points = result.getPoints();
|
||||
path.moveTo(points.get(0).x, points.get(0).y);
|
||||
for (int i = points.size() - 1; i >= 0; i--) {
|
||||
Point p = points.get(i);
|
||||
path.lineTo(p.x, p.y);
|
||||
}
|
||||
canvas.drawPath(path, paint);
|
||||
canvas.drawPath(path, paintFillAlpha);
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
|
|
@ -0,0 +1,200 @@
|
|||
package com.baidu.paddle.lite.demo.ocr;
|
||||
|
||||
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;
|
||||
EditTextPreference etInputShape = null;
|
||||
EditTextPreference etInputMean = null;
|
||||
EditTextPreference etInputStd = null;
|
||||
EditTextPreference etScoreThreshold = 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;
|
||||
List<String> preInstalledScoreThresholds = 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<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>();
|
||||
preInstalledScoreThresholds = new ArrayList<String>();
|
||||
// Add ssd_mobilenet_v1_pascalvoc_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));
|
||||
preInstalledInputShapes.add(getString(R.string.INPUT_SHAPE_DEFAULT));
|
||||
preInstalledInputMeans.add(getString(R.string.INPUT_MEAN_DEFAULT));
|
||||
preInstalledInputStds.add(getString(R.string.INPUT_STD_DEFAULT));
|
||||
preInstalledScoreThresholds.add(getString(R.string.SCORE_THRESHOLD_DEFAULT));
|
||||
|
||||
// Setup 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));
|
||||
etInputShape = (EditTextPreference) findPreference(getString(R.string.INPUT_SHAPE_KEY));
|
||||
etInputMean = (EditTextPreference) findPreference(getString(R.string.INPUT_MEAN_KEY));
|
||||
etInputStd = (EditTextPreference) findPreference(getString(R.string.INPUT_STD_KEY));
|
||||
etScoreThreshold = (EditTextPreference) findPreference(getString(R.string.SCORE_THRESHOLD_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.putString(getString(R.string.INPUT_SHAPE_KEY), preInstalledInputShapes.get(modelIdx));
|
||||
editor.putString(getString(R.string.INPUT_MEAN_KEY), preInstalledInputMeans.get(modelIdx));
|
||||
editor.putString(getString(R.string.INPUT_STD_KEY), preInstalledInputStds.get(modelIdx));
|
||||
editor.putString(getString(R.string.SCORE_THRESHOLD_KEY),
|
||||
preInstalledScoreThresholds.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);
|
||||
etScoreThreshold.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));
|
||||
String inputShape = sharedPreferences.getString(getString(R.string.INPUT_SHAPE_KEY),
|
||||
getString(R.string.INPUT_SHAPE_DEFAULT));
|
||||
String inputMean = sharedPreferences.getString(getString(R.string.INPUT_MEAN_KEY),
|
||||
getString(R.string.INPUT_MEAN_DEFAULT));
|
||||
String inputStd = sharedPreferences.getString(getString(R.string.INPUT_STD_KEY),
|
||||
getString(R.string.INPUT_STD_DEFAULT));
|
||||
String scoreThreshold = sharedPreferences.getString(getString(R.string.SCORE_THRESHOLD_KEY),
|
||||
getString(R.string.SCORE_THRESHOLD_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);
|
||||
etInputMean.setSummary(inputMean);
|
||||
etInputMean.setText(inputMean);
|
||||
etInputStd.setSummary(inputStd);
|
||||
etInputStd.setText(inputStd);
|
||||
etScoreThreshold.setText(scoreThreshold);
|
||||
etScoreThreshold.setSummary(scoreThreshold);
|
||||
}
|
||||
|
||||
@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();
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,113 @@
|
|||
package com.baidu.paddle.lite.demo.ocr;
|
||||
|
||||
import android.content.Context;
|
||||
import android.graphics.Bitmap;
|
||||
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() {
|
||||
return false;
|
||||
// String hardware = android.os.Build.HARDWARE;
|
||||
// return hardware.equalsIgnoreCase("kirin810") || hardware.equalsIgnoreCase("kirin990");
|
||||
}
|
||||
|
||||
public static Bitmap resizeWithStep(Bitmap bitmap, int maxLength, int step) {
|
||||
int width = bitmap.getWidth();
|
||||
int height = bitmap.getHeight();
|
||||
int maxWH = Math.max(width, height);
|
||||
float ratio = 1;
|
||||
int newWidth = width;
|
||||
int newHeight = height;
|
||||
if (maxWH > maxLength) {
|
||||
ratio = maxLength * 1.0f / maxWH;
|
||||
newWidth = (int) Math.floor(ratio * width);
|
||||
newHeight = (int) Math.floor(ratio * height);
|
||||
}
|
||||
|
||||
newWidth = newWidth - newWidth % step;
|
||||
if (newWidth == 0) {
|
||||
newWidth = step;
|
||||
}
|
||||
newHeight = newHeight - newHeight % step;
|
||||
if (newHeight == 0) {
|
||||
newHeight = step;
|
||||
}
|
||||
return Bitmap.createScaledBitmap(bitmap, newWidth, newHeight, true);
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,34 @@
|
|||
<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>
|
||||
|
|
@ -0,0 +1,170 @@
|
|||
<?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>
|
||||
|
|
@ -0,0 +1,99 @@
|
|||
<?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=".MainActivity">
|
||||
|
||||
<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>
|
||||
|
|
@ -0,0 +1,21 @@
|
|||
<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>
|
||||
|
|
@ -0,0 +1,5 @@
|
|||
<?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>
|
||||
|
|
@ -0,0 +1,5 @@
|
|||
<?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>
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 2.9 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 4.8 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 2.0 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 2.7 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 4.4 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 6.7 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 6.2 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 10 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 8.9 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 15 KiB |
|
|
@ -0,0 +1,39 @@
|
|||
<?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>
|
||||
|
|
@ -0,0 +1,6 @@
|
|||
<?xml version="1.0" encoding="utf-8"?>
|
||||
<resources>
|
||||
<color name="colorPrimary">#008577</color>
|
||||
<color name="colorPrimaryDark">#00574B</color>
|
||||
<color name="colorAccent">#D81B60</color>
|
||||
</resources>
|
||||
|
|
@ -0,0 +1,26 @@
|
|||
<resources>
|
||||
<string name="app_name">OCR Chinese</string>
|
||||
<string name="CHOOSE_PRE_INSTALLED_MODEL_KEY">CHOOSE_PRE_INSTALLED_MODEL_KEY</string>
|
||||
<string name="ENABLE_CUSTOM_SETTINGS_KEY">ENABLE_CUSTOM_SETTINGS_KEY</string>
|
||||
<string name="MODEL_PATH_KEY">MODEL_PATH_KEY</string>
|
||||
<string name="LABEL_PATH_KEY">LABEL_PATH_KEY</string>
|
||||
<string name="IMAGE_PATH_KEY">IMAGE_PATH_KEY</string>
|
||||
<string name="CPU_THREAD_NUM_KEY">CPU_THREAD_NUM_KEY</string>
|
||||
<string name="CPU_POWER_MODE_KEY">CPU_POWER_MODE_KEY</string>
|
||||
<string name="INPUT_COLOR_FORMAT_KEY">INPUT_COLOR_FORMAT_KEY</string>
|
||||
<string name="INPUT_SHAPE_KEY">INPUT_SHAPE_KEY</string>
|
||||
<string name="INPUT_MEAN_KEY">INPUT_MEAN_KEY</string>
|
||||
<string name="INPUT_STD_KEY">INPUT_STD_KEY</string>
|
||||
<string name="SCORE_THRESHOLD_KEY">SCORE_THRESHOLD_KEY</string>
|
||||
<string name="MODEL_PATH_DEFAULT">models/ocr_v1_for_cpu</string>
|
||||
<string name="LABEL_PATH_DEFAULT">labels/ppocr_keys_v1.txt</string>
|
||||
<string name="IMAGE_PATH_DEFAULT">images/5.jpg</string>
|
||||
<string name="CPU_THREAD_NUM_DEFAULT">4</string>
|
||||
<string name="CPU_POWER_MODE_DEFAULT">LITE_POWER_HIGH</string>
|
||||
<string name="INPUT_COLOR_FORMAT_DEFAULT">BGR</string>
|
||||
<string name="INPUT_SHAPE_DEFAULT">1,3,960</string>
|
||||
<string name="INPUT_MEAN_DEFAULT">0.485, 0.456, 0.406</string>
|
||||
<string name="INPUT_STD_DEFAULT">0.229,0.224,0.225</string>
|
||||
<string name="SCORE_THRESHOLD_DEFAULT">0.1</string>
|
||||
</resources>
|
||||
|
||||
|
|
@ -0,0 +1,25 @@
|
|||
<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>
|
||||
|
|
@ -0,0 +1,75 @@
|
|||
<?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/MODEL_PATH_DEFAULT"
|
||||
android:key="@string/CHOOSE_PRE_INSTALLED_MODEL_KEY"
|
||||
android:negativeButtonText="@null"
|
||||
android:positiveButtonText="@null"
|
||||
android:title="Choose pre-installed models" />
|
||||
<CheckBoxPreference
|
||||
android:defaultValue="false"
|
||||
android:key="@string/ENABLE_CUSTOM_SETTINGS_KEY"
|
||||
android:summaryOn="Enable"
|
||||
android:summaryOff="Disable"
|
||||
android:title="Enable custom settings"/>
|
||||
<EditTextPreference
|
||||
android:key="@string/MODEL_PATH_KEY"
|
||||
android:defaultValue="@string/MODEL_PATH_DEFAULT"
|
||||
android:title="Model Path" />
|
||||
<EditTextPreference
|
||||
android:key="@string/LABEL_PATH_KEY"
|
||||
android:defaultValue="@string/LABEL_PATH_DEFAULT"
|
||||
android:title="Label Path" />
|
||||
<EditTextPreference
|
||||
android:key="@string/IMAGE_PATH_KEY"
|
||||
android:defaultValue="@string/IMAGE_PATH_DEFAULT"
|
||||
android:title="Image Path" />
|
||||
</PreferenceCategory>
|
||||
<PreferenceCategory android:title="CPU Settings">
|
||||
<ListPreference
|
||||
android:defaultValue="@string/CPU_THREAD_NUM_DEFAULT"
|
||||
android:key="@string/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/CPU_POWER_MODE_DEFAULT"
|
||||
android:key="@string/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/INPUT_COLOR_FORMAT_DEFAULT"
|
||||
android:key="@string/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/INPUT_SHAPE_KEY"
|
||||
android:defaultValue="@string/INPUT_SHAPE_DEFAULT"
|
||||
android:title="Input Shape: (1,1,max_width_height) or (1,3,max_width_height)" />
|
||||
<EditTextPreference
|
||||
android:key="@string/INPUT_MEAN_KEY"
|
||||
android:defaultValue="@string/INPUT_MEAN_DEFAULT"
|
||||
android:title="Input Mean: (channel/255-mean)/std" />
|
||||
<EditTextPreference
|
||||
android:key="@string/INPUT_STD_KEY"
|
||||
android:defaultValue="@string/INPUT_STD_DEFAULT"
|
||||
android:title="Input Std: (channel/255-mean)/std" />
|
||||
</PreferenceCategory>
|
||||
<PreferenceCategory android:title="Output Settings">
|
||||
<EditTextPreference
|
||||
android:key="@string/SCORE_THRESHOLD_KEY"
|
||||
android:defaultValue="@string/SCORE_THRESHOLD_DEFAULT"
|
||||
android:title="Score Threshold" />
|
||||
</PreferenceCategory>
|
||||
</PreferenceScreen>
|
||||
|
|
@ -0,0 +1,17 @@
|
|||
package com.baidu.paddle.lite.demo.ocr;
|
||||
|
||||
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);
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,27 @@
|
|||
// 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
|
||||
}
|
||||
|
|
@ -0,0 +1,15 @@
|
|||
# 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
|
||||
|
||||
|
||||
Binary file not shown.
|
|
@ -0,0 +1,6 @@
|
|||
#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
|
||||
|
|
@ -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" "$@"
|
||||
|
|
@ -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
|
||||
|
|
@ -0,0 +1 @@
|
|||
include ':app'
|
||||
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Reference in New Issue