├── .gitignore
├── README.md
├── android
    ├── AndroidManifest.xml
    ├── build.gradle
    ├── gradle
    │   └── wrapper
    │   │   ├── gradle-wrapper.jar
    │   │   └── gradle-wrapper.properties
    ├── gradlew
    ├── gradlew.bat
    ├── res
    │   ├── drawable-hdpi
    │   │   └── icon.png
    │   ├── drawable-ldpi
    │   │   └── icon.png
    │   ├── drawable-mdpi
    │   │   └── icon.png
    │   └── values
    │   │   └── libs.xml
    └── src
    │   └── com
    │       └── amin
    │           └── QtAndroidGallery
    │               └── QtAndroidGallery.java
├── assets
    ├── ManjaroMix.qss
    ├── ai.png
    └── icon.png
├── docs
    ├── demo1.gif
    ├── demo2.gif
    ├── p1.png
    ├── p2.png
    └── p3.png
├── main.cpp
├── model
    └── modules_ncnn.py
├── myqlabel.cpp
├── myqlabel.h
├── myvideosurface.cpp
├── myvideosurface.h
├── pic.qrc
├── widget.cpp
├── widget.h
├── widget.ui
├── yolo.cpp
├── yolo.h
└── yolov8.pro


/.gitignore:
--------------------------------------------------------------------------------
 1 | # This file is used to ignore files which are generated
 2 | # ----------------------------------------------------------------------------
 3 | 
 4 | *~
 5 | *.autosave
 6 | *.a
 7 | *.core
 8 | *.moc
 9 | *.o
10 | *.obj
11 | *.orig
12 | *.rej
13 | *.so
14 | *.so.*
15 | *_pch.h.cpp
16 | *_resource.rc
17 | *.qm
18 | .#*
19 | *.*#
20 | core
21 | !core/
22 | tags
23 | .DS_Store
24 | .directory
25 | *.debug
26 | Makefile*
27 | *.prl
28 | *.app
29 | moc_*.cpp
30 | ui_*.h
31 | qrc_*.cpp
32 | Thumbs.db
33 | *.res
34 | *.rc
35 | /.qmake.cache
36 | /.qmake.stash
37 | 
38 | # qtcreator generated files
39 | *.pro.user*
40 | 
41 | # xemacs temporary files
42 | *.flc
43 | 
44 | # Vim temporary files
45 | .*.swp
46 | 
47 | # Visual Studio generated files
48 | *.ib_pdb_index
49 | *.idb
50 | *.ilk
51 | *.pdb
52 | *.sln
53 | *.suo
54 | *.vcproj
55 | *vcproj.*.*.user
56 | *.ncb
57 | *.sdf
58 | *.opensdf
59 | *.vcxproj
60 | *vcxproj.*
61 | 
62 | # MinGW generated files
63 | *.Debug
64 | *.Release
65 | 
66 | # Python byte code
67 | *.pyc
68 | 
69 | # Binaries
70 | # --------
71 | *.dll
72 | *.exe
73 | 
74 | 


--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
 1 | ## YOLOv8 安卓手机部署
 2 | 
 3 | 本项目将YOLOv8s通过QT和NCNN部署到小米手机上运行
 4 | 
 5 | ### 1.模型转换的Trick
 6 | 
 7 | + 修改`ltralytics\nn\modules.py`
 8 | 
 9 | 这一部分主要涉及两个方面的修改一个`c2f bloack`中将split改为slice(**该过程不是必要的**)，另一个是去掉detect的头（加上detect的头可以转出来，但是ncnn转出的模型维度不正确，detect的head将在ncnn中通过自定义layer实现）
10 | 
11 | <div align=center>
12 |     <img src="./docs/p1.png"/>
13 | </div>
14 | 
15 | <div align=center>
16 |     <img src="./docs/p2.png"/>
17 | </div>
18 | 
19 | + 转onnx
20 | 
21 | 请参考： https://github.com/DataXujing/YOLOv8
22 | 
23 | + 使用ONNX2NCNN生成ncnn支持的模型
24 | 
25 | ```
26 | onnx2ncnn yolov8s.onnx yolov8s.param yolov8s.bin
27 | ```
28 | 
29 | + ncnnoptimize生成FP16模式的模型
30 | 
31 | ```
32 | ncnnoptimize.exe yolov8s.param yolov8s.bin yolov8s_opt.param yolov8s_opt.bin 65536
33 | ```
34 | 
35 | ### 2.基于QT的NCNN安卓程序编译
36 | 
37 | 关于QT安卓开发的相关配置和QT和NCNN开发安卓程序的其他应用请参考笔者的其他几个项目，内有详细的介绍
38 | 
39 | + https://github.com/DataXujing/Qt_NCNN_NanoDet
40 | + https://github.com/DataXujing/ncnn_android_yolov6
41 | 
42 | <div align=center>
43 |     <img src="./docs/p3.png"/>
44 | </div>
45 | 
46 | 该部分代码除了模型文件已经全部在该项目中！
47 | 
48 | ### 3.小米手机上的Demo
49 | 
50 | 
51 | 
52 | |         小米手机Demo1         | 小米手机Demo2 |
53 | | :---------------------------: | ------------- |
54 | | <img src="./docs/demo1.gif"/> |               |
55 | 
56 | 
57 | 
58 | ### 4.download apk
59 | 
60 | + apk下载地址：https://github.com/DataXujing/ncnn_android_yolov8/releases
61 | 


--------------------------------------------------------------------------------
/android/AndroidManifest.xml:
--------------------------------------------------------------------------------
 1 | <?xml version="1.0"?>
 2 | <manifest package="org.qtproject.yolov8" xmlns:android="http://schemas.android.com/apk/res/android" android:versionName="-- %%INSERT_VERSION_NAME%% --" android:versionCode="-- %%INSERT_VERSION_CODE%% --" android:installLocation="auto">
 3 |     <uses-sdk android:minSdkVersion="21" android:targetSdkVersion="28"/>
 4 | 
 5 |     <!-- The following comment will be replaced upon deployment with default permissions based on the dependencies of the application.
 6 |          Remove the comment if you do not require these default permissions. -->
 7 |     <!-- %%INSERT_PERMISSIONS -->
 8 | 
 9 |     <!-- The following comment will be replaced upon deployment with default features based on the dependencies of the application.
10 |          Remove the comment if you do not require these default features. -->
11 |     <!-- %%INSERT_FEATURES -->
12 | 
13 |     <supports-screens android:largeScreens="true" android:normalScreens="true" android:anyDensity="true" android:smallScreens="true"/>
14 | 
15 |     <application android:hardwareAccelerated="true" android:name="org.qtproject.qt5.android.bindings.QtApplication" android:label="YOLOv8" android:extractNativeLibs="true" android:icon="@drawable/icon">
16 |         <activity android:configChanges="orientation|uiMode|screenLayout|screenSize|smallestScreenSize|layoutDirection|locale|fontScale|keyboard|keyboardHidden|navigation|mcc|mnc|density" android:name="org.qtproject.qt5.android.bindings.QtActivity" android:label="Yolov8" android:screenOrientation="unspecified" android:launchMode="singleTop">
17 |             <intent-filter>
18 |                 <action android:name="android.intent.action.MAIN"/>
19 |                 <category android:name="android.intent.category.LAUNCHER"/>
20 |             </intent-filter>
21 | 
22 |             <!-- Application arguments -->
23 |             <!-- meta-data android:name="android.app.arguments" android:value="arg1 arg2 arg3"/ -->
24 |             <!-- Application arguments -->
25 | 
26 |             <meta-data android:name="android.app.lib_name" android:value="-- %%INSERT_APP_LIB_NAME%% --"/>
27 |             <meta-data android:name="android.app.qt_sources_resource_id" android:resource="@array/qt_sources"/>
28 |             <meta-data android:name="android.app.repository" android:value="default"/>
29 |             <meta-data android:name="android.app.qt_libs_resource_id" android:resource="@array/qt_libs"/>
30 |             <meta-data android:name="android.app.bundled_libs_resource_id" android:resource="@array/bundled_libs"/>
31 |             <!-- Deploy Qt libs as part of package -->
32 |             <meta-data android:name="android.app.bundle_local_qt_libs" android:value="-- %%BUNDLE_LOCAL_QT_LIBS%% --"/>
33 | 
34 |             <!-- Run with local libs -->
35 |             <meta-data android:name="android.app.use_local_qt_libs" android:value="-- %%USE_LOCAL_QT_LIBS%% --"/>
36 |             <meta-data android:name="android.app.libs_prefix" android:value="/data/local/tmp/qt/"/>
37 |             <meta-data android:name="android.app.load_local_libs_resource_id" android:resource="@array/load_local_libs"/>
38 |             <meta-data android:name="android.app.load_local_jars" android:value="-- %%INSERT_LOCAL_JARS%% --"/>
39 |             <meta-data android:name="android.app.static_init_classes" android:value="-- %%INSERT_INIT_CLASSES%% --"/>
40 |             <!-- Used to specify custom system library path to run with local system libs -->
41 |             <!-- <meta-data android:name="android.app.system_libs_prefix" android:value="/system/lib/"/> -->
42 |             <!--  Messages maps -->
43 |             <meta-data android:value="@string/ministro_not_found_msg" android:name="android.app.ministro_not_found_msg"/>
44 |             <meta-data android:value="@string/ministro_needed_msg" android:name="android.app.ministro_needed_msg"/>
45 |             <meta-data android:value="@string/fatal_error_msg" android:name="android.app.fatal_error_msg"/>
46 |             <meta-data android:value="@string/unsupported_android_version" android:name="android.app.unsupported_android_version"/>
47 |             <!--  Messages maps -->
48 | 
49 |             <!-- Splash screen -->
50 |             <!-- Orientation-specific (portrait/landscape) data is checked first. If not available for current orientation,
51 |                  then android.app.splash_screen_drawable. For best results, use together with splash_screen_sticky and
52 |                  use hideSplashScreen() with a fade-out animation from Qt Android Extras to hide the splash screen when you
53 |                  are done populating your window with content. -->
54 |             <!-- meta-data android:name="android.app.splash_screen_drawable_portrait" android:resource="@drawable/logo_portrait" / -->
55 |             <!-- meta-data android:name="android.app.splash_screen_drawable_landscape" android:resource="@drawable/logo_landscape" / -->
56 |             <!-- meta-data android:name="android.app.splash_screen_drawable" android:resource="@drawable/logo"/ -->
57 |             <!-- meta-data android:name="android.app.splash_screen_sticky" android:value="true"/ -->
58 |             <!-- Splash screen -->
59 | 
60 |             <!-- Background running -->
61 |             <!-- Warning: changing this value to true may cause unexpected crashes if the
62 |                           application still try to draw after
63 |                           "applicationStateChanged(Qt::ApplicationSuspended)"
64 |                           signal is sent! -->
65 |             <meta-data android:name="android.app.background_running" android:value="false"/>
66 |             <!-- Background running -->
67 | 
68 |             <!-- auto screen scale factor -->
69 |             <meta-data android:name="android.app.auto_screen_scale_factor" android:value="false"/>
70 |             <!-- auto screen scale factor -->
71 | 
72 |             <!-- extract android style -->
73 |             <!-- available android:values :
74 |                 * default - In most cases this will be the same as "full", but it can also be something else if needed, e.g., for compatibility reasons
75 |                 * full - useful QWidget & Quick Controls 1 apps
76 |                 * minimal - useful for Quick Controls 2 apps, it is much faster than "full"
77 |                 * none - useful for apps that don't use any of the above Qt modules
78 |                 -->
79 |             <meta-data android:name="android.app.extract_android_style" android:value="default"/>
80 |             <!-- extract android style -->
81 |     </activity>
82 | 
83 |     <!-- For adding service(s) please check: https://wiki.qt.io/AndroidServices -->
84 | 
85 |     </application>
86 | 
87 |     <!-- 权限 -->
88 |     <uses-permission android:name="android.permission.INTERNET"/>
89 |     <uses-permission android:name="android.permission.WRITE_EXTERNAL_STORAGE"/>
90 |     <uses-permission android:name="android.permission.CAMERA"/>
91 | 
92 | </manifest>
93 | 


--------------------------------------------------------------------------------
/android/build.gradle:
--------------------------------------------------------------------------------
 1 | buildscript {
 2 |     repositories {
 3 |         google()
 4 |         jcenter()
 5 |     }
 6 | 
 7 |     dependencies {
 8 |         classpath 'com.android.tools.build:gradle:3.5.0'
 9 |     }
10 | }
11 | 
12 | repositories {
13 |     google()
14 |     jcenter()
15 | }
16 | 
17 | apply plugin: 'com.android.application'
18 | 
19 | dependencies {
20 |     implementation fileTree(dir: 'libs', include: ['*.jar', '*.aar'])
21 | }
22 | 
23 | android {
24 |     /*******************************************************
25 |      * The following variables:
26 |      * - androidBuildToolsVersion,
27 |      * - androidCompileSdkVersion
28 |      * - qt5AndroidDir - holds the path to qt android files
29 |      *                   needed to build any Qt application
30 |      *                   on Android.
31 |      *
32 |      * are defined in gradle.properties file. This file is
33 |      * updated by QtCreator and androiddeployqt tools.
34 |      * Changing them manually might break the compilation!
35 |      *******************************************************/
36 | 
37 |     compileSdkVersion androidCompileSdkVersion.toInteger()
38 | 
39 |     buildToolsVersion '28.0.3'
40 | 
41 |     sourceSets {
42 |         main {
43 |             manifest.srcFile 'AndroidManifest.xml'
44 |             java.srcDirs = [qt5AndroidDir + '/src', 'src', 'java']
45 |             aidl.srcDirs = [qt5AndroidDir + '/src', 'src', 'aidl']
46 |             res.srcDirs = [qt5AndroidDir + '/res', 'res']
47 |             resources.srcDirs = ['resources']
48 |             renderscript.srcDirs = ['src']
49 |             assets.srcDirs = ['assets']
50 |             jniLibs.srcDirs = ['libs']
51 |        }
52 |     }
53 | 
54 |     lintOptions {
55 |         abortOnError false
56 |     }
57 | 
58 |     // Do not compress Qt binary resources file
59 |     aaptOptions {
60 |         noCompress 'rcc'
61 |     }
62 | 
63 |     defaultConfig {
64 |         resConfigs "en"
65 |     }
66 | }
67 | 


--------------------------------------------------------------------------------
/android/gradle/wrapper/gradle-wrapper.jar:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/DataXujing/ncnn_android_yolov8/298db901d8520888e133e906ce73445ead3842ba/android/gradle/wrapper/gradle-wrapper.jar


--------------------------------------------------------------------------------
/android/gradle/wrapper/gradle-wrapper.properties:
--------------------------------------------------------------------------------
1 | distributionBase=GRADLE_USER_HOME
2 | distributionPath=wrapper/dists
3 | distributionUrl=https\://services.gradle.org/distributions/gradle-5.5.1-bin.zip
4 | zipStoreBase=GRADLE_USER_HOME
5 | zipStorePath=wrapper/dists
6 | 


--------------------------------------------------------------------------------
/android/gradlew:
--------------------------------------------------------------------------------
  1 | #!/usr/bin/env sh
  2 | 
  3 | ##############################################################################
  4 | ##
  5 | ##  Gradle start up script for UN*X
  6 | ##
  7 | ##############################################################################
  8 | 
  9 | # Attempt to set APP_HOME
 10 | # Resolve links: $0 may be a link
 11 | PRG="$0"
 12 | # Need this for relative symlinks.
 13 | while [ -h "$PRG" ] ; do
 14 |     ls=`ls -ld "$PRG"`
 15 |     link=`expr "$ls" : '.*-> \(.*\)$'`
 16 |     if expr "$link" : '/.*' > /dev/null; then
 17 |         PRG="$link"
 18 |     else
 19 |         PRG=`dirname "$PRG"`"/$link"
 20 |     fi
 21 | done
 22 | SAVED="`pwd`"
 23 | cd "`dirname \"$PRG\"`/" >/dev/null
 24 | APP_HOME="`pwd -P`"
 25 | cd "$SAVED" >/dev/null
 26 | 
 27 | APP_NAME="Gradle"
 28 | APP_BASE_NAME=`basename "$0"`
 29 | 
 30 | # Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script.
 31 | DEFAULT_JVM_OPTS=""
 32 | 
 33 | # Use the maximum available, or set MAX_FD != -1 to use that value.
 34 | MAX_FD="maximum"
 35 | 
 36 | warn () {
 37 |     echo "$*"
 38 | }
 39 | 
 40 | die () {
 41 |     echo
 42 |     echo "$*"
 43 |     echo
 44 |     exit 1
 45 | }
 46 | 
 47 | # OS specific support (must be 'true' or 'false').
 48 | cygwin=false
 49 | msys=false
 50 | darwin=false
 51 | nonstop=false
 52 | case "`uname`" in
 53 |   CYGWIN* )
 54 |     cygwin=true
 55 |     ;;
 56 |   Darwin* )
 57 |     darwin=true
 58 |     ;;
 59 |   MINGW* )
 60 |     msys=true
 61 |     ;;
 62 |   NONSTOP* )
 63 |     nonstop=true
 64 |     ;;
 65 | esac
 66 | 
 67 | CLASSPATH=$APP_HOME/gradle/wrapper/gradle-wrapper.jar
 68 | 
 69 | # Determine the Java command to use to start the JVM.
 70 | if [ -n "$JAVA_HOME" ] ; then
 71 |     if [ -x "$JAVA_HOME/jre/sh/java" ] ; then
 72 |         # IBM's JDK on AIX uses strange locations for the executables
 73 |         JAVACMD="$JAVA_HOME/jre/sh/java"
 74 |     else
 75 |         JAVACMD="$JAVA_HOME/bin/java"
 76 |     fi
 77 |     if [ ! -x "$JAVACMD" ] ; then
 78 |         die "ERROR: JAVA_HOME is set to an invalid directory: $JAVA_HOME
 79 | 
 80 | Please set the JAVA_HOME variable in your environment to match the
 81 | location of your Java installation."
 82 |     fi
 83 | else
 84 |     JAVACMD="java"
 85 |     which java >/dev/null 2>&1 || die "ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH.
 86 | 
 87 | Please set the JAVA_HOME variable in your environment to match the
 88 | location of your Java installation."
 89 | fi
 90 | 
 91 | # Increase the maximum file descriptors if we can.
 92 | if [ "$cygwin" = "false" -a "$darwin" = "false" -a "$nonstop" = "false" ] ; then
 93 |     MAX_FD_LIMIT=`ulimit -H -n`
 94 |     if [ $? -eq 0 ] ; then
 95 |         if [ "$MAX_FD" = "maximum" -o "$MAX_FD" = "max" ] ; then
 96 |             MAX_FD="$MAX_FD_LIMIT"
 97 |         fi
 98 |         ulimit -n $MAX_FD
 99 |         if [ $? -ne 0 ] ; then
100 |             warn "Could not set maximum file descriptor limit: $MAX_FD"
101 |         fi
102 |     else
103 |         warn "Could not query maximum file descriptor limit: $MAX_FD_LIMIT"
104 |     fi
105 | fi
106 | 
107 | # For Darwin, add options to specify how the application appears in the dock
108 | if $darwin; then
109 |     GRADLE_OPTS="$GRADLE_OPTS \"-Xdock:name=$APP_NAME\" \"-Xdock:icon=$APP_HOME/media/gradle.icns\""
110 | fi
111 | 
112 | # For Cygwin, switch paths to Windows format before running java
113 | if $cygwin ; then
114 |     APP_HOME=`cygpath --path --mixed "$APP_HOME"`
115 |     CLASSPATH=`cygpath --path --mixed "$CLASSPATH"`
116 |     JAVACMD=`cygpath --unix "$JAVACMD"`
117 | 
118 |     # We build the pattern for arguments to be converted via cygpath
119 |     ROOTDIRSRAW=`find -L / -maxdepth 1 -mindepth 1 -type d 2>/dev/null`
120 |     SEP=""
121 |     for dir in $ROOTDIRSRAW ; do
122 |         ROOTDIRS="$ROOTDIRS$SEP$dir"
123 |         SEP="|"
124 |     done
125 |     OURCYGPATTERN="(^($ROOTDIRS))"
126 |     # Add a user-defined pattern to the cygpath arguments
127 |     if [ "$GRADLE_CYGPATTERN" != "" ] ; then
128 |         OURCYGPATTERN="$OURCYGPATTERN|($GRADLE_CYGPATTERN)"
129 |     fi
130 |     # Now convert the arguments - kludge to limit ourselves to /bin/sh
131 |     i=0
132 |     for arg in "$@" ; do
133 |         CHECK=`echo "$arg"|egrep -c "$OURCYGPATTERN" -`
134 |         CHECK2=`echo "$arg"|egrep -c "^-"`                                 ### Determine if an option
135 | 
136 |         if [ $CHECK -ne 0 ] && [ $CHECK2 -eq 0 ] ; then                    ### Added a condition
137 |             eval `echo args$i`=`cygpath --path --ignore --mixed "$arg"`
138 |         else
139 |             eval `echo args$i`="\"$arg\""
140 |         fi
141 |         i=$((i+1))
142 |     done
143 |     case $i in
144 |         (0) set -- ;;
145 |         (1) set -- "$args0" ;;
146 |         (2) set -- "$args0" "$args1" ;;
147 |         (3) set -- "$args0" "$args1" "$args2" ;;
148 |         (4) set -- "$args0" "$args1" "$args2" "$args3" ;;
149 |         (5) set -- "$args0" "$args1" "$args2" "$args3" "$args4" ;;
150 |         (6) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" ;;
151 |         (7) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" ;;
152 |         (8) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" "$args7" ;;
153 |         (9) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" "$args7" "$args8" ;;
154 |     esac
155 | fi
156 | 
157 | # Escape application args
158 | save () {
159 |     for i do printf %s\\n "$i" | sed "s/'/'\\\\''/g;1s/^/'/;\$s/\$/' \\\\/" ; done
160 |     echo " "
161 | }
162 | APP_ARGS=$(save "$@")
163 | 
164 | # Collect all arguments for the java command, following the shell quoting and substitution rules
165 | eval set -- $DEFAULT_JVM_OPTS $JAVA_OPTS $GRADLE_OPTS "\"-Dorg.gradle.appname=$APP_BASE_NAME\"" -classpath "\"$CLASSPATH\"" org.gradle.wrapper.GradleWrapperMain "$APP_ARGS"
166 | 
167 | # by default we should be in the correct project dir, but when run from Finder on Mac, the cwd is wrong
168 | if [ "$(uname)" = "Darwin" ] && [ "$HOME" = "$PWD" ]; then
169 |   cd "$(dirname "$0")"
170 | fi
171 | 
172 | exec "$JAVACMD" "$@"
173 | 


--------------------------------------------------------------------------------
/android/gradlew.bat:
--------------------------------------------------------------------------------
 1 | @if "%DEBUG%" == "" @echo off
 2 | @rem ##########################################################################
 3 | @rem
 4 | @rem  Gradle startup script for Windows
 5 | @rem
 6 | @rem ##########################################################################
 7 | 
 8 | @rem Set local scope for the variables with windows NT shell
 9 | if "%OS%"=="Windows_NT" setlocal
10 | 
11 | set DIRNAME=%~dp0
12 | if "%DIRNAME%" == "" set DIRNAME=.
13 | set APP_BASE_NAME=%~n0
14 | set APP_HOME=%DIRNAME%
15 | 
16 | @rem Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script.
17 | set DEFAULT_JVM_OPTS=
18 | 
19 | @rem Find java.exe
20 | if defined JAVA_HOME goto findJavaFromJavaHome
21 | 
22 | set JAVA_EXE=java.exe
23 | %JAVA_EXE% -version >NUL 2>&1
24 | if "%ERRORLEVEL%" == "0" goto init
25 | 
26 | echo.
27 | echo ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH.
28 | echo.
29 | echo Please set the JAVA_HOME variable in your environment to match the
30 | echo location of your Java installation.
31 | 
32 | goto fail
33 | 
34 | :findJavaFromJavaHome
35 | set JAVA_HOME=%JAVA_HOME:"=%
36 | set JAVA_EXE=%JAVA_HOME%/bin/java.exe
37 | 
38 | if exist "%JAVA_EXE%" goto init
39 | 
40 | echo.
41 | echo ERROR: JAVA_HOME is set to an invalid directory: %JAVA_HOME%
42 | echo.
43 | echo Please set the JAVA_HOME variable in your environment to match the
44 | echo location of your Java installation.
45 | 
46 | goto fail
47 | 
48 | :init
49 | @rem Get command-line arguments, handling Windows variants
50 | 
51 | if not "%OS%" == "Windows_NT" goto win9xME_args
52 | 
53 | :win9xME_args
54 | @rem Slurp the command line arguments.
55 | set CMD_LINE_ARGS=
56 | set _SKIP=2
57 | 
58 | :win9xME_args_slurp
59 | if "x%~1" == "x" goto execute
60 | 
61 | set CMD_LINE_ARGS=%*
62 | 
63 | :execute
64 | @rem Setup the command line
65 | 
66 | set CLASSPATH=%APP_HOME%\gradle\wrapper\gradle-wrapper.jar
67 | 
68 | @rem Execute Gradle
69 | "%JAVA_EXE%" %DEFAULT_JVM_OPTS% %JAVA_OPTS% %GRADLE_OPTS% "-Dorg.gradle.appname=%APP_BASE_NAME%" -classpath "%CLASSPATH%" org.gradle.wrapper.GradleWrapperMain %CMD_LINE_ARGS%
70 | 
71 | :end
72 | @rem End local scope for the variables with windows NT shell
73 | if "%ERRORLEVEL%"=="0" goto mainEnd
74 | 
75 | :fail
76 | rem Set variable GRADLE_EXIT_CONSOLE if you need the _script_ return code instead of
77 | rem the _cmd.exe /c_ return code!
78 | if  not "" == "%GRADLE_EXIT_CONSOLE%" exit 1
79 | exit /b 1
80 | 
81 | :mainEnd
82 | if "%OS%"=="Windows_NT" endlocal
83 | 
84 | :omega
85 | 


--------------------------------------------------------------------------------
/android/res/drawable-hdpi/icon.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/DataXujing/ncnn_android_yolov8/298db901d8520888e133e906ce73445ead3842ba/android/res/drawable-hdpi/icon.png


--------------------------------------------------------------------------------
/android/res/drawable-ldpi/icon.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/DataXujing/ncnn_android_yolov8/298db901d8520888e133e906ce73445ead3842ba/android/res/drawable-ldpi/icon.png


--------------------------------------------------------------------------------
/android/res/drawable-mdpi/icon.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/DataXujing/ncnn_android_yolov8/298db901d8520888e133e906ce73445ead3842ba/android/res/drawable-mdpi/icon.png


--------------------------------------------------------------------------------
/android/res/values/libs.xml:
--------------------------------------------------------------------------------
 1 | <?xml version='1.0' encoding='utf-8'?>
 2 | <resources>
 3 |     <array name="qt_sources">
 4 |         <item>https://download.qt.io/ministro/android/qt5/qt-5.14</item>
 5 |     </array>
 6 | 
 7 |     <!-- The following is handled automatically by the deployment tool. It should
 8 |          not be edited manually. -->
 9 | 
10 |     <array name="bundled_libs">
11 |         <!-- %%INSERT_EXTRA_LIBS%% -->
12 |     </array>
13 | 
14 |     <array name="qt_libs">
15 |         <!-- %%INSERT_QT_LIBS%% -->
16 |     </array>
17 | 
18 |     <array name="load_local_libs">
19 |         <!-- %%INSERT_LOCAL_LIBS%% -->
20 |     </array>
21 | 
22 | </resources>
23 | 


--------------------------------------------------------------------------------
/android/src/com/amin/QtAndroidGallery/QtAndroidGallery.java:
--------------------------------------------------------------------------------
  1 | package com.amin.QtAndroidGallery;
  2 | 
  3 | import org.qtproject.qt5.android.bindings.QtApplication;
  4 | import org.qtproject.qt5.android.bindings.QtActivity;
  5 | 
  6 | import android.content.Context;
  7 | import android.content.Intent;
  8 | import android.database.Cursor;
  9 | import android.graphics.Bitmap;
 10 | import android.graphics.BitmapFactory;
 11 | import android.net.Uri;
 12 | import android.os.Bundle;
 13 | import android.os.Environment;
 14 | import android.provider.MediaStore;
 15 | import android.util.Log;
 16 | import android.os.Build;
 17 | import android.os.Build.VERSION;
 18 | import android.widget.Toast;
 19 | 
 20 | import java.io.File;
 21 | import java.io.IOException;
 22 | import java.text.SimpleDateFormat;
 23 | import java.util.ArrayList;
 24 | import java.util.Date;
 25 | import java.util.List;
 26 | import android.provider.DocumentsContract;
 27 | import     android.content.ContentUris;
 28 | 
 29 | public class QtAndroidGallery extends QtActivity
 30 | {
 31 | 
 32 |     public static native void fileSelected(String fileName);
 33 | 
 34 |     static final int REQUEST_OPEN_IMAGE = 1;
 35 |     public String lastCameraFileUri;
 36 |     static final int REQUEST_CAPTURE_IMAGE = 2;
 37 | 
 38 |     private static QtAndroidGallery m_instance;
 39 | 
 40 |     public QtAndroidGallery()
 41 |     {
 42 |         m_instance = this;
 43 |     }
 44 | 
 45 |     @Override
 46 |     public void onCreate(Bundle savedInstanceState)
 47 |     {
 48 |         super.onCreate(savedInstanceState);
 49 |     }
 50 | 
 51 |     @Override
 52 |     protected void onDestroy()
 53 |     {
 54 |         super.onDestroy();
 55 |     }
 56 | 
 57 |     static void openAnImage()
 58 |     {
 59 |         m_instance.dispatchOpenGallery();
 60 |     }
 61 | 
 62 |     @Override
 63 |     protected void onActivityResult(int requestCode, int resultCode, Intent data)
 64 |     {
 65 |        if (resultCode == RESULT_OK)
 66 |         {
 67 |             if(requestCode == REQUEST_OPEN_IMAGE)
 68 |             {
 69 |                  System.out.println("debug 123456789");
 70 |                  String filePath = getPath(getApplicationContext(), data.getData());
 71 |                 fileSelected(filePath);
 72 |             }
 73 |             else if(requestCode == REQUEST_CAPTURE_IMAGE)
 74 |             {
 75 |                 String filePath = lastCameraFileUri;
 76 |                 fileSelected(filePath);
 77 |              }
 78 |         }
 79 |         else
 80 |         {
 81 |             fileSelected(":(");
 82 |         }
 83 | 
 84 |         super.onActivityResult(requestCode, resultCode, data);
 85 |     }
 86 | 
 87 |     private void dispatchOpenGallery()
 88 |     {
 89 |         Intent intent = new Intent(Intent.ACTION_GET_CONTENT);
 90 |         intent.setType("image/*");
 91 |         startActivityForResult(intent, REQUEST_OPEN_IMAGE);
 92 |     }
 93 | 
 94 |     public String getRealPathFromURI(Context context, Uri contentUri)
 95 |     {
 96 |         Cursor cursor = null;
 97 |         try
 98 |         {
 99 |             String[] proj = { MediaStore.Images.Media.DATA };
100 |             cursor = context.getContentResolver().query(contentUri,  proj, null, null, null);
101 |             int column_index = cursor.getColumnIndexOrThrow(MediaStore.Images.Media.DATA);
102 |             cursor.moveToFirst();
103 |             return cursor.getString(column_index);
104 |         }
105 |         finally
106 |         {
107 |             if (cursor != null)
108 |             {
109 |                 cursor.close();
110 |             }
111 |         }
112 |     }
113 | 
114 | 
115 | 
116 | /**
117 |      * Get a file path from a Uri. This will get the the path for Storage Access
118 |      * Framework Documents, as well as the _data field for the MediaStore and
119 |      * other file-based ContentProviders.
120 |      *
121 |      * @param context The context.
122 |      * @param uri The Uri to query.
123 |      * @author paulburke
124 |      */
125 |     public static String getPath(final Context context, final Uri uri) {
126 | 
127 |         final boolean isKitKat = Build.VERSION.SDK_INT >= Build.VERSION_CODES.KITKAT;
128 | 
129 |         // DocumentProvider
130 |         if (isKitKat && DocumentsContract.isDocumentUri(context, uri)) {
131 |             // ExternalStorageProvider
132 |             if (isExternalStorageDocument(uri)) {
133 |                 final String docId = DocumentsContract.getDocumentId(uri);
134 |                 final String[] split = docId.split(":");
135 |                 final String type = split[0];
136 | 
137 |                 if ("primary".equalsIgnoreCase(type)) {
138 |                     return Environment.getExternalStorageDirectory() + "/" + split[1];
139 |                 }
140 | 
141 |                 // TODO handle non-primary volumes
142 |             }
143 |             // DownloadsProvider
144 |             else if (isDownloadsDocument(uri)) {
145 | 
146 |                 final String id = DocumentsContract.getDocumentId(uri);
147 |                 final Uri contentUri = ContentUris.withAppendedId(
148 |                         Uri.parse("content://downloads/public_downloads"), Long.valueOf(id));
149 | 
150 |                 return getDataColumn(context, contentUri, null, null);
151 |             }
152 |             // MediaProvider
153 |             else if (isMediaDocument(uri)) {
154 |                 final String docId = DocumentsContract.getDocumentId(uri);
155 |                 final String[] split = docId.split(":");
156 |                 final String type = split[0];
157 | 
158 |                 Uri contentUri = null;
159 |                 if ("image".equals(type)) {
160 |                     contentUri = MediaStore.Images.Media.EXTERNAL_CONTENT_URI;
161 |                 } else if ("video".equals(type)) {
162 |                     contentUri = MediaStore.Video.Media.EXTERNAL_CONTENT_URI;
163 |                 } else if ("audio".equals(type)) {
164 |                     contentUri = MediaStore.Audio.Media.EXTERNAL_CONTENT_URI;
165 |                 }
166 | 
167 |                 final String selection = "_id=?";
168 |                 final String[] selectionArgs = new String[] {
169 |                         split[1]
170 |                 };
171 | 
172 |                 return getDataColumn(context, contentUri, selection, selectionArgs);
173 |             }
174 |         }
175 |         // MediaStore (and general)
176 |         else if ("content".equalsIgnoreCase(uri.getScheme())) {
177 |             return getDataColumn(context, uri, null, null);
178 |         }
179 |         // File
180 |         else if ("file".equalsIgnoreCase(uri.getScheme())) {
181 |             return uri.getPath();
182 |         }
183 | 
184 |         return null;
185 |     }
186 | 
187 |     /**
188 |      * Get the value of the data column for this Uri. This is useful for
189 |      * MediaStore Uris, and other file-based ContentProviders.
190 |      *
191 |      * @param context The context.
192 |      * @param uri The Uri to query.
193 |      * @param selection (Optional) Filter used in the query.
194 |      * @param selectionArgs (Optional) Selection arguments used in the query.
195 |      * @return The value of the _data column, which is typically a file path.
196 |      */
197 |     public static String getDataColumn(Context context, Uri uri, String selection,
198 |             String[] selectionArgs) {
199 | 
200 |         Cursor cursor = null;
201 |         final String column = "_data";
202 |         final String[] projection = {
203 |                 column
204 |         };
205 | 
206 |         try {
207 |             cursor = context.getContentResolver().query(uri, projection, selection, selectionArgs,
208 |                     null);
209 |             if (cursor != null && cursor.moveToFirst()) {
210 |                 final int column_index = cursor.getColumnIndexOrThrow(column);
211 |                 return cursor.getString(column_index);
212 |             }
213 |         } finally {
214 |             if (cursor != null)
215 |                 cursor.close();
216 |         }
217 |         return null;
218 |     }
219 | 
220 | 
221 |     /**
222 |      * @param uri The Uri to check.
223 |      * @return Whether the Uri authority is ExternalStorageProvider.
224 |      */
225 |     public static boolean isExternalStorageDocument(Uri uri) {
226 |         return "com.android.externalstorage.documents".equals(uri.getAuthority());
227 |     }
228 | 
229 |     /**
230 |      * @param uri The Uri to check.
231 |      * @return Whether the Uri authority is DownloadsProvider.
232 |      */
233 |     public static boolean isDownloadsDocument(Uri uri) {
234 |         return "com.android.providers.downloads.documents".equals(uri.getAuthority());
235 |     }
236 | 
237 |     /**
238 |      * @param uri The Uri to check.
239 |      * @return Whether the Uri authority is MediaProvider.
240 |      */
241 |     public static boolean isMediaDocument(Uri uri) {
242 |         return "com.android.providers.media.documents".equals(uri.getAuthority());
243 |     }
244 | 
245 | 
246 |     static void captureAnImage()
247 |     {
248 |         m_instance.dispatchTakePictureIntent();
249 |     }
250 | 
251 |     private void dispatchTakePictureIntent()
252 |     {
253 |     Intent takePictureIntent = new Intent(MediaStore.ACTION_IMAGE_CAPTURE);
254 | 
255 |     // Ensure that there’s a camera activity to handle the intent
256 |     if (takePictureIntent.resolveActivity(getPackageManager()) != null)
257 |     {
258 |     // Create the File where the photo should go
259 |         File photoFile = null;
260 |         try
261 |         {
262 |             photoFile = m_instance.createImageFile();
263 |         }
264 |         catch (IOException ex)
265 |         {
266 |         // Error occurred while creating the File
267 |             Toast.makeText(QtAndroidGallery.this, ex.getLocalizedMessage(), Toast.LENGTH_LONG).show();
268 |             Toast.makeText(QtAndroidGallery.this, ex.getMessage(), Toast.LENGTH_LONG).show();
269 |         }
270 |         // Continue only if the File was successfully created
271 |         if (photoFile != null)
272 |         {
273 |             takePictureIntent.putExtra(MediaStore.EXTRA_OUTPUT, Uri.fromFile(photoFile));
274 | 
275 |             lastCameraFileUri = photoFile.toString();
276 | 
277 |             startActivityForResult(takePictureIntent, REQUEST_CAPTURE_IMAGE);
278 |         }
279 |     }
280 |     else
281 |     {
282 |         Toast.makeText(QtAndroidGallery.this, "Problems with your camera?!", Toast.LENGTH_SHORT).show();
283 |     }
284 |  }
285 | 
286 | 
287 |     private File createImageFile() throws IOException
288 |     {
289 |         // Create an image file name
290 |         String timeStamp = new SimpleDateFormat("yyyyMMdd_HHmmss").format(new Date());
291 |         String imageFileName = "MYAPPTEMP_" + timeStamp + "_";
292 |         File storageDir = Environment.getExternalStoragePublicDirectory(Environment.DIRECTORY_PICTURES);
293 |         File image = File.createTempFile(imageFileName, /* prefix */
294 |         ".jpg", /* suffix */
295 |         storageDir /* directory */
296 |         );
297 | 
298 |         return image;
299 |     }
300 | 
301 | 
302 | }
303 | 
304 | 
305 | 


--------------------------------------------------------------------------------
/assets/ManjaroMix.qss:
--------------------------------------------------------------------------------
  1 | /*
  2 | ManjaroMix Style Sheet for QT Applications
  3 | Author: Jaime A. Quiroga P.
  4 | Company: GTRONICK
  5 | Last updated: 25/02/2020, 15:42.
  6 | Available at: https://github.com/GTRONICK/QSS/blob/master/ManjaroMix.qss
  7 | */
  8 | QMainWindow {
  9 | 	background-color:#151a1e;
 10 | }
 11 | QCalendar {
 12 | 	background-color: #151a1e;
 13 | }
 14 | QTextEdit {
 15 | 	border-width: 1px;
 16 | 	border-style: solid;
 17 | 	border-color: #4fa08b;
 18 | 	background-color: #222b2e;
 19 | 	color: #d3dae3;
 20 | }
 21 | QPlainTextEdit {
 22 | 	border-width: 1px;
 23 | 	border-style: solid;
 24 | 	border-color: #4fa08b;
 25 | 	background-color: #222b2e;
 26 | 	color: #d3dae3;
 27 | }
 28 | QToolButton {
 29 | 	border-style: solid;
 30 | 	border-top-color: qlineargradient(spread:pad, x1:0.5, y1:1, x2:0.5, y2:0, stop:0 rgb(215, 215, 215), stop:1 rgb(222, 222, 222));
 31 | 	border-right-color: qlineargradient(spread:pad, x1:0, y1:0.5, x2:1, y2:0.5, stop:0 rgb(217, 217, 217), stop:1 rgb(227, 227, 227));
 32 | 	border-left-color: qlineargradient(spread:pad, x1:0, y1:0.5, x2:1, y2:0.5, stop:0 rgb(227, 227, 227), stop:1 rgb(217, 217, 217));
 33 | 	border-bottom-color: qlineargradient(spread:pad, x1:0.5, y1:1, x2:0.5, y2:0, stop:0 rgb(215, 215, 215), stop:1 rgb(222, 222, 222));
 34 | 	border-width: 1px;
 35 | 	border-radius: 5px;
 36 | 	color: #d3dae3;
 37 | 	padding: 2px;
 38 | 	background-color: rgb(255,255,255);
 39 | }
 40 | QToolButton:hover{
 41 | 	border-style: solid;
 42 | 	border-top-color: qlineargradient(spread:pad, x1:0.5, y1:1, x2:0.5, y2:0, stop:0 rgb(195, 195, 195), stop:1 rgb(222, 222, 222));
 43 | 	border-right-color: qlineargradient(spread:pad, x1:0, y1:0.5, x2:1, y2:0.5, stop:0 rgb(197, 197, 197), stop:1 rgb(227, 227, 227));
 44 | 	border-left-color: qlineargradient(spread:pad, x1:0, y1:0.5, x2:1, y2:0.5, stop:0 rgb(227, 227, 227), stop:1 rgb(197, 197, 197));
 45 | 	border-bottom-color: qlineargradient(spread:pad, x1:0.5, y1:1, x2:0.5, y2:0, stop:0 rgb(195, 195, 195), stop:1 rgb(222, 222, 222));
 46 | 	border-width: 1px;
 47 | 	border-radius: 5px;
 48 | 	color: rgb(0,0,0);
 49 | 	padding: 2px;
 50 | 	background-color: rgb(255,255,255);
 51 | }
 52 | QToolButton:pressed{
 53 | 	border-style: solid;
 54 | 	border-top-color: qlineargradient(spread:pad, x1:0.5, y1:1, x2:0.5, y2:0, stop:0 rgb(215, 215, 215), stop:1 rgb(222, 222, 222));
 55 | 	border-right-color: qlineargradient(spread:pad, x1:0, y1:0.5, x2:1, y2:0.5, stop:0 rgb(217, 217, 217), stop:1 rgb(227, 227, 227));
 56 | 	border-left-color: qlineargradient(spread:pad, x1:0, y1:0.5, x2:1, y2:0.5, stop:0 rgb(227, 227, 227), stop:1 rgb(217, 217, 217));
 57 | 	border-bottom-color: qlineargradient(spread:pad, x1:0.5, y1:1, x2:0.5, y2:0, stop:0 rgb(215, 215, 215), stop:1 rgb(222, 222, 222));
 58 | 	border-width: 1px;
 59 | 	border-radius: 5px;
 60 | 	color: rgb(0,0,0);
 61 | 	padding: 2px;
 62 | 	background-color: rgb(142,142,142);
 63 | }
 64 | QPushButton{
 65 | 	border-style: solid;
 66 | 	border-color: #050a0e;
 67 | 	border-width: 1px;
 68 | 	border-radius: 5px;
 69 | 	color: #d3dae3;
 70 | 	padding: 2px;
 71 | 	background-color: #151a1e;
 72 | }
 73 | QPushButton::default{
 74 | 	border-style: solid;
 75 | 	border-color: #050a0e;
 76 | 	border-width: 1px;
 77 | 	border-radius: 5px;
 78 | 	color: #FFFFFF;
 79 | 	padding: 2px;
 80 | 	background-color: #151a1e;;
 81 | }
 82 | QPushButton:hover{
 83 | 	border-style: solid;
 84 | 	border-color: #050a0e;
 85 | 	border-width: 1px;
 86 | 	border-radius: 5px;
 87 | 	color: #d3dae3;
 88 | 	padding: 2px;
 89 | 	background-color: #1c1f1f;
 90 | }
 91 | QPushButton:pressed{
 92 | 	border-style: solid;
 93 | 	border-color: #050a0e;
 94 | 	border-width: 1px;
 95 | 	border-radius: 5px;
 96 | 	color: #d3dae3;
 97 | 	padding: 2px;
 98 | 	background-color: #2c2f2f;
 99 | }
100 | QPushButton:disabled{
101 | 	border-style: solid;
102 | 	border-top-color: qlineargradient(spread:pad, x1:0.5, y1:1, x2:0.5, y2:0, stop:0 rgb(215, 215, 215), stop:1 rgb(222, 222, 222));
103 | 	border-right-color: qlineargradient(spread:pad, x1:0, y1:0.5, x2:1, y2:0.5, stop:0 rgb(217, 217, 217), stop:1 rgb(227, 227, 227));
104 | 	border-left-color: qlineargradient(spread:pad, x1:0, y1:0.5, x2:1, y2:0.5, stop:0 rgb(227, 227, 227), stop:1 rgb(217, 217, 217));
105 | 	border-bottom-color: qlineargradient(spread:pad, x1:0.5, y1:1, x2:0.5, y2:0, stop:0 rgb(215, 215, 215), stop:1 rgb(222, 222, 222));
106 | 	border-width: 1px;
107 | 	border-radius: 5px;
108 | 	color: #808086;
109 | 	padding: 2px;
110 | 	background-color: rgb(142,142,142);
111 | }
112 | QLineEdit {
113 | 	border-width: 1px;
114 | 	border-style: solid;
115 | 	border-color: #4fa08b;
116 | 	background-color: #222b2e;
117 | 	color: #d3dae3;
118 | }
119 | QLabel {
120 | 	color: #d3dae3;
121 | }
122 | QLCDNumber {
123 | 	color: #4d9b87;
124 | }
125 | QProgressBar {
126 | 	text-align: center;
127 | 	color: #d3dae3;
128 | 	border-radius: 10px;
129 | 	border-color: transparent;
130 | 	border-style: solid;
131 | 	background-color: #52595d;
132 | }
133 | QProgressBar::chunk {
134 | 	background-color: #214037	;
135 | 	border-radius: 10px;
136 | }
137 | QMenuBar {
138 | 	background-color: #151a1e;
139 | }
140 | QMenuBar::item {
141 | 	color: #d3dae3;
142 |   	spacing: 3px;
143 |   	padding: 1px 4px;
144 | 	background-color: #151a1e;
145 | }
146 | 
147 | QMenuBar::item:selected {
148 |   	background-color: #252a2e;
149 | 	color: #FFFFFF;
150 | }
151 | QMenu {
152 | 	background-color: #151a1e;
153 | }
154 | QMenu::item:selected {
155 | 	background-color: #252a2e;
156 | 	color: #FFFFFF;
157 | }
158 | QMenu::item {
159 | 	color: #d3dae3;
160 | 	background-color: #151a1e;
161 | }
162 | QTabWidget {
163 | 	color:rgb(0,0,0);
164 | 	background-color:#000000;
165 | }
166 | QTabWidget::pane {
167 | 		border-color: #050a0e;
168 | 		background-color: #1e282c;
169 | 		border-style: solid;
170 | 		border-width: 1px;
171 |     	border-bottom-left-radius: 4px;
172 | 		border-bottom-right-radius: 4px;
173 | }
174 | QTabBar::tab:first {
175 | 	border-style: solid;
176 | 	border-left-width:1px;
177 | 	border-right-width:0px;
178 | 	border-top-width:1px;
179 | 	border-bottom-width:0px;
180 | 	border-top-color: #050a0e;
181 | 	border-left-color: #050a0e;
182 | 	border-bottom-color: #050a0e;
183 | 	border-top-left-radius: 4px;
184 | 	color: #d3dae3;
185 | 	padding: 3px;
186 | 	margin-left:0px;
187 | 	background-color: #151a1e;
188 | }
189 | QTabBar::tab:last {
190 | 	border-style: solid;
191 | 	border-top-width:1px;
192 | 	border-left-width:1px;
193 | 	border-right-width:1px;
194 | 	border-bottom-width:0px;
195 | 	border-color: #050a0e;
196 | 	border-top-right-radius: 4px;
197 | 	color: #d3dae3;
198 | 	padding: 3px;
199 | 	margin-left:0px;
200 | 	background-color: #151a1e;
201 | }
202 | QTabBar::tab {
203 | 	border-style: solid;
204 | 	border-top-width:1px;
205 | 	border-bottom-width:0px;
206 | 	border-left-width:1px;
207 | 	border-top-color: #050a0e;
208 | 	border-left-color: #050a0e;
209 | 	border-bottom-color: #050a0e;
210 | 	color: #d3dae3;
211 | 	padding: 3px;
212 | 	margin-left:0px;
213 | 	background-color: #151a1e;
214 | }
215 | QTabBar::tab:selected, QTabBar::tab:last:selected, QTabBar::tab:hover {
216 |   	border-style: solid;
217 |   	border-left-width:1px;
218 | 	border-bottom-width:0px;
219 | 	border-right-color: transparent;
220 | 	border-top-color: #050a0e;
221 | 	border-left-color: #050a0e;
222 | 	border-bottom-color: #050a0e;
223 | 	color: #FFFFFF;
224 | 	padding: 3px;
225 | 	margin-left:0px;
226 | 	background-color: #1e282c;
227 | }
228 | 
229 | QTabBar::tab:selected, QTabBar::tab:first:selected, QTabBar::tab:hover {
230 |   	border-style: solid;
231 |   	border-left-width:1px;
232 |   	border-bottom-width:0px;
233 |   	border-top-width:1px;
234 | 	border-right-color: transparent;
235 | 	border-top-color: #050a0e;
236 | 	border-left-color: #050a0e;
237 | 	border-bottom-color: #050a0e;
238 | 	color: #FFFFFF;
239 | 	padding: 3px;
240 | 	margin-left:0px;
241 | 	background-color: #1e282c;
242 | }
243 | 
244 | QCheckBox {
245 | 	color: #d3dae3;
246 | 	padding: 2px;
247 | }
248 | QCheckBox:disabled {
249 | 	color: #808086;
250 | 	padding: 2px;
251 | }
252 | 
253 | QCheckBox:hover {
254 | 	border-radius:4px;
255 | 	border-style:solid;
256 | 	padding-left: 1px;
257 | 	padding-right: 1px;
258 | 	padding-bottom: 1px;
259 | 	padding-top: 1px;
260 | 	border-width:1px;
261 | 	border-color: transparent;
262 | }
263 | QCheckBox::indicator:checked {
264 | 
265 | 	height: 10px;
266 | 	width: 10px;
267 | 	border-style:solid;
268 | 	border-width: 1px;
269 | 	border-color: #4fa08b;
270 | 	color: #000000;
271 | 	background-color: qradialgradient(cx:0.4, cy:0.4, radius: 1.5,fx:0, fy:0, stop:0 #1e282c, stop:0.3 #1e282c, stop:0.4 #4fa08b, stop:0.5 #1e282c, stop:1 #1e282c);
272 | }
273 | QCheckBox::indicator:unchecked {
274 | 
275 | 	height: 10px;
276 | 	width: 10px;
277 | 	border-style:solid;
278 | 	border-width: 1px;
279 | 	border-color: #4fa08b;
280 | 	color: #000000;
281 | }
282 | QRadioButton {
283 | 	color: #d3dae3;
284 | 	padding: 1px;
285 | }
286 | QRadioButton::indicator:checked {
287 | 	height: 10px;
288 | 	width: 10px;
289 | 	border-style:solid;
290 | 	border-radius:5px;
291 | 	border-width: 1px;
292 | 	border-color: #4fa08b;
293 | 	color: #a9b7c6;
294 | 	background-color: qradialgradient(cx:0.5, cy:0.5, radius:0.4,fx:0.5, fy:0.5, stop:0 #4fa08b, stop:1 #1e282c);
295 | }
296 | QRadioButton::indicator:!checked {
297 | 	height: 10px;
298 | 	width: 10px;
299 | 	border-style:solid;
300 | 	border-radius:5px;
301 | 	border-width: 1px;
302 | 	border-color: #4fa08b;
303 | 	color: #a9b7c6;
304 | 	background-color: transparent;
305 | }
306 | QStatusBar {
307 | 	color:#027f7f;
308 | }
309 | QSpinBox {
310 | 	color: #d3dae3;
311 | 	background-color: #222b2e;
312 | 	border-width: 1px;
313 | 	border-style: solid;
314 | 	border-color: #4fa08b;
315 | }
316 | QDoubleSpinBox {
317 | 	color: #d3dae3;
318 | 	background-color: #222b2e;
319 | 	border-width: 1px;
320 | 	border-style: solid;
321 | 	border-color: #4fa08b;
322 | }
323 | QTimeEdit {
324 | 	color: #d3dae3;
325 | 	background-color: #222b2e;
326 | 	border-width: 1px;
327 | 	border-style: solid;
328 | 	border-color: #4fa08b;
329 | }
330 | QDateTimeEdit {
331 | 	color: #d3dae3;
332 | 	background-color: #222b2e;
333 | 	border-width: 1px;
334 | 	border-style: solid;
335 | 	border-color: #4fa08b;
336 | }
337 | QDateEdit {
338 | 	color: #d3dae3;
339 | 	background-color: #222b2e;
340 | 	border-width: 1px;
341 | 	border-style: solid;
342 | 	border-color: #4fa08b;
343 | }
344 | QFontComboBox {
345 | 	color: #d3dae3;
346 | 	background-color: #222b2e;
347 | 	border-width: 1px;
348 | 	border-style: solid;
349 | 	border-color: #4fa08b;
350 | }
351 | QComboBox {
352 | 	color: #d3dae3;
353 | 	background-color: #222b2e;
354 | 	border-width: 1px;
355 | 	border-style: solid;
356 | 	border-color: #4fa08b;
357 | }
358 | 
359 | QDial {
360 | 	background: #16a085;
361 | }
362 | 
363 | QToolBox {
364 | 	color: #a9b7c6;
365 | 	background-color: #222b2e;
366 | }
367 | QToolBox::tab {
368 | 	color: #a9b7c6;
369 | 	background-color:#222b2e;
370 | }
371 | QToolBox::tab:selected {
372 | 	color: #FFFFFF;
373 | 	background-color:#222b2e;
374 | }
375 | QScrollArea {
376 | 	color: #FFFFFF;
377 | 	background-color:#222b2e;
378 | }
379 | QSlider::groove:horizontal {
380 | 	height: 5px;
381 | 	background-color: #52595d;
382 | }
383 | QSlider::groove:vertical {
384 | 	width: 5px;
385 | 	background-color: #52595d;
386 | }
387 | QSlider::handle:horizontal {
388 | 	background: #1a2224;
389 | 	border-style: solid;
390 | 	border-width: 1px;
391 | 	border-color: rgb(207,207,207);
392 | 	width: 12px;
393 | 	margin: -5px 0;
394 | 	border-radius: 7px;
395 | }
396 | QSlider::handle:vertical {
397 | 	background: #1a2224;
398 | 	border-style: solid;
399 | 	border-width: 1px;
400 | 	border-color: rgb(207,207,207);
401 | 	height: 12px;
402 | 	margin: 0 -5px;
403 | 	border-radius: 7px;
404 | }
405 | QSlider::add-page:horizontal {
406 |     background: #52595d;
407 | }
408 | QSlider::add-page:vertical {
409 |     background: #52595d;
410 | }
411 | QSlider::sub-page:horizontal {
412 |     background-color: #15433a;
413 | }
414 | QSlider::sub-page:vertical {
415 |     background-color: #15433a;
416 | }
417 | QScrollBar:horizontal {
418 | 	max-height: 10px;
419 | 	border: 1px transparent grey;
420 | 	margin: 0px 20px 0px 20px;
421 | 	background: transparent;
422 | }
423 | QScrollBar:vertical {
424 | 	max-width: 10px;
425 | 	border: 1px transparent grey;
426 | 	margin: 20px 0px 20px 0px;
427 | 	background: transparent;
428 | }
429 | QScrollBar::handle:horizontal {
430 | 	background: #52595d;
431 | 	border-style: transparent;
432 | 	border-radius: 4px;
433 | 	min-width: 25px;
434 | }
435 | QScrollBar::handle:horizontal:hover {
436 | 	background: #58a492;
437 | 	border-style: transparent;
438 | 	border-radius: 4px;
439 | 	min-width: 25px;
440 | }
441 | QScrollBar::handle:vertical {
442 | 	background: #52595d;
443 | 	border-style: transparent;
444 | 	border-radius: 4px;
445 | 	min-height: 25px;
446 | }
447 | QScrollBar::handle:vertical:hover {
448 | 	background: #58a492;
449 | 	border-style: transparent;
450 | 	border-radius: 4px;
451 | 	min-height: 25px;
452 | }
453 | QScrollBar::add-line:horizontal {
454 |    border: 2px transparent grey;
455 |    border-top-right-radius: 4px;
456 |    border-bottom-right-radius: 4px;
457 |    background: #15433a;
458 |    width: 20px;
459 |    subcontrol-position: right;
460 |    subcontrol-origin: margin;
461 | }
462 | QScrollBar::add-line:horizontal:pressed {
463 |    border: 2px transparent grey;
464 |    border-top-right-radius: 4px;
465 |    border-bottom-right-radius: 4px;
466 |    background: rgb(181,181,181);
467 |    width: 20px;
468 |    subcontrol-position: right;
469 |    subcontrol-origin: margin;
470 | }
471 | QScrollBar::add-line:vertical {
472 |    border: 2px transparent grey;
473 |    border-bottom-left-radius: 4px;
474 |    border-bottom-right-radius: 4px;
475 |    background: #15433a;
476 |    height: 20px;
477 |    subcontrol-position: bottom;
478 |    subcontrol-origin: margin;
479 | }
480 | QScrollBar::add-line:vertical:pressed {
481 |    border: 2px transparent grey;
482 |    border-bottom-left-radius: 4px;
483 |    border-bottom-right-radius: 4px;
484 |    background: rgb(181,181,181);
485 |    height: 20px;
486 |    subcontrol-position: bottom;
487 |    subcontrol-origin: margin;
488 | }
489 | QScrollBar::sub-line:horizontal {
490 |    border: 2px transparent grey;
491 |    border-top-left-radius: 4px;
492 |    border-bottom-left-radius: 4px;
493 |    background: #15433a;
494 |    width: 20px;
495 |    subcontrol-position: left;
496 |    subcontrol-origin: margin;
497 | }
498 | QScrollBar::sub-line:horizontal:pressed {
499 |    border: 2px transparent grey;
500 |    border-top-left-radius: 4px;
501 |    border-bottom-left-radius: 4px;
502 |    background: rgb(181,181,181);
503 |    width: 20px;
504 |    subcontrol-position: left;
505 |    subcontrol-origin: margin;
506 | }
507 | QScrollBar::sub-line:vertical {
508 |    border: 2px transparent grey;
509 |    border-top-left-radius: 4px;
510 |    border-top-right-radius: 4px;
511 |    background: #15433a;
512 |    height: 20px;
513 |    subcontrol-position: top;
514 |    subcontrol-origin: margin;
515 | }
516 | QScrollBar::sub-line:vertical:pressed {
517 |    border: 2px transparent grey;
518 |    border-top-left-radius: 4px;
519 |    border-top-right-radius: 4px;
520 |    background: rgb(181,181,181);
521 |    height: 20px;
522 |    subcontrol-position: top;
523 |    subcontrol-origin: margin;
524 | }
525 | 
526 | QScrollBar::add-page:horizontal, QScrollBar::sub-page:horizontal {
527 |    background: none;
528 | }
529 | QScrollBar::add-page:vertical, QScrollBar::sub-page:vertical {
530 |    background: none;
531 | }
532 | 


--------------------------------------------------------------------------------
/assets/ai.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/DataXujing/ncnn_android_yolov8/298db901d8520888e133e906ce73445ead3842ba/assets/ai.png


--------------------------------------------------------------------------------
/assets/icon.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/DataXujing/ncnn_android_yolov8/298db901d8520888e133e906ce73445ead3842ba/assets/icon.png


--------------------------------------------------------------------------------
/docs/demo1.gif:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/DataXujing/ncnn_android_yolov8/298db901d8520888e133e906ce73445ead3842ba/docs/demo1.gif


--------------------------------------------------------------------------------
/docs/demo2.gif:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/DataXujing/ncnn_android_yolov8/298db901d8520888e133e906ce73445ead3842ba/docs/demo2.gif


--------------------------------------------------------------------------------
/docs/p1.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/DataXujing/ncnn_android_yolov8/298db901d8520888e133e906ce73445ead3842ba/docs/p1.png


--------------------------------------------------------------------------------
/docs/p2.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/DataXujing/ncnn_android_yolov8/298db901d8520888e133e906ce73445ead3842ba/docs/p2.png


--------------------------------------------------------------------------------
/docs/p3.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/DataXujing/ncnn_android_yolov8/298db901d8520888e133e906ce73445ead3842ba/docs/p3.png


--------------------------------------------------------------------------------
/main.cpp:
--------------------------------------------------------------------------------
 1 | #include "widget.h"
 2 | 
 3 | #include "yolo.h"
 4 | 
 5 | #include <QApplication>
 6 | #include <QFile>
 7 | 
 8 | Yolo *yolov8 = new Yolo();
 9 | 
10 | int main(int argc, char *argv[])
11 | {
12 |     QApplication a(argc, argv);
13 | 
14 |     // 加载QSS
15 | 
16 |     QFile qss_(":/assets/ManjaroMix.qss");
17 |     if( qss_.open(QFile::ReadOnly)){
18 |         qDebug("open success");
19 |         QString style = QLatin1String(qss_.readAll());
20 |         a.setStyleSheet(style);
21 |         qss_.close();
22 |     }
23 |     else{
24 |        qDebug("Open failed");
25 |     }
26 | 
27 |     int target_size = 640;
28 |         float norm_vals[3] = { 1 / 255.f, 1 / 255.f, 1 / 255.f };
29 |         float mean_vals[3] = { 103.53f, 116.28f, 123.675f };
30 | 
31 |         yolov8->load(target_size, mean_vals,norm_vals);
32 | 
33 | 
34 | 
35 |     Widget w;
36 |     w.show();
37 |     return a.exec();
38 | }
39 | 


--------------------------------------------------------------------------------
/model/modules_ncnn.py:
--------------------------------------------------------------------------------
  1 | # Ultralytics YOLO 🚀, GPL-3.0 license
  2 | """
  3 | Common modules
  4 | """
  5 | 
  6 | import math
  7 | import warnings
  8 | from copy import copy
  9 | from pathlib import Path
 10 | 
 11 | import cv2
 12 | import numpy as np
 13 | import pandas as pd
 14 | import requests
 15 | import torch
 16 | import torch.nn as nn
 17 | from PIL import Image, ImageOps
 18 | from torch.cuda import amp
 19 | 
 20 | from ultralytics.nn.autobackend import AutoBackend
 21 | from ultralytics.yolo.data.augment import LetterBox
 22 | from ultralytics.yolo.utils import LOGGER, colorstr
 23 | from ultralytics.yolo.utils.files import increment_path
 24 | from ultralytics.yolo.utils.ops import Profile, make_divisible, non_max_suppression, scale_boxes, xyxy2xywh
 25 | from ultralytics.yolo.utils.plotting import Annotator, colors, save_one_box
 26 | from ultralytics.yolo.utils.tal import dist2bbox, make_anchors
 27 | from ultralytics.yolo.utils.torch_utils import copy_attr, smart_inference_mode
 28 | 
 29 | # from utils.plots import feature_visualization TODO
 30 | 
 31 | 
 32 | def autopad(k, p=None, d=1):  # kernel, padding, dilation
 33 |     # Pad to 'same' shape outputs
 34 |     if d > 1:
 35 |         k = d * (k - 1) + 1 if isinstance(k, int) else [d * (x - 1) + 1 for x in k]  # actual kernel-size
 36 |     if p is None:
 37 |         p = k // 2 if isinstance(k, int) else [x // 2 for x in k]  # auto-pad
 38 |     return p
 39 | 
 40 | 
 41 | class Conv(nn.Module):
 42 |     # Standard convolution with args(ch_in, ch_out, kernel, stride, padding, groups, dilation, activation)
 43 |     default_act = nn.SiLU()  # default activation
 44 | 
 45 |     def __init__(self, c1, c2, k=1, s=1, p=None, g=1, d=1, act=True):
 46 |         super().__init__()
 47 |         self.conv = nn.Conv2d(c1, c2, k, s, autopad(k, p, d), groups=g, dilation=d, bias=False)
 48 |         self.bn = nn.BatchNorm2d(c2)
 49 |         self.act = self.default_act if act is True else act if isinstance(act, nn.Module) else nn.Identity()
 50 | 
 51 |     def forward(self, x):
 52 |         return self.act(self.bn(self.conv(x)))
 53 | 
 54 |     def forward_fuse(self, x):
 55 |         return self.act(self.conv(x))
 56 | 
 57 | 
 58 | class DWConv(Conv):
 59 |     # Depth-wise convolution
 60 |     def __init__(self, c1, c2, k=1, s=1, d=1, act=True):  # ch_in, ch_out, kernel, stride, dilation, activation
 61 |         super().__init__(c1, c2, k, s, g=math.gcd(c1, c2), d=d, act=act)
 62 | 
 63 | 
 64 | class DWConvTranspose2d(nn.ConvTranspose2d):
 65 |     # Depth-wise transpose convolution
 66 |     def __init__(self, c1, c2, k=1, s=1, p1=0, p2=0):  # ch_in, ch_out, kernel, stride, padding, padding_out
 67 |         super().__init__(c1, c2, k, s, p1, p2, groups=math.gcd(c1, c2))
 68 | 
 69 | 
 70 | class ConvTranspose(nn.Module):
 71 |     # Convolution transpose 2d layer
 72 |     default_act = nn.SiLU()  # default activation
 73 | 
 74 |     def __init__(self, c1, c2, k=2, s=2, p=0, bn=True, act=True):
 75 |         super().__init__()
 76 |         self.conv_transpose = nn.ConvTranspose2d(c1, c2, k, s, p, bias=not bn)
 77 |         self.bn = nn.BatchNorm2d(c2) if bn else nn.Identity()
 78 |         self.act = self.default_act if act is True else act if isinstance(act, nn.Module) else nn.Identity()
 79 | 
 80 |     def forward(self, x):
 81 |         return self.act(self.bn(self.conv_transpose(x)))
 82 | 
 83 | 
 84 | class DFL(nn.Module):
 85 |     # DFL module
 86 |     def __init__(self, c1=16):
 87 |         super().__init__()
 88 |         self.conv = nn.Conv2d(c1, 1, 1, bias=False).requires_grad_(False)
 89 |         x = torch.arange(c1, dtype=torch.float)
 90 |         self.conv.weight.data[:] = nn.Parameter(x.view(1, c1, 1, 1))
 91 |         self.c1 = c1
 92 | 
 93 |     def forward(self, x):
 94 |         b, c, a = x.shape  # batch, channels, anchors
 95 |         return self.conv(x.view(b, 4, self.c1, a).transpose(2, 1).softmax(1)).view(b, 4, a)
 96 |         # return self.conv(x.view(b, self.c1, 4, a).softmax(1)).view(b, 4, a)
 97 | 
 98 | 
 99 | class TransformerLayer(nn.Module):
100 |     # Transformer layer https://arxiv.org/abs/2010.11929 (LayerNorm layers removed for better performance)
101 |     def __init__(self, c, num_heads):
102 |         super().__init__()
103 |         self.q = nn.Linear(c, c, bias=False)
104 |         self.k = nn.Linear(c, c, bias=False)
105 |         self.v = nn.Linear(c, c, bias=False)
106 |         self.ma = nn.MultiheadAttention(embed_dim=c, num_heads=num_heads)
107 |         self.fc1 = nn.Linear(c, c, bias=False)
108 |         self.fc2 = nn.Linear(c, c, bias=False)
109 | 
110 |     def forward(self, x):
111 |         x = self.ma(self.q(x), self.k(x), self.v(x))[0] + x
112 |         x = self.fc2(self.fc1(x)) + x
113 |         return x
114 | 
115 | 
116 | class TransformerBlock(nn.Module):
117 |     # Vision Transformer https://arxiv.org/abs/2010.11929
118 |     def __init__(self, c1, c2, num_heads, num_layers):
119 |         super().__init__()
120 |         self.conv = None
121 |         if c1 != c2:
122 |             self.conv = Conv(c1, c2)
123 |         self.linear = nn.Linear(c2, c2)  # learnable position embedding
124 |         self.tr = nn.Sequential(*(TransformerLayer(c2, num_heads) for _ in range(num_layers)))
125 |         self.c2 = c2
126 | 
127 |     def forward(self, x):
128 |         if self.conv is not None:
129 |             x = self.conv(x)
130 |         b, _, w, h = x.shape
131 |         p = x.flatten(2).permute(2, 0, 1)
132 |         return self.tr(p + self.linear(p)).permute(1, 2, 0).reshape(b, self.c2, w, h)
133 | 
134 | 
135 | class Bottleneck(nn.Module):
136 |     # Standard bottleneck
137 |     def __init__(self, c1, c2, shortcut=True, g=1, k=(3, 3), e=0.5):  # ch_in, ch_out, shortcut, kernels, groups, expand
138 |         super().__init__()
139 |         c_ = int(c2 * e)  # hidden channels
140 |         self.cv1 = Conv(c1, c_, k[0], 1)
141 |         self.cv2 = Conv(c_, c2, k[1], 1, g=g)
142 |         self.add = shortcut and c1 == c2
143 | 
144 |     def forward(self, x):
145 |         return x + self.cv2(self.cv1(x)) if self.add else self.cv2(self.cv1(x))
146 | 
147 | 
148 | class BottleneckCSP(nn.Module):
149 |     # CSP Bottleneck https://github.com/WongKinYiu/CrossStagePartialNetworks
150 |     def __init__(self, c1, c2, n=1, shortcut=True, g=1, e=0.5):  # ch_in, ch_out, number, shortcut, groups, expansion
151 |         super().__init__()
152 |         c_ = int(c2 * e)  # hidden channels
153 |         self.cv1 = Conv(c1, c_, 1, 1)
154 |         self.cv2 = nn.Conv2d(c1, c_, 1, 1, bias=False)
155 |         self.cv3 = nn.Conv2d(c_, c_, 1, 1, bias=False)
156 |         self.cv4 = Conv(2 * c_, c2, 1, 1)
157 |         self.bn = nn.BatchNorm2d(2 * c_)  # applied to cat(cv2, cv3)
158 |         self.act = nn.SiLU()
159 |         self.m = nn.Sequential(*(Bottleneck(c_, c_, shortcut, g, e=1.0) for _ in range(n)))
160 | 
161 |     def forward(self, x):
162 |         y1 = self.cv3(self.m(self.cv1(x)))
163 |         y2 = self.cv2(x)
164 |         return self.cv4(self.act(self.bn(torch.cat((y1, y2), 1))))
165 | 
166 | 
167 | class C3(nn.Module):
168 |     # CSP Bottleneck with 3 convolutions
169 |     def __init__(self, c1, c2, n=1, shortcut=True, g=1, e=0.5):  # ch_in, ch_out, number, shortcut, groups, expansion
170 |         super().__init__()
171 |         c_ = int(c2 * e)  # hidden channels
172 |         self.cv1 = Conv(c1, c_, 1, 1)
173 |         self.cv2 = Conv(c1, c_, 1, 1)
174 |         self.cv3 = Conv(2 * c_, c2, 1)  # optional act=FReLU(c2)
175 |         self.m = nn.Sequential(*(Bottleneck(c_, c_, shortcut, g, e=1.0) for _ in range(n)))
176 | 
177 |     def forward(self, x):
178 |         return self.cv3(torch.cat((self.m(self.cv1(x)), self.cv2(x)), 1))
179 | 
180 | 
181 | class C2(nn.Module):
182 |     # CSP Bottleneck with 2 convolutions
183 |     def __init__(self, c1, c2, n=1, shortcut=True, g=1, e=0.5):  # ch_in, ch_out, number, shortcut, groups, expansion
184 |         super().__init__()
185 |         self.c = int(c2 * e)  # hidden channels
186 |         self.cv1 = Conv(c1, 2 * self.c, 1, 1)
187 |         self.cv2 = Conv(2 * self.c, c2, 1)  # optional act=FReLU(c2)
188 |         # self.attention = ChannelAttention(2 * self.c)  # or SpatialAttention()
189 |         self.m = nn.Sequential(*(Bottleneck(self.c, self.c, shortcut, g, k=((3, 3), (3, 3)), e=1.0) for _ in range(n)))
190 | 
191 |     def forward(self, x):
192 |         a, b = self.cv1(x).split((self.c, self.c), 1)
193 |         return self.cv2(torch.cat((self.m(a), b), 1))
194 | 
195 | 
196 | class C2f(nn.Module):
197 |     # CSP Bottleneck with 2 convolutions
198 |     def __init__(self, c1, c2, n=1, shortcut=False, g=1, e=0.5):  # ch_in, ch_out, number, shortcut, groups, expansion
199 |         super().__init__()
200 |         self.c = int(c2 * e)  # hidden channels
201 |         self.cv1 = Conv(c1, 2 * self.c, 1, 1)
202 |         self.cv2 = Conv((2 + n) * self.c, c2, 1)  # optional act=FReLU(c2)
203 |         self.m = nn.ModuleList(Bottleneck(self.c, self.c, shortcut, g, k=((3, 3), (3, 3)), e=1.0) for _ in range(n))
204 | 
205 |     # <-----------------------------------------------------
206 |     def forward(self, x):
207 |         # y = list(self.cv1(x).split((self.c, self.c), 1))
208 |         # y.extend(m(y[-1]) for m in self.m)
209 |         # return self.cv2(torch.cat(y, 1))
210 | 
211 |         x = self.cv1(x)
212 |         x = [x, x[:, self.c:, ...]]
213 |         x.extend(m(x[-1]) for m in self.m)
214 |         x.pop(1)
215 |         return self.cv2(torch.cat(x, 1))
216 | 
217 | 
218 | 
219 | 
220 | class ChannelAttention(nn.Module):
221 |     # Channel-attention module https://github.com/open-mmlab/mmdetection/tree/v3.0.0rc1/configs/rtmdet
222 |     def __init__(self, channels: int) -> None:
223 |         super().__init__()
224 |         self.pool = nn.AdaptiveAvgPool2d(1)
225 |         self.fc = nn.Conv2d(channels, channels, 1, 1, 0, bias=True)
226 |         self.act = nn.Sigmoid()
227 | 
228 |     def forward(self, x: torch.Tensor) -> torch.Tensor:
229 |         return x * self.act(self.fc(self.pool(x)))
230 | 
231 | 
232 | class SpatialAttention(nn.Module):
233 |     # Spatial-attention module
234 |     def __init__(self, kernel_size=7):
235 |         super().__init__()
236 |         assert kernel_size in (3, 7), 'kernel size must be 3 or 7'
237 |         padding = 3 if kernel_size == 7 else 1
238 |         self.cv1 = nn.Conv2d(2, 1, kernel_size, padding=padding, bias=False)
239 |         self.act = nn.Sigmoid()
240 | 
241 |     def forward(self, x):
242 |         return x * self.act(self.cv1(torch.cat([torch.mean(x, 1, keepdim=True), torch.max(x, 1, keepdim=True)[0]], 1)))
243 | 
244 | 
245 | class CBAM(nn.Module):
246 |     # CSP Bottleneck with 3 convolutions
247 |     def __init__(self, c1, ratio=16, kernel_size=7):  # ch_in, ch_out, number, shortcut, groups, expansion
248 |         super().__init__()
249 |         self.channel_attention = ChannelAttention(c1)
250 |         self.spatial_attention = SpatialAttention(kernel_size)
251 | 
252 |     def forward(self, x):
253 |         return self.spatial_attention(self.channel_attention(x))
254 | 
255 | 
256 | class C1(nn.Module):
257 |     # CSP Bottleneck with 3 convolutions
258 |     def __init__(self, c1, c2, n=1):  # ch_in, ch_out, number, shortcut, groups, expansion
259 |         super().__init__()
260 |         self.cv1 = Conv(c1, c2, 1, 1)
261 |         self.m = nn.Sequential(*(Conv(c2, c2, 3) for _ in range(n)))
262 | 
263 |     def forward(self, x):
264 |         y = self.cv1(x)
265 |         return self.m(y) + y
266 | 
267 | 
268 | class C3x(C3):
269 |     # C3 module with cross-convolutions
270 |     def __init__(self, c1, c2, n=1, shortcut=True, g=1, e=0.5):
271 |         super().__init__(c1, c2, n, shortcut, g, e)
272 |         self.c_ = int(c2 * e)
273 |         self.m = nn.Sequential(*(Bottleneck(self.c_, self.c_, shortcut, g, k=((1, 3), (3, 1)), e=1) for _ in range(n)))
274 | 
275 | 
276 | class C3TR(C3):
277 |     # C3 module with TransformerBlock()
278 |     def __init__(self, c1, c2, n=1, shortcut=True, g=1, e=0.5):
279 |         super().__init__(c1, c2, n, shortcut, g, e)
280 |         c_ = int(c2 * e)
281 |         self.m = TransformerBlock(c_, c_, 4, n)
282 | 
283 | 
284 | class C3Ghost(C3):
285 |     # C3 module with GhostBottleneck()
286 |     def __init__(self, c1, c2, n=1, shortcut=True, g=1, e=0.5):
287 |         super().__init__(c1, c2, n, shortcut, g, e)
288 |         c_ = int(c2 * e)  # hidden channels
289 |         self.m = nn.Sequential(*(GhostBottleneck(c_, c_) for _ in range(n)))
290 | 
291 | 
292 | class SPP(nn.Module):
293 |     # Spatial Pyramid Pooling (SPP) layer https://arxiv.org/abs/1406.4729
294 |     def __init__(self, c1, c2, k=(5, 9, 13)):
295 |         super().__init__()
296 |         c_ = c1 // 2  # hidden channels
297 |         self.cv1 = Conv(c1, c_, 1, 1)
298 |         self.cv2 = Conv(c_ * (len(k) + 1), c2, 1, 1)
299 |         self.m = nn.ModuleList([nn.MaxPool2d(kernel_size=x, stride=1, padding=x // 2) for x in k])
300 | 
301 |     def forward(self, x):
302 |         x = self.cv1(x)
303 |         with warnings.catch_warnings():
304 |             warnings.simplefilter('ignore')  # suppress torch 1.9.0 max_pool2d() warning
305 |             return self.cv2(torch.cat([x] + [m(x) for m in self.m], 1))
306 | 
307 | 
308 | class SPPF(nn.Module):
309 |     # Spatial Pyramid Pooling - Fast (SPPF) layer for YOLOv5 by Glenn Jocher
310 |     def __init__(self, c1, c2, k=5):  # equivalent to SPP(k=(5, 9, 13))
311 |         super().__init__()
312 |         c_ = c1 // 2  # hidden channels
313 |         self.cv1 = Conv(c1, c_, 1, 1)
314 |         self.cv2 = Conv(c_ * 4, c2, 1, 1)
315 |         self.m = nn.MaxPool2d(kernel_size=k, stride=1, padding=k // 2)
316 | 
317 |     def forward(self, x):
318 |         x = self.cv1(x)
319 |         with warnings.catch_warnings():
320 |             warnings.simplefilter('ignore')  # suppress torch 1.9.0 max_pool2d() warning
321 |             y1 = self.m(x)
322 |             y2 = self.m(y1)
323 |             return self.cv2(torch.cat((x, y1, y2, self.m(y2)), 1))
324 | 
325 | 
326 | class Focus(nn.Module):
327 |     # Focus wh information into c-space
328 |     def __init__(self, c1, c2, k=1, s=1, p=None, g=1, act=True):  # ch_in, ch_out, kernel, stride, padding, groups
329 |         super().__init__()
330 |         self.conv = Conv(c1 * 4, c2, k, s, p, g, act=act)
331 |         # self.contract = Contract(gain=2)
332 | 
333 |     def forward(self, x):  # x(b,c,w,h) -> y(b,4c,w/2,h/2)
334 |         return self.conv(torch.cat((x[..., ::2, ::2], x[..., 1::2, ::2], x[..., ::2, 1::2], x[..., 1::2, 1::2]), 1))
335 |         # return self.conv(self.contract(x))
336 | 
337 | 
338 | class GhostConv(nn.Module):
339 |     # Ghost Convolution https://github.com/huawei-noah/ghostnet
340 |     def __init__(self, c1, c2, k=1, s=1, g=1, act=True):  # ch_in, ch_out, kernel, stride, groups
341 |         super().__init__()
342 |         c_ = c2 // 2  # hidden channels
343 |         self.cv1 = Conv(c1, c_, k, s, None, g, act=act)
344 |         self.cv2 = Conv(c_, c_, 5, 1, None, c_, act=act)
345 | 
346 |     def forward(self, x):
347 |         y = self.cv1(x)
348 |         return torch.cat((y, self.cv2(y)), 1)
349 | 
350 | 
351 | class GhostBottleneck(nn.Module):
352 |     # Ghost Bottleneck https://github.com/huawei-noah/ghostnet
353 |     def __init__(self, c1, c2, k=3, s=1):  # ch_in, ch_out, kernel, stride
354 |         super().__init__()
355 |         c_ = c2 // 2
356 |         self.conv = nn.Sequential(
357 |             GhostConv(c1, c_, 1, 1),  # pw
358 |             DWConv(c_, c_, k, s, act=False) if s == 2 else nn.Identity(),  # dw
359 |             GhostConv(c_, c2, 1, 1, act=False))  # pw-linear
360 |         self.shortcut = nn.Sequential(DWConv(c1, c1, k, s, act=False), Conv(c1, c2, 1, 1,
361 |                                                                             act=False)) if s == 2 else nn.Identity()
362 | 
363 |     def forward(self, x):
364 |         return self.conv(x) + self.shortcut(x)
365 | 
366 | 
367 | class Concat(nn.Module):
368 |     # Concatenate a list of tensors along dimension
369 |     def __init__(self, dimension=1):
370 |         super().__init__()
371 |         self.d = dimension
372 | 
373 |     def forward(self, x):
374 |         return torch.cat(x, self.d)
375 | 
376 | 
377 | class AutoShape(nn.Module):
378 |     # YOLOv5 input-robust model wrapper for passing cv2/np/PIL/torch inputs. Includes preprocessing, inference and NMS
379 |     conf = 0.25  # NMS confidence threshold
380 |     iou = 0.45  # NMS IoU threshold
381 |     agnostic = False  # NMS class-agnostic
382 |     multi_label = False  # NMS multiple labels per box
383 |     classes = None  # (optional list) filter by class, i.e. = [0, 15, 16] for COCO persons, cats and dogs
384 |     max_det = 1000  # maximum number of detections per image
385 |     amp = False  # Automatic Mixed Precision (AMP) inference
386 | 
387 |     def __init__(self, model, verbose=True):
388 |         super().__init__()
389 |         if verbose:
390 |             LOGGER.info('Adding AutoShape... ')
391 |         copy_attr(self, model, include=('yaml', 'nc', 'hyp', 'names', 'stride', 'abc'), exclude=())  # copy attributes
392 |         self.dmb = isinstance(model, AutoBackend)  # DetectMultiBackend() instance
393 |         self.pt = not self.dmb or model.pt  # PyTorch model
394 |         self.model = model.eval()
395 |         if self.pt:
396 |             m = self.model.model.model[-1] if self.dmb else self.model.model[-1]  # Detect()
397 |             m.inplace = False  # Detect.inplace=False for safe multithread inference
398 |             m.export = True  # do not output loss values
399 | 
400 |     def _apply(self, fn):
401 |         # Apply to(), cpu(), cuda(), half() to model tensors that are not parameters or registered buffers
402 |         self = super()._apply(fn)
403 |         if self.pt:
404 |             m = self.model.model.model[-1] if self.dmb else self.model.model[-1]  # Detect()
405 |             m.stride = fn(m.stride)
406 |             m.grid = list(map(fn, m.grid))
407 |             if isinstance(m.anchor_grid, list):
408 |                 m.anchor_grid = list(map(fn, m.anchor_grid))
409 |         return self
410 | 
411 |     @smart_inference_mode()
412 |     def forward(self, ims, size=640, augment=False, profile=False):
413 |         # Inference from various sources. For size(height=640, width=1280), RGB images example inputs are:
414 |         #   file:        ims = 'data/images/zidane.jpg'  # str or PosixPath
415 |         #   URI:             = 'https://ultralytics.com/images/zidane.jpg'
416 |         #   OpenCV:          = cv2.imread('image.jpg')[:,:,::-1]  # HWC BGR to RGB x(640,1280,3)
417 |         #   PIL:             = Image.open('image.jpg') or ImageGrab.grab()  # HWC x(640,1280,3)
418 |         #   numpy:           = np.zeros((640,1280,3))  # HWC
419 |         #   torch:           = torch.zeros(16,3,320,640)  # BCHW (scaled to size=640, 0-1 values)
420 |         #   multiple:        = [Image.open('image1.jpg'), Image.open('image2.jpg'), ...]  # list of images
421 | 
422 |         dt = (Profile(), Profile(), Profile())
423 |         with dt[0]:
424 |             if isinstance(size, int):  # expand
425 |                 size = (size, size)
426 |             p = next(self.model.parameters()) if self.pt else torch.empty(1, device=self.model.device)  # param
427 |             autocast = self.amp and (p.device.type != 'cpu')  # Automatic Mixed Precision (AMP) inference
428 |             if isinstance(ims, torch.Tensor):  # torch
429 |                 with amp.autocast(autocast):
430 |                     return self.model(ims.to(p.device).type_as(p), augment=augment)  # inference
431 | 
432 |             # Pre-process
433 |             n, ims = (len(ims), list(ims)) if isinstance(ims, (list, tuple)) else (1, [ims])  # number, list of images
434 |             shape0, shape1, files = [], [], []  # image and inference shapes, filenames
435 |             for i, im in enumerate(ims):
436 |                 f = f'image{i}'  # filename
437 |                 if isinstance(im, (str, Path)):  # filename or uri
438 |                     im, f = Image.open(requests.get(im, stream=True).raw if str(im).startswith('http') else im), im
439 |                     im = np.asarray(ImageOps.exif_transpose(im))
440 |                 elif isinstance(im, Image.Image):  # PIL Image
441 |                     im, f = np.asarray(ImageOps.exif_transpose(im)), getattr(im, 'filename', f) or f
442 |                 files.append(Path(f).with_suffix('.jpg').name)
443 |                 if im.shape[0] < 5:  # image in CHW
444 |                     im = im.transpose((1, 2, 0))  # reverse dataloader .transpose(2, 0, 1)
445 |                 im = im[..., :3] if im.ndim == 3 else cv2.cvtColor(im, cv2.COLOR_GRAY2BGR)  # enforce 3ch input
446 |                 s = im.shape[:2]  # HWC
447 |                 shape0.append(s)  # image shape
448 |                 g = max(size) / max(s)  # gain
449 |                 shape1.append([y * g for y in s])
450 |                 ims[i] = im if im.data.contiguous else np.ascontiguousarray(im)  # update
451 |             shape1 = [make_divisible(x, self.stride) for x in np.array(shape1).max(0)] if self.pt else size  # inf shape
452 |             x = [LetterBox(shape1, auto=False)(image=im)["img"] for im in ims]  # pad
453 |             x = np.ascontiguousarray(np.array(x).transpose((0, 3, 1, 2)))  # stack and BHWC to BCHW
454 |             x = torch.from_numpy(x).to(p.device).type_as(p) / 255  # uint8 to fp16/32
455 | 
456 |         with amp.autocast(autocast):
457 |             # Inference
458 |             with dt[1]:
459 |                 y = self.model(x, augment=augment)  # forward
460 | 
461 |             # Post-process
462 |             with dt[2]:
463 |                 y = non_max_suppression(y if self.dmb else y[0],
464 |                                         self.conf,
465 |                                         self.iou,
466 |                                         self.classes,
467 |                                         self.agnostic,
468 |                                         self.multi_label,
469 |                                         max_det=self.max_det)  # NMS
470 |                 for i in range(n):
471 |                     scale_boxes(shape1, y[i][:, :4], shape0[i])
472 | 
473 |             return Detections(ims, y, files, dt, self.names, x.shape)
474 | 
475 | 
476 | class Detections:
477 |     # YOLOv5 detections class for inference results
478 |     def __init__(self, ims, pred, files, times=(0, 0, 0), names=None, shape=None):
479 |         super().__init__()
480 |         d = pred[0].device  # device
481 |         gn = [torch.tensor([*(im.shape[i] for i in [1, 0, 1, 0]), 1, 1], device=d) for im in ims]  # normalizations
482 |         self.ims = ims  # list of images as numpy arrays
483 |         self.pred = pred  # list of tensors pred[0] = (xyxy, conf, cls)
484 |         self.names = names  # class names
485 |         self.files = files  # image filenames
486 |         self.times = times  # profiling times
487 |         self.xyxy = pred  # xyxy pixels
488 |         self.xywh = [xyxy2xywh(x) for x in pred]  # xywh pixels
489 |         self.xyxyn = [x / g for x, g in zip(self.xyxy, gn)]  # xyxy normalized
490 |         self.xywhn = [x / g for x, g in zip(self.xywh, gn)]  # xywh normalized
491 |         self.n = len(self.pred)  # number of images (batch size)
492 |         self.t = tuple(x.t / self.n * 1E3 for x in times)  # timestamps (ms)
493 |         self.s = tuple(shape)  # inference BCHW shape
494 | 
495 |     def _run(self, pprint=False, show=False, save=False, crop=False, render=False, labels=True, save_dir=Path('')):
496 |         s, crops = '', []
497 |         for i, (im, pred) in enumerate(zip(self.ims, self.pred)):
498 |             s += f'\nimage {i + 1}/{len(self.pred)}: {im.shape[0]}x{im.shape[1]} '  # string
499 |             if pred.shape[0]:
500 |                 for c in pred[:, -1].unique():
501 |                     n = (pred[:, -1] == c).sum()  # detections per class
502 |                     s += f"{n} {self.names[int(c)]}{'s' * (n > 1)}, "  # add to string
503 |                 s = s.rstrip(', ')
504 |                 if show or save or render or crop:
505 |                     annotator = Annotator(im, example=str(self.names))
506 |                     for *box, conf, cls in reversed(pred):  # xyxy, confidence, class
507 |                         label = f'{self.names[int(cls)]} {conf:.2f}'
508 |                         if crop:
509 |                             file = save_dir / 'crops' / self.names[int(cls)] / self.files[i] if save else None
510 |                             crops.append({
511 |                                 'box': box,
512 |                                 'conf': conf,
513 |                                 'cls': cls,
514 |                                 'label': label,
515 |                                 'im': save_one_box(box, im, file=file, save=save)})
516 |                         else:  # all others
517 |                             annotator.box_label(box, label if labels else '', color=colors(cls))
518 |                     im = annotator.im
519 |             else:
520 |                 s += '(no detections)'
521 | 
522 |             im = Image.fromarray(im.astype(np.uint8)) if isinstance(im, np.ndarray) else im  # from np
523 |             if show:
524 |                 im.show(self.files[i])  # show
525 |             if save:
526 |                 f = self.files[i]
527 |                 im.save(save_dir / f)  # save
528 |                 if i == self.n - 1:
529 |                     LOGGER.info(f"Saved {self.n} image{'s' * (self.n > 1)} to {colorstr('bold', save_dir)}")
530 |             if render:
531 |                 self.ims[i] = np.asarray(im)
532 |         if pprint:
533 |             s = s.lstrip('\n')
534 |             return f'{s}\nSpeed: %.1fms pre-process, %.1fms inference, %.1fms NMS per image at shape {self.s}' % self.t
535 |         if crop:
536 |             if save:
537 |                 LOGGER.info(f'Saved results to {save_dir}\n')
538 |             return crops
539 | 
540 |     def show(self, labels=True):
541 |         self._run(show=True, labels=labels)  # show results
542 | 
543 |     def save(self, labels=True, save_dir='runs/detect/exp', exist_ok=False):
544 |         save_dir = increment_path(save_dir, exist_ok, mkdir=True)  # increment save_dir
545 |         self._run(save=True, labels=labels, save_dir=save_dir)  # save results
546 | 
547 |     def crop(self, save=True, save_dir='runs/detect/exp', exist_ok=False):
548 |         save_dir = increment_path(save_dir, exist_ok, mkdir=True) if save else None
549 |         return self._run(crop=True, save=save, save_dir=save_dir)  # crop results
550 | 
551 |     def render(self, labels=True):
552 |         self._run(render=True, labels=labels)  # render results
553 |         return self.ims
554 | 
555 |     def pandas(self):
556 |         # return detections as pandas DataFrames, i.e. print(results.pandas().xyxy[0])
557 |         new = copy(self)  # return copy
558 |         ca = 'xmin', 'ymin', 'xmax', 'ymax', 'confidence', 'class', 'name'  # xyxy columns
559 |         cb = 'xcenter', 'ycenter', 'width', 'height', 'confidence', 'class', 'name'  # xywh columns
560 |         for k, c in zip(['xyxy', 'xyxyn', 'xywh', 'xywhn'], [ca, ca, cb, cb]):
561 |             a = [[x[:5] + [int(x[5]), self.names[int(x[5])]] for x in x.tolist()] for x in getattr(self, k)]  # update
562 |             setattr(new, k, [pd.DataFrame(x, columns=c) for x in a])
563 |         return new
564 | 
565 |     def tolist(self):
566 |         # return a list of Detections objects, i.e. 'for result in results.tolist():'
567 |         r = range(self.n)  # iterable
568 |         x = [Detections([self.ims[i]], [self.pred[i]], [self.files[i]], self.times, self.names, self.s) for i in r]
569 |         # for d in x:
570 |         #    for k in ['ims', 'pred', 'xyxy', 'xyxyn', 'xywh', 'xywhn']:
571 |         #        setattr(d, k, getattr(d, k)[0])  # pop out of list
572 |         return x
573 | 
574 |     def print(self):
575 |         LOGGER.info(self.__str__())
576 | 
577 |     def __len__(self):  # override len(results)
578 |         return self.n
579 | 
580 |     def __str__(self):  # override print(results)
581 |         return self._run(pprint=True)  # print results
582 | 
583 |     def __repr__(self):
584 |         return f'YOLOv5 {self.__class__} instance\n' + self.__str__()
585 | 
586 | 
587 | class Proto(nn.Module):
588 |     # YOLOv8 mask Proto module for segmentation models
589 |     def __init__(self, c1, c_=256, c2=32):  # ch_in, number of protos, number of masks
590 |         super().__init__()
591 |         self.cv1 = Conv(c1, c_, k=3)
592 |         self.upsample = nn.ConvTranspose2d(c_, c_, 2, 2, 0, bias=True)  # nn.Upsample(scale_factor=2, mode='nearest')
593 |         self.cv2 = Conv(c_, c_, k=3)
594 |         self.cv3 = Conv(c_, c2)
595 | 
596 |     def forward(self, x):
597 |         return self.cv3(self.cv2(self.upsample(self.cv1(x))))
598 | 
599 | 
600 | class Ensemble(nn.ModuleList):
601 |     # Ensemble of models
602 |     def __init__(self):
603 |         super().__init__()
604 | 
605 |     def forward(self, x, augment=False, profile=False, visualize=False):
606 |         y = [module(x, augment, profile, visualize)[0] for module in self]
607 |         # y = torch.stack(y).max(0)[0]  # max ensemble
608 |         # y = torch.stack(y).mean(0)  # mean ensemble
609 |         y = torch.cat(y, 1)  # nms ensemble
610 |         return y, None  # inference, train output
611 | 
612 | 
613 | # heads  # <---------------------------------------
614 | class Detect(nn.Module):
615 |     # YOLOv5 Detect head for detection models
616 |     dynamic = False  # force grid reconstruction
617 |     export = False  # export mode
618 |     shape = None
619 |     anchors = torch.empty(0)  # init
620 |     strides = torch.empty(0)  # init
621 | 
622 |     def __init__(self, nc=80, ch=()):  # detection layer
623 |         super().__init__()
624 |         self.nc = nc  # number of classes
625 |         self.nl = len(ch)  # number of detection layers
626 |         self.reg_max = 16  # DFL channels (ch[0] // 16 to scale 4/8/12/16/20 for n/s/m/l/x)
627 |         self.no = nc + self.reg_max * 4  # number of outputs per anchor
628 |         self.stride = torch.zeros(self.nl)  # strides computed during build
629 | 
630 |         c2, c3 = max((16, ch[0] // 4, self.reg_max * 4)), max(ch[0], self.nc)  # channels
631 |         self.cv2 = nn.ModuleList(
632 |             nn.Sequential(Conv(x, c2, 3), Conv(c2, c2, 3), nn.Conv2d(c2, 4 * self.reg_max, 1)) for x in ch)
633 |         self.cv3 = nn.ModuleList(nn.Sequential(Conv(x, c3, 3), Conv(c3, c3, 3), nn.Conv2d(c3, self.nc, 1)) for x in ch)
634 |         self.dfl = DFL(self.reg_max) if self.reg_max > 1 else nn.Identity()
635 | 
636 |     def forward(self, x):
637 |         shape = x[0].shape  # BCHW
638 |         for i in range(self.nl):
639 |             x[i] = torch.cat((self.cv2[i](x[i]), self.cv3[i](x[i])), 1)
640 | 
641 | 
642 |         if self.training:
643 |             return x
644 |         elif self.dynamic or self.shape != shape:
645 |             self.anchors, self.strides = (x.transpose(0, 1) for x in make_anchors(x, self.stride, 0.5))
646 |             self.shape = shape
647 | 
648 |         # 修改成这样的return
649 |         return torch.cat([xi.view(shape[0], self.no, -1) for xi in x], 2).permute(0, 2,1)
650 | 
651 |         # box, cls = torch.cat([xi.view(shape[0], self.no, -1) for xi in x], 2).split((self.reg_max * 4, self.nc), 1)
652 |         # dbox = dist2bbox(self.dfl(box), self.anchors.unsqueeze(0), xywh=True, dim=1) * self.strides
653 |         # y = torch.cat((dbox, cls.sigmoid()), 1)
654 |         # return y if self.export else (y, x)
655 | 
656 |     def bias_init(self):
657 |         # Initialize Detect() biases, WARNING: requires stride availability
658 |         m = self  # self.model[-1]  # Detect() module
659 |         # cf = torch.bincount(torch.tensor(np.concatenate(dataset.labels, 0)[:, 0]).long(), minlength=nc) + 1
660 |         # ncf = math.log(0.6 / (m.nc - 0.999999)) if cf is None else torch.log(cf / cf.sum())  # nominal class frequency
661 |         for a, b, s in zip(m.cv2, m.cv3, m.stride):  # from
662 |             a[-1].bias.data[:] = 1.0  # box
663 |             b[-1].bias.data[:m.nc] = math.log(5 / m.nc / (640 / s) ** 2)  # cls (.01 objects, 80 classes, 640 img)
664 | 
665 | 
666 | class Segment(Detect):
667 |     # YOLOv5 Segment head for segmentation models
668 |     def __init__(self, nc=80, nm=32, npr=256, ch=()):
669 |         super().__init__(nc, ch)
670 |         self.nm = nm  # number of masks
671 |         self.npr = npr  # number of protos
672 |         self.proto = Proto(ch[0], self.npr, self.nm)  # protos
673 |         self.detect = Detect.forward
674 | 
675 |         c4 = max(ch[0] // 4, self.nm)
676 |         self.cv4 = nn.ModuleList(nn.Sequential(Conv(x, c4, 3), Conv(c4, c4, 3), nn.Conv2d(c4, self.nm, 1)) for x in ch)
677 | 
678 |     def forward(self, x):
679 |         p = self.proto(x[0])  # mask protos
680 |         bs = p.shape[0]  # batch size
681 | 
682 |         mc = torch.cat([self.cv4[i](x[i]).view(bs, self.nm, -1) for i in range(self.nl)], 2)  # mask coefficients
683 |         x = self.detect(self, x)
684 |         if self.training:
685 |             return x, mc, p
686 |         return (torch.cat([x, mc], 1), p) if self.export else (torch.cat([x[0], mc], 1), (x[1], mc, p))
687 | 
688 | 
689 | class Classify(nn.Module):
690 |     # YOLOv5 classification head, i.e. x(b,c1,20,20) to x(b,c2)
691 |     def __init__(self, c1, c2, k=1, s=1, p=None, g=1):  # ch_in, ch_out, kernel, stride, padding, groups
692 |         super().__init__()
693 |         c_ = 1280  # efficientnet_b0 size
694 |         self.conv = Conv(c1, c_, k, s, autopad(k, p), g)
695 |         self.pool = nn.AdaptiveAvgPool2d(1)  # to x(b,c_,1,1)
696 |         self.drop = nn.Dropout(p=0.0, inplace=True)
697 |         self.linear = nn.Linear(c_, c2)  # to x(b,c2)
698 | 
699 |     def forward(self, x):
700 |         if isinstance(x, list):
701 |             x = torch.cat(x, 1)
702 |         return self.linear(self.drop(self.pool(self.conv(x)).flatten(1)))
703 | 


--------------------------------------------------------------------------------
/myqlabel.cpp:
--------------------------------------------------------------------------------
 1 | #include "myqlabel.h"
 2 | 
 3 | myqlabel::myqlabel(const QString &Titter, QWidget *parent)
 4 |     :QLabel(parent)
 5 | {
 6 |      this->setText(Titter);
 7 |      connect(this, SIGNAL(clicked()), this, SLOT(slotClicked()));
 8 | }
 9 | 
10 | myqlabel::~myqlabel()
11 | {
12 | 
13 | }
14 | 
15 | void myqlabel::slotClicked()
16 | {
17 |     this->setPixmap(QPixmap(""));
18 | 
19 | }
20 | void myqlabel::mousePressEvent(QMouseEvent*)
21 | {
22 |     emit clicked();
23 | }
24 | 
25 | 


--------------------------------------------------------------------------------
/myqlabel.h:
--------------------------------------------------------------------------------
 1 | #ifndef MYQLABEL_H
 2 | #define MYQLABEL_H
 3 | 
 4 | #include <QObject>
 5 | #include <QLabel>
 6 | #include <QMessageBox>
 7 | 
 8 | 
 9 | class myqlabel : public QLabel
10 | {
11 |     Q_OBJECT
12 | public:
13 |     myqlabel(const QString &Titter,QWidget *parent=0);
14 |     ~myqlabel();
15 | signals:
16 |     //点击信号
17 |     void clicked();
18 | public slots:
19 |     //点击信号响应槽
20 |     void slotClicked();
21 | protected:
22 |     //鼠标按下事件
23 |     void mousePressEvent(QMouseEvent*/* event*/);
24 | };
25 | 
26 | 
27 | #endif // MYQLABEL_H
28 | 


--------------------------------------------------------------------------------
/myvideosurface.cpp:
--------------------------------------------------------------------------------
 1 | #include "myvideosurface.h"
 2 | 
 3 | MyVideoSurface::MyVideoSurface()
 4 | {
 5 | 
 6 | }
 7 | 
 8 | //支持的像素格式
 9 | QList<QVideoFrame::PixelFormat> MyVideoSurface::supportedPixelFormats(QAbstractVideoBuffer::HandleType handleType) const
10 | {
11 |     if(handleType == QAbstractVideoBuffer::NoHandle){
12 |         return QList<QVideoFrame::PixelFormat>() << QVideoFrame::Format_RGB32
13 |                                                  << QVideoFrame::Format_ARGB32
14 |                                                  << QVideoFrame::Format_ARGB32_Premultiplied
15 |                                                  << QVideoFrame::Format_RGB565
16 |                                                  << QVideoFrame::Format_NV21
17 |                                                  << QVideoFrame::Format_RGB555;
18 |     }
19 |     else {
20 |         return QList<QVideoFrame::PixelFormat>();
21 |     }
22 | }
23 | 
24 | //将视频流中像素格式转换成格式对等的图片格式，若无对等的格式，返回QImage::Format_Invalid
25 | bool MyVideoSurface::isFormatSupported(const QVideoSurfaceFormat &videoformat) const
26 | {
27 |     //imageFormatFromPixelFormat()-----返回与视频帧像素格式等效的图像格式
28 |     //pixelFormat()-----返回视频流中帧的像素格式
29 |     return QVideoFrame::imageFormatFromPixelFormat(videoformat.pixelFormat()) != QImage::Format_Invalid;
30 | }
31 | 
32 | //这些虚函数，会自动被调用，start检测图像是否可以对等转换，每一帧有没有
33 | bool MyVideoSurface::start(const QVideoSurfaceFormat &videoformat)
34 | {
35 | //    qDebug() << QVideoFrame::imageFormatFromPixelFormat(videoformat.pixelFormat());              //格式是RGB32
36 | //    if(QVideoFrame::imageFormatFromPixelFormat(videoformat.pixelFormat()) != QImage::Format_Invalid && !videoformat.frameSize().isEmpty()){
37 | //        QAbstractVideoSurface::start(videoformat);
38 | //        return true;
39 | //    }
40 |     QAbstractVideoSurface::start(videoformat);
41 |     return false;
42 | }
43 | 
44 | bool MyVideoSurface::present(const QVideoFrame &frame)
45 | {
46 | //    qDebug() << frame.size();
47 |     if (frame.isValid()){
48 |         QVideoFrame cloneFrame(frame);                                      //每一帧视频都会进入present中，内部机制
49 |         emit frameAvailable(cloneFrame);                                    //直接把视频帧发送出去
50 |         return true;
51 |     }
52 |     stop();
53 |     return false;
54 | }
55 | 
56 | void MyVideoSurface::stop()
57 | {
58 |     QAbstractVideoSurface::stop();
59 | }
60 | 
61 | 
62 | 


--------------------------------------------------------------------------------
/myvideosurface.h:
--------------------------------------------------------------------------------
 1 | #ifndef MYVIDEOSURFACE_H
 2 | #define MYVIDEOSURFACE_H
 3 | 
 4 | 
 5 | #include <QAbstractVideoSurface>
 6 | #include <QDebug>
 7 | #include <QVideoSurfaceFormat>
 8 | #include <QVideoFrame>
 9 | 
10 | class MyVideoSurface : public QAbstractVideoSurface
11 | {
12 |     Q_OBJECT
13 | public:
14 |     MyVideoSurface();
15 | 
16 |     QList<QVideoFrame::PixelFormat> supportedPixelFormats(QAbstractVideoBuffer::HandleType type = QAbstractVideoBuffer::NoHandle) const Q_DECL_OVERRIDE;
17 |     bool isFormatSupported(const QVideoSurfaceFormat &) const Q_DECL_OVERRIDE;    //将视频流中像素格式转换成格式对等的图片格式，若无对等的格式，返回QImage::Format_Invalid
18 |     bool start(const QVideoSurfaceFormat &) Q_DECL_OVERRIDE;                       //只要摄像头开，就会调用
19 |     bool present(const QVideoFrame &) Q_DECL_OVERRIDE;                             //每一帧画面将回到这里处理
20 |     void stop() Q_DECL_OVERRIDE;
21 | 
22 | signals:
23 |     void frameAvailable(QVideoFrame cloneFrame);
24 | 
25 | };
26 | 
27 | #endif // MYVIDEOSURFACE_H
28 | 


--------------------------------------------------------------------------------
/pic.qrc:
--------------------------------------------------------------------------------
 1 | <RCC>
 2 |     <qresource prefix="/">
 3 |         <file>assets/ai.png</file>
 4 |         <file>assets/icon.png</file>
 5 |         <file>assets/ManjaroMix.qss</file>
 6 |         <file>model/yolov8s_opt.bin</file>
 7 |         <file>model/yolov8s_opt.param</file>
 8 |     </qresource>
 9 | </RCC>
10 | 


--------------------------------------------------------------------------------
/widget.cpp:
--------------------------------------------------------------------------------
  1 | 
  2 | 
  3 | #include "widget.h"
  4 | #include "ui_widget.h"
  5 | #include "yolo.h"
  6 | #include <opencv2/core/core.hpp>
  7 | #include <opencv2/highgui/highgui.hpp>
  8 | #include <opencv2/imgproc/imgproc.hpp>
  9 | #include <QTest>
 10 | 
 11 | extern Yolo * yolov8;
 12 | const float prob_threshold = 0.25f;
 13 | const float nms_threshold = 0.45f;
 14 | 
 15 | cv::Mat ChangeToMat(QImage image)
 16 | {
 17 | 
 18 | //    image = image.convertToFormat(QImage::Format_RGB888);
 19 |     cv::Mat tmp(image.height(),image.width(),CV_8UC3,(uchar*)image.bits(),image.bytesPerLine());
 20 |     cv::Mat result; // deep copy just in case (my lack of knowledge with open cv)
 21 |     cv::cvtColor(tmp, result, cv::COLOR_BGR2RGB);
 22 |         return result;
 23 | }
 24 | 
 25 | QImage ChangeToQIamge(cv::Mat mat)
 26 | {
 27 |     cv::cvtColor(mat, mat, cv::COLOR_BGR2RGB);
 28 |     QImage qim((const unsigned char*)mat.data, mat.cols, mat.rows, mat.step,
 29 |     QImage::Format_RGB888);
 30 |     return qim;
 31 | }
 32 | 
 33 | 
 34 | 
 35 | Widget::Widget(QWidget *parent)
 36 |     : QWidget(parent)
 37 |     , ui(new Ui::Widget)
 38 | {
 39 |     ui->setupUi(this);
 40 | 
 41 |     camera=new QCamera;//摄像头
 42 |     capture = new QCameraImageCapture(camera);
 43 |     viewfinder=new QCameraViewfinder(this);//取景器
 44 | 
 45 |     // static QMetaObject::Connection connect(const QObject *sender, const char *signal, const QObject *receiver, const char *member,
 46 |     // Qt::ConnectionType = Qt::AutoConnection);
 47 |     //第一个参数sender为发送对象；第二个参数为发送对象里面的一个信号；第三个参数为接收对象；第四个参数为接收对象里面的槽函数。一般我们使用发送者触发信号，然后执行接收者的槽函数。
 48 |     QObject::connect(capture, SIGNAL(imageCaptured(int,QImage)), this, SLOT(displayImage(int,QImage)));
 49 |     camera->setCaptureMode(QCamera::CaptureStillImage);
 50 | //    camera->setViewfinder(viewfinder);
 51 |     mySurface = new MyVideoSurface();
 52 |     camera->setViewfinder(mySurface);
 53 |     //处理myvideosurface中每一帧视频
 54 |     connect(mySurface, SIGNAL(frameAvailable(QVideoFrame)), this, SLOT(rcvFrame(QVideoFrame)), Qt::DirectConnection);
 55 | 
 56 |     camera->start(); //启动摄像头
 57 | 
 58 |     //获取摄像头支持的分辨率、帧率等参数
 59 | //    QList<QCameraViewfinderSettings > ViewSets = camera->supportedViewfinderSettings();
 60 | //    int i = 0;
 61 | //    qDebug() << "viewfinderResolutions sizes.len = " << ViewSets.length();
 62 | //    foreach (QCameraViewfinderSettings ViewSet, ViewSets) {
 63 | //        qDebug() << i++ <<" max rate = " << ViewSet.maximumFrameRate() << "min rate = "<< ViewSet.minimumFrameRate() << "resolution "<<ViewSet.resolution()<<\
 64 | //                    "Format="<<ViewSet.pixelFormat()<<""<<ViewSet.pixelAspectRatio();
 65 | //    }
 66 | 
 67 |     //设置摄像头参数
 68 |     QCameraViewfinderSettings camerasettings;
 69 |     camerasettings.setResolution(640,480);
 70 |     camerasettings.setPixelFormat(QVideoFrame::Format_NV21);
 71 |     camerasettings.setMaximumFrameRate(30);
 72 |     camerasettings.setMinimumFrameRate(30);
 73 | 
 74 |     camera->setViewfinderSettings(camerasettings);
 75 | 
 76 | }
 77 | 
 78 | Widget::~Widget()
 79 | {
 80 |     delete ui;
 81 | }
 82 | 
 83 | 
 84 | void Widget::displayImage(int ,QImage image)
 85 | {
 86 |     image=image.convertToFormat(QImage::Format_RGB888);
 87 | 
 88 |     cv::Mat cv_image;
 89 |     cv_image = ChangeToMat(image);
 90 | 
 91 |     std::vector<Object> objects;
 92 |     yolov8->detect(cv_image, objects, prob_threshold, nms_threshold);
 93 |     yolov8->draw(cv_image, objects);
 94 | 
 95 |     QImage q_image = ChangeToQIamge(cv_image);
 96 | 
 97 |     ui->label->setPixmap(QPixmap::fromImage(q_image));
 98 |    //    qDebug() << image.size();
 99 | 
100 | //    QTest::qSleep(5000);
101 | //    ui->label->setPixmap(QPixmap(""));//清除图片
102 | 
103 | }
104 | 
105 | void Widget::rcvFrame(QVideoFrame m_currentFrame)
106 | {
107 | //    qDebug() << "received" << m_currentFrame.size();
108 | 
109 |     m_currentFrame.map(QAbstractVideoBuffer::ReadOnly);
110 | //    unsigned char *pix_ptr = m_currentFrame.bits();
111 | //    qDebug("%d %d %d %d", *pix_ptr, *(pix_ptr+1), *(pix_ptr+2), *(pix_ptr+3));
112 |         //将视频帧转化成QImage,devicePixelRatio设备像素比，bytesPerLine一行的像素字节（1280*4=5120）
113 | 
114 |     videoImg = QImage(m_currentFrame.width(), m_currentFrame.height(), QImage::Format_RGB888);
115 |     NV21_T_RGB(m_currentFrame.width(), m_currentFrame.height(), m_currentFrame.bits(), videoImg.bits());
116 | //    videoImg =  QImage(m_currentFrame.bits(),
117 | //                   m_currentFrame.width(),
118 | //                   m_currentFrame.height(),
119 | //                   QImage::Format_Grayscale8).copy();       //这里要做一个copy,因为char* pdata在emit后释放了
120 | //    videoImg = videoImg.mirrored(true, false);                          //水平翻转，原始图片是反的
121 | 
122 | //    qDebug() <<  "image" << videoImg;  //可以看看输出啥东西
123 | //    QString currentTime = QDateTime::currentDateTime().toString("yyyyMMddhhmmss");
124 | //    QString savefile = QString("E:/study/QT/opencamera/opencamera/%1.jpg").arg(currentTime);
125 | //    qDebug() << videoImg.save(savefile);
126 |     m_currentFrame.unmap();                                         //释放map拷贝的内存
127 |     QCameraInfo cameraInfo(*camera); // needed to get the camera sensor position and orientation
128 | 
129 | //    // Get the current display orientation
130 | //    const QScreen *screen = QGuiApplication::primaryScreen();
131 | //    const int screenAngle = screen->angleBetween(screen->nativeOrientation(), screen->orientation());
132 | 
133 | //    int rotation;
134 | //    if (cameraInfo.position() == QCamera::BackFace) {
135 | //        rotation = (cameraInfo.orientation() - screenAngle) % 360;
136 | //    } else {
137 | //        // Front position, compensate the mirror
138 | //        rotation = (360 - cameraInfo.orientation() + screenAngle) % 360;
139 | //    }
140 | 
141 | //    // Rotate the frame so it always shows in the correct orientation
142 |     videoImg = videoImg.transformed(QTransform().rotate(90));
143 | 
144 |     QWidget::update();                                              //更新了，就会触发paintEvent画图
145 | }
146 | 
147 | void Widget::paintEvent(QPaintEvent *event)
148 | {
149 |     QPainter painter(this);
150 | //    QRect rect(0, 0, 480, 640);
151 |     //this->frameGeometry().width() << this->frameGeometry().height();
152 |     QRect rect(5, 5, this->frameGeometry().width()-10, this->frameGeometry().height()-10);
153 | 
154 | 
155 |     //设置画笔
156 |     QPen pen;
157 |     pen.setWidth(5);                    //线宽
158 |     pen.setColor(Qt::red);
159 |     pen.setStyle(Qt::SolidLine);        //实线
160 |     pen.setCapStyle(Qt::FlatCap);       //线端点样式
161 |     pen.setJoinStyle(Qt::BevelJoin);    //线连接点样式
162 |     painter.setPen(pen);
163 |     painter.drawRect(rect);
164 | 
165 |     //qDebug() <<  "image" << videoImg;     //第一次输出的QImage(null)
166 |     //只要窗口启动，就会触发paintEvent，所以第一次是null,不可以画图。
167 |     if(videoImg != QImage(nullptr)){
168 |         painter.drawImage(rect, videoImg);
169 |     }
170 | }
171 | 
172 | 
173 | void Widget::on_pushButton_clicked()
174 | {
175 |     capture->capture();
176 | 
177 | }
178 | 
179 | void Widget::NV21_T_RGB(unsigned int width , unsigned int height , unsigned char *yuyv , unsigned char *rgb)
180 | {
181 |     const int nv_start = width * height ;
182 |     unsigned int i, j, index = 0, rgb_index = 0;
183 |     unsigned char y, u, v;
184 |     int r, g, b, nv_index = 0;
185 | 
186 |     for(i = 0; i < height; i++){
187 |         for(j = 0; j < width; j ++){
188 |             //nv_index = (rgb_index / 2 - width / 2 * ((i + 1) / 2)) * 2;
189 |             nv_index = i / 2  * width + j - j % 2;
190 | 
191 |             y = yuyv[rgb_index];
192 |             u = yuyv[nv_start + nv_index ];
193 |             v = yuyv[nv_start + nv_index + 1];
194 | 
195 |             r = y + (140 * (v-128))/100;  //r
196 |             g = y - (34 * (u-128))/100 - (71 * (v-128))/100; //g
197 |             b = y + (177 * (u-128))/100; //b
198 | 
199 |             if(r > 255)   r = 255;
200 |             if(g > 255)   g = 255;
201 |             if(b > 255)   b = 255;
202 |             if(r < 0)     r = 0;
203 |             if(g < 0)     g = 0;
204 |             if(b < 0)     b = 0;
205 | 
206 |             index = rgb_index % width + (height - i - 1) * width;
207 |             //rgb[index * 3+0] = b;
208 |             //rgb[index * 3+1] = g;
209 |             //rgb[index * 3+2] = r;
210 | 
211 |             //颠倒图像
212 |             //rgb[height * width * 3 - i * width * 3 - 3 * j - 1] = b;
213 |             //rgb[height * width * 3 - i * width * 3 - 3 * j - 2] = g;
214 |             //rgb[height * width * 3 - i * width * 3 - 3 * j - 3] = r;
215 | 
216 |             //正面图像
217 |             rgb[i * width * 3 + 3 * j + 0] = b;
218 |             rgb[i * width * 3 + 3 * j + 1] = g;
219 |             rgb[i * width * 3 + 3 * j + 2] = r;
220 | 
221 |             rgb_index++;
222 |         }
223 |     }
224 | //    return 0;
225 | }
226 | 
227 | 
228 | void Widget::on_label_linkHovered(const QString &link)
229 | {
230 | 
231 | }
232 | 


--------------------------------------------------------------------------------
/widget.h:
--------------------------------------------------------------------------------
 1 | #ifndef WIDGET_H
 2 | #define WIDGET_H
 3 | 
 4 | #include <QWidget>
 5 | 
 6 | #include <QDebug>
 7 | #include <QCamera>
 8 | #include <QCameraInfo>
 9 | #include <QCameraViewfinder>
10 | #include <QCameraViewfinderSettings>
11 | #include <QCameraImageCapture>
12 | #include <myvideosurface.h>
13 | #include <QImage>
14 | #include <QPainter>
15 | #include <QScreen>
16 | 
17 | 
18 | QT_BEGIN_NAMESPACE
19 | namespace Ui { class Widget; }
20 | QT_END_NAMESPACE
21 | 
22 | class Widget : public QWidget
23 | {
24 |     Q_OBJECT
25 | 
26 | public:
27 |     Widget(QWidget *parent = nullptr);
28 |     ~Widget();
29 | 
30 | void NV21_T_RGB(unsigned int width , unsigned int height , unsigned char *yuyv , unsigned char *rgb);
31 | 
32 | private:
33 |     Ui::Widget *ui;
34 |     QCamera *camera;
35 |     QCameraImageCapture *capture;
36 |     QCameraViewfinder *viewfinder;
37 |     MyVideoSurface *mySurface;
38 |     QImage videoImg;
39 | 
40 | public slots:
41 |     void displayImage(int ,QImage image);
42 |     void rcvFrame(QVideoFrame);                            //接收图像帧数据
43 |     void paintEvent(QPaintEvent *event);
44 | 
45 | private slots:
46 |     void on_pushButton_clicked();
47 |     void on_label_linkHovered(const QString &link);
48 | };
49 | 
50 | #endif // MAINWINDOW_H
51 | 


--------------------------------------------------------------------------------
/widget.ui:
--------------------------------------------------------------------------------
 1 | <?xml version="1.0" encoding="UTF-8"?>
 2 | <ui version="4.0">
 3 |  <class>Widget</class>
 4 |  <widget class="QWidget" name="Widget">
 5 |   <property name="geometry">
 6 |    <rect>
 7 |     <x>0</x>
 8 |     <y>0</y>
 9 |     <width>564</width>
10 |     <height>640</height>
11 |    </rect>
12 |   </property>
13 |   <property name="windowTitle">
14 |    <string>Widget</string>
15 |   </property>
16 |   <widget class="QLabel" name="label">
17 |    <property name="geometry">
18 |     <rect>
19 |      <x>10</x>
20 |      <y>70</y>
21 |      <width>491</width>
22 |      <height>551</height>
23 |     </rect>
24 |    </property>
25 |    <property name="text">
26 |     <string/>
27 |    </property>
28 |   </widget>
29 |   <widget class="QWidget" name="horizontalLayoutWidget">
30 |    <property name="geometry">
31 |     <rect>
32 |      <x>0</x>
33 |      <y>9</y>
34 |      <width>501</width>
35 |      <height>51</height>
36 |     </rect>
37 |    </property>
38 |    <layout class="QHBoxLayout" name="horizontalLayout">
39 |     <item>
40 |      <widget class="QLabel" name="label_2">
41 |       <property name="styleSheet">
42 |        <string notr="true">font: 75 14pt &quot;微软雅黑&quot;;
43 | font: 20pt &quot;Arial&quot;;</string>
44 |       </property>
45 |       <property name="text">
46 |        <string>YOLOv8</string>
47 |       </property>
48 |      </widget>
49 |     </item>
50 |     <item>
51 |      <widget class="QPushButton" name="pushButton">
52 |       <property name="styleSheet">
53 |        <string notr="true">font: 75 11pt &quot;微软雅黑&quot;;
54 | font: 20pt &quot;Arial&quot;;</string>
55 |       </property>
56 |       <property name="text">
57 |        <string>YOLO8识别</string>
58 |       </property>
59 |       <property name="icon">
60 |        <iconset resource="pic.qrc">
61 |         <normaloff>:/assets/ai.png</normaloff>:/assets/ai.png</iconset>
62 |       </property>
63 |      </widget>
64 |     </item>
65 |    </layout>
66 |   </widget>
67 |  </widget>
68 |  <resources>
69 |   <include location="pic.qrc"/>
70 |  </resources>
71 |  <connections/>
72 | </ui>
73 | 


--------------------------------------------------------------------------------
/yolo.cpp:
--------------------------------------------------------------------------------
  1 | // yolov8_ncnn.cpp : 此文件包含 "main" 函数。程序执行将在此处开始并结束。
  2 | //
  3 | 
  4 | // Tencent is pleased to support the open source community by making ncnn available.
  5 | //
  6 | // Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved.
  7 | //
  8 | // Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
  9 | // in compliance with the License. You may obtain a copy of the License at
 10 | //
 11 | // https://opensource.org/licenses/BSD-3-Clause
 12 | //
 13 | // Unless required by applicable law or agreed to in writing, software distributed
 14 | // under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
 15 | // CONDITIONS OF ANY KIND, either express or implied. See the License for the
 16 | // specific language governing permissions and limitations under the License.
 17 | 
 18 | #include "yolo.h"
 19 | 
 20 | #include <opencv2/core/core.hpp>
 21 | #include <opencv2/imgproc/imgproc.hpp>
 22 | 
 23 | //#include "cpu.h"
 24 | #include <QFile>
 25 | #include <iostream>
 26 | 
 27 | static float fast_exp(float x)
 28 | {
 29 | 	union {
 30 | 		uint32_t i;
 31 | 		float f;
 32 | 	} v{};
 33 | 	v.i = (1 << 23) * (1.4426950409 * x + 126.93490512f);
 34 | 	return v.f;
 35 | }
 36 | 
 37 | static float sigmoid(float x)
 38 | {
 39 | 	return 1.0f / (1.0f + fast_exp(-x));
 40 | }
 41 | static float intersection_area(const Object& a, const Object& b)
 42 | {
 43 | 	cv::Rect_<float> inter = a.rect & b.rect;
 44 | 	return inter.area();
 45 | }
 46 | 
 47 | static void qsort_descent_inplace(std::vector<Object>& faceobjects, int left, int right)
 48 | {
 49 | 	int i = left;
 50 | 	int j = right;
 51 | 	float p = faceobjects[(left + right) / 2].prob;
 52 | 
 53 | 	while (i <= j)
 54 | 	{
 55 | 		while (faceobjects[i].prob > p)
 56 | 			i++;
 57 | 
 58 | 		while (faceobjects[j].prob < p)
 59 | 			j--;
 60 | 
 61 | 		if (i <= j)
 62 | 		{
 63 | 			// swap
 64 | 			std::swap(faceobjects[i], faceobjects[j]);
 65 | 
 66 | 			i++;
 67 | 			j--;
 68 | 		}
 69 | 	}
 70 | 
 71 | 	//     #pragma omp parallel sections
 72 | 	{
 73 | 		//         #pragma omp section
 74 | 		{
 75 | 			if (left < j) qsort_descent_inplace(faceobjects, left, j);
 76 | 		}
 77 | 		//         #pragma omp section
 78 | 		{
 79 | 			if (i < right) qsort_descent_inplace(faceobjects, i, right);
 80 | 		}
 81 | 	}
 82 | }
 83 | 
 84 | static void qsort_descent_inplace(std::vector<Object>& faceobjects)
 85 | {
 86 | 	if (faceobjects.empty())
 87 | 		return;
 88 | 
 89 | 	qsort_descent_inplace(faceobjects, 0, faceobjects.size() - 1);
 90 | }
 91 | 
 92 | static void nms_sorted_bboxes(const std::vector<Object>& faceobjects, std::vector<int>& picked, float nms_threshold)
 93 | {
 94 | 	picked.clear();
 95 | 
 96 | 	const int n = faceobjects.size();
 97 | 
 98 | 	std::vector<float> areas(n);
 99 | 	for (int i = 0; i < n; i++)
100 | 	{
101 | 		areas[i] = faceobjects[i].rect.width * faceobjects[i].rect.height;
102 | 	}
103 | 
104 | 	for (int i = 0; i < n; i++)
105 | 	{
106 | 		const Object& a = faceobjects[i];
107 | 
108 | 		int keep = 1;
109 | 		for (int j = 0; j < (int)picked.size(); j++)
110 | 		{
111 | 			const Object& b = faceobjects[picked[j]];
112 | 
113 | 			// intersection over union
114 | 			float inter_area = intersection_area(a, b);
115 | 			float union_area = areas[i] + areas[picked[j]] - inter_area;
116 | 			// float IoU = inter_area / union_area
117 | 			if (inter_area / union_area > nms_threshold)
118 | 				keep = 0;
119 | 		}
120 | 
121 | 		if (keep)
122 | 			picked.push_back(i);
123 | 	}
124 | }
125 | static void generate_grids_and_stride(const int target_w, const int target_h, std::vector<int>& strides, std::vector<GridAndStride>& grid_strides)
126 | {
127 | 	for (int i = 0; i < (int)strides.size(); i++)
128 | 	{
129 | 		int stride = strides[i];
130 | 		int num_grid_w = target_w / stride;
131 | 		int num_grid_h = target_h / stride;
132 | 		for (int g1 = 0; g1 < num_grid_h; g1++)
133 | 		{
134 | 			for (int g0 = 0; g0 < num_grid_w; g0++)
135 | 			{
136 | 				GridAndStride gs;
137 | 				gs.grid0 = g0;
138 | 				gs.grid1 = g1;
139 | 				gs.stride = stride;
140 | 				grid_strides.push_back(gs);
141 | 			}
142 | 		}
143 | 	}
144 | }
145 | static void generate_proposals(std::vector<GridAndStride> grid_strides, const ncnn::Mat& pred, float prob_threshold, std::vector<Object>& objects)
146 | {
147 | 	const int num_points = grid_strides.size();
148 | 	const int num_class = 4; //<--------------
149 | 	const int reg_max_1 = 16;
150 | 
151 | 	for (int i = 0; i < num_points; i++)
152 | 	{
153 | 		const float* scores = pred.row(i) + 4 * reg_max_1;
154 | 
155 | 		// find label with max score
156 | 		int label = -1;
157 | 		float score = -FLT_MAX;
158 | 		for (int k = 0; k < num_class; k++)
159 | 		{
160 | 			float confidence = scores[k];
161 | 			if (confidence > score)
162 | 			{
163 | 				label = k;
164 | 				score = confidence;
165 | 			}
166 | 		}
167 | 		float box_prob = sigmoid(score);
168 | 		if (box_prob >= prob_threshold)
169 | 		{
170 | 			ncnn::Mat bbox_pred(reg_max_1, 4, (void*)pred.row(i));
171 | 			{
172 | 				ncnn::Layer* softmax = ncnn::create_layer("Softmax");
173 | 
174 | 				ncnn::ParamDict pd;
175 | 				pd.set(0, 1); // axis
176 | 				pd.set(1, 1);
177 | 				softmax->load_param(pd);
178 | 
179 | 				ncnn::Option opt;
180 | 				opt.num_threads = 1;
181 | 				opt.use_packing_layout = false;
182 | 
183 | 				softmax->create_pipeline(opt);
184 | 
185 | 				softmax->forward_inplace(bbox_pred, opt);
186 | 
187 | 				softmax->destroy_pipeline(opt);
188 | 
189 | 				delete softmax;
190 | 			}
191 | 
192 | 			float pred_ltrb[4];
193 | 			for (int k = 0; k < 4; k++)
194 | 			{
195 | 				float dis = 0.f;
196 | 				const float* dis_after_sm = bbox_pred.row(k);
197 | 				for (int l = 0; l < reg_max_1; l++)
198 | 				{
199 | 					dis += l * dis_after_sm[l];
200 | 				}
201 | 
202 | 				pred_ltrb[k] = dis * grid_strides[i].stride;
203 | 			}
204 | 
205 | 			float pb_cx = (grid_strides[i].grid0 + 0.5f) * grid_strides[i].stride;
206 | 			float pb_cy = (grid_strides[i].grid1 + 0.5f) * grid_strides[i].stride;
207 | 
208 | 			float x0 = pb_cx - pred_ltrb[0];
209 | 			float y0 = pb_cy - pred_ltrb[1];
210 | 			float x1 = pb_cx + pred_ltrb[2];
211 | 			float y1 = pb_cy + pred_ltrb[3];
212 | 
213 | 			Object obj;
214 | 			obj.rect.x = x0;
215 | 			obj.rect.y = y0;
216 | 			obj.rect.width = x1 - x0;
217 | 			obj.rect.height = y1 - y0;
218 | 			obj.label = label;
219 | 			obj.prob = box_prob;
220 | 
221 | 			objects.push_back(obj);
222 | 		}
223 | 	}
224 | }
225 | 
226 | Yolo::Yolo()
227 | {
228 | 	blob_pool_allocator.set_size_compare_ratio(0.f);
229 | 	workspace_pool_allocator.set_size_compare_ratio(0.f);
230 | }
231 | 
232 | 
233 | int Yolo::load(int _target_size, const float* _mean_vals, const float* _norm_vals, bool use_gpu)
234 | {
235 | /*	yolo.clear();
236 | 	blob_pool_allocator.clear();
237 | 	workspace_pool_allocator.clear()*/;
238 | 
239 | //	ncnn::set_cpu_powersave(2);
240 | //	ncnn::set_omp_num_threads(ncnn::get_big_cpu_count());
241 | 
242 | 	yolo.opt = ncnn::Option();
243 | 
244 | //#if NCNN_VULKAN
245 | //	yolo.opt.use_vulkan_compute = use_gpu;
246 | //#endif
247 | 
248 | 	//yolo.opt.num_threads = ncnn::get_big_cpu_count();
249 | 	//yolo.opt.blob_allocator = &blob_pool_allocator;
250 | 	//yolo.opt.workspace_allocator = &workspace_pool_allocator;
251 | 
252 | 
253 | 
254 |     QFile::copy("assets:/pic/yolov8s_opt.param", "yolov8s_opt.param");
255 |     QFile::copy("assets:/pic/yolov8s_opt.bin", "yolov8s_opt.bin");
256 |     yolo.load_param("yolov8s_opt.param");
257 |     yolo.load_model( "yolov8s_opt.bin");
258 | 
259 | 
260 | //	yolo.load_param("./model/yolov8s_opt.param");
261 | //	yolo.load_model("./model/yolov8s_opt.bin");
262 | 
263 | 	target_size = _target_size;
264 | 	mean_vals[0] = _mean_vals[0];
265 | 	mean_vals[1] = _mean_vals[1];
266 | 	mean_vals[2] = _mean_vals[2];
267 | 	norm_vals[0] = _norm_vals[0];
268 | 	norm_vals[1] = _norm_vals[1];
269 | 	norm_vals[2] = _norm_vals[2];
270 | 
271 | 	return 0;
272 | }
273 | 
274 | int Yolo::detect(const cv::Mat& rgb, std::vector<Object>& objects, float prob_threshold, float nms_threshold)
275 | {
276 | 	int width = rgb.cols;
277 | 	int height = rgb.rows;
278 | 
279 | 	// pad to multiple of 32
280 | 	int w = width;
281 | 	int h = height;
282 | 	float scale = 1.f;
283 | 	if (w > h)
284 | 	{
285 | 		scale = (float)target_size / w;
286 | 		w = target_size;
287 | 		h = h * scale;
288 | 	}
289 | 	else
290 | 	{
291 | 		scale = (float)target_size / h;
292 | 		h = target_size;
293 | 		w = w * scale;
294 | 	}
295 | 
296 | 	ncnn::Mat in = ncnn::Mat::from_pixels_resize(rgb.data, ncnn::Mat::PIXEL_RGB2BGR, width, height, w, h);
297 | 
298 | 	// pad to target_size rectangle
299 | 	int wpad = (w + 31) / 32 * 32 - w;
300 | 	int hpad = (h + 31) / 32 * 32 - h;
301 | 	ncnn::Mat in_pad;
302 | 	ncnn::copy_make_border(in, in_pad, hpad / 2, hpad - hpad / 2, wpad / 2, wpad - wpad / 2, ncnn::BORDER_CONSTANT, 0.f);
303 | 
304 | 	in_pad.substract_mean_normalize(0, norm_vals);
305 | 
306 | 	ncnn::Extractor ex = yolo.create_extractor();
307 | 
308 | 	ex.input("images", in_pad);
309 | 
310 | 	std::vector<Object> proposals;
311 | 
312 | 	ncnn::Mat out;
313 | 	ex.extract("output0", out);
314 | 
315 | 	std::cout << "---------YES, " << out.dims << " width," <<  out.w << " height," << out.h << " , " << out.c << std::endl;
316 | 	// 解析output + NMS TODO
317 | 
318 | 	std::vector<int> strides = { 8, 16, 32 }; // might have stride=64
319 | 	std::vector<GridAndStride> grid_strides;
320 | 	generate_grids_and_stride(in_pad.w, in_pad.h, strides, grid_strides);
321 | 	generate_proposals(grid_strides, out, prob_threshold, proposals);
322 | 
323 | 	// sort all proposals by score from highest to lowest
324 | 	qsort_descent_inplace(proposals);
325 | 
326 | 	// apply nms with nms_threshold
327 | 	std::vector<int> picked;
328 | 	nms_sorted_bboxes(proposals, picked, nms_threshold);
329 | 
330 | 	int count = picked.size();
331 | 
332 | 	objects.resize(count);
333 | 	for (int i = 0; i < count; i++)
334 | 	{
335 | 		objects[i] = proposals[picked[i]];
336 | 
337 | 		// adjust offset to original unpadded
338 | 		float x0 = (objects[i].rect.x - (wpad / 2)) / scale;
339 | 		float y0 = (objects[i].rect.y - (hpad / 2)) / scale;
340 | 		float x1 = (objects[i].rect.x + objects[i].rect.width - (wpad / 2)) / scale;
341 | 		float y1 = (objects[i].rect.y + objects[i].rect.height - (hpad / 2)) / scale;
342 | 
343 | 		// clip
344 | 		x0 = std::max(std::min(x0, (float)(width - 1)), 0.f);
345 | 		y0 = std::max(std::min(y0, (float)(height - 1)), 0.f);
346 | 		x1 = std::max(std::min(x1, (float)(width - 1)), 0.f);
347 | 		y1 = std::max(std::min(y1, (float)(height - 1)), 0.f);
348 | 
349 | 		objects[i].rect.x = x0;
350 | 		objects[i].rect.y = y0;
351 | 		objects[i].rect.width = x1 - x0;
352 | 		objects[i].rect.height = y1 - y0;
353 | 	}
354 | 
355 | 	// sort objects by area
356 | 	struct
357 | 	{
358 | 		bool operator()(const Object& a, const Object& b) const
359 | 		{
360 | 			return a.rect.area() > b.rect.area();
361 | 		}
362 | 	} objects_area_greater;
363 | 	std::sort(objects.begin(), objects.end(), objects_area_greater);
364 | 
365 | 	return 0;
366 | }
367 | 
368 | int Yolo::draw(cv::Mat& rgb, const std::vector<Object>& objects)
369 | {
370 | 	static const char* class_names[] = {
371 | 		"person", "cat","dog","horse"
372 | 	};
373 | 
374 | 	static const unsigned char colors[19][3] = {
375 | 		{ 54,  67, 244},
376 | 		{ 99,  30, 233},
377 | 		{176,  39, 156},
378 | 		{183,  58, 103},
379 | 		{181,  81,  63},
380 | 		{243, 150,  33},
381 | 		{244, 169,   3},
382 | 		{212, 188,   0},
383 | 		{136, 150,   0},
384 | 		{ 80, 175,  76},
385 | 		{ 74, 195, 139},
386 | 		{ 57, 220, 205},
387 | 		{ 59, 235, 255},
388 | 		{  7, 193, 255},
389 | 		{  0, 152, 255},
390 | 		{ 34,  87, 255},
391 | 		{ 72,  85, 121},
392 | 		{158, 158, 158},
393 | 		{139, 125,  96}
394 | 	};
395 | 
396 | 	int color_index = 0;
397 | 
398 | 	for (size_t i = 0; i < objects.size(); i++)
399 | 	{
400 | 		const Object& obj = objects[i];
401 | 
402 | 		//         fprintf(stderr, "%d = %.5f at %.2f %.2f %.2f x %.2f\n", obj.label, obj.prob,
403 | 		//                 obj.rect.x, obj.rect.y, obj.rect.width, obj.rect.height);
404 | 
405 | 		const unsigned char* color = colors[color_index % 19];
406 | 		color_index++;
407 | 
408 | 		cv::Scalar cc(color[0], color[1], color[2]);
409 | 
410 | 		cv::rectangle(rgb, obj.rect, cc, 2);
411 | 
412 |         char text[256];
413 |         sprintf(text, "%s %.1f%%", class_names[obj.label], obj.prob * 100);
414 |         //std::string text = class_names[obj.label] + std::to_string(round(obj.prob * 10000)/100);
415 | 
416 | 		int baseLine = 0;
417 | 		cv::Size label_size = cv::getTextSize(text, cv::FONT_HERSHEY_SIMPLEX, 0.5, 1, &baseLine);
418 | 
419 | 		int x = obj.rect.x;
420 | 		int y = obj.rect.y - label_size.height - baseLine;
421 | 		if (y < 0)
422 | 			y = 0;
423 | 		if (x + label_size.width > rgb.cols)
424 | 			x = rgb.cols - label_size.width;
425 | 
426 | 		cv::rectangle(rgb, cv::Rect(cv::Point(x, y), cv::Size(label_size.width, label_size.height + baseLine)), cc, -1);
427 | 
428 | 		cv::Scalar textcc = (color[0] + color[1] + color[2] >= 381) ? cv::Scalar(0, 0, 0) : cv::Scalar(255, 255, 255);
429 | 
430 | 		cv::putText(rgb, text, cv::Point(x, y + label_size.height), cv::FONT_HERSHEY_SIMPLEX, 0.5, textcc, 1);
431 | 	}
432 | 
433 | 	return 0;
434 | }
435 | 


--------------------------------------------------------------------------------
/yolo.h:
--------------------------------------------------------------------------------
 1 | // Tencent is pleased to support the open source community by making ncnn available.
 2 | //
 3 | // Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved.
 4 | //
 5 | // Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
 6 | // in compliance with the License. You may obtain a copy of the License at
 7 | //
 8 | // https://opensource.org/licenses/BSD-3-Clause
 9 | //
10 | // Unless required by applicable law or agreed to in writing, software distributed
11 | // under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
12 | // CONDITIONS OF ANY KIND, either express or implied. See the License for the
13 | // specific language governing permissions and limitations under the License.
14 | 
15 | #ifndef YOLO_H
16 | #define YOLO_H
17 | 
18 | #include <opencv2/core/core.hpp>
19 | 
20 | #include <net.h>
21 | 
22 | struct Object
23 | {
24 |     cv::Rect_<float> rect;
25 |     int label;
26 |     float prob;
27 | };
28 | struct GridAndStride
29 | {
30 |     int grid0;
31 |     int grid1;
32 |     int stride;
33 | };
34 | class Yolo
35 | {
36 | public:
37 |     Yolo();
38 | 
39 |     int load(int target_size, const float* mean_vals, const float* norm_vals, bool use_gpu = false);
40 | 
41 |     int detect(const cv::Mat& rgb, std::vector<Object>& objects, float prob_threshold = 0.4f, float nms_threshold = 0.5f);
42 | 
43 |     int draw(cv::Mat& rgb, const std::vector<Object>& objects);
44 | 
45 | private:
46 |     ncnn::Net yolo;
47 |     int target_size;
48 |     float mean_vals[3];
49 |     float norm_vals[3];
50 |     ncnn::UnlockedPoolAllocator blob_pool_allocator;
51 |     ncnn::PoolAllocator workspace_pool_allocator;
52 | };
53 | 
54 | #endif // NANODET_H
55 | 


--------------------------------------------------------------------------------
/yolov8.pro:
--------------------------------------------------------------------------------
  1 | QT       += core gui multimedia multimediawidgets
  2 | QT += androidextras testlib
  3 | 
  4 | greaterThan(QT_MAJOR_VERSION, 4): QT += widgets
  5 | 
  6 | CONFIG += c++11
  7 | 
  8 | # The following define makes your compiler emit warnings if you use
  9 | # any Qt feature that has been marked deprecated (the exact warnings
 10 | # depend on your compiler). Please consult the documentation of the
 11 | # deprecated API in order to know how to port your code away from it.
 12 | DEFINES += QT_DEPRECATED_WARNINGS
 13 | 
 14 | # You can also make your code fail to compile if it uses deprecated APIs.
 15 | # In order to do so, uncomment the following line.
 16 | # You can also select to disable deprecated APIs only up to a certain version of Qt.
 17 | #DEFINES += QT_DISABLE_DEPRECATED_BEFORE=0x060000    # disables all the APIs deprecated before Qt 6.0.0
 18 | 
 19 | SOURCES += \
 20 |     main.cpp \
 21 |     myqlabel.cpp \
 22 |     myvideosurface.cpp \
 23 |     widget.cpp \
 24 |     yolo.cpp
 25 | 
 26 | HEADERS += \
 27 |     myqlabel.h \
 28 |     myvideosurface.h \
 29 |     widget.h \
 30 |     yolo.h
 31 | 
 32 | FORMS += \
 33 |     widget.ui
 34 | 
 35 | # Default rules for deployment.
 36 | qnx: target.path = /tmp/$${TARGET}/bin
 37 | else: unix:!android: target.path = /opt/$${TARGET}/bin
 38 | !isEmpty(target.path): INSTALLS += target
 39 | 
 40 | QMAKE_CXXFLAGS += -fopenmp -static-openmp
 41 | QMAKE_LFLAGS += -fopenmp -static-openmp
 42 | LIBS += -fopenmp -static-openmp
 43 | 
 44 | android {
 45 | ANDROID_OPENCV = F:/andriod_env/OpenCV-android-sdk/sdk/native
 46 | #ANDROID_OPENCV = D:/NCNN/opencv-mobile-4.5.1-android/sdk/native
 47 | INCLUDEPATH += \
 48 | $$ANDROID_OPENCV/jni/include/opencv2 \
 49 | $$ANDROID_OPENCV/jni/include \
 50 | F:/andriod_env/ncnn/ncnn-20220729-android/armeabi-v7a/include \
 51 | F:/andriod_env/ncnn/ncnn-20220729-android/armeabi-v7a/include/ncnn
 52 | 
 53 | 
 54 | LIBS += \
 55 | $$ANDROID_OPENCV/staticlibs/armeabi-v7a/libopencv_ml.a \
 56 | $$ANDROID_OPENCV/staticlibs/armeabi-v7a/libopencv_objdetect.a \
 57 | $$ANDROID_OPENCV/staticlibs/armeabi-v7a/libopencv_calib3d.a \
 58 | $$ANDROID_OPENCV/staticlibs/armeabi-v7a/libopencv_video.a \
 59 | $$ANDROID_OPENCV/staticlibs/armeabi-v7a/libopencv_features2d.a \
 60 | $$ANDROID_OPENCV/staticlibs/armeabi-v7a/libopencv_highgui.a \
 61 | $$ANDROID_OPENCV/staticlibs/armeabi-v7a/libopencv_flann.a \
 62 | $$ANDROID_OPENCV/staticlibs/armeabi-v7a/libopencv_imgproc.a \
 63 | $$ANDROID_OPENCV/staticlibs/armeabi-v7a/libopencv_dnn.a \
 64 | $$ANDROID_OPENCV/staticlibs/armeabi-v7a/libopencv_core.a \
 65 | $$ANDROID_OPENCV/3rdparty/libs/armeabi-v7a/libcpufeatures.a \
 66 | $$ANDROID_OPENCV/3rdparty/libs/armeabi-v7a/libIlmImf.a \
 67 | #$$ANDROID_OPENCV/3rdparty/libs/armeabi-v7a/liblibjasper.a \
 68 | $$ANDROID_OPENCV/3rdparty/libs/armeabi-v7a/liblibjpeg-turbo.a \
 69 | $$ANDROID_OPENCV/3rdparty/libs/armeabi-v7a/liblibpng.a \
 70 | $$ANDROID_OPENCV/3rdparty/libs/armeabi-v7a/liblibprotobuf.a \
 71 | $$ANDROID_OPENCV/3rdparty/libs/armeabi-v7a/liblibtiff.a \
 72 | $$ANDROID_OPENCV/3rdparty/libs/armeabi-v7a/liblibwebp.a \
 73 | $$ANDROID_OPENCV/3rdparty/libs/armeabi-v7a/libquirc.a \
 74 | $$ANDROID_OPENCV/3rdparty/libs/armeabi-v7a/libtbb.a \
 75 | $$ANDROID_OPENCV/3rdparty/libs/armeabi-v7a/libtegra_hal.a \
 76 | $$ANDROID_OPENCV/libs/armeabi-v7a/libopencv_java4.so \
 77 | F:/andriod_env/ncnn/ncnn-20220729-android/armeabi-v7a/lib/libncnn.a \
 78 | F:/andriod_env/qtforandroid/android-ndk-r21/platforms/android-28/arch-arm/usr/lib/libandroid.so \
 79 | F:/andriod_env/qtforandroid/android-ndk-r21/toolchains/llvm/prebuilt/windows-x86_64/lib64/clang/9.0.8/lib/linux/arm/libomp.a \
 80 | F:/andriod_env/qtforandroid/android-ndk-r21/toolchains/llvm/prebuilt/windows-x86_64/lib64/clang/9.0.8/lib/linux/arm/libomp.so
 81 | 
 82 | # opencv-mobile配置 已废弃
 83 | #$$ANDROID_OPENCV/staticlibs/armeabi-v7a/libopencv_core.a \
 84 | #$$ANDROID_OPENCV/staticlibs/armeabi-v7a/libopencv_features2d.a \
 85 | #$$ANDROID_OPENCV/staticlibs/armeabi-v7a/libopencv_highgui.a \
 86 | #$$ANDROID_OPENCV/staticlibs/armeabi-v7a/libopencv_imgproc.a \
 87 | #$$ANDROID_OPENCV/staticlibs/armeabi-v7a/libopencv_photo.a \
 88 | #$$ANDROID_OPENCV/staticlibs/armeabi-v7a/libopencv_video.a \
 89 | 
 90 | # add other file to assets
 91 | 
 92 | data.files += assets/ai.png
 93 | data.files += assets/icon.png
 94 | data.files += model/yolov8s_opt.param
 95 | data.files += model/yolov8s_opt.bin
 96 | 
 97 | data.path = /assets/pic
 98 | INSTALLS += data
 99 | 
100 | }
101 | 
102 | 
103 | ANDROID_EXTRA_LIBS += F:/andriod_env/OpenCV-android-sdk/sdk/native/libs/armeabi-v7a/libopencv_java4.so \
104 |                       F:/andriod_env/qtforandroid/android-ndk-r21/platforms/android-28/arch-arm/usr/lib/libandroid.so \
105 |                       F:/andriod_env/qtforandroid/android-ndk-r21/toolchains/llvm/prebuilt/windows-x86_64/lib64/clang/9.0.8/lib/linux/arm/libomp.so
106 | 
107 | DISTFILES += \
108 |     android/AndroidManifest.xml \
109 |     android/build.gradle \
110 |     android/gradle/wrapper/gradle-wrapper.jar \
111 |     android/gradle/wrapper/gradle-wrapper.properties \
112 |     android/gradlew \
113 |     android/gradlew.bat \
114 |     android/res/values/libs.xml
115 | 
116 | ANDROID_PACKAGE_SOURCE_DIR = $$PWD/android
117 | 
118 | RESOURCES += \
119 |     pic.qrc
120 | 


--------------------------------------------------------------------------------