commit
eca0ef34ec
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@ -3,10 +3,8 @@ English | [简体中文](README_cn.md)
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## Introduction
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PaddleOCR aims to create rich, leading, and practical OCR tools that help users train better models and apply them into practice.
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**Live stream on coming day**: July 21, 2020 at 8 pm BiliBili station live stream
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**Recent updates**
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- 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)
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- 2020.7.15, Add mobile App demo , support both iOS and Android ( based on easyedge and Paddle Lite)
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- 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.
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- 2020.7.15, Add several related datasets, data annotation and synthesis tools.
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@ -3,9 +3,8 @@
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## 简介
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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。
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**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**
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**近期更新**
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- 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)
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- 2020.7.15 添加基于EasyEdge和Paddle-Lite的移动端DEMO,支持iOS和Android系统
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- 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
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- 2020.7.15 整理OCR相关数据集、常用数据标注以及合成工具
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@ -25,6 +25,15 @@
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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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<provider
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android:name="android.support.v4.content.FileProvider"
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android:authorities="com.baidu.paddle.lite.demo.ocr.fileprovider"
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android:exported="false"
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android:grantUriPermissions="true">
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<meta-data
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android:name="android.support.FILE_PROVIDER_PATHS"
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android:resource="@xml/file_paths"></meta-data>
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</provider>
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</application>
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</manifest>
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@ -3,14 +3,17 @@ package com.baidu.paddle.lite.demo.ocr;
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import android.Manifest;
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import android.app.ProgressDialog;
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import android.content.ContentResolver;
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import android.content.Context;
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import android.content.Intent;
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import android.content.SharedPreferences;
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import android.content.pm.PackageManager;
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import android.database.Cursor;
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import android.graphics.Bitmap;
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import android.graphics.BitmapFactory;
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import android.media.ExifInterface;
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import android.net.Uri;
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import android.os.Bundle;
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import android.os.Environment;
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import android.os.Handler;
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import android.os.HandlerThread;
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import android.os.Message;
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@ -19,6 +22,7 @@ import android.provider.MediaStore;
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import android.support.annotation.NonNull;
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import android.support.v4.app.ActivityCompat;
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import android.support.v4.content.ContextCompat;
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import android.support.v4.content.FileProvider;
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import android.support.v7.app.AppCompatActivity;
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import android.text.method.ScrollingMovementMethod;
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import android.util.Log;
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@ -32,6 +36,8 @@ import android.widget.Toast;
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import java.io.File;
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import java.io.IOException;
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import java.io.InputStream;
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import java.text.SimpleDateFormat;
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import java.util.Date;
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public class MainActivity extends AppCompatActivity {
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private static final String TAG = MainActivity.class.getSimpleName();
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@ -69,6 +75,7 @@ public class MainActivity extends AppCompatActivity {
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protected float[] inputMean = new float[]{};
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protected float[] inputStd = new float[]{};
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protected float scoreThreshold = 0.1f;
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private String currentPhotoPath;
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protected Predictor predictor = new Predictor();
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@ -368,18 +375,56 @@ public class MainActivity extends AppCompatActivity {
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}
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private void takePhoto() {
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Intent takePhotoIntent = new Intent(MediaStore.ACTION_IMAGE_CAPTURE);
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if (takePhotoIntent.resolveActivity(getPackageManager()) != null) {
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startActivityForResult(takePhotoIntent, TAKE_PHOTO_REQUEST_CODE);
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Intent takePictureIntent = new Intent(MediaStore.ACTION_IMAGE_CAPTURE);
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// Ensure that there's a camera activity to handle the intent
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if (takePictureIntent.resolveActivity(getPackageManager()) != null) {
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// Create the File where the photo should go
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File photoFile = null;
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try {
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photoFile = createImageFile();
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} catch (IOException ex) {
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Log.e("MainActitity", ex.getMessage(), ex);
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Toast.makeText(MainActivity.this,
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"Create Camera temp file failed: " + ex.getMessage(), Toast.LENGTH_SHORT).show();
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}
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// Continue only if the File was successfully created
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if (photoFile != null) {
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Log.i(TAG, "FILEPATH " + getExternalFilesDir("Pictures").getAbsolutePath());
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Uri photoURI = FileProvider.getUriForFile(this,
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"com.baidu.paddle.lite.demo.ocr.fileprovider",
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photoFile);
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currentPhotoPath = photoFile.getAbsolutePath();
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takePictureIntent.putExtra(MediaStore.EXTRA_OUTPUT, photoURI);
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startActivityForResult(takePictureIntent, TAKE_PHOTO_REQUEST_CODE);
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Log.i(TAG, "startActivityForResult finished");
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}
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}
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}
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private File createImageFile() throws IOException {
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// Create an image file name
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String timeStamp = new SimpleDateFormat("yyyyMMdd_HHmmss").format(new Date());
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String imageFileName = "JPEG_" + timeStamp + "_";
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File storageDir = getExternalFilesDir(Environment.DIRECTORY_PICTURES);
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File image = File.createTempFile(
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imageFileName, /* prefix */
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".bmp", /* suffix */
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storageDir /* directory */
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);
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return image;
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}
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@Override
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protected void onActivityResult(int requestCode, int resultCode, Intent data) {
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super.onActivityResult(requestCode, resultCode, data);
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if (resultCode == RESULT_OK && data != null) {
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if (resultCode == RESULT_OK) {
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switch (requestCode) {
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case OPEN_GALLERY_REQUEST_CODE:
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if (data == null) {
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break;
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}
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try {
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ContentResolver resolver = getContentResolver();
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Uri uri = data.getData();
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}
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break;
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case TAKE_PHOTO_REQUEST_CODE:
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Bundle extras = data.getExtras();
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Bitmap image = (Bitmap) extras.get("data");
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onImageChanged(image);
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if (currentPhotoPath != null) {
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ExifInterface exif = null;
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try {
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exif = new ExifInterface(currentPhotoPath);
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} catch (IOException e) {
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e.printStackTrace();
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}
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int orientation = exif.getAttributeInt(ExifInterface.TAG_ORIENTATION,
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ExifInterface.ORIENTATION_UNDEFINED);
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Log.i(TAG, "rotation " + orientation);
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Bitmap image = BitmapFactory.decodeFile(currentPhotoPath);
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image = Utils.rotateBitmap(image, orientation);
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onImageChanged(image);
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} else {
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Log.e(TAG, "currentPhotoPath is null");
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}
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break;
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default:
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break;
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@ -35,8 +35,8 @@ public class OCRPredictorNative {
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}
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public void release(){
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if (nativePointer != 0){
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public void release() {
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if (nativePointer != 0) {
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nativePointer = 0;
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destory(nativePointer);
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}
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@ -127,12 +127,12 @@ public class Predictor {
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}
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public void releaseModel() {
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if (paddlePredictor != null){
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if (paddlePredictor != null) {
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paddlePredictor.release();
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paddlePredictor = null;
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}
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isLoaded = false;
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cpuThreadNum = 4;
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cpuThreadNum = 1;
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cpuPowerMode = "LITE_POWER_HIGH";
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modelPath = "";
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modelName = "";
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@ -287,9 +287,7 @@ public class Predictor {
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if (image == null) {
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return;
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}
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// Scale image to the size of input tensor
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Bitmap rgbaImage = image.copy(Bitmap.Config.ARGB_8888, true);
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this.inputImage = rgbaImage;
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this.inputImage = image.copy(Bitmap.Config.ARGB_8888, true);
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}
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private ArrayList<OcrResultModel> postprocess(ArrayList<OcrResultModel> results) {
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@ -310,7 +308,7 @@ public class Predictor {
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private void drawResults(ArrayList<OcrResultModel> results) {
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StringBuffer outputResultSb = new StringBuffer("");
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for (int i=0;i<results.size();i++) {
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for (int i = 0; i < results.size(); i++) {
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OcrResultModel result = results.get(i);
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StringBuilder sb = new StringBuilder("");
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sb.append(result.getLabel());
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@ -320,7 +318,7 @@ public class Predictor {
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sb.append("(").append(p.x).append(",").append(p.y).append(") ");
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}
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Log.i(TAG, sb.toString());
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outputResultSb.append(i+1).append(": ").append(result.getLabel()).append("\n");
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outputResultSb.append(i + 1).append(": ").append(result.getLabel()).append("\n");
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}
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outputResult = outputResultSb.toString();
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outputImage = inputImage;
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@ -2,6 +2,8 @@ package com.baidu.paddle.lite.demo.ocr;
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import android.content.Context;
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import android.graphics.Bitmap;
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import android.graphics.Matrix;
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import android.media.ExifInterface;
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import android.os.Environment;
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import java.io.*;
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@ -110,4 +112,48 @@ public class Utils {
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}
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return Bitmap.createScaledBitmap(bitmap, newWidth, newHeight, true);
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}
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public static Bitmap rotateBitmap(Bitmap bitmap, int orientation) {
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Matrix matrix = new Matrix();
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switch (orientation) {
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case ExifInterface.ORIENTATION_NORMAL:
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return bitmap;
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case ExifInterface.ORIENTATION_FLIP_HORIZONTAL:
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matrix.setScale(-1, 1);
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break;
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case ExifInterface.ORIENTATION_ROTATE_180:
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matrix.setRotate(180);
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break;
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case ExifInterface.ORIENTATION_FLIP_VERTICAL:
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matrix.setRotate(180);
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matrix.postScale(-1, 1);
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break;
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case ExifInterface.ORIENTATION_TRANSPOSE:
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matrix.setRotate(90);
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matrix.postScale(-1, 1);
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break;
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case ExifInterface.ORIENTATION_ROTATE_90:
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matrix.setRotate(90);
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break;
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case ExifInterface.ORIENTATION_TRANSVERSE:
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matrix.setRotate(-90);
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matrix.postScale(-1, 1);
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break;
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case ExifInterface.ORIENTATION_ROTATE_270:
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matrix.setRotate(-90);
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break;
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default:
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return bitmap;
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}
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try {
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Bitmap bmRotated = Bitmap.createBitmap(bitmap, 0, 0, bitmap.getWidth(), bitmap.getHeight(), matrix, true);
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bitmap.recycle();
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return bmRotated;
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}
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catch (OutOfMemoryError e) {
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e.printStackTrace();
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return null;
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}
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}
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}
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@ -0,0 +1,4 @@
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<?xml version="1.0" encoding="utf-8"?>
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<paths xmlns:android="http://schemas.android.com/apk/res/android">
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<external-files-path name="my_images" path="Pictures" />
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</paths>
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@ -1,8 +1,17 @@
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project(ocr_system CXX C)
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option(WITH_MKL "Compile demo with MKL/OpenBlas support, default use MKL." ON)
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option(WITH_GPU "Compile demo with GPU/CPU, default use CPU." OFF)
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option(WITH_STATIC_LIB "Compile demo with static/shared library, default use static." ON)
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option(USE_TENSORRT "Compile demo with TensorRT." OFF)
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option(WITH_TENSORRT "Compile demo with TensorRT." OFF)
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SET(PADDLE_LIB "" CACHE PATH "Location of libraries")
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SET(OPENCV_DIR "" CACHE PATH "Location of libraries")
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SET(CUDA_LIB "" CACHE PATH "Location of libraries")
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SET(CUDNN_LIB "" CACHE PATH "Location of libraries")
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SET(TENSORRT_DIR "" CACHE PATH "Compile demo with TensorRT")
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set(DEMO_NAME "ocr_system")
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macro(safe_set_static_flag)
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@ -15,24 +24,60 @@ macro(safe_set_static_flag)
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endforeach(flag_var)
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endmacro()
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11 -g -fpermissive")
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set(CMAKE_STATIC_LIBRARY_PREFIX "")
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message("flags" ${CMAKE_CXX_FLAGS})
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set(CMAKE_CXX_FLAGS_RELEASE "-O3")
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if (WITH_MKL)
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ADD_DEFINITIONS(-DUSE_MKL)
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endif()
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if(NOT DEFINED PADDLE_LIB)
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message(FATAL_ERROR "please set PADDLE_LIB with -DPADDLE_LIB=/path/paddle/lib")
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endif()
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if(NOT DEFINED DEMO_NAME)
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message(FATAL_ERROR "please set DEMO_NAME with -DDEMO_NAME=demo_name")
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if(NOT DEFINED OPENCV_DIR)
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message(FATAL_ERROR "please set OPENCV_DIR with -DOPENCV_DIR=/path/opencv")
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endif()
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set(OPENCV_DIR ${OPENCV_DIR})
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find_package(OpenCV REQUIRED PATHS ${OPENCV_DIR}/share/OpenCV NO_DEFAULT_PATH)
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if (WIN32)
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include_directories("${PADDLE_LIB}/paddle/fluid/inference")
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include_directories("${PADDLE_LIB}/paddle/include")
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link_directories("${PADDLE_LIB}/paddle/fluid/inference")
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find_package(OpenCV REQUIRED PATHS ${OPENCV_DIR}/build/ NO_DEFAULT_PATH)
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else ()
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find_package(OpenCV REQUIRED PATHS ${OPENCV_DIR}/share/OpenCV NO_DEFAULT_PATH)
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include_directories("${PADDLE_LIB}/paddle/include")
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link_directories("${PADDLE_LIB}/paddle/lib")
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endif ()
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include_directories(${OpenCV_INCLUDE_DIRS})
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include_directories("${PADDLE_LIB}/paddle/include")
|
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if (WIN32)
|
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add_definitions("/DGOOGLE_GLOG_DLL_DECL=")
|
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set(CMAKE_C_FLAGS_DEBUG "${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")
|
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set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} /bigobj /MT")
|
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if (WITH_STATIC_LIB)
|
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safe_set_static_flag()
|
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add_definitions(-DSTATIC_LIB)
|
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endif()
|
||||
else()
|
||||
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -g -o3 -std=c++11")
|
||||
set(CMAKE_STATIC_LIBRARY_PREFIX "")
|
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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()
|
|
@ -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)。
|
|
@ -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
|
||||
|
||||
|
|
|
@ -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], " ");
|
||||
|
|
|
@ -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;
|
||||
}
|
||||
|
||||
|
|
|
@ -1,8 +1,7 @@
|
|||
|
||||
OPENCV_DIR=your_opencv_dir
|
||||
LIB_DIR=your_paddle_inference_dir
|
||||
CUDA_LIB_DIR=your_cuda_lib_dir
|
||||
CUDNN_LIB_DIR=/your_cudnn_lib_dir
|
||||
CUDNN_LIB_DIR=your_cudnn_lib_dir
|
||||
|
||||
BUILD_DIR=build
|
||||
rm -rf ${BUILD_DIR}
|
||||
|
@ -11,7 +10,6 @@ cd ${BUILD_DIR}
|
|||
cmake .. \
|
||||
-DPADDLE_LIB=${LIB_DIR} \
|
||||
-DWITH_MKL=ON \
|
||||
-DDEMO_NAME=ocr_system \
|
||||
-DWITH_GPU=OFF \
|
||||
-DWITH_STATIC_LIB=OFF \
|
||||
-DUSE_TENSORRT=OFF \
|
||||
|
|
|
@ -15,8 +15,7 @@ det_model_dir ./inference/det_db
|
|||
# rec config
|
||||
rec_model_dir ./inference/rec_crnn
|
||||
char_list_file ../../ppocr/utils/ppocr_keys_v1.txt
|
||||
img_path ../../doc/imgs/11.jpg
|
||||
|
||||
# show the detection results
|
||||
visualize 0
|
||||
visualize 1
|
||||
|
||||
|
|
|
@ -18,7 +18,7 @@ Paddle Lite是飞桨轻量化推理引擎,为手机、IOT端提供高效推理
|
|||
1. [Docker](https://paddle-lite.readthedocs.io/zh/latest/user_guides/source_compile.html#docker)
|
||||
2. [Linux](https://paddle-lite.readthedocs.io/zh/latest/user_guides/source_compile.html#android)
|
||||
3. [MAC OS](https://paddle-lite.readthedocs.io/zh/latest/user_guides/source_compile.html#id13)
|
||||
4. [Windows](https://paddle-lite.readthedocs.io/zh/latest/demo_guides/x86.html#windows)
|
||||
4. [Windows](https://paddle-lite.readthedocs.io/zh/latest/demo_guides/x86.html#id4)
|
||||
|
||||
### 1.2 准备预测库
|
||||
|
||||
|
@ -84,7 +84,7 @@ Paddle-Lite 提供了多种策略来自动优化原始的模型,其中包括
|
|||
|
||||
|模型简介|检测模型|识别模型|Paddle-Lite版本|
|
||||
|-|-|-|-|
|
||||
|超轻量级中文OCR opt优化模型|[下载地址](https://paddleocr.bj.bcebos.com/deploy/lite/ch_det_mv3_db_opt.nb)|[下载地址](https://paddleocr.bj.bcebos.com/deploy/lite/ch_rec_mv3_crnn_opt.nb)|2.6.1|
|
||||
|超轻量级中文OCR opt优化模型|[下载地址](https://paddleocr.bj.bcebos.com/deploy/lite/ch_det_mv3_db_opt.nb)|[下载地址](https://paddleocr.bj.bcebos.com/deploy/lite/ch_rec_mv3_crnn_opt.nb)|develop|
|
||||
|
||||
如果直接使用上述表格中的模型进行部署,可略过下述步骤,直接阅读 [2.2节](#2.2与手机联调)。
|
||||
|
||||
|
|
|
@ -17,7 +17,7 @@ deployment solutions for end-side deployment issues.
|
|||
[build for Docker](https://paddle-lite.readthedocs.io/zh/latest/user_guides/source_compile.html#docker)
|
||||
[build for Linux](https://paddle-lite.readthedocs.io/zh/latest/user_guides/source_compile.html#android)
|
||||
[build for MAC OS](https://paddle-lite.readthedocs.io/zh/latest/user_guides/source_compile.html#id13)
|
||||
[build for windows](https://paddle-lite.readthedocs.io/zh/latest/demo_guides/x86.html#windows)
|
||||
[build for windows](https://paddle-lite.readthedocs.io/zh/latest/demo_guides/x86.html#id4)
|
||||
|
||||
## 3. Download prebuild library for android and ios
|
||||
|
||||
|
@ -155,7 +155,7 @@ demo/cxx/ocr/
|
|||
|-- debug/
|
||||
| |--ch_det_mv3_db_opt.nb Detection model
|
||||
| |--ch_rec_mv3_crnn_opt.nb Recognition model
|
||||
| |--11.jpg image for OCR
|
||||
| |--11.jpg Image for OCR
|
||||
| |--ppocr_keys_v1.txt Dictionary file
|
||||
| |--libpaddle_light_api_shared.so C++ .so file
|
||||
| |--config.txt Config file
|
||||
|
|
|
@ -0,0 +1,71 @@
|
|||
# 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.
|
||||
|
||||
from paddle_serving_client import Client
|
||||
import cv2
|
||||
import sys
|
||||
import numpy as np
|
||||
import os
|
||||
from paddle_serving_client import Client
|
||||
from paddle_serving_app.reader import Sequential, ResizeByFactor
|
||||
from paddle_serving_app.reader import Div, Normalize, Transpose
|
||||
from paddle_serving_app.reader import DBPostProcess, FilterBoxes
|
||||
from paddle_serving_server_gpu.web_service import WebService
|
||||
import time
|
||||
import re
|
||||
import base64
|
||||
|
||||
|
||||
class OCRService(WebService):
|
||||
def init_det(self):
|
||||
self.det_preprocess = Sequential([
|
||||
ResizeByFactor(32, 960), Div(255),
|
||||
Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]), Transpose(
|
||||
(2, 0, 1))
|
||||
])
|
||||
self.filter_func = FilterBoxes(10, 10)
|
||||
self.post_func = DBPostProcess({
|
||||
"thresh": 0.3,
|
||||
"box_thresh": 0.5,
|
||||
"max_candidates": 1000,
|
||||
"unclip_ratio": 1.5,
|
||||
"min_size": 3
|
||||
})
|
||||
|
||||
def preprocess(self, feed=[], fetch=[]):
|
||||
data = base64.b64decode(feed[0]["image"].encode('utf8'))
|
||||
data = np.fromstring(data, np.uint8)
|
||||
im = cv2.imdecode(data, cv2.IMREAD_COLOR)
|
||||
self.ori_h, self.ori_w, _ = im.shape
|
||||
det_img = self.det_preprocess(im)
|
||||
_, self.new_h, self.new_w = det_img.shape
|
||||
return {"image": det_img[np.newaxis, :].copy()}, ["concat_1.tmp_0"]
|
||||
|
||||
def postprocess(self, feed={}, fetch=[], fetch_map=None):
|
||||
det_out = fetch_map["concat_1.tmp_0"]
|
||||
ratio_list = [
|
||||
float(self.new_h) / self.ori_h, float(self.new_w) / self.ori_w
|
||||
]
|
||||
dt_boxes_list = self.post_func(det_out, [ratio_list])
|
||||
dt_boxes = self.filter_func(dt_boxes_list[0], [self.ori_h, self.ori_w])
|
||||
return {"dt_boxes": dt_boxes.tolist()}
|
||||
|
||||
|
||||
ocr_service = OCRService(name="ocr")
|
||||
ocr_service.load_model_config("ocr_det_model")
|
||||
ocr_service.set_gpus("0")
|
||||
ocr_service.prepare_server(workdir="workdir", port=9292, device="gpu", gpuid=0)
|
||||
ocr_service.init_det()
|
||||
ocr_service.run_debugger_service()
|
||||
ocr_service.run_web_service()
|
|
@ -0,0 +1,72 @@
|
|||
# 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.
|
||||
|
||||
from paddle_serving_client import Client
|
||||
import cv2
|
||||
import sys
|
||||
import numpy as np
|
||||
import os
|
||||
from paddle_serving_client import Client
|
||||
from paddle_serving_app.reader import Sequential, ResizeByFactor
|
||||
from paddle_serving_app.reader import Div, Normalize, Transpose
|
||||
from paddle_serving_app.reader import DBPostProcess, FilterBoxes
|
||||
from paddle_serving_server_gpu.web_service import WebService
|
||||
import time
|
||||
import re
|
||||
import base64
|
||||
|
||||
|
||||
class OCRService(WebService):
|
||||
def init_det(self):
|
||||
self.det_preprocess = Sequential([
|
||||
ResizeByFactor(32, 960), Div(255),
|
||||
Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]), Transpose(
|
||||
(2, 0, 1))
|
||||
])
|
||||
self.filter_func = FilterBoxes(10, 10)
|
||||
self.post_func = DBPostProcess({
|
||||
"thresh": 0.3,
|
||||
"box_thresh": 0.5,
|
||||
"max_candidates": 1000,
|
||||
"unclip_ratio": 1.5,
|
||||
"min_size": 3
|
||||
})
|
||||
|
||||
def preprocess(self, feed=[], fetch=[]):
|
||||
data = base64.b64decode(feed[0]["image"].encode('utf8'))
|
||||
data = np.fromstring(data, np.uint8)
|
||||
im = cv2.imdecode(data, cv2.IMREAD_COLOR)
|
||||
self.ori_h, self.ori_w, _ = im.shape
|
||||
det_img = self.det_preprocess(im)
|
||||
_, self.new_h, self.new_w = det_img.shape
|
||||
print(det_img)
|
||||
return {"image": det_img}, ["concat_1.tmp_0"]
|
||||
|
||||
def postprocess(self, feed={}, fetch=[], fetch_map=None):
|
||||
det_out = fetch_map["concat_1.tmp_0"]
|
||||
ratio_list = [
|
||||
float(self.new_h) / self.ori_h, float(self.new_w) / self.ori_w
|
||||
]
|
||||
dt_boxes_list = self.post_func(det_out, [ratio_list])
|
||||
dt_boxes = self.filter_func(dt_boxes_list[0], [self.ori_h, self.ori_w])
|
||||
return {"dt_boxes": dt_boxes.tolist()}
|
||||
|
||||
|
||||
ocr_service = OCRService(name="ocr")
|
||||
ocr_service.load_model_config("ocr_det_model")
|
||||
ocr_service.set_gpus("0")
|
||||
ocr_service.prepare_server(workdir="workdir", port=9292, device="gpu", gpuid=0)
|
||||
ocr_service.init_det()
|
||||
ocr_service.run_rpc_service()
|
||||
ocr_service.run_web_service()
|
|
@ -0,0 +1,103 @@
|
|||
# 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.
|
||||
|
||||
from paddle_serving_client import Client
|
||||
from paddle_serving_app.reader import OCRReader
|
||||
import cv2
|
||||
import sys
|
||||
import numpy as np
|
||||
import os
|
||||
from paddle_serving_client import Client
|
||||
from paddle_serving_app.reader import Sequential, URL2Image, ResizeByFactor
|
||||
from paddle_serving_app.reader import Div, Normalize, Transpose
|
||||
from paddle_serving_app.reader import DBPostProcess, FilterBoxes, GetRotateCropImage, SortedBoxes
|
||||
from paddle_serving_server_gpu.web_service import WebService
|
||||
from paddle_serving_app.local_predict import Debugger
|
||||
import time
|
||||
import re
|
||||
import base64
|
||||
|
||||
|
||||
class OCRService(WebService):
|
||||
def init_det_debugger(self, det_model_config):
|
||||
self.det_preprocess = Sequential([
|
||||
ResizeByFactor(32, 960), Div(255),
|
||||
Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]), Transpose(
|
||||
(2, 0, 1))
|
||||
])
|
||||
self.det_client = Debugger()
|
||||
self.det_client.load_model_config(
|
||||
det_model_config, gpu=True, profile=False)
|
||||
self.ocr_reader = OCRReader()
|
||||
|
||||
def preprocess(self, feed=[], fetch=[]):
|
||||
data = base64.b64decode(feed[0]["image"].encode('utf8'))
|
||||
data = np.fromstring(data, np.uint8)
|
||||
im = cv2.imdecode(data, cv2.IMREAD_COLOR)
|
||||
ori_h, ori_w, _ = im.shape
|
||||
det_img = self.det_preprocess(im)
|
||||
_, new_h, new_w = det_img.shape
|
||||
det_img = det_img[np.newaxis, :]
|
||||
det_img = det_img.copy()
|
||||
det_out = self.det_client.predict(
|
||||
feed={"image": det_img}, fetch=["concat_1.tmp_0"])
|
||||
filter_func = FilterBoxes(10, 10)
|
||||
post_func = DBPostProcess({
|
||||
"thresh": 0.3,
|
||||
"box_thresh": 0.5,
|
||||
"max_candidates": 1000,
|
||||
"unclip_ratio": 1.5,
|
||||
"min_size": 3
|
||||
})
|
||||
sorted_boxes = SortedBoxes()
|
||||
ratio_list = [float(new_h) / ori_h, float(new_w) / ori_w]
|
||||
dt_boxes_list = post_func(det_out["concat_1.tmp_0"], [ratio_list])
|
||||
dt_boxes = filter_func(dt_boxes_list[0], [ori_h, ori_w])
|
||||
dt_boxes = sorted_boxes(dt_boxes)
|
||||
get_rotate_crop_image = GetRotateCropImage()
|
||||
img_list = []
|
||||
max_wh_ratio = 0
|
||||
for i, dtbox in enumerate(dt_boxes):
|
||||
boximg = get_rotate_crop_image(im, dt_boxes[i])
|
||||
img_list.append(boximg)
|
||||
h, w = boximg.shape[0:2]
|
||||
wh_ratio = w * 1.0 / h
|
||||
max_wh_ratio = max(max_wh_ratio, wh_ratio)
|
||||
if len(img_list) == 0:
|
||||
return [], []
|
||||
_, w, h = self.ocr_reader.resize_norm_img(img_list[0],
|
||||
max_wh_ratio).shape
|
||||
imgs = np.zeros((len(img_list), 3, w, h)).astype('float32')
|
||||
for id, img in enumerate(img_list):
|
||||
norm_img = self.ocr_reader.resize_norm_img(img, max_wh_ratio)
|
||||
imgs[id] = norm_img
|
||||
feed = {"image": imgs.copy()}
|
||||
fetch = ["ctc_greedy_decoder_0.tmp_0", "softmax_0.tmp_0"]
|
||||
return feed, fetch
|
||||
|
||||
def postprocess(self, feed={}, fetch=[], fetch_map=None):
|
||||
rec_res = self.ocr_reader.postprocess(fetch_map, with_score=True)
|
||||
res_lst = []
|
||||
for res in rec_res:
|
||||
res_lst.append(res[0])
|
||||
res = {"res": res_lst}
|
||||
return res
|
||||
|
||||
|
||||
ocr_service = OCRService(name="ocr")
|
||||
ocr_service.load_model_config("ocr_rec_model")
|
||||
ocr_service.prepare_server(workdir="workdir", port=9292)
|
||||
ocr_service.init_det_debugger(det_model_config="ocr_det_model")
|
||||
ocr_service.run_debugger_service(gpu=True)
|
||||
ocr_service.run_web_service()
|
|
@ -0,0 +1,37 @@
|
|||
# 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.
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
import requests
|
||||
import json
|
||||
import cv2
|
||||
import base64
|
||||
import os, sys
|
||||
import time
|
||||
|
||||
def cv2_to_base64(image):
|
||||
#data = cv2.imencode('.jpg', image)[1]
|
||||
return base64.b64encode(image).decode(
|
||||
'utf8') #data.tostring()).decode('utf8')
|
||||
|
||||
headers = {"Content-type": "application/json"}
|
||||
url = "http://127.0.0.1:9292/ocr/prediction"
|
||||
test_img_dir = "../../doc/imgs/"
|
||||
for img_file in os.listdir(test_img_dir):
|
||||
with open(os.path.join(test_img_dir, img_file), 'rb') as file:
|
||||
image_data1 = file.read()
|
||||
image = cv2_to_base64(image_data1)
|
||||
data = {"feed": [{"image": image}], "fetch": ["res"]}
|
||||
r = requests.post(url=url, headers=headers, data=json.dumps(data))
|
||||
print(r.json())
|
|
@ -0,0 +1,99 @@
|
|||
# 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.
|
||||
|
||||
from paddle_serving_client import Client
|
||||
from paddle_serving_app.reader import OCRReader
|
||||
import cv2
|
||||
import sys
|
||||
import numpy as np
|
||||
import os
|
||||
from paddle_serving_client import Client
|
||||
from paddle_serving_app.reader import Sequential, URL2Image, ResizeByFactor
|
||||
from paddle_serving_app.reader import Div, Normalize, Transpose
|
||||
from paddle_serving_app.reader import DBPostProcess, FilterBoxes, GetRotateCropImage, SortedBoxes
|
||||
from paddle_serving_server_gpu.web_service import WebService
|
||||
import time
|
||||
import re
|
||||
import base64
|
||||
|
||||
|
||||
class OCRService(WebService):
|
||||
def init_det_client(self, det_port, det_client_config):
|
||||
self.det_preprocess = Sequential([
|
||||
ResizeByFactor(32, 960), Div(255),
|
||||
Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]), Transpose(
|
||||
(2, 0, 1))
|
||||
])
|
||||
self.det_client = Client()
|
||||
self.det_client.load_client_config(det_client_config)
|
||||
self.det_client.connect(["127.0.0.1:{}".format(det_port)])
|
||||
self.ocr_reader = OCRReader()
|
||||
|
||||
def preprocess(self, feed=[], fetch=[]):
|
||||
data = base64.b64decode(feed[0]["image"].encode('utf8'))
|
||||
data = np.fromstring(data, np.uint8)
|
||||
im = cv2.imdecode(data, cv2.IMREAD_COLOR)
|
||||
ori_h, ori_w, _ = im.shape
|
||||
det_img = self.det_preprocess(im)
|
||||
det_out = self.det_client.predict(
|
||||
feed={"image": det_img}, fetch=["concat_1.tmp_0"])
|
||||
_, new_h, new_w = det_img.shape
|
||||
filter_func = FilterBoxes(10, 10)
|
||||
post_func = DBPostProcess({
|
||||
"thresh": 0.3,
|
||||
"box_thresh": 0.5,
|
||||
"max_candidates": 1000,
|
||||
"unclip_ratio": 1.5,
|
||||
"min_size": 3
|
||||
})
|
||||
sorted_boxes = SortedBoxes()
|
||||
ratio_list = [float(new_h) / ori_h, float(new_w) / ori_w]
|
||||
dt_boxes_list = post_func(det_out["concat_1.tmp_0"], [ratio_list])
|
||||
dt_boxes = filter_func(dt_boxes_list[0], [ori_h, ori_w])
|
||||
dt_boxes = sorted_boxes(dt_boxes)
|
||||
get_rotate_crop_image = GetRotateCropImage()
|
||||
feed_list = []
|
||||
img_list = []
|
||||
max_wh_ratio = 0
|
||||
for i, dtbox in enumerate(dt_boxes):
|
||||
boximg = get_rotate_crop_image(im, dt_boxes[i])
|
||||
img_list.append(boximg)
|
||||
h, w = boximg.shape[0:2]
|
||||
wh_ratio = w * 1.0 / h
|
||||
max_wh_ratio = max(max_wh_ratio, wh_ratio)
|
||||
for img in img_list:
|
||||
norm_img = self.ocr_reader.resize_norm_img(img, max_wh_ratio)
|
||||
feed = {"image": norm_img}
|
||||
feed_list.append(feed)
|
||||
fetch = ["ctc_greedy_decoder_0.tmp_0", "softmax_0.tmp_0"]
|
||||
return feed_list, fetch
|
||||
|
||||
def postprocess(self, feed={}, fetch=[], fetch_map=None):
|
||||
rec_res = self.ocr_reader.postprocess(fetch_map, with_score=True)
|
||||
res_lst = []
|
||||
for res in rec_res:
|
||||
res_lst.append(res[0])
|
||||
res = {"res": res_lst}
|
||||
return res
|
||||
|
||||
|
||||
ocr_service = OCRService(name="ocr")
|
||||
ocr_service.load_model_config("ocr_rec_model")
|
||||
ocr_service.set_gpus("0")
|
||||
ocr_service.prepare_server(workdir="workdir", port=9292, device="gpu", gpuid=0)
|
||||
ocr_service.init_det_client(
|
||||
det_port=9293,
|
||||
det_client_config="ocr_det_client/serving_client_conf.prototxt")
|
||||
ocr_service.run_rpc_service()
|
||||
ocr_service.run_web_service()
|
|
@ -1,28 +1,83 @@
|
|||
# Paddle Serving 服务部署
|
||||
# Paddle Serving 服务部署(Beta)
|
||||
|
||||
本教程将介绍基于[Paddle Serving](https://github.com/PaddlePaddle/Serving)部署PaddleOCR在线预测服务的详细步骤。
|
||||
|
||||
## 快速启动服务
|
||||
|
||||
### 1. 准备环境
|
||||
我们先安装Paddle Serving相关组件
|
||||
我们推荐用户使用GPU来做Paddle Serving的OCR服务部署
|
||||
|
||||
**CUDA版本:9.0**
|
||||
**CUDNN版本:7.0**
|
||||
**操作系统版本:CentOS 6以上**
|
||||
|
||||
```
|
||||
#以下提供beta版本的paddle serving whl包,欢迎试用,正式版会在7月底正式上线
|
||||
wget --no-check-certificate https://paddle-serving.bj.bcebos.com/others/paddle_serving_server_gpu-0.3.2-py2-none-any.whl
|
||||
wget --no-check-certificate https://paddle-serving.bj.bcebos.com/others/paddle_serving_app-0.1.2-py2-none-any.whl
|
||||
wget --no-check-certificate https://paddle-serving.bj.bcebos.com/others/paddle_serving_client-0.3.2-cp27-none-any.whl
|
||||
python -m pip install paddle_serving_app-0.1.2-py2-none-any.whl paddle_serving_server_gpu-0.3.2-py2-none-any.whl paddle_serving_client-0.3.2-cp27-none-any.whl
|
||||
```
|
||||
|
||||
### 2. 模型转换
|
||||
可以使用`paddle_serving_app`提供的模型,执行下列命令
|
||||
```
|
||||
python -m paddle_serving_app.package --get_model ocr_rec
|
||||
tar -xzvf ocr_rec.tar.gz
|
||||
python -m paddle_serving_app.package --get_model ocr_det
|
||||
tar -xzvf ocr_det.tar.gz
|
||||
```
|
||||
执行上述命令会下载`db_crnn_mobile`的模型,如果想要下载规模更大的`db_crnn_server`模型,可以在下载预测模型并解压之后。参考[如何从Paddle保存的预测模型转为Paddle Serving格式可部署的模型](https://github.com/PaddlePaddle/Serving/blob/develop/doc/INFERENCE_TO_SERVING_CN.md)。
|
||||
|
||||
### 3. 启动服务
|
||||
启动服务可以根据实际需求选择启动`标准版`或者`快速版`,两种方式的对比如下表:
|
||||
|
||||
|版本|特点|适用场景|
|
||||
|-|-|-|
|
||||
|标准版|||
|
||||
|快速版|||
|
||||
|标准版|稳定性高,分布式部署|适用于吞吐量大,需要跨机房部署的情况|
|
||||
|快速版|部署方便,预测速度快|适用于对预测速度要求高,迭代速度快的场景|
|
||||
|
||||
#### 方式1. 启动标准版服务
|
||||
|
||||
```
|
||||
python -m paddle_serving_server_gpu.serve --model ocr_det_model --port 9293 --gpu_id 0
|
||||
python ocr_web_server.py
|
||||
```
|
||||
|
||||
#### 方式2. 启动快速版服务
|
||||
|
||||
```
|
||||
python ocr_local_server.py
|
||||
```
|
||||
|
||||
## 发送预测请求
|
||||
|
||||
```
|
||||
python ocr_web_client.py
|
||||
```
|
||||
|
||||
## 返回结果格式说明
|
||||
|
||||
返回结果是json格式
|
||||
```
|
||||
{u'result': {u'res': [u'\u571f\u5730\u6574\u6cbb\u4e0e\u571f\u58e4\u4fee\u590d\u7814\u7a76\u4e2d\u5fc3', u'\u534e\u5357\u519c\u4e1a\u5927\u5b661\u7d20\u56fe']}}
|
||||
```
|
||||
我们也可以打印结果json串中`res`字段的每一句话
|
||||
```
|
||||
土地整治与土壤修复研究中心
|
||||
华南农业大学1素图
|
||||
```
|
||||
|
||||
## 自定义修改服务逻辑
|
||||
|
||||
在`ocr_web_server.py`或是`ocr_local_server.py`当中的`preprocess`函数里面做了检测服务和识别服务的前处理,`postprocess`函数里面做了识别的后处理服务,可以在相应的函数中做修改。调用了`paddle_serving_app`库提供的常见CV模型的前处理/后处理库。
|
||||
|
||||
如果想要单独启动Paddle Serving的检测服务和识别服务,参见下列表格, 执行对应的脚本即可。
|
||||
|
||||
| 模型 | 标准版 | 快速版 |
|
||||
| ---- | ----------------- | ------------------- |
|
||||
| 检测 | det_web_server.py | det_local_server.py |
|
||||
| 识别 | rec_web_server.py | rec_local_server.py |
|
||||
|
||||
更多信息参见[Paddle Serving](https://github.com/PaddlePaddle/Serving)
|
||||
|
|
|
@ -0,0 +1,72 @@
|
|||
# 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.
|
||||
|
||||
from paddle_serving_client import Client
|
||||
from paddle_serving_app.reader import OCRReader
|
||||
import cv2
|
||||
import sys
|
||||
import numpy as np
|
||||
import os
|
||||
from paddle_serving_client import Client
|
||||
from paddle_serving_app.reader import Sequential, URL2Image, ResizeByFactor
|
||||
from paddle_serving_app.reader import Div, Normalize, Transpose
|
||||
from paddle_serving_app.reader import DBPostProcess, FilterBoxes, GetRotateCropImage, SortedBoxes
|
||||
from paddle_serving_server_gpu.web_service import WebService
|
||||
import time
|
||||
import re
|
||||
import base64
|
||||
|
||||
|
||||
class OCRService(WebService):
|
||||
def init_rec(self):
|
||||
self.ocr_reader = OCRReader()
|
||||
|
||||
def preprocess(self, feed=[], fetch=[]):
|
||||
img_list = []
|
||||
for feed_data in feed:
|
||||
data = base64.b64decode(feed_data["image"].encode('utf8'))
|
||||
data = np.fromstring(data, np.uint8)
|
||||
im = cv2.imdecode(data, cv2.IMREAD_COLOR)
|
||||
img_list.append(im)
|
||||
max_wh_ratio = 0
|
||||
for i, boximg in enumerate(img_list):
|
||||
h, w = boximg.shape[0:2]
|
||||
wh_ratio = w * 1.0 / h
|
||||
max_wh_ratio = max(max_wh_ratio, wh_ratio)
|
||||
_, w, h = self.ocr_reader.resize_norm_img(img_list[0],
|
||||
max_wh_ratio).shape
|
||||
imgs = np.zeros((len(img_list), 3, w, h)).astype('float32')
|
||||
for i, img in enumerate(img_list):
|
||||
norm_img = self.ocr_reader.resize_norm_img(img, max_wh_ratio)
|
||||
imgs[i] = norm_img
|
||||
feed = {"image": imgs.copy()}
|
||||
fetch = ["ctc_greedy_decoder_0.tmp_0", "softmax_0.tmp_0"]
|
||||
return feed, fetch
|
||||
|
||||
def postprocess(self, feed={}, fetch=[], fetch_map=None):
|
||||
rec_res = self.ocr_reader.postprocess(fetch_map, with_score=True)
|
||||
res_lst = []
|
||||
for res in rec_res:
|
||||
res_lst.append(res[0])
|
||||
res = {"res": res_lst}
|
||||
return res
|
||||
|
||||
|
||||
ocr_service = OCRService(name="ocr")
|
||||
ocr_service.load_model_config("ocr_rec_model")
|
||||
ocr_service.set_gpus("0")
|
||||
ocr_service.init_rec()
|
||||
ocr_service.prepare_server(workdir="workdir", port=9292, device="gpu", gpuid=0)
|
||||
ocr_service.run_debugger_service()
|
||||
ocr_service.run_web_service()
|
|
@ -0,0 +1,71 @@
|
|||
# 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.
|
||||
|
||||
from paddle_serving_client import Client
|
||||
from paddle_serving_app.reader import OCRReader
|
||||
import cv2
|
||||
import sys
|
||||
import numpy as np
|
||||
import os
|
||||
from paddle_serving_client import Client
|
||||
from paddle_serving_app.reader import Sequential, URL2Image, ResizeByFactor
|
||||
from paddle_serving_app.reader import Div, Normalize, Transpose
|
||||
from paddle_serving_app.reader import DBPostProcess, FilterBoxes, GetRotateCropImage, SortedBoxes
|
||||
from paddle_serving_server_gpu.web_service import WebService
|
||||
import time
|
||||
import re
|
||||
import base64
|
||||
|
||||
|
||||
class OCRService(WebService):
|
||||
def init_rec(self):
|
||||
self.ocr_reader = OCRReader()
|
||||
|
||||
def preprocess(self, feed=[], fetch=[]):
|
||||
# TODO: to handle batch rec images
|
||||
img_list = []
|
||||
for feed_data in feed:
|
||||
data = base64.b64decode(feed_data["image"].encode('utf8'))
|
||||
data = np.fromstring(data, np.uint8)
|
||||
im = cv2.imdecode(data, cv2.IMREAD_COLOR)
|
||||
img_list.append(im)
|
||||
feed_list = []
|
||||
max_wh_ratio = 0
|
||||
for i, boximg in enumerate(img_list):
|
||||
h, w = boximg.shape[0:2]
|
||||
wh_ratio = w * 1.0 / h
|
||||
max_wh_ratio = max(max_wh_ratio, wh_ratio)
|
||||
for img in img_list:
|
||||
norm_img = self.ocr_reader.resize_norm_img(img, max_wh_ratio)
|
||||
feed = {"image": norm_img}
|
||||
feed_list.append(feed)
|
||||
fetch = ["ctc_greedy_decoder_0.tmp_0", "softmax_0.tmp_0"]
|
||||
return feed_list, fetch
|
||||
|
||||
def postprocess(self, feed={}, fetch=[], fetch_map=None):
|
||||
rec_res = self.ocr_reader.postprocess(fetch_map, with_score=True)
|
||||
res_lst = []
|
||||
for res in rec_res:
|
||||
res_lst.append(res[0])
|
||||
res = {"res": res_lst}
|
||||
return res
|
||||
|
||||
|
||||
ocr_service = OCRService(name="ocr")
|
||||
ocr_service.load_model_config("ocr_rec_model")
|
||||
ocr_service.set_gpus("0")
|
||||
ocr_service.init_rec()
|
||||
ocr_service.prepare_server(workdir="workdir", port=9292, device="gpu", gpuid=0)
|
||||
ocr_service.run_rpc_service()
|
||||
ocr_service.run_web_service()
|
|
@ -80,3 +80,6 @@ git clone https://gitee.com/paddlepaddle/PaddleOCR
|
|||
cd PaddleOCR
|
||||
pip3 install -r requirments.txt
|
||||
```
|
||||
|
||||
注意,windows环境下,建议从[这里](https://www.lfd.uci.edu/~gohlke/pythonlibs/#shapely)下载shapely安装包完成安装,
|
||||
直接通过pip安装的shapely库可能出现`[winRrror 126] 找不到指定模块的问题`。
|
||||
|
|
|
@ -69,7 +69,7 @@ $ hub serving start --modules [Module1==Version1, Module2==Version2, ...] \
|
|||
|
||||
#### 方式2. 配置文件启动(支持CPU、GPU)
|
||||
**启动命令:**
|
||||
```hub serving start --config/-c config.json```
|
||||
```hub serving start -c config.json```
|
||||
|
||||
其中,`config.json`格式如下:
|
||||
```python
|
||||
|
|
|
@ -1,4 +1,5 @@
|
|||
# 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
|
||||
|
|
|
@ -82,3 +82,9 @@ git clone https://gitee.com/paddlepaddle/PaddleOCR
|
|||
cd PaddleOCR
|
||||
pip3 install -r requirments.txt
|
||||
```
|
||||
|
||||
If you getting this error `OSError: [WinError 126] The specified module could not be found` when you install shapely on windows.
|
||||
|
||||
Please try to download Shapely whl file using [http://www.lfd.uci.edu/~gohlke/pythonlibs/#shapely](http://www.lfd.uci.edu/~gohlke/pythonlibs/#shapely).
|
||||
|
||||
Reference: [Solve shapely installation on windows](https://stackoverflow.com/questions/44398265/install-shapely-oserror-winerror-126-the-specified-module-could-not-be-found)
|
||||
|
|
|
@ -1,5 +1,5 @@
|
|||
# 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 Chinese OCR model are provided.
|
||||
- 2020.7.15, Add several related datasets, data annotation and synthesis tools.
|
||||
|
|
|
@ -78,7 +78,7 @@ class MobileNetV3():
|
|||
|
||||
supported_scale = [0.35, 0.5, 0.75, 1.0, 1.25]
|
||||
assert self.scale in supported_scale, \
|
||||
"supported scale are {} but input scale is {}".format(supported_scale, scale)
|
||||
"supported scales are {} but input scale is {}".format(supported_scale, self.scale)
|
||||
|
||||
def __call__(self, input):
|
||||
scale = self.scale
|
||||
|
|
Loading…
Reference in New Issue