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PaddleOCR
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5
README.md
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@ -3,10 +3,8 @@ English | [简体中文](README_cn.md)
## Introduction
PaddleOCR aims to create rich, leading, and practical OCR tools that help users train better models and apply them into practice.
**Live stream on coming day**: July 21, 2020 at 8 pm BiliBili station live stream
**Recent updates**
- 2020.7.23, Release the playback and PPT of live class on BiliBili station, PaddleOCR Introduction, [address](https://aistudio.baidu.com/aistudio/course/introduce/1519)
- 2020.7.15, Add mobile App demo , support both iOS and Android ( based on easyedge and Paddle Lite)
- 2020.7.15, Improve the deployment ability, add the C + + inference , serving deployment. In addtion, the benchmarks of the ultra-lightweight OCR model are provided.
- 2020.7.15, Add several related datasets, data annotation and synthesis tools.
@ -214,3 +212,4 @@ We welcome all the contributions to PaddleOCR and appreciate for your feedback v
- Many thanks to [lyl120117](https://github.com/lyl120117) for contributing the code for printing the network structure.
- Thanks [xiangyubo](https://github.com/xiangyubo) for contributing the handwritten Chinese OCR datasets.
- Thanks [authorfu](https://github.com/authorfu) for contributing Android demo and [xiadeye](https://github.com/xiadeye) contributing iOS demo, respectively.
- Thanks [BeyondYourself](https://github.com/BeyondYourself) for contributing many great suggestions and simplifying part of the code style.

8
README_cn.md
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@ -3,9 +3,8 @@
## 简介
PaddleOCR旨在打造一套丰富、领先、且实用的OCR工具库，助力使用者训练出更好的模型，并应用落地。
**直播预告：2020年7月21日晚8点B站直播，PaddleOCR开源大礼包全面解读，直播地址当天更新**
**近期更新**
- 2020.7.23 发布7月21日B站直播课回放和PPT，PaddleOCR开源大礼包全面解读，[获取地址](https://aistudio.baidu.com/aistudio/course/introduce/1519)
- 2020.7.15 添加基于EasyEdge和Paddle-Lite的移动端DEMO，支持iOS和Android系统
- 2020.7.15 完善预测部署，添加基于C++预测引擎推理、服务化部署和端侧部署方案，以及超轻量级中文OCR模型预测耗时Benchmark
- 2020.7.15 整理OCR相关数据集、常用数据标注以及合成工具
@ -33,7 +32,7 @@ PaddleOCR旨在打造一套丰富、领先、且实用的OCR工具库，助力
上图是超轻量级中文OCR模型效果展示，更多效果图请见[效果展示页面](./doc/doc_ch/visualization.md)。
- 超轻量级中文OCR在线体验地址：https://www.paddlepaddle.org.cn/hub/scene/ocr
- 移动端DEMO体验(基于EasyEdge和Paddle-Lite, 支持iOS和Android系统)：[安装包二维码获取地址](https://ai.baidu.com/easyedge/app/openSource?from=paddlelite)
- 移动端DEMO体验(基于EasyEdge和Paddle-Lite, 支持iOS和Android系统)：[安装包二维码获取地址](https://ai.baidu.com/easyedge/app/openSource?from=paddlelite)
Android手机也可以扫描下面二维码安装体验。
@ -206,8 +205,9 @@ PaddleOCR文本识别算法的训练和使用请参考文档教程中[模型训
## 贡献代码
我们非常欢迎你为PaddleOCR贡献代码，也十分感谢你的反馈。
- 非常感谢 [Khanh Tran](https://github.com/xxxpsyduck) 贡献了英文文档。
- 非常感谢 [Khanh Tran](https://github.com/xxxpsyduck) 贡献了英文文档
- 非常感谢 [zhangxin](https://github.com/ZhangXinNan)([Blog](https://blog.csdn.net/sdlypyzq)) 贡献新的可视化方式、添加.gitgnore、处理手动设置PYTHONPATH环境变量的问题
- 非常感谢 [lyl120117](https://github.com/lyl120117) 贡献打印网络结构的代码
- 非常感谢 [xiangyubo](https://github.com/xiangyubo) 贡献手写中文OCR数据集
- 非常感谢 [authorfu](https://github.com/authorfu) 贡献Android和[xiadeye](https://github.com/xiadeye) 贡献IOS的demo代码
- 非常感谢 [BeyondYourself](https://github.com/BeyondYourself) 给PaddleOCR提了很多非常棒的建议，并简化了PaddleOCR的部分代码风格。

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deploy/android_demo/README.md
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@ -1,6 +1,6 @@
# 如何快速测试
### 1. 安装最新版本的Android Studio
可以从https://developer.android.com/studio下载。本Demo使用是4.0版本Android Studio编写。
可以从https://developer.android.com/studio 下载。本Demo使用是4.0版本Android Studio编写。
### 2. 按照NDK 20 以上版本
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。

11
deploy/android_demo/app/build.gradle
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@ -3,11 +3,11 @@ import java.security.MessageDigest
apply plugin: 'com.android.application'
android {
compileSdkVersion 28
compileSdkVersion 29
defaultConfig {
applicationId "com.baidu.paddle.lite.demo.ocr"
minSdkVersion 15
targetSdkVersion 28
minSdkVersion 23
targetSdkVersion 29
versionCode 1
versionName "1.0"
testInstrumentationRunner "android.support.test.runner.AndroidJUnitRunner"
@ -39,9 +39,8 @@ android {
dependencies {
implementation fileTree(include: ['*.jar'], dir: 'libs')
implementation 'com.android.support:appcompat-v7:28.0.0'
implementation 'com.android.support.constraint:constraint-layout:1.1.3'
implementation 'com.android.support:design:28.0.0'
implementation 'androidx.appcompat:appcompat:1.1.0'
implementation 'androidx.constraintlayout:constraintlayout:1.1.3'
testImplementation 'junit:junit:4.12'
androidTestImplementation 'com.android.support.test:runner:1.0.2'
androidTestImplementation 'com.android.support.test.espresso:espresso-core:3.0.2'

11
deploy/android_demo/app/src/main/AndroidManifest.xml
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@ -14,10 +14,10 @@
android:roundIcon="@mipmap/ic_launcher_round"
android:supportsRtl="true"
android:theme="@style/AppTheme">
<!-- to test MiniActivity, change this to com.baidu.paddle.lite.demo.ocr.MiniActivity -->
<activity android:name="com.baidu.paddle.lite.demo.ocr.MainActivity">
<intent-filter>
<action android:name="android.intent.action.MAIN"/>
<category android:name="android.intent.category.LAUNCHER"/>
</intent-filter>
</activity>
@ -25,6 +25,15 @@
android:name="com.baidu.paddle.lite.demo.ocr.SettingsActivity"
android:label="Settings">
</activity>
<provider
android:name="androidx.core.content.FileProvider"
android:authorities="com.baidu.paddle.lite.demo.ocr.fileprovider"
android:exported="false"
android:grantUriPermissions="true">
<meta-data
android:name="android.support.FILE_PROVIDER_PATHS"
android:resource="@xml/file_paths"></meta-data>
</provider>
</application>
</manifest>

2
deploy/android_demo/app/src/main/cpp/native.cpp
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@ -30,7 +30,7 @@ Java_com_baidu_paddle_lite_demo_ocr_OCRPredictorNative_init(JNIEnv *env, jobject
}
/**
* "LITE_POWER_HIGH" 转为 paddle::lite_api::LITE_POWER_HIGH
* "LITE_POWER_HIGH" convert to paddle::lite_api::LITE_POWER_HIGH
* @param cpu_mode
* @return
*/

2
deploy/android_demo/app/src/main/cpp/ocr_ppredictor.cpp
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@ -37,7 +37,7 @@ int OCR_PPredictor::init_from_file(const std::string &det_model_path, const std:
return RETURN_OK;
}
/**
* 调试用，保存第一步的框选结果
* for debug use, show result of First Step
* @param filter_boxes
* @param boxes
* @param srcimg

24
deploy/android_demo/app/src/main/cpp/ocr_ppredictor.h
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@ -12,26 +12,26 @@
namespace ppredictor {
/**
* 配置
* Config
*/
struct OCR_Config {
int thread_num = 4; // 线程数
int thread_num = 4; // Thread num
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,
* PolyGone Result
*/
struct OCRPredictResult {
std::vector<int> word_index; //
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
* OCR there are 2 models
* 1. First model（det），select polygones to show where are the texts
* 2. crop from the origin images, use these polygones to infer
*/
class OCR_PPredictor : public PPredictor_Interface {
public:
@ -50,7 +50,7 @@ public:
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
* Return OCR result
* @param dims
* @param input_data
* @param input_len
@ -69,7 +69,7 @@ public:
private:
/**
* 从第一个模型的结果中计算有文字的四边形
* calcul Polygone from the result image of first model
* @param pred
* @param output_height
* @param output_width
@ -81,7 +81,7 @@ private:
const cv::Mat &origin);
/**
* 第二个模型的推理
* infer for second model
*
* @param boxes
* @param origin
@ -91,14 +91,14 @@ private:
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
* Postprocess or sencod model to extract text
* @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
* calculate confidence of second model text result
* @param res
* @return
*/

8
deploy/android_demo/app/src/main/cpp/ppredictor.h
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@ -7,7 +7,7 @@
namespace ppredictor {
/**
* PaddleLite Preditor 通用接口
* PaddleLite Preditor Common Interface
*/
class PPredictor_Interface {
public:
@ -21,7 +21,7 @@ public:
};
/**
* 通用推理
* Common Predictor
*/
class PPredictor : public PPredictor_Interface {
public:
@ -33,9 +33,9 @@ public:
}
/**
* 初始化paddlitelite的opt模型，nb格式，与init_paddle二选一
* init paddlitelite opt model，nb format ，or use ini_paddle
* @param model_content
* @return 0 目前是固定值0， 之后其他值表示失败
* @return 0
*/
virtual int init_nb(const std::string &model_content);

8
deploy/android_demo/app/src/main/cpp/predictor_output.h
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@ -21,10 +21,10 @@ public:
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
std::vector<float> data; // return float, or use data_int
std::vector<int> data_int; // several layers return int ，or use data
std::vector<int64_t> shape; // PaddleLite output shape
std::vector<std::vector<uint64_t>> lod; // PaddleLite output lod
private:
std::unique_ptr<const paddle::lite_api::Tensor> _tensor;

11
deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/AppCompatPreferenceActivity.java
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@ -19,15 +19,16 @@ 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;
import androidx.annotation.LayoutRes;
import androidx.annotation.Nullable;
import androidx.appcompat.app.ActionBar;
import androidx.appcompat.app.AppCompatDelegate;
import androidx.appcompat.widget.Toolbar;
/**
* A {@link PreferenceActivity} which implements and proxies the necessary calls
* to be used with AppCompat.

81
deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/MainActivity.java
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@ -3,23 +3,22 @@ package com.baidu.paddle.lite.demo.ocr;
import android.Manifest;
import android.app.ProgressDialog;
import android.content.ContentResolver;
import android.content.Context;
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.media.ExifInterface;
import android.net.Uri;
import android.os.Bundle;
import android.os.Environment;
import android.os.Handler;
import android.os.HandlerThread;
import android.os.Message;
import android.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;
@ -29,9 +28,17 @@ import android.widget.ImageView;
import android.widget.TextView;
import android.widget.Toast;
import androidx.annotation.NonNull;
import androidx.appcompat.app.AppCompatActivity;
import androidx.core.app.ActivityCompat;
import androidx.core.content.ContextCompat;
import androidx.core.content.FileProvider;
import java.io.File;
import java.io.IOException;
import java.io.InputStream;
import java.text.SimpleDateFormat;
import java.util.Date;
public class MainActivity extends AppCompatActivity {
private static final String TAG = MainActivity.class.getSimpleName();
@ -69,6 +76,7 @@ public class MainActivity extends AppCompatActivity {
protected float[] inputMean = new float[]{};
protected float[] inputStd = new float[]{};
protected float scoreThreshold = 0.1f;
private String currentPhotoPath;
protected Predictor predictor = new Predictor();
@ -368,18 +376,56 @@ public class MainActivity extends AppCompatActivity {
}
private void takePhoto() {
Intent takePhotoIntent = new Intent(MediaStore.ACTION_IMAGE_CAPTURE);
if (takePhotoIntent.resolveActivity(getPackageManager()) != null) {
startActivityForResult(takePhotoIntent, TAKE_PHOTO_REQUEST_CODE);
Intent takePictureIntent = new Intent(MediaStore.ACTION_IMAGE_CAPTURE);
// Ensure that there's a camera activity to handle the intent
if (takePictureIntent.resolveActivity(getPackageManager()) != null) {
// Create the File where the photo should go
File photoFile = null;
try {
photoFile = createImageFile();
} catch (IOException ex) {
Log.e("MainActitity", ex.getMessage(), ex);
Toast.makeText(MainActivity.this,
"Create Camera temp file failed: " + ex.getMessage(), Toast.LENGTH_SHORT).show();
}
// Continue only if the File was successfully created
if (photoFile != null) {
Log.i(TAG, "FILEPATH " + getExternalFilesDir("Pictures").getAbsolutePath());
Uri photoURI = FileProvider.getUriForFile(this,
"com.baidu.paddle.lite.demo.ocr.fileprovider",
photoFile);
currentPhotoPath = photoFile.getAbsolutePath();
takePictureIntent.putExtra(MediaStore.EXTRA_OUTPUT, photoURI);
startActivityForResult(takePictureIntent, TAKE_PHOTO_REQUEST_CODE);
Log.i(TAG, "startActivityForResult finished");
}
}
}
private File createImageFile() throws IOException {
// Create an image file name
String timeStamp = new SimpleDateFormat("yyyyMMdd_HHmmss").format(new Date());
String imageFileName = "JPEG_" + timeStamp + "_";
File storageDir = getExternalFilesDir(Environment.DIRECTORY_PICTURES);
File image = File.createTempFile(
imageFileName, /* prefix */
".bmp", /* suffix */
storageDir /* directory */
);
return image;
}
@Override
protected void onActivityResult(int requestCode, int resultCode, Intent data) {
super.onActivityResult(requestCode, resultCode, data);
if (resultCode == RESULT_OK && data != null) {
if (resultCode == RESULT_OK) {
switch (requestCode) {
case OPEN_GALLERY_REQUEST_CODE:
if (data == null) {
break;
}
try {
ContentResolver resolver = getContentResolver();
Uri uri = data.getData();
@ -393,9 +439,22 @@ public class MainActivity extends AppCompatActivity {
}
break;
case TAKE_PHOTO_REQUEST_CODE:
Bundle extras = data.getExtras();
Bitmap image = (Bitmap) extras.get("data");
onImageChanged(image);
if (currentPhotoPath != null) {
ExifInterface exif = null;
try {
exif = new ExifInterface(currentPhotoPath);
} catch (IOException e) {
e.printStackTrace();
}
int orientation = exif.getAttributeInt(ExifInterface.TAG_ORIENTATION,
ExifInterface.ORIENTATION_UNDEFINED);
Log.i(TAG, "rotation " + orientation);
Bitmap image = BitmapFactory.decodeFile(currentPhotoPath);
image = Utils.rotateBitmap(image, orientation);
onImageChanged(image);
} else {
Log.e(TAG, "currentPhotoPath is null");
}
break;
default:
break;

157
deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/MiniActivity.java
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@ -0,0 +1,157 @@
package com.baidu.paddle.lite.demo.ocr;
import android.graphics.Bitmap;
import android.graphics.BitmapFactory;
import android.os.Build;
import android.os.Bundle;
import android.os.Handler;
import android.os.HandlerThread;
import android.os.Message;
import android.util.Log;
import android.view.View;
import android.widget.Button;
import android.widget.ImageView;
import android.widget.TextView;
import android.widget.Toast;
import androidx.appcompat.app.AppCompatActivity;
import java.io.IOException;
import java.io.InputStream;
public class MiniActivity extends AppCompatActivity {
public static final int REQUEST_LOAD_MODEL = 0;
public static final int REQUEST_RUN_MODEL = 1;
public static final int REQUEST_UNLOAD_MODEL = 2;
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;
private static final String TAG = "MiniActivity";
protected Handler receiver = null; // Receive messages from worker thread
protected Handler sender = null; // Send command to worker thread
protected HandlerThread worker = null; // Worker thread to load&run model
protected volatile Predictor predictor = null;
private String assetModelDirPath = "models/ocr_v1_for_cpu";
private String assetlabelFilePath = "labels/ppocr_keys_v1.txt";
private Button button;
private ImageView imageView; // image result
private TextView textView; // text result
@Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_mini);
Log.i(TAG, "SHOW in Logcat");
// Prepare the worker thread for mode loading and inference
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()) {
runOnUiThread(new Runnable() {
@Override
public void run() {
Toast.makeText(MiniActivity.this, "Load model failed!", Toast.LENGTH_SHORT).show();
}
});
}
break;
case REQUEST_RUN_MODEL:
// Run model if model is loaded
final boolean isSuccessed = onRunModel();
runOnUiThread(new Runnable() {
@Override
public void run() {
if (isSuccessed){
onRunModelSuccessed();
}else{
Toast.makeText(MiniActivity.this, "Run model failed!", Toast.LENGTH_SHORT).show();
}
}
});
break;
}
}
};
sender.sendEmptyMessage(REQUEST_LOAD_MODEL); // corresponding to REQUEST_LOAD_MODEL， to call onLoadModel()
imageView = findViewById(R.id.imageView);
textView = findViewById(R.id.sample_text);
button = findViewById(R.id.button);
button.setOnClickListener(new View.OnClickListener() {
@Override
public void onClick(View v) {
sender.sendEmptyMessage(REQUEST_RUN_MODEL);
}
});
}
@Override
protected void onDestroy() {
onUnloadModel();
if (Build.VERSION.SDK_INT >= Build.VERSION_CODES.JELLY_BEAN_MR2) {
worker.quitSafely();
} else {
worker.quit();
}
super.onDestroy();
}
/**
* call in onCreate, model init
*
* @return
*/
private boolean onLoadModel() {
if (predictor == null) {
predictor = new Predictor();
}
return predictor.init(this, assetModelDirPath, assetlabelFilePath);
}
/**
* init engine
* call in onCreate
*
* @return
*/
private boolean onRunModel() {
try {
String assetImagePath = "images/5.jpg";
InputStream imageStream = getAssets().open(assetImagePath);
Bitmap image = BitmapFactory.decodeStream(imageStream);
// Input is Bitmap
predictor.setInputImage(image);
return predictor.isLoaded() && predictor.runModel();
} catch (IOException e) {
e.printStackTrace();
return false;
}
}
private void onRunModelSuccessed() {
Log.i(TAG, "onRunModelSuccessed");
textView.setText(predictor.outputResult);
imageView.setImageBitmap(predictor.outputImage);
}
private void onUnloadModel() {
if (predictor != null) {
predictor.releaseModel();
}
}
}

4
deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/OCRPredictorNative.java
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@ -35,8 +35,8 @@ public class OCRPredictorNative {
}
public void release(){
if (nativePointer != 0){
public void release() {
if (nativePointer != 0) {
nativePointer = 0;
destory(nativePointer);
}

34
deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/Predictor.java
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@ -38,7 +38,7 @@ public class Predictor {
protected float scoreThreshold = 0.1f;
protected Bitmap inputImage = null;
protected Bitmap outputImage = null;
protected String outputResult = "";
protected volatile String outputResult = "";
protected float preprocessTime = 0;
protected float postprocessTime = 0;
@ -46,6 +46,16 @@ public class Predictor {
public Predictor() {
}
public boolean init(Context appCtx, String modelPath, String labelPath) {
isLoaded = loadModel(appCtx, modelPath, cpuThreadNum, cpuPowerMode);
if (!isLoaded) {
return false;
}
isLoaded = loadLabel(appCtx, labelPath);
return isLoaded;
}
public boolean init(Context appCtx, String modelPath, String labelPath, int cpuThreadNum, String cpuPowerMode,
String inputColorFormat,
long[] inputShape, float[] inputMean,
@ -76,11 +86,7 @@ public class Predictor {
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);
boolean isLoaded = init(appCtx, modelPath, labelPath);
if (!isLoaded) {
return false;
}
@ -127,12 +133,12 @@ public class Predictor {
}
public void releaseModel() {
if (paddlePredictor != null){
if (paddlePredictor != null) {
paddlePredictor.release();
paddlePredictor = null;
}
isLoaded = false;
cpuThreadNum = 4;
cpuThreadNum = 1;
cpuPowerMode = "LITE_POWER_HIGH";
modelPath = "";
modelName = "";
@ -222,7 +228,7 @@ public class Predictor {
for (int i = 0; i < warmupIterNum; i++) {
paddlePredictor.runImage(inputData, width, height, channels, inputImage);
}
warmupIterNum = 0; // 之后不要再warm了
warmupIterNum = 0; // do not need warm
// Run inference
start = new Date();
ArrayList<OcrResultModel> results = paddlePredictor.runImage(inputData, width, height, channels, inputImage);
@ -287,9 +293,7 @@ public class Predictor {
if (image == null) {
return;
}
// Scale image to the size of input tensor
Bitmap rgbaImage = image.copy(Bitmap.Config.ARGB_8888, true);
this.inputImage = rgbaImage;
this.inputImage = image.copy(Bitmap.Config.ARGB_8888, true);
}
private ArrayList<OcrResultModel> postprocess(ArrayList<OcrResultModel> results) {
@ -310,7 +314,7 @@ public class Predictor {
private void drawResults(ArrayList<OcrResultModel> results) {
StringBuffer outputResultSb = new StringBuffer("");
for (int i=0;i<results.size();i++) {
for (int i = 0; i < results.size(); i++) {
OcrResultModel result = results.get(i);
StringBuilder sb = new StringBuilder("");
sb.append(result.getLabel());
@ -319,8 +323,8 @@ public class Predictor {
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");
Log.i(TAG, sb.toString()); // show LOG in Logcat panel
outputResultSb.append(i + 1).append(": ").append(result.getLabel()).append("\n");
}
outputResult = outputResultSb.toString();
outputImage = inputImage;

3
deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/SettingsActivity.java
Unescape View File

@ -5,7 +5,8 @@ import android.os.Bundle;
import android.preference.CheckBoxPreference;
import android.preference.EditTextPreference;
import android.preference.ListPreference;
import android.support.v7.app.ActionBar;
import androidx.appcompat.app.ActionBar;
import java.util.ArrayList;
import java.util.List;

46
deploy/android_demo/app/src/main/java/com/baidu/paddle/lite/demo/ocr/Utils.java
Unescape View File

@ -2,6 +2,8 @@ package com.baidu.paddle.lite.demo.ocr;
import android.content.Context;
import android.graphics.Bitmap;
import android.graphics.Matrix;
import android.media.ExifInterface;
import android.os.Environment;
import java.io.*;
@ -110,4 +112,48 @@ public class Utils {
}
return Bitmap.createScaledBitmap(bitmap, newWidth, newHeight, true);
}
public static Bitmap rotateBitmap(Bitmap bitmap, int orientation) {
Matrix matrix = new Matrix();
switch (orientation) {
case ExifInterface.ORIENTATION_NORMAL:
return bitmap;
case ExifInterface.ORIENTATION_FLIP_HORIZONTAL:
matrix.setScale(-1, 1);
break;
case ExifInterface.ORIENTATION_ROTATE_180:
matrix.setRotate(180);
break;
case ExifInterface.ORIENTATION_FLIP_VERTICAL:
matrix.setRotate(180);
matrix.postScale(-1, 1);
break;
case ExifInterface.ORIENTATION_TRANSPOSE:
matrix.setRotate(90);
matrix.postScale(-1, 1);
break;
case ExifInterface.ORIENTATION_ROTATE_90:
matrix.setRotate(90);
break;
case ExifInterface.ORIENTATION_TRANSVERSE:
matrix.setRotate(-90);
matrix.postScale(-1, 1);
break;
case ExifInterface.ORIENTATION_ROTATE_270:
matrix.setRotate(-90);
break;
default:
return bitmap;
}
try {
Bitmap bmRotated = Bitmap.createBitmap(bitmap, 0, 0, bitmap.getWidth(), bitmap.getHeight(), matrix, true);
bitmap.recycle();
return bmRotated;
}
catch (OutOfMemoryError e) {
e.printStackTrace();
return null;
}
}
}

4
deploy/android_demo/app/src/main/res/layout/activity_main.xml
Unescape View File

@ -1,5 +1,5 @@
<?xml version="1.0" encoding="utf-8"?>
<android.support.constraint.ConstraintLayout xmlns:android="http://schemas.android.com/apk/res/android"
<androidx.constraintlayout.widget.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"
@ -96,4 +96,4 @@
</RelativeLayout>
</android.support.constraint.ConstraintLayout>
</androidx.constraintlayout.widget.ConstraintLayout>

46
deploy/android_demo/app/src/main/res/layout/activity_mini.xml
Unescape View File

@ -0,0 +1,46 @@
<?xml version="1.0" encoding="utf-8"?>
<!-- for MiniActivity Use Only -->
<androidx.constraintlayout.widget.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"
app:layout_constraintLeft_toLeftOf="parent"
app:layout_constraintLeft_toRightOf="parent"
tools:context=".MainActivity">
<TextView
android:id="@+id/sample_text"
android:layout_width="0dp"
android:layout_height="wrap_content"
android:text="Hello World!"
app:layout_constraintLeft_toLeftOf="parent"
app:layout_constraintRight_toRightOf="parent"
app:layout_constraintTop_toBottomOf="@id/imageView"
android:scrollbars="vertical"
/>
<ImageView
android:id="@+id/imageView"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
android:paddingTop="20dp"
android:paddingBottom="20dp"
app:layout_constraintBottom_toTopOf="@id/imageView"
app:layout_constraintLeft_toLeftOf="parent"
app:layout_constraintRight_toRightOf="parent"
app:layout_constraintTop_toTopOf="parent"
tools:srcCompat="@tools:sample/avatars" />
<Button
android:id="@+id/button"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
android:layout_marginBottom="4dp"
android:text="Button"
app:layout_constraintBottom_toBottomOf="parent"
app:layout_constraintLeft_toLeftOf="parent"
app:layout_constraintRight_toRightOf="parent"
tools:layout_editor_absoluteX="161dp" />
</androidx.constraintlayout.widget.ConstraintLayout>

4
deploy/android_demo/app/src/main/res/xml/file_paths.xml
Unescape View File

@ -0,0 +1,4 @@
<?xml version="1.0" encoding="utf-8"?>
<paths xmlns:android="http://schemas.android.com/apk/res/android">
<external-files-path name="my_images" path="Pictures" />
</paths>

164
deploy/cpp_infer/CMakeLists.txt
Unescape View File

@ -1,8 +1,17 @@
project(ocr_system CXX C)
option(WITH_MKL "Compile demo with MKL/OpenBlas support, default use MKL." ON)
option(WITH_GPU "Compile demo with GPU/CPU, default use CPU." OFF)
option(WITH_STATIC_LIB "Compile demo with static/shared library, default use static." ON)
option(USE_TENSORRT "Compile demo with TensorRT." OFF)
option(WITH_TENSORRT "Compile demo with TensorRT." OFF)
SET(PADDLE_LIB "" CACHE PATH "Location of libraries")
SET(OPENCV_DIR "" CACHE PATH "Location of libraries")
SET(CUDA_LIB "" CACHE PATH "Location of libraries")
SET(CUDNN_LIB "" CACHE PATH "Location of libraries")
SET(TENSORRT_DIR "" CACHE PATH "Compile demo with TensorRT")
set(DEMO_NAME "ocr_system")
macro(safe_set_static_flag)
@ -15,24 +24,60 @@ macro(safe_set_static_flag)
endforeach(flag_var)
endmacro()
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11 -g -fpermissive")
set(CMAKE_STATIC_LIBRARY_PREFIX "")
message("flags" ${CMAKE_CXX_FLAGS})
set(CMAKE_CXX_FLAGS_RELEASE "-O3")
if (WITH_MKL)
ADD_DEFINITIONS(-DUSE_MKL)
endif()
if(NOT DEFINED PADDLE_LIB)
message(FATAL_ERROR "please set PADDLE_LIB with -DPADDLE_LIB=/path/paddle/lib")
endif()
if(NOT DEFINED DEMO_NAME)
message(FATAL_ERROR "please set DEMO_NAME with -DDEMO_NAME=demo_name")
if(NOT DEFINED OPENCV_DIR)
message(FATAL_ERROR "please set OPENCV_DIR with -DOPENCV_DIR=/path/opencv")
endif()
set(OPENCV_DIR ${OPENCV_DIR})
find_package(OpenCV REQUIRED PATHS ${OPENCV_DIR}/share/OpenCV NO_DEFAULT_PATH)
if (WIN32)
include_directories("${PADDLE_LIB}/paddle/fluid/inference")
include_directories("${PADDLE_LIB}/paddle/include")
link_directories("${PADDLE_LIB}/paddle/fluid/inference")
find_package(OpenCV REQUIRED PATHS ${OPENCV_DIR}/build/ NO_DEFAULT_PATH)
else ()
find_package(OpenCV REQUIRED PATHS ${OPENCV_DIR}/share/OpenCV NO_DEFAULT_PATH)
include_directories("${PADDLE_LIB}/paddle/include")
link_directories("${PADDLE_LIB}/paddle/lib")
endif ()
include_directories(${OpenCV_INCLUDE_DIRS})
include_directories("${PADDLE_LIB}/paddle/include")
if (WIN32)
add_definitions("/DGOOGLE_GLOG_DLL_DECL=")
set(CMAKE_C_FLAGS_DEBUG "${CMAKE_C_FLAGS_DEBUG} /bigobj /MTd")
set(CMAKE_C_FLAGS_RELEASE "${CMAKE_C_FLAGS_RELEASE} /bigobj /MT")
set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} /bigobj /MTd")
set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} /bigobj /MT")
if (WITH_STATIC_LIB)
safe_set_static_flag()
add_definitions(-DSTATIC_LIB)
endif()
else()
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -g -o3 -std=c++11")
set(CMAKE_STATIC_LIBRARY_PREFIX "")
endif()
message("flags" ${CMAKE_CXX_FLAGS})
if (WITH_GPU)
if (NOT DEFINED CUDA_LIB OR ${CUDA_LIB} STREQUAL "")
message(FATAL_ERROR "please set CUDA_LIB with -DCUDA_LIB=/path/cuda-8.0/lib64")
endif()
if (NOT WIN32)
if (NOT DEFINED CUDNN_LIB)
message(FATAL_ERROR "please set CUDNN_LIB with -DCUDNN_LIB=/path/cudnn_v7.4/cuda/lib64")
endif()
endif(NOT WIN32)
endif()
include_directories("${PADDLE_LIB}/third_party/install/protobuf/include")
include_directories("${PADDLE_LIB}/third_party/install/glog/include")
include_directories("${PADDLE_LIB}/third_party/install/gflags/include")
@ -43,10 +88,12 @@ include_directories("${PADDLE_LIB}/third_party/eigen3")
include_directories("${CMAKE_SOURCE_DIR}/")
if (USE_TENSORRT AND WITH_GPU)
include_directories("${TENSORRT_ROOT}/include")
link_directories("${TENSORRT_ROOT}/lib")
endif()
if (NOT WIN32)
if (WITH_TENSORRT AND WITH_GPU)
include_directories("${TENSORRT_DIR}/include")
link_directories("${TENSORRT_DIR}/lib")
endif()
endif(NOT WIN32)
link_directories("${PADDLE_LIB}/third_party/install/zlib/lib")
@ -57,17 +104,24 @@ link_directories("${PADDLE_LIB}/third_party/install/xxhash/lib")
link_directories("${PADDLE_LIB}/paddle/lib")
AUX_SOURCE_DIRECTORY(./src SRCS)
add_executable(${DEMO_NAME} ${SRCS})
if(WITH_MKL)
include_directories("${PADDLE_LIB}/third_party/install/mklml/include")
set(MATH_LIB ${PADDLE_LIB}/third_party/install/mklml/lib/libmklml_intel${CMAKE_SHARED_LIBRARY_SUFFIX}
${PADDLE_LIB}/third_party/install/mklml/lib/libiomp5${CMAKE_SHARED_LIBRARY_SUFFIX})
if (WIN32)
set(MATH_LIB ${PADDLE_LIB}/third_party/install/mklml/lib/mklml.lib
${PADDLE_LIB}/third_party/install/mklml/lib/libiomp5md.lib)
else ()
set(MATH_LIB ${PADDLE_LIB}/third_party/install/mklml/lib/libmklml_intel${CMAKE_SHARED_LIBRARY_SUFFIX}
${PADDLE_LIB}/third_party/install/mklml/lib/libiomp5${CMAKE_SHARED_LIBRARY_SUFFIX})
execute_process(COMMAND cp -r ${PADDLE_LIB}/third_party/install/mklml/lib/libmklml_intel${CMAKE_SHARED_LIBRARY_SUFFIX} /usr/lib)
endif ()
set(MKLDNN_PATH "${PADDLE_LIB}/third_party/install/mkldnn")
if(EXISTS ${MKLDNN_PATH})
include_directories("${MKLDNN_PATH}/include")
set(MKLDNN_LIB ${MKLDNN_PATH}/lib/libmkldnn.so.0)
if (WIN32)
set(MKLDNN_LIB ${MKLDNN_PATH}/lib/mkldnn.lib)
else ()
set(MKLDNN_LIB ${MKLDNN_PATH}/lib/libmkldnn.so.0)
endif ()
endif()
else()
set(MATH_LIB ${PADDLE_LIB}/third_party/install/openblas/lib/libopenblas${CMAKE_STATIC_LIBRARY_SUFFIX})
@ -82,24 +136,66 @@ else()
${PADDLE_LIB}/paddle/lib/libpaddle_fluid${CMAKE_SHARED_LIBRARY_SUFFIX})
endif()
set(EXTERNAL_LIB "-lrt -ldl -lpthread -lm")
if (NOT WIN32)
set(DEPS ${DEPS}
${MATH_LIB} ${MKLDNN_LIB}
glog gflags protobuf z xxhash
)
if(EXISTS "${PADDLE_LIB}/third_party/install/snappystream/lib")
set(DEPS ${DEPS} snappystream)
endif()
if (EXISTS "${PADDLE_LIB}/third_party/install/snappy/lib")
set(DEPS ${DEPS} snappy)
endif()
else()
set(DEPS ${DEPS}
${MATH_LIB} ${MKLDNN_LIB}
glog gflags_static libprotobuf xxhash)
set(DEPS ${DEPS} libcmt shlwapi)
if (EXISTS "${PADDLE_LIB}/third_party/install/snappy/lib")
set(DEPS ${DEPS} snappy)
endif()
if(EXISTS "${PADDLE_LIB}/third_party/install/snappystream/lib")
set(DEPS ${DEPS} snappystream)
endif()
endif(NOT WIN32)
set(DEPS ${DEPS}
${MATH_LIB} ${MKLDNN_LIB}
glog gflags protobuf z xxhash
${EXTERNAL_LIB} ${OpenCV_LIBS})
if(WITH_GPU)
if (USE_TENSORRT)
set(DEPS ${DEPS}
${TENSORRT_ROOT}/lib/libnvinfer${CMAKE_SHARED_LIBRARY_SUFFIX})
set(DEPS ${DEPS}
${TENSORRT_ROOT}/lib/libnvinfer_plugin${CMAKE_SHARED_LIBRARY_SUFFIX})
if(NOT WIN32)
if (WITH_TENSORRT)
set(DEPS ${DEPS} ${TENSORRT_DIR}/lib/libnvinfer${CMAKE_SHARED_LIBRARY_SUFFIX})
set(DEPS ${DEPS} ${TENSORRT_DIR}/lib/libnvinfer_plugin${CMAKE_SHARED_LIBRARY_SUFFIX})
endif()
set(DEPS ${DEPS} ${CUDA_LIB}/libcudart${CMAKE_SHARED_LIBRARY_SUFFIX})
set(DEPS ${DEPS} ${CUDNN_LIB}/libcudnn${CMAKE_SHARED_LIBRARY_SUFFIX})
else()
set(DEPS ${DEPS} ${CUDA_LIB}/cudart${CMAKE_STATIC_LIBRARY_SUFFIX} )
set(DEPS ${DEPS} ${CUDA_LIB}/cublas${CMAKE_STATIC_LIBRARY_SUFFIX} )
set(DEPS ${DEPS} ${CUDNN_LIB}/cudnn${CMAKE_STATIC_LIBRARY_SUFFIX})
endif()
set(DEPS ${DEPS} ${CUDA_LIB}/libcudart${CMAKE_SHARED_LIBRARY_SUFFIX})
set(DEPS ${DEPS} ${CUDA_LIB}/libcudart${CMAKE_SHARED_LIBRARY_SUFFIX} )
set(DEPS ${DEPS} ${CUDA_LIB}/libcublas${CMAKE_SHARED_LIBRARY_SUFFIX} )
set(DEPS ${DEPS} ${CUDNN_LIB}/libcudnn${CMAKE_SHARED_LIBRARY_SUFFIX} )
endif()
if (NOT WIN32)
set(EXTERNAL_LIB "-ldl -lrt -lgomp -lz -lm -lpthread")
set(DEPS ${DEPS} ${EXTERNAL_LIB})
endif()
set(DEPS ${DEPS} ${OpenCV_LIBS})
AUX_SOURCE_DIRECTORY(./src SRCS)
add_executable(${DEMO_NAME} ${SRCS})
target_link_libraries(${DEMO_NAME} ${DEPS})
if (WIN32 AND WITH_MKL)
add_custom_command(TARGET ${DEMO_NAME} POST_BUILD
COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_LIB}/third_party/install/mklml/lib/mklml.dll ./mklml.dll
COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_LIB}/third_party/install/mklml/lib/libiomp5md.dll ./libiomp5md.dll
COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_LIB}/third_party/install/mkldnn/lib/mkldnn.dll ./mkldnn.dll
COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_LIB}/third_party/install/mklml/lib/mklml.dll ./release/mklml.dll
COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_LIB}/third_party/install/mklml/lib/libiomp5md.dll ./release/libiomp5md.dll
COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_LIB}/third_party/install/mkldnn/lib/mkldnn.dll ./release/mkldnn.dll
)
endif()

95
deploy/cpp_infer/docs/windows_vs2019_build.md
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@ -0,0 +1,95 @@
# Visual Studio 2019 Community CMake 编译指南
PaddleOCR在Windows 平台下基于`Visual Studio 2019 Community` 进行了测试。微软从`Visual Studio 2017`开始即支持直接管理`CMake`跨平台编译项目，但是直到`2019`才提供了稳定和完全的支持，所以如果你想使用CMake管理项目编译构建，我们推荐你使用`Visual Studio 2019`环境下构建。
## 前置条件
* Visual Studio 2019
* CUDA 9.0 / CUDA 10.0，cudnn 7+ （仅在使用GPU版本的预测库时需要）
* CMake 3.0+
请确保系统已经安装好上述基本软件，我们使用的是`VS2019`的社区版。
**下面所有示例以工作目录为 `D:\projects`演示**。
### Step1: 下载PaddlePaddle C++ 预测库 fluid_inference
PaddlePaddle C++ 预测库针对不同的`CPU`和`CUDA`版本提供了不同的预编译版本，请根据实际情况下载: [C++预测库下载列表](https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/advanced_guide/inference_deployment/inference/windows_cpp_inference.html)
解压后`D:\projects\fluid_inference`目录包含内容为：
```
fluid_inference
├── paddle # paddle核心库和头文件
|
├── third_party # 第三方依赖库和头文件
|
└── version.txt # 版本和编译信息
```
### Step2: 安装配置OpenCV
1. 在OpenCV官网下载适用于Windows平台的3.4.6版本， [下载地址](https://sourceforge.net/projects/opencvlibrary/files/3.4.6/opencv-3.4.6-vc14_vc15.exe/download)
2. 运行下载的可执行文件，将OpenCV解压至指定目录，如`D:\projects\opencv`
3. 配置环境变量，如下流程所示
- 我的电脑->属性->高级系统设置->环境变量
- 在系统变量中找到Path（如没有，自行创建），并双击编辑
- 新建，将opencv路径填入并保存，如`D:\projects\opencv\build\x64\vc14\bin`
### Step3: 使用Visual Studio 2019直接编译CMake
1. 打开Visual Studio 2019 Community，点击`继续但无需代码`
![step2](https://paddleseg.bj.bcebos.com/inference/vs2019_step1.png)
2. 点击： `文件`->`打开`->`CMake`
![step2.1](https://paddleseg.bj.bcebos.com/inference/vs2019_step2.png)
选择项目代码所在路径，并打开`CMakeList.txt`：
![step2.2](https://paddleseg.bj.bcebos.com/inference/vs2019_step3.png)
3. 点击：`项目`->`cpp_inference_demo的CMake设置`
![step3](https://paddleseg.bj.bcebos.com/inference/vs2019_step4.png)
4. 点击`浏览`，分别设置编译选项指定`CUDA`、`CUDNN_LIB`、`OpenCV`、`Paddle预测库`的路径
三个编译参数的含义说明如下（带`*`表示仅在使用**GPU版本**预测库时指定, 其中CUDA库版本尽量对齐，**使用9.0、10.0版本，不使用9.2、10.1等版本CUDA库**）：
| 参数名 | 含义 |
| ---- | ---- |
| *CUDA_LIB | CUDA的库路径 |
| *CUDNN_LIB | CUDNN的库路径 |
| OPENCV_DIR | OpenCV的安装路径 |
| PADDLE_LIB | Paddle预测库的路径 |
**注意：**
1. 使用`CPU`版预测库，请把`WITH_GPU`的勾去掉
2. 如果使用的是`openblas`版本，请把`WITH_MKL`勾去掉
![step4](https://paddleseg.bj.bcebos.com/inference/vs2019_step5.png)
**设置完成后**, 点击上图中`保存并生成CMake缓存以加载变量`。
5. 点击`生成`->`全部生成`
![step6](https://paddleseg.bj.bcebos.com/inference/vs2019_step6.png)
### Step4: 预测及可视化
上述`Visual Studio 2019`编译产出的可执行文件在`out\build\x64-Release`目录下，打开`cmd`，并切换到该目录：
```
cd D:\projects\PaddleOCR\deploy\cpp_infer\out\build\x64-Release
```
可执行文件`ocr_system.exe`即为样例的预测程序，其主要使用方法如下
```shell
#预测图片 `D:\projects\PaddleOCR\doc\imgs\10.jpg`
.\ocr_system.exe D:\projects\PaddleOCR\deploy\cpp_infer\tools\config.txt D:\projects\PaddleOCR\doc\imgs\10.jpg
```
第一个参数为配置文件路径，第二个参数为需要预测的图片路径。
### 注意
* 在Windows下的终端中执行文件exe时，可能会发生乱码的现象，此时需要在终端中输入`CHCP 65001`，将终端的编码方式由GBK编码(默认)改为UTF-8编码，更加具体的解释可以参考这篇博客：[https://blog.csdn.net/qq_35038153/article/details/78430359](https://blog.csdn.net/qq_35038153/article/details/78430359)。

3
deploy/cpp_infer/readme.md
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@ -7,6 +7,9 @@
### 运行准备
- Linux环境，推荐使用docker。
- Windows环境，目前支持基于`Visual Studio 2019 Community`进行编译。
* 该文档主要介绍基于Linux环境的PaddleOCR C++预测流程，如果需要在Windows下基于预测库进行C++预测，具体编译方法请参考[Windows下编译教程](./docs/windows_vs2019_build.md)
### 1.1 编译opencv库

2
deploy/cpp_infer/src/config.cpp
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@ -44,7 +44,7 @@ Config::LoadConfig(const std::string &config_path) {
std::map<std::string, std::string> dict;
for (int i = 0; i < config.size(); i++) {
// pass for empty line or comment
if (config[i].size() <= 1 or config[i][0] == '#') {
if (config[i].size() <= 1 || config[i][0] == '#') {
continue;
}
std::vector<std::string> res = split(config[i], " ");

15
deploy/cpp_infer/src/utility.cpp
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@ -39,22 +39,21 @@ std::vector<std::string> Utility::ReadDict(const std::string &path) {
void Utility::VisualizeBboxes(
const cv::Mat &srcimg,
const std::vector<std::vector<std::vector<int>>> &boxes) {
cv::Point rook_points[boxes.size()][4];
for (int n = 0; n < boxes.size(); n++) {
for (int m = 0; m < boxes[0].size(); m++) {
rook_points[n][m] = cv::Point(int(boxes[n][m][0]), int(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]};
cv::Point rook_points[4];
for (int m = 0; m < boxes[n].size(); m++) {
rook_points[m] = cv::Point(int(boxes[n][m][0]), int(boxes[n][m][1]));
}
const cv::Point *ppt[1] = {rook_points};
int npt[] = {4};
cv::polylines(img_vis, ppt, npt, 1, 1, CV_RGB(0, 255, 0), 2, 8, 0);
}
cv::imwrite("./ocr_vis.png", img_vis);
std::cout << "The detection visualized image saved in ./ocr_vis.png.pn"
std::cout << "The detection visualized image saved in ./ocr_vis.png"
<< std::endl;
}

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