Commit 83303bc7 authored by LDOUBLEV's avatar LDOUBLEV
Browse files

fix conflicts

parents 3af943f3 af0bac58
package com.baidu.paddle.lite.demo.ocr;
import org.junit.Test;
import static org.junit.Assert.*;
/**
* Example local unit test, which will execute on the development machine (host).
*
* @see <a href="http://d.android.com/tools/testing">Testing documentation</a>
*/
public class ExampleUnitTest {
@Test
public void addition_isCorrect() {
assertEquals(4, 2 + 2);
}
}
\ No newline at end of file
// Top-level build file where you can add configuration options common to all sub-projects/modules.
buildscript {
repositories {
google()
jcenter()
}
dependencies {
classpath 'com.android.tools.build:gradle:4.1.2'
// NOTE: Do not place your application dependencies here; they belong
// in the individual module build.gradle files
}
}
allprojects {
repositories {
google()
jcenter()
}
}
task clean(type: Delete) {
delete rootProject.buildDir
}
# Project-wide Gradle settings.
# IDE (e.g. Android Studio) users:
# Gradle settings configured through the IDE *will override*
# any settings specified in this file.
# For more details on how to configure your build environment visit
# http://www.gradle.org/docs/current/userguide/build_environment.html
# Specifies the JVM arguments used for the daemon process.
# The setting is particularly useful for tweaking memory settings.
org.gradle.jvmargs=-Xmx1536m
# When configured, Gradle will run in incubating parallel mode.
# This option should only be used with decoupled projects. More details, visit
# http://www.gradle.org/docs/current/userguide/multi_project_builds.html#sec:decoupled_projects
# org.gradle.parallel=true
android.useAndroidX=true
#Thu Feb 04 20:28:08 CST 2021
distributionBase=GRADLE_USER_HOME
distributionPath=wrapper/dists
zipStoreBase=GRADLE_USER_HOME
zipStorePath=wrapper/dists
distributionUrl=https\://services.gradle.org/distributions/gradle-6.5-bin.zip
#!/usr/bin/env sh
##############################################################################
##
## Gradle start up script for UN*X
##
##############################################################################
# Attempt to set APP_HOME
# Resolve links: $0 may be a link
PRG="$0"
# Need this for relative symlinks.
while [ -h "$PRG" ] ; do
ls=`ls -ld "$PRG"`
link=`expr "$ls" : '.*-> \(.*\)$'`
if expr "$link" : '/.*' > /dev/null; then
PRG="$link"
else
PRG=`dirname "$PRG"`"/$link"
fi
done
SAVED="`pwd`"
cd "`dirname \"$PRG\"`/" >/dev/null
APP_HOME="`pwd -P`"
cd "$SAVED" >/dev/null
APP_NAME="Gradle"
APP_BASE_NAME=`basename "$0"`
# Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script.
DEFAULT_JVM_OPTS=""
# Use the maximum available, or set MAX_FD != -1 to use that value.
MAX_FD="maximum"
warn () {
echo "$*"
}
die () {
echo
echo "$*"
echo
exit 1
}
# OS specific support (must be 'true' or 'false').
cygwin=false
msys=false
darwin=false
nonstop=false
case "`uname`" in
CYGWIN* )
cygwin=true
;;
Darwin* )
darwin=true
;;
MINGW* )
msys=true
;;
NONSTOP* )
nonstop=true
;;
esac
CLASSPATH=$APP_HOME/gradle/wrapper/gradle-wrapper.jar
# Determine the Java command to use to start the JVM.
if [ -n "$JAVA_HOME" ] ; then
if [ -x "$JAVA_HOME/jre/sh/java" ] ; then
# IBM's JDK on AIX uses strange locations for the executables
JAVACMD="$JAVA_HOME/jre/sh/java"
else
JAVACMD="$JAVA_HOME/bin/java"
fi
if [ ! -x "$JAVACMD" ] ; then
die "ERROR: JAVA_HOME is set to an invalid directory: $JAVA_HOME
Please set the JAVA_HOME variable in your environment to match the
location of your Java installation."
fi
else
JAVACMD="java"
which java >/dev/null 2>&1 || die "ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH.
Please set the JAVA_HOME variable in your environment to match the
location of your Java installation."
fi
# Increase the maximum file descriptors if we can.
if [ "$cygwin" = "false" -a "$darwin" = "false" -a "$nonstop" = "false" ] ; then
MAX_FD_LIMIT=`ulimit -H -n`
if [ $? -eq 0 ] ; then
if [ "$MAX_FD" = "maximum" -o "$MAX_FD" = "max" ] ; then
MAX_FD="$MAX_FD_LIMIT"
fi
ulimit -n $MAX_FD
if [ $? -ne 0 ] ; then
warn "Could not set maximum file descriptor limit: $MAX_FD"
fi
else
warn "Could not query maximum file descriptor limit: $MAX_FD_LIMIT"
fi
fi
# For Darwin, add options to specify how the application appears in the dock
if $darwin; then
GRADLE_OPTS="$GRADLE_OPTS \"-Xdock:name=$APP_NAME\" \"-Xdock:icon=$APP_HOME/media/gradle.icns\""
fi
# For Cygwin, switch paths to Windows format before running java
if $cygwin ; then
APP_HOME=`cygpath --path --mixed "$APP_HOME"`
CLASSPATH=`cygpath --path --mixed "$CLASSPATH"`
JAVACMD=`cygpath --unix "$JAVACMD"`
# We build the pattern for arguments to be converted via cygpath
ROOTDIRSRAW=`find -L / -maxdepth 1 -mindepth 1 -type d 2>/dev/null`
SEP=""
for dir in $ROOTDIRSRAW ; do
ROOTDIRS="$ROOTDIRS$SEP$dir"
SEP="|"
done
OURCYGPATTERN="(^($ROOTDIRS))"
# Add a user-defined pattern to the cygpath arguments
if [ "$GRADLE_CYGPATTERN" != "" ] ; then
OURCYGPATTERN="$OURCYGPATTERN|($GRADLE_CYGPATTERN)"
fi
# Now convert the arguments - kludge to limit ourselves to /bin/sh
i=0
for arg in "$@" ; do
CHECK=`echo "$arg"|egrep -c "$OURCYGPATTERN" -`
CHECK2=`echo "$arg"|egrep -c "^-"` ### Determine if an option
if [ $CHECK -ne 0 ] && [ $CHECK2 -eq 0 ] ; then ### Added a condition
eval `echo args$i`=`cygpath --path --ignore --mixed "$arg"`
else
eval `echo args$i`="\"$arg\""
fi
i=$((i+1))
done
case $i in
(0) set -- ;;
(1) set -- "$args0" ;;
(2) set -- "$args0" "$args1" ;;
(3) set -- "$args0" "$args1" "$args2" ;;
(4) set -- "$args0" "$args1" "$args2" "$args3" ;;
(5) set -- "$args0" "$args1" "$args2" "$args3" "$args4" ;;
(6) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" ;;
(7) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" ;;
(8) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" "$args7" ;;
(9) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" "$args7" "$args8" ;;
esac
fi
# Escape application args
save () {
for i do printf %s\\n "$i" | sed "s/'/'\\\\''/g;1s/^/'/;\$s/\$/' \\\\/" ; done
echo " "
}
APP_ARGS=$(save "$@")
# Collect all arguments for the java command, following the shell quoting and substitution rules
eval set -- $DEFAULT_JVM_OPTS $JAVA_OPTS $GRADLE_OPTS "\"-Dorg.gradle.appname=$APP_BASE_NAME\"" -classpath "\"$CLASSPATH\"" org.gradle.wrapper.GradleWrapperMain "$APP_ARGS"
# by default we should be in the correct project dir, but when run from Finder on Mac, the cwd is wrong
if [ "$(uname)" = "Darwin" ] && [ "$HOME" = "$PWD" ]; then
cd "$(dirname "$0")"
fi
exec "$JAVACMD" "$@"
@if "%DEBUG%" == "" @echo off
@rem ##########################################################################
@rem
@rem Gradle startup script for Windows
@rem
@rem ##########################################################################
@rem Set local scope for the variables with windows NT shell
if "%OS%"=="Windows_NT" setlocal
set DIRNAME=%~dp0
if "%DIRNAME%" == "" set DIRNAME=.
set APP_BASE_NAME=%~n0
set APP_HOME=%DIRNAME%
@rem Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script.
set DEFAULT_JVM_OPTS=
@rem Find java.exe
if defined JAVA_HOME goto findJavaFromJavaHome
set JAVA_EXE=java.exe
%JAVA_EXE% -version >NUL 2>&1
if "%ERRORLEVEL%" == "0" goto init
echo.
echo ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH.
echo.
echo Please set the JAVA_HOME variable in your environment to match the
echo location of your Java installation.
goto fail
:findJavaFromJavaHome
set JAVA_HOME=%JAVA_HOME:"=%
set JAVA_EXE=%JAVA_HOME%/bin/java.exe
if exist "%JAVA_EXE%" goto init
echo.
echo ERROR: JAVA_HOME is set to an invalid directory: %JAVA_HOME%
echo.
echo Please set the JAVA_HOME variable in your environment to match the
echo location of your Java installation.
goto fail
:init
@rem Get command-line arguments, handling Windows variants
if not "%OS%" == "Windows_NT" goto win9xME_args
:win9xME_args
@rem Slurp the command line arguments.
set CMD_LINE_ARGS=
set _SKIP=2
:win9xME_args_slurp
if "x%~1" == "x" goto execute
set CMD_LINE_ARGS=%*
:execute
@rem Setup the command line
set CLASSPATH=%APP_HOME%\gradle\wrapper\gradle-wrapper.jar
@rem Execute Gradle
"%JAVA_EXE%" %DEFAULT_JVM_OPTS% %JAVA_OPTS% %GRADLE_OPTS% "-Dorg.gradle.appname=%APP_BASE_NAME%" -classpath "%CLASSPATH%" org.gradle.wrapper.GradleWrapperMain %CMD_LINE_ARGS%
:end
@rem End local scope for the variables with windows NT shell
if "%ERRORLEVEL%"=="0" goto mainEnd
:fail
rem Set variable GRADLE_EXIT_CONSOLE if you need the _script_ return code instead of
rem the _cmd.exe /c_ return code!
if not "" == "%GRADLE_EXIT_CONSOLE%" exit 1
exit /b 1
:mainEnd
if "%OS%"=="Windows_NT" endlocal
:omega
project(ocr_system CXX C) project(ppocr CXX C)
cmake_minimum_required(VERSION 3.14)
option(WITH_MKL "Compile demo with MKL/OpenBlas support, default use MKL." ON) 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_GPU "Compile demo with GPU/CPU, default use CPU." OFF)
...@@ -11,7 +12,7 @@ SET(CUDA_LIB "" CACHE PATH "Location of libraries") ...@@ -11,7 +12,7 @@ SET(CUDA_LIB "" CACHE PATH "Location of libraries")
SET(CUDNN_LIB "" CACHE PATH "Location of libraries") SET(CUDNN_LIB "" CACHE PATH "Location of libraries")
SET(TENSORRT_DIR "" CACHE PATH "Compile demo with TensorRT") SET(TENSORRT_DIR "" CACHE PATH "Compile demo with TensorRT")
set(DEMO_NAME "ocr_system") set(DEMO_NAME "ppocr")
macro(safe_set_static_flag) macro(safe_set_static_flag)
...@@ -38,10 +39,8 @@ endif() ...@@ -38,10 +39,8 @@ endif()
if (WIN32) if (WIN32)
include_directories("${PADDLE_LIB}/paddle/fluid/inference")
include_directories("${PADDLE_LIB}/paddle/include") include_directories("${PADDLE_LIB}/paddle/include")
link_directories("${PADDLE_LIB}/paddle/lib") link_directories("${PADDLE_LIB}/paddle/lib")
link_directories("${PADDLE_LIB}/paddle/fluid/inference")
find_package(OpenCV REQUIRED PATHS ${OPENCV_DIR}/build/ NO_DEFAULT_PATH) find_package(OpenCV REQUIRED PATHS ${OPENCV_DIR}/build/ NO_DEFAULT_PATH)
else () else ()
...@@ -208,9 +207,12 @@ endif() ...@@ -208,9 +207,12 @@ endif()
set(DEPS ${DEPS} ${OpenCV_LIBS}) set(DEPS ${DEPS} ${OpenCV_LIBS})
include(FetchContent)
include(external-cmake/auto-log.cmake)
include_directories(${FETCHCONTENT_BASE_DIR}/extern_autolog-src)
AUX_SOURCE_DIRECTORY(./src SRCS) AUX_SOURCE_DIRECTORY(./src SRCS)
add_executable(${DEMO_NAME} ${SRCS}) add_executable(${DEMO_NAME} ${SRCS})
target_link_libraries(${DEMO_NAME} ${DEPS}) target_link_libraries(${DEMO_NAME} ${DEPS})
if (WIN32 AND WITH_MKL) if (WIN32 AND WITH_MKL)
......
This image diff could not be displayed because it is too large. You can view the blob instead.
...@@ -5,20 +5,20 @@ PaddleOCR在Windows 平台下基于`Visual Studio 2019 Community` 进行了测 ...@@ -5,20 +5,20 @@ PaddleOCR在Windows 平台下基于`Visual Studio 2019 Community` 进行了测
## 前置条件 ## 前置条件
* Visual Studio 2019 * 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) * CUDA 10.2,cudnn 7+ (仅在使用GPU版本的预测库时需要)
* CMake 3.0+ * 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。 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** **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 ### Step1: 下载PaddlePaddle C++ 预测库 paddle_inference
PaddlePaddle C++ 预测库针对不同的`CPU``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/guides/05_inference_deployment/inference/windows_cpp_inference.html) PaddlePaddle C++ 预测库针对不同的`CPU``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://paddleinference.paddlepaddle.org.cn/user_guides/download_lib.html#windows)
解压后`D:\projects\fluid_inference`目录包含内容为: 解压后`D:\projects\paddle_inference`目录包含内容为:
``` ```
fluid_inference paddle_inference
├── paddle # paddle核心库和头文件 ├── paddle # paddle核心库和头文件
| |
├── third_party # 第三方依赖库和头文件 ├── third_party # 第三方依赖库和头文件
...@@ -46,13 +46,13 @@ fluid_inference ...@@ -46,13 +46,13 @@ fluid_inference
![step2.2](https://paddleseg.bj.bcebos.com/inference/vs2019_step3.png) ![step2.2](https://paddleseg.bj.bcebos.com/inference/vs2019_step3.png)
3. 点击:`项目`->`cpp_inference_demo的CMake设置` 3. 点击:`项目`->`CMake设置`
![step3](https://paddleseg.bj.bcebos.com/inference/vs2019_step4.png) ![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 4. 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**): 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):
| 参数名 | 含义 | | 参数名 | 含义 |
| ---- | ---- | | ---- | ---- |
...@@ -67,6 +67,11 @@ fluid_inference ...@@ -67,6 +67,11 @@ fluid_inference
![step4](https://paddleseg.bj.bcebos.com/inference/vs2019_step5.png) ![step4](https://paddleseg.bj.bcebos.com/inference/vs2019_step5.png)
下面给出with GPU的配置示例:
![step5](./vs2019_build_withgpu_config.png)
**注意:**
CMAKE_BACKWARDS的版本要根据平台安装cmake的版本进行设置。
**设置完成后**, 点击上图中`保存并生成CMake缓存以加载变量` **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` 5. 点击`生成`->`全部生成`
...@@ -74,22 +79,34 @@ fluid_inference ...@@ -74,22 +79,34 @@ fluid_inference
![step6](https://paddleseg.bj.bcebos.com/inference/vs2019_step6.png) ![step6](https://paddleseg.bj.bcebos.com/inference/vs2019_step6.png)
### Step4: 预测及可视化 ### Step4: 预测
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 上述`Visual Studio 2019`编译产出的可执行文件在`out\build\x64-Release\Release`目录下,打开`cmd`,并切换到`D:\projects\PaddleOCR\deploy\cpp_infer\`
``` ```
cd D:\projects\PaddleOCR\deploy\cpp_infer\out\build\x64-Release cd D:\projects\PaddleOCR\deploy\cpp_infer
``` ```
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 可执行文件`ppocr.exe`即为样例的预测程序,其主要使用方法如下,更多使用方法可以参考[说明文档](../readme.md)`运行demo`部分。
```shell ```shell
#预测图片 `D:\projects\PaddleOCR\doc\imgs\10.jpg` #识别中文图片 `D:\projects\PaddleOCR\doc\imgs_words\ch\`
.\ocr_system.exe D:\projects\PaddleOCR\deploy\cpp_infer\tools\config.txt D:\projects\PaddleOCR\doc\imgs\10.jpg .\out\build\x64-Release\Release\ppocr.exe rec --rec_model_dir=D:\projects\PaddleOCR\ch_ppocr_mobile_v2.0_rec_infer --image_dir=D:\projects\PaddleOCR\doc\imgs_words\ch\
#识别英文图片 'D:\projects\PaddleOCR\doc\imgs_words\en\'
.\out\build\x64-Release\Release\ppocr.exe rec --rec_model_dir=D:\projects\PaddleOCR\inference\rec_mv3crnn --image_dir=D:\projects\PaddleOCR\doc\imgs_words\en\ --char_list_file=D:\projects\PaddleOCR\ppocr\utils\dict\en_dict.txt
``` ```
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。
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,第三个参数为配置文本识别的字典。
### 注意 ### FQA
* 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)。 * 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)。
* 编译时,如果报错`错误:C1083 无法打开包括文件:"dirent.h":No such file or directory`,可以参考该[文档](https://blog.csdn.net/Dora_blank/article/details/117740837#41_C1083_direnthNo_such_file_or_directory_54),新建`dirent.h`文件,并添加到`utility.cpp`的头文件引用中。同时修改`utility.cpp`70行:`lstat`改成`stat`。
* 编译时,如果报错`Autolog未定义`,新建`autolog.h`文件,内容为:[autolog.h](https://github.com/LDOUBLEV/AutoLog/blob/main/auto_log/autolog.h),并添加到`main.cpp`的头文件引用中,再次编译。
* 运行时,如果弹窗报错找不到`paddle_inference.dll`或者`openblas.dll`,在`D:\projects\paddle_inference`预测库内找到这两个文件,复制到`D:\projects\PaddleOCR\deploy\cpp_infer\out\build\x64-Release\Release`目录下。不用重新编译,再次运行即可。
* 运行时,弹窗报错提示`应用程序无法正常启动(0xc0000142)`,并且`cmd`窗口内提示`You are using Paddle compiled with TensorRT, but TensorRT dynamic library is not found.`,把tensort目录下的lib里面的所有dll文件复制到release目录下,再次运行即可。
find_package(Git REQUIRED)
include(FetchContent)
set(FETCHCONTENT_BASE_DIR "${CMAKE_CURRENT_BINARY_DIR}/third-party")
FetchContent_Declare(
extern_Autolog
PREFIX autolog
GIT_REPOSITORY https://github.com/LDOUBLEV/AutoLog.git
GIT_TAG main
)
FetchContent_MakeAvailable(extern_Autolog)
...@@ -668,7 +668,7 @@ void DisposeOutPts(OutPt *&pp) { ...@@ -668,7 +668,7 @@ void DisposeOutPts(OutPt *&pp) {
//------------------------------------------------------------------------------ //------------------------------------------------------------------------------
inline void InitEdge(TEdge *e, TEdge *eNext, TEdge *ePrev, const IntPoint &Pt) { inline void InitEdge(TEdge *e, TEdge *eNext, TEdge *ePrev, const IntPoint &Pt) {
std::memset(e, 0, sizeof(TEdge)); std::memset(e, int(0), sizeof(TEdge));
e->Next = eNext; e->Next = eNext;
e->Prev = ePrev; e->Prev = ePrev;
e->Curr = Pt; e->Curr = Pt;
...@@ -1895,17 +1895,17 @@ void Clipper::InsertLocalMinimaIntoAEL(const cInt botY) { ...@@ -1895,17 +1895,17 @@ void Clipper::InsertLocalMinimaIntoAEL(const cInt botY) {
TEdge *rb = lm->RightBound; TEdge *rb = lm->RightBound;
OutPt *Op1 = 0; OutPt *Op1 = 0;
if (!lb) { if (!lb || !rb) {
// nb: don't insert LB into either AEL or SEL // nb: don't insert LB into either AEL or SEL
InsertEdgeIntoAEL(rb, 0); InsertEdgeIntoAEL(rb, 0);
SetWindingCount(*rb); SetWindingCount(*rb);
if (IsContributing(*rb)) if (IsContributing(*rb))
Op1 = AddOutPt(rb, rb->Bot); Op1 = AddOutPt(rb, rb->Bot);
} else if (!rb) { //} else if (!rb) {
InsertEdgeIntoAEL(lb, 0); // InsertEdgeIntoAEL(lb, 0);
SetWindingCount(*lb); // SetWindingCount(*lb);
if (IsContributing(*lb)) // if (IsContributing(*lb))
Op1 = AddOutPt(lb, lb->Bot); // Op1 = AddOutPt(lb, lb->Bot);
InsertScanbeam(lb->Top.Y); InsertScanbeam(lb->Top.Y);
} else { } else {
InsertEdgeIntoAEL(lb, 0); InsertEdgeIntoAEL(lb, 0);
...@@ -2547,13 +2547,13 @@ void Clipper::ProcessHorizontal(TEdge *horzEdge) { ...@@ -2547,13 +2547,13 @@ void Clipper::ProcessHorizontal(TEdge *horzEdge) {
if (dir == dLeftToRight) { if (dir == dLeftToRight) {
maxIt = m_Maxima.begin(); maxIt = m_Maxima.begin();
while (maxIt != m_Maxima.end() && *maxIt <= horzEdge->Bot.X) while (maxIt != m_Maxima.end() && *maxIt <= horzEdge->Bot.X)
maxIt++; ++maxIt;
if (maxIt != m_Maxima.end() && *maxIt >= eLastHorz->Top.X) if (maxIt != m_Maxima.end() && *maxIt >= eLastHorz->Top.X)
maxIt = m_Maxima.end(); maxIt = m_Maxima.end();
} else { } else {
maxRit = m_Maxima.rbegin(); maxRit = m_Maxima.rbegin();
while (maxRit != m_Maxima.rend() && *maxRit > horzEdge->Bot.X) while (maxRit != m_Maxima.rend() && *maxRit > horzEdge->Bot.X)
maxRit++; ++maxRit;
if (maxRit != m_Maxima.rend() && *maxRit <= eLastHorz->Top.X) if (maxRit != m_Maxima.rend() && *maxRit <= eLastHorz->Top.X)
maxRit = m_Maxima.rend(); maxRit = m_Maxima.rend();
} }
...@@ -2576,13 +2576,13 @@ void Clipper::ProcessHorizontal(TEdge *horzEdge) { ...@@ -2576,13 +2576,13 @@ void Clipper::ProcessHorizontal(TEdge *horzEdge) {
while (maxIt != m_Maxima.end() && *maxIt < e->Curr.X) { while (maxIt != m_Maxima.end() && *maxIt < e->Curr.X) {
if (horzEdge->OutIdx >= 0 && !IsOpen) if (horzEdge->OutIdx >= 0 && !IsOpen)
AddOutPt(horzEdge, IntPoint(*maxIt, horzEdge->Bot.Y)); AddOutPt(horzEdge, IntPoint(*maxIt, horzEdge->Bot.Y));
maxIt++; ++maxIt;
} }
} else { } else {
while (maxRit != m_Maxima.rend() && *maxRit > e->Curr.X) { while (maxRit != m_Maxima.rend() && *maxRit > e->Curr.X) {
if (horzEdge->OutIdx >= 0 && !IsOpen) if (horzEdge->OutIdx >= 0 && !IsOpen)
AddOutPt(horzEdge, IntPoint(*maxRit, horzEdge->Bot.Y)); AddOutPt(horzEdge, IntPoint(*maxRit, horzEdge->Bot.Y));
maxRit++; ++maxRit;
} }
} }
}; };
......
...@@ -31,6 +31,8 @@ ...@@ -31,6 +31,8 @@
* * * *
*******************************************************************************/ *******************************************************************************/
#pragma once
#ifndef clipper_hpp #ifndef clipper_hpp
#define clipper_hpp #define clipper_hpp
......
// 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.
#pragma once
#include <iomanip>
#include <iostream>
#include <map>
#include <ostream>
#include <string>
#include <vector>
#include "include/utility.h"
namespace PaddleOCR {
class OCRConfig {
public:
explicit OCRConfig(const std::string &config_file) {
config_map_ = LoadConfig(config_file);
this->use_gpu = bool(stoi(config_map_["use_gpu"]));
this->gpu_id = stoi(config_map_["gpu_id"]);
this->gpu_mem = stoi(config_map_["gpu_mem"]);
this->cpu_math_library_num_threads =
stoi(config_map_["cpu_math_library_num_threads"]);
this->use_mkldnn = bool(stoi(config_map_["use_mkldnn"]));
this->max_side_len = stoi(config_map_["max_side_len"]);
this->det_db_thresh = stod(config_map_["det_db_thresh"]);
this->det_db_box_thresh = stod(config_map_["det_db_box_thresh"]);
this->det_db_unclip_ratio = stod(config_map_["det_db_unclip_ratio"]);
this->det_model_dir.assign(config_map_["det_model_dir"]);
this->rec_model_dir.assign(config_map_["rec_model_dir"]);
this->char_list_file.assign(config_map_["char_list_file"]);
this->use_angle_cls = bool(stoi(config_map_["use_angle_cls"]));
this->cls_model_dir.assign(config_map_["cls_model_dir"]);
this->cls_thresh = stod(config_map_["cls_thresh"]);
this->visualize = bool(stoi(config_map_["visualize"]));
this->use_tensorrt = bool(stoi(config_map_["use_tensorrt"]));
this->use_fp16 = bool(stod(config_map_["use_fp16"]));
}
bool use_gpu = false;
int gpu_id = 0;
int gpu_mem = 4000;
int cpu_math_library_num_threads = 1;
bool use_mkldnn = false;
int max_side_len = 960;
double det_db_thresh = 0.3;
double det_db_box_thresh = 0.5;
double det_db_unclip_ratio = 2.0;
std::string det_model_dir;
std::string rec_model_dir;
bool use_angle_cls;
std::string char_list_file;
std::string cls_model_dir;
double cls_thresh;
bool visualize = true;
bool use_tensorrt = false;
bool use_fp16 = false;
void PrintConfigInfo();
private:
// Load configuration
std::map<std::string, std::string> LoadConfig(const std::string &config_file);
std::vector<std::string> split(const std::string &str,
const std::string &delim);
std::map<std::string, std::string> config_map_;
};
} // namespace PaddleOCR
...@@ -12,6 +12,8 @@ ...@@ -12,6 +12,8 @@
// See the License for the specific language governing permissions and // See the License for the specific language governing permissions and
// limitations under the License. // limitations under the License.
#pragma once
#include "opencv2/core.hpp" #include "opencv2/core.hpp"
#include "opencv2/imgcodecs.hpp" #include "opencv2/imgcodecs.hpp"
#include "opencv2/imgproc.hpp" #include "opencv2/imgproc.hpp"
...@@ -40,7 +42,7 @@ public: ...@@ -40,7 +42,7 @@ public:
const int &gpu_id, const int &gpu_mem, const int &gpu_id, const int &gpu_mem,
const int &cpu_math_library_num_threads, const int &cpu_math_library_num_threads,
const bool &use_mkldnn, const double &cls_thresh, const bool &use_mkldnn, const double &cls_thresh,
const bool &use_tensorrt, const bool &use_fp16) { const bool &use_tensorrt, const std::string &precision) {
this->use_gpu_ = use_gpu; this->use_gpu_ = use_gpu;
this->gpu_id_ = gpu_id; this->gpu_id_ = gpu_id;
this->gpu_mem_ = gpu_mem; this->gpu_mem_ = gpu_mem;
...@@ -49,7 +51,7 @@ public: ...@@ -49,7 +51,7 @@ public:
this->cls_thresh = cls_thresh; this->cls_thresh = cls_thresh;
this->use_tensorrt_ = use_tensorrt; this->use_tensorrt_ = use_tensorrt;
this->use_fp16_ = use_fp16; this->precision_ = precision;
LoadModel(model_dir); LoadModel(model_dir);
} }
...@@ -73,7 +75,7 @@ private: ...@@ -73,7 +75,7 @@ private:
std::vector<float> scale_ = {1 / 0.5f, 1 / 0.5f, 1 / 0.5f}; std::vector<float> scale_ = {1 / 0.5f, 1 / 0.5f, 1 / 0.5f};
bool is_scale_ = true; bool is_scale_ = true;
bool use_tensorrt_ = false; bool use_tensorrt_ = false;
bool use_fp16_ = false; std::string precision_ = "fp32";
// pre-process // pre-process
ClsResizeImg resize_op_; ClsResizeImg resize_op_;
Normalize normalize_op_; Normalize normalize_op_;
......
...@@ -44,8 +44,9 @@ public: ...@@ -44,8 +44,9 @@ public:
const bool &use_mkldnn, const int &max_side_len, const bool &use_mkldnn, const int &max_side_len,
const double &det_db_thresh, const double &det_db_thresh,
const double &det_db_box_thresh, const double &det_db_box_thresh,
const double &det_db_unclip_ratio, const bool &visualize, const double &det_db_unclip_ratio,
const bool &use_tensorrt, const bool &use_fp16) { const bool &use_polygon_score, const bool &visualize,
const bool &use_tensorrt, const std::string &precision) {
this->use_gpu_ = use_gpu; this->use_gpu_ = use_gpu;
this->gpu_id_ = gpu_id; this->gpu_id_ = gpu_id;
this->gpu_mem_ = gpu_mem; this->gpu_mem_ = gpu_mem;
...@@ -57,10 +58,11 @@ public: ...@@ -57,10 +58,11 @@ public:
this->det_db_thresh_ = det_db_thresh; this->det_db_thresh_ = det_db_thresh;
this->det_db_box_thresh_ = det_db_box_thresh; this->det_db_box_thresh_ = det_db_box_thresh;
this->det_db_unclip_ratio_ = det_db_unclip_ratio; this->det_db_unclip_ratio_ = det_db_unclip_ratio;
this->use_polygon_score_ = use_polygon_score;
this->visualize_ = visualize; this->visualize_ = visualize;
this->use_tensorrt_ = use_tensorrt; this->use_tensorrt_ = use_tensorrt;
this->use_fp16_ = use_fp16; this->precision_ = precision;
LoadModel(model_dir); LoadModel(model_dir);
} }
...@@ -69,7 +71,7 @@ public: ...@@ -69,7 +71,7 @@ public:
void LoadModel(const std::string &model_dir); void LoadModel(const std::string &model_dir);
// Run predictor // Run predictor
void Run(cv::Mat &img, std::vector<std::vector<std::vector<int>>> &boxes); void Run(cv::Mat &img, std::vector<std::vector<std::vector<int>>> &boxes, std::vector<double> *times);
private: private:
std::shared_ptr<Predictor> predictor_; std::shared_ptr<Predictor> predictor_;
...@@ -85,10 +87,11 @@ private: ...@@ -85,10 +87,11 @@ private:
double det_db_thresh_ = 0.3; double det_db_thresh_ = 0.3;
double det_db_box_thresh_ = 0.5; double det_db_box_thresh_ = 0.5;
double det_db_unclip_ratio_ = 2.0; double det_db_unclip_ratio_ = 2.0;
bool use_polygon_score_ = false;
bool visualize_ = true; bool visualize_ = true;
bool use_tensorrt_ = false; bool use_tensorrt_ = false;
bool use_fp16_ = false; std::string precision_ = "fp32";
std::vector<float> mean_ = {0.485f, 0.456f, 0.406f}; std::vector<float> mean_ = {0.485f, 0.456f, 0.406f};
std::vector<float> scale_ = {1 / 0.229f, 1 / 0.224f, 1 / 0.225f}; std::vector<float> scale_ = {1 / 0.229f, 1 / 0.224f, 1 / 0.225f};
......
...@@ -12,6 +12,8 @@ ...@@ -12,6 +12,8 @@
// See the License for the specific language governing permissions and // See the License for the specific language governing permissions and
// limitations under the License. // limitations under the License.
#pragma once
#include "opencv2/core.hpp" #include "opencv2/core.hpp"
#include "opencv2/imgcodecs.hpp" #include "opencv2/imgcodecs.hpp"
#include "opencv2/imgproc.hpp" #include "opencv2/imgproc.hpp"
...@@ -42,14 +44,14 @@ public: ...@@ -42,14 +44,14 @@ public:
const int &gpu_id, const int &gpu_mem, const int &gpu_id, const int &gpu_mem,
const int &cpu_math_library_num_threads, const int &cpu_math_library_num_threads,
const bool &use_mkldnn, const string &label_path, const bool &use_mkldnn, const string &label_path,
const bool &use_tensorrt, const bool &use_fp16) { const bool &use_tensorrt, const std::string &precision) {
this->use_gpu_ = use_gpu; this->use_gpu_ = use_gpu;
this->gpu_id_ = gpu_id; this->gpu_id_ = gpu_id;
this->gpu_mem_ = gpu_mem; this->gpu_mem_ = gpu_mem;
this->cpu_math_library_num_threads_ = cpu_math_library_num_threads; this->cpu_math_library_num_threads_ = cpu_math_library_num_threads;
this->use_mkldnn_ = use_mkldnn; this->use_mkldnn_ = use_mkldnn;
this->use_tensorrt_ = use_tensorrt; this->use_tensorrt_ = use_tensorrt;
this->use_fp16_ = use_fp16; this->precision_ = precision;
this->label_list_ = Utility::ReadDict(label_path); this->label_list_ = Utility::ReadDict(label_path);
this->label_list_.insert(this->label_list_.begin(), this->label_list_.insert(this->label_list_.begin(),
...@@ -62,8 +64,7 @@ public: ...@@ -62,8 +64,7 @@ public:
// Load Paddle inference model // Load Paddle inference model
void LoadModel(const std::string &model_dir); void LoadModel(const std::string &model_dir);
void Run(std::vector<std::vector<std::vector<int>>> boxes, cv::Mat &img, void Run(cv::Mat &img, std::vector<double> *times);
Classifier *cls);
private: private:
std::shared_ptr<Predictor> predictor_; std::shared_ptr<Predictor> predictor_;
...@@ -80,7 +81,7 @@ private: ...@@ -80,7 +81,7 @@ private:
std::vector<float> scale_ = {1 / 0.5f, 1 / 0.5f, 1 / 0.5f}; std::vector<float> scale_ = {1 / 0.5f, 1 / 0.5f, 1 / 0.5f};
bool is_scale_ = true; bool is_scale_ = true;
bool use_tensorrt_ = false; bool use_tensorrt_ = false;
bool use_fp16_ = false; std::string precision_ = "fp32";
// pre-process // pre-process
CrnnResizeImg resize_op_; CrnnResizeImg resize_op_;
Normalize normalize_op_; Normalize normalize_op_;
...@@ -89,9 +90,6 @@ private: ...@@ -89,9 +90,6 @@ private:
// post-process // post-process
PostProcessor post_processor_; PostProcessor post_processor_;
cv::Mat GetRotateCropImage(const cv::Mat &srcimage,
std::vector<std::vector<int>> box);
}; // class CrnnRecognizer }; // class CrnnRecognizer
} // namespace PaddleOCR } // namespace PaddleOCR
...@@ -51,10 +51,12 @@ public: ...@@ -51,10 +51,12 @@ public:
float &ssid); float &ssid);
float BoxScoreFast(std::vector<std::vector<float>> box_array, cv::Mat pred); float BoxScoreFast(std::vector<std::vector<float>> box_array, cv::Mat pred);
float PolygonScoreAcc(std::vector<cv::Point> contour, cv::Mat pred);
std::vector<std::vector<std::vector<int>>> std::vector<std::vector<std::vector<int>>>
BoxesFromBitmap(const cv::Mat pred, const cv::Mat bitmap, BoxesFromBitmap(const cv::Mat pred, const cv::Mat bitmap,
const float &box_thresh, const float &det_db_unclip_ratio); const float &box_thresh, const float &det_db_unclip_ratio,
const bool &use_polygon_score);
std::vector<std::vector<std::vector<int>>> std::vector<std::vector<std::vector<int>>>
FilterTagDetRes(std::vector<std::vector<std::vector<int>>> boxes, FilterTagDetRes(std::vector<std::vector<std::vector<int>>> boxes,
......
...@@ -44,6 +44,12 @@ public: ...@@ -44,6 +44,12 @@ public:
inline static size_t argmax(ForwardIterator first, ForwardIterator last) { inline static size_t argmax(ForwardIterator first, ForwardIterator last) {
return std::distance(first, std::max_element(first, last)); return std::distance(first, std::max_element(first, last));
} }
static void GetAllFiles(const char *dir_name,
std::vector<std::string> &all_inputs);
static cv::Mat GetRotateCropImage(const cv::Mat &srcimage,
std::vector<std::vector<int>> box);
}; };
} // namespace PaddleOCR } // namespace PaddleOCR
\ No newline at end of file
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