{"id":1753,"date":"2025-03-24T08:49:59","date_gmt":"2025-03-23T23:49:59","guid":{"rendered":"https:\/\/dexall.co.jp\/articles\/?p=1753"},"modified":"2025-03-24T08:49:59","modified_gmt":"2025-03-23T23:49:59","slug":"opencv-c%e5%85%a5%e9%96%80%ef%bc%9a%e7%94%bb%e5%83%8f%e5%87%a6%e7%90%86%e3%81%ae%e5%ae%9f%e8%a3%85%e3%81%8b%e3%82%89%e6%9c%80%e9%81%a9%e5%8c%96%e3%81%be%e3%81%a7%e5%ae%8c%e5%85%a8%e8%a7%a3%e8%aa%ac","status":"publish","type":"post","link":"https:\/\/dexall.co.jp\/articles\/?p=1753","title":{"rendered":"OpenCV C++\u5165\u9580\uff1a\u753b\u50cf\u51e6\u7406\u306e\u5b9f\u88c5\u304b\u3089\u6700\u9069\u5316\u307e\u3067\u5b8c\u5168\u89e3\u8aac"},"content":{"rendered":"\n<div class=\"toc\"><br \/>\n<b>Warning<\/b>:  Undefined array key \"is_admin\" in <b>\/home\/xs392991\/dexall.co.jp\/public_html\/articles\/wp-content\/themes\/sango-theme\/library\/gutenberg\/dist\/classes\/Toc.php<\/b> on line <b>116<\/b><br \/>\n<br \/>\n<b>Warning<\/b>:  Undefined array key \"is_category_top\" in <b>\/home\/xs392991\/dexall.co.jp\/public_html\/articles\/wp-content\/themes\/sango-theme\/library\/gutenberg\/dist\/classes\/Toc.php<\/b> on line <b>121<\/b><br \/>\n<br \/>\n<b>Warning<\/b>:  Undefined array key \"is_top\" in <b>\/home\/xs392991\/dexall.co.jp\/public_html\/articles\/wp-content\/themes\/sango-theme\/library\/gutenberg\/dist\/classes\/Toc.php<\/b> on line <b>128<\/b><br \/>\n    <div id=\"toc_container\" class=\"sgb-toc--bullets js-smooth-scroll\" data-dialog-title=\"\u76ee\u6b21\">\n      <p class=\"toc_title\">\u76ee\u6b21 <\/p>\n      <ul class=\"toc_list\">  <li class=\"first\">    <a href=\"#i-0\">OpenCV C++\u74b0\u5883\u69cb\u7bc9\u30ac\u30a4\u30c9<\/a>    <ul class=\"menu_level_1\">      <li class=\"first\">        <a href=\"#i-1\">Windows \u3067\u306e OpenCV \u74b0\u5883\u69cb\u7bc9\u624b\u9806<\/a>      <\/li>      <li>        <a href=\"#i-2\">Linux \u3067\u306e OpenCV \u74b0\u5883\u69cb\u7bc9\u624b\u9806<\/a>      <\/li>      <li class=\"last\">        <a href=\"#i-3\">Visual Studio \u3067\u306e OpenCV \u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u8a2d\u5b9a<\/a>      <\/li>    <\/ul>  <\/li>  <li>    <a href=\"#i-4\">OpenCV C++ \u3067\u306e\u57fa\u672c\u7684\u306a\u753b\u50cf\u51e6\u7406<\/a>    <ul class=\"menu_level_1\">      <li class=\"first\">        <a href=\"#i-5\">\u753b\u50cf\u306e\u8aad\u307f\u8fbc\u307f\u3068\u8868\u793a\u306e\u5b9f\u88c5\u65b9\u6cd5<\/a>      <\/li>      <li>        <a href=\"#i-6\">\u753b\u50cf\u306e\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\u51e6\u7406\u306e\u5b9f\u88c5\u4f8b<\/a>      <\/li>      <li class=\"last\">        <a href=\"#i-7\">\u30a8\u30c3\u30b8\u691c\u51fa\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306e\u5b9f\u88c5\u624b\u9806<\/a>      <\/li>    <\/ul>  <\/li>  <li>    <a href=\"#i-8\">\u5b9f\u8df5\u7684\u306aOpenCV C++ \u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0<\/a>    <ul class=\"menu_level_1\">      <li class=\"first\">        <a href=\"#i-9\">\u9854\u691c\u51fa\u30b7\u30b9\u30c6\u30e0\u306e\u5b9f\u88c5\u65b9\u6cd5<\/a>      <\/li>      <li>        <a href=\"#i-10\">\u52d5\u753b\u51e6\u7406\u306e\u52b9\u7387\u7684\u306a\u30c6\u30af\u30cb\u30c3\u30af\u5b9f\u88c5<\/a>      <\/li>      <li class=\"last\">        <a href=\"#i-11\">\u7269\u4f53\u8ffd\u8de1\u30b7\u30b9\u30c6\u30e0\u306e\u5b9f\u88c5\u4f8b<\/a>      <\/li>    <\/ul>  <\/li>  <li>    <a href=\"#i-12\">OpenCV C++\u306e\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u6700\u9069\u5316<\/a>    <ul class=\"menu_level_1\">      <li class=\"first\">        <a href=\"#i-13\">\u30e1\u30e2\u30ea\u4f7f\u7528\u91cf\u306e\u6700\u9069\u5316\u624b\u6cd5<\/a>      <\/li>      <li>        <a href=\"#i-14\">\u51e6\u7406\u901f\u5ea6\u3092\u5411\u4e0a\u3055\u305b\u308b\u30c6\u30af\u30cb\u30c3\u30af\u5b9f\u88c5<\/a>      <\/li>      <li class=\"last\">        <a href=\"#i-15\">\u4e26\u5217\u51e6\u7406\u306b\u3088\u308b\u9ad8\u901f\u5316\u306e\u5b9f\u88c5\u65b9\u6cd5<\/a>      <\/li>    <\/ul>  <\/li>  <li>    <a href=\"#i-16\">OpenCV C++\u306e\u5b9f\u52d9\u3067\u306e\u6d3b\u7528\u4e8b\u4f8b<\/a>    <ul class=\"menu_level_1\">      <li class=\"first\">        <a href=\"#i-17\">\u7523\u696d\u7528\u753b\u50cf\u691c\u67fb\u30b7\u30b9\u30c6\u30e0\u306e\u5b9f\u88c5\u4f8b<\/a>      <\/li>      <li>        <a href=\"#i-18\">\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\u30b7\u30b9\u30c6\u30e0\u3067\u306e\u6d3b\u7528\u65b9\u6cd5<\/a>      <\/li>      <li class=\"last\">        <a href=\"#i-19\">\u533b\u7642\u753b\u50cf\u51e6\u7406\u3067\u306e\u5fdc\u7528\u6280\u8853<\/a>      <\/li>    <\/ul>  <\/li>  <li class=\"last\">    <a href=\"#i-20\">OpenCV C++ \u3067\u306e\u30c8\u30e9\u30d6\u30eb\u30b7\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0<\/a>    <ul class=\"menu_level_1\">      <li class=\"first\">        <a href=\"#i-21\">\u4e00\u822c\u7684\u306a\u30a8\u30e9\u30fc\u3068\u305d\u306e\u89e3\u6c7a\u65b9\u6cd5<\/a>      <\/li>      <li>        <a href=\"#i-22\">\u30c7\u30d0\u30c3\u30b0\u30c6\u30af\u30cb\u30c3\u30af\u3068\u30d9\u30b9\u30c8\u30d7\u30e9\u30af\u30c6\u30a3\u30b9<\/a>      <\/li>      <li class=\"last\">        <a href=\"#i-23\">\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u554f\u984c\u306e\u8a3a\u65ad\u3068\u6539\u5584\u65b9\u6cd5<\/a>      <\/li>    <\/ul>  <\/li><\/ul>\n      <a href=\"#\" class=\"sgb-toc-button js-toc-button\" rel=\"nofollow\" data-open-dialog=\"true\"><i class=\"fa fa-list\"><\/i><span class=\"sgb-toc-button__text\">\u76ee\u6b21\u3078<\/span><\/a>\n    <\/div><\/div><h2 class=\"wp-block-heading\" id=\"i-0\">OpenCV C++\u74b0\u5883\u69cb\u7bc9\u30ac\u30a4\u30c9<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"i-1\">Windows \u3067\u306e OpenCV \u74b0\u5883\u69cb\u7bc9\u624b\u9806<\/h3>\n\n\n\n<p>Windows\u3067\u306eOpenCV\u74b0\u5883\u69cb\u7bc9\u306f\u3001\u4ee5\u4e0b\u306e\u624b\u9806\u3067\u884c\u3044\u307e\u3059\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u4e8b\u524d\u6e96\u5099<\/strong><\/li>\n<\/ol>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Visual Studio\uff08\u63a8\u5968\uff1a\u6700\u65b0\u7248\uff09\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb<\/li>\n\n\n\n<li>CMake\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\uff08https:\/\/cmake.org\/download\/\uff09<\/li>\n\n\n\n<li>Git\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u307e\u305f\u306fOpenCV\u306e\u30bd\u30fc\u30b9\u30b3\u30fc\u30c9\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9<\/li>\n<\/ul>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>OpenCV\u306e\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3068\u30d3\u30eb\u30c9<\/strong><\/li>\n<\/ol>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\"># GitHub\u304b\u3089OpenCV\u3092\u30af\u30ed\u30fc\u30f3\ngit clone https:\/\/github.com\/opencv\/opencv.git\ncd opencv\ngit checkout 4.9.0  # \u6700\u65b0\u306e\u5b89\u5b9a\u7248\u3092\u4f7f\u7528\n\n# \u30d3\u30eb\u30c9\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u306e\u4f5c\u6210\nmkdir build\ncd build\n\n# CMake\u306e\u5b9f\u884c\ncmake -DCMAKE_BUILD_TYPE=Release -DBUILD_EXAMPLES=ON ..\n\n# Visual Studio\u3067\u30d3\u30eb\u30c9\ncmake --build . --config Release<\/pre>\n\n\n\n<ol start=\"3\" class=\"wp-block-list\">\n<li><strong>\u74b0\u5883\u5909\u6570\u306e\u8a2d\u5b9a<\/strong><\/li>\n<\/ol>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u30b7\u30b9\u30c6\u30e0\u74b0\u5883\u5909\u6570\u306e\u300cPath\u300d\u306b\u4ee5\u4e0b\u3092\u8ffd\u52a0\uff1a\n<ul class=\"wp-block-list\">\n<li><code>C:\\opencv\\build\\install\\x64\\vc17\\bin<\/code>\uff08\u30d3\u30eb\u30c9\u30d1\u30b9\u306b\u5fdc\u3058\u3066\u5909\u66f4\uff09<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<ol start=\"3\" class=\"wp-block-list\">\n<li><strong>\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u306e\u78ba\u8a8d<\/strong><\/li>\n<\/ol>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">#include &lt;opencv2\/opencv.hpp&gt;\n#include &lt;iostream&gt;\n\nint main() {\n    std::cout &lt;&lt; \"OpenCV version: \" &lt;&lt; CV_VERSION &lt;&lt; std::endl;\n    return 0;\n}<\/pre>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"i-2\">Linux \u3067\u306e OpenCV \u74b0\u5883\u69cb\u7bc9\u624b\u9806<\/h3>\n\n\n\n<p>Linux\u3067\u306f\u3001\u5fc5\u8981\u306a\u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u3066\u304b\u3089OpenCV\u3092\u30d3\u30eb\u30c9\u3057\u307e\u3059\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u5fc5\u8981\u306a\u30d1\u30c3\u30b1\u30fc\u30b8\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb<\/strong><\/li>\n<\/ol>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">sudo apt update\nsudo apt install build-essential cmake pkg-config\nsudo apt install libjpeg-dev libpng-dev libtiff-dev\nsudo apt install libavcodec-dev libavformat-dev libswscale-dev\nsudo apt install libv4l-dev libxvidcore-dev libx264-dev\nsudo apt install libgtk-3-dev\nsudo apt install libatlas-base-dev gfortran<\/pre>\n\n\n\n<ol start=\"2\" class=\"wp-block-list\">\n<li><strong>OpenCV\u306e\u30d3\u30eb\u30c9\u3068\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb<\/strong><\/li>\n<\/ol>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\"># \u30bd\u30fc\u30b9\u30b3\u30fc\u30c9\u306e\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\nwget -O opencv.zip https:\/\/github.com\/opencv\/opencv\/archive\/4.9.0.zip\nunzip opencv.zip\ncd opencv-4.9.0\n\n# \u30d3\u30eb\u30c9\nmkdir build\ncd build\ncmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=\/usr\/local ..\nmake -j$(nproc)\nsudo make install<\/pre>\n\n\n\n<ol start=\"3\" class=\"wp-block-list\">\n<li><strong>\u30e9\u30a4\u30d6\u30e9\u30ea\u30d1\u30b9\u306e\u66f4\u65b0<\/strong><\/li>\n<\/ol>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">sudo ldconfig<\/pre>\n\n\n\n<ol start=\"4\" class=\"wp-block-list\">\n<li><strong>\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u306e\u78ba\u8a8d<\/strong><\/li>\n<\/ol>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">pkg-config --modversion opencv4<\/pre>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"i-3\">Visual Studio \u3067\u306e OpenCV \u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u8a2d\u5b9a<\/h3>\n\n\n\n<p>\u65b0\u898f\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3067OpenCV\u3092\u4f7f\u7528\u3059\u308b\u305f\u3081\u306e\u8a2d\u5b9a\u624b\u9806\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u30d7\u30ed\u30d1\u30c6\u30a3\u306e\u8a2d\u5b9a<\/strong><\/li>\n<\/ol>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u306e\u30d7\u30ed\u30d1\u30c6\u30a3\u30da\u30fc\u30b8\u3092\u958b\u304f<\/li>\n\n\n\n<li>\u300cC\/C++\u300d\u2192\u300c\u8ffd\u52a0\u306e\u30a4\u30f3\u30af\u30eb\u30fc\u30c9\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u300d\u306b\u8ffd\u52a0\uff1a<br><code>C:\\opencv\\build\\install\\include<\/code><\/li>\n\n\n\n<li>\u300c\u30ea\u30f3\u30ab\u30fc\u300d\u2192\u300c\u8ffd\u52a0\u306e\u30e9\u30a4\u30d6\u30e9\u30ea\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u300d\u306b\u8ffd\u52a0\uff1a<br><code>C:\\opencv\\build\\install\\x64\\vc17\\lib<\/code><\/li>\n<\/ul>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u4f9d\u5b58\u30e9\u30a4\u30d6\u30e9\u30ea\u306e\u8a2d\u5b9a<\/strong><\/li>\n<\/ol>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u300c\u30ea\u30f3\u30ab\u30fc\u300d\u2192\u300c\u5165\u529b\u300d\u2192\u300c\u8ffd\u52a0\u306e\u4f9d\u5b58\u30d5\u30a1\u30a4\u30eb\u300d\u306b\u8ffd\u52a0\uff1a<br><code>opencv_world490.lib # Release\u30d3\u30eb\u30c9\u7528 opencv_world490d.lib # Debug\u30d3\u30eb\u30c9\u7528<\/code><\/li>\n<\/ul>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u52d5\u4f5c\u78ba\u8a8d\u7528\u30b5\u30f3\u30d7\u30eb\u30b3\u30fc\u30c9<\/strong><\/li>\n<\/ol>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">#include &lt;opencv2\/opencv.hpp&gt;\n#include &lt;iostream&gt;\n\nint main() {\n    \/\/ \u753b\u50cf\u306e\u8aad\u307f\u8fbc\u307f\n    cv::Mat img = cv::imread(\"sample.jpg\");\n\n    if(img.empty()) {\n        std::cout &lt;&lt; \"Error: \u753b\u50cf\u3092\u8aad\u307f\u8fbc\u3081\u307e\u305b\u3093\u3067\u3057\u305f\u3002\" &lt;&lt; std::endl;\n        return -1;\n    }\n\n    \/\/ \u753b\u50cf\u306e\u8868\u793a\n    cv::imshow(\"Sample Image\", img);\n    cv::waitKey(0);\n\n    return 0;\n}<\/pre>\n\n\n\n<ol start=\"4\" class=\"wp-block-list\">\n<li><strong>\u4e00\u822c\u7684\u306a\u30c8\u30e9\u30d6\u30eb\u30b7\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0<\/strong><\/li>\n<\/ol>\n\n\n\n<ul class=\"wp-block-list\">\n<li>DLL\u304c\u898b\u3064\u304b\u3089\u306a\u3044\u30a8\u30e9\u30fc \u2192 bin\u30d5\u30a9\u30eb\u30c0\u3092\u74b0\u5883\u5909\u6570Path\u306b\u8ffd\u52a0<\/li>\n\n\n\n<li>\u30ea\u30f3\u30ab\u30fc\u30a8\u30e9\u30fc \u2192 \u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u8a2d\u5b9a\u3067\u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\uff08x64\/x86\uff09\u3068OpenCV\u306e\u30d3\u30eb\u30c9\u8a2d\u5b9a\u304c\u4e00\u81f4\u3057\u3066\u3044\u308b\u304b\u78ba\u8a8d<\/li>\n\n\n\n<li>\u30a4\u30f3\u30af\u30eb\u30fc\u30c9\u30a8\u30e9\u30fc \u2192 \u30d1\u30b9\u304c\u6b63\u3057\u304f\u8a2d\u5b9a\u3055\u308c\u3066\u3044\u308b\u304b\u78ba\u8a8d<\/li>\n<\/ul>\n\n\n\n<p>\u3053\u308c\u3089\u306e\u624b\u9806\u306b\u5f93\u3046\u3053\u3068\u3067\u3001Windows\u3001Linux\u3001\u304a\u3088\u3073Visual Studio\u3067\u5b8c\u5168\u306aOpenCV C++\u958b\u767a\u74b0\u5883\u3092\u69cb\u7bc9\u3067\u304d\u307e\u3059\u3002\u74b0\u5883\u69cb\u7bc9\u5f8c\u306f\u3001\u30b5\u30f3\u30d7\u30eb\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3057\u3066\u6b63\u5e38\u306b\u52d5\u4f5c\u3059\u308b\u3053\u3068\u3092\u78ba\u8a8d\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"i-4\">OpenCV C++ \u3067\u306e\u57fa\u672c\u7684\u306a\u753b\u50cf\u51e6\u7406<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"i-5\">\u753b\u50cf\u306e\u8aad\u307f\u8fbc\u307f\u3068\u8868\u793a\u306e\u5b9f\u88c5\u65b9\u6cd5<\/h3>\n\n\n\n<p>\u57fa\u672c\u7684\u306a\u753b\u50cf\u64cd\u4f5c\u306e\u5b9f\u88c5\u304b\u3089\u59cb\u3081\u307e\u3057\u3087\u3046\u3002\u4ee5\u4e0b\u306e\u30b3\u30fc\u30c9\u306f\u3001\u753b\u50cf\u306e\u8aad\u307f\u8fbc\u307f\u3001\u8868\u793a\u3001\u4fdd\u5b58\u306e\u57fa\u672c\u7684\u306a\u64cd\u4f5c\u3092\u793a\u3057\u3066\u3044\u307e\u3059\uff1a<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">#include &lt;opencv2\/opencv.hpp&gt;\n#include &lt;iostream&gt;\n\nint main() {\n    \/\/ \u753b\u50cf\u306e\u8aad\u307f\u8fbc\u307f\n    cv::Mat image = cv::imread(\"input.jpg\");\n\n    \/\/ \u8aad\u307f\u8fbc\u307f\u306e\u78ba\u8a8d\n    if (image.empty()) {\n        std::cout &lt;&lt; \"Error: \u753b\u50cf\u3092\u8aad\u307f\u8fbc\u3081\u307e\u305b\u3093\u3067\u3057\u305f\u3002\" &lt;&lt; std::endl;\n        return -1;\n    }\n\n    \/\/ \u753b\u50cf\u60c5\u5831\u306e\u8868\u793a\n    std::cout &lt;&lt; \"\u753b\u50cf\u30b5\u30a4\u30ba: \" &lt;&lt; image.size() &lt;&lt; std::endl;\n    std::cout &lt;&lt; \"\u30c1\u30e3\u30f3\u30cd\u30eb\u6570: \" &lt;&lt; image.channels() &lt;&lt; std::endl;\n\n    \/\/ \u753b\u50cf\u306e\u8868\u793a\n    cv::imshow(\"Original Image\", image);\n\n    \/\/ \u30b0\u30ec\u30fc\u30b9\u30b1\u30fc\u30eb\u5909\u63db\n    cv::Mat gray_image;\n    cv::cvtColor(image, gray_image, cv::COLOR_BGR2GRAY);\n    cv::imshow(\"Grayscale Image\", gray_image);\n\n    \/\/ \u753b\u50cf\u306e\u4fdd\u5b58\n    cv::imwrite(\"output_gray.jpg\", gray_image);\n\n    \/\/ \u30ad\u30fc\u5165\u529b\u5f85\u3061\n    cv::waitKey(0);\n\n    return 0;\n}<\/pre>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"i-6\">\u753b\u50cf\u306e\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\u51e6\u7406\u306e\u5b9f\u88c5\u4f8b<\/h3>\n\n\n\n<p>\u753b\u50cf\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\u306f\u753b\u50cf\u51e6\u7406\u306e\u57fa\u672c\u7684\u304b\u3064\u91cd\u8981\u306a\u64cd\u4f5c\u3067\u3059\u3002\u4ee5\u4e0b\u306b\u4e3b\u8981\u306a\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\u51e6\u7406\u306e\u5b9f\u88c5\u4f8b\u3092\u793a\u3057\u307e\u3059\uff1a<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">#include &lt;opencv2\/opencv.hpp&gt;\n\nint main() {\n    cv::Mat image = cv::imread(\"input.jpg\");\n    if (image.empty()) return -1;\n\n    \/\/ \u30ac\u30a6\u30b7\u30a2\u30f3\u30d6\u30e9\u30fc\n    cv::Mat gaussian_blur;\n    cv::GaussianBlur(image, gaussian_blur, cv::Size(5, 5), 0);\n\n    \/\/ \u30e1\u30c7\u30a3\u30a2\u30f3\u30d5\u30a3\u30eb\u30bf\n    cv::Mat median_blur;\n    cv::medianBlur(image, median_blur, 5);\n\n    \/\/ \u30d0\u30a4\u30e9\u30c6\u30e9\u30eb\u30d5\u30a3\u30eb\u30bf\n    cv::Mat bilateral_filter;\n    cv::bilateralFilter(image, bilateral_filter, 9, 75, 75);\n\n    \/\/ \u30ab\u30b9\u30bf\u30e0\u30ab\u30fc\u30cd\u30eb\u306b\u3088\u308b\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\n    cv::Mat kernel = (cv::Mat_&lt;float&gt;(3,3) &lt;&lt;\n        -1, -1, -1,\n        -1,  9, -1,\n        -1, -1, -1);\n    cv::Mat sharpened;\n    cv::filter2D(image, sharpened, -1, kernel);\n\n    \/\/ \u7d50\u679c\u306e\u8868\u793a\u3068\u4fdd\u5b58\n    cv::imshow(\"Original\", image);\n    cv::imshow(\"Gaussian Blur\", gaussian_blur);\n    cv::imshow(\"Median Blur\", median_blur);\n    cv::imshow(\"Bilateral Filter\", bilateral_filter);\n    cv::imshow(\"Sharpened\", sharpened);\n\n    cv::waitKey(0);\n    return 0;\n}<\/pre>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"i-7\">\u30a8\u30c3\u30b8\u691c\u51fa\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306e\u5b9f\u88c5\u624b\u9806<\/h3>\n\n\n\n<p>\u30a8\u30c3\u30b8\u691c\u51fa\u306f\u7269\u4f53\u8a8d\u8b58\u3084\u7279\u5fb4\u62bd\u51fa\u306e\u57fa\u790e\u3068\u306a\u308b\u91cd\u8981\u306a\u51e6\u7406\u3067\u3059\u3002\u4ee3\u8868\u7684\u306a\u30a8\u30c3\u30b8\u691c\u51fa\u624b\u6cd5\u306e\u5b9f\u88c5\u4f8b\u3092\u793a\u3057\u307e\u3059\uff1a<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">#include &lt;opencv2\/opencv.hpp&gt;\n\nint main() {\n    \/\/ \u753b\u50cf\u306e\u8aad\u307f\u8fbc\u307f\u3068\u30b0\u30ec\u30fc\u30b9\u30b1\u30fc\u30eb\u5909\u63db\n    cv::Mat image = cv::imread(\"input.jpg\");\n    if (image.empty()) return -1;\n\n    cv::Mat gray;\n    cv::cvtColor(image, gray, cv::COLOR_BGR2GRAY);\n\n    \/\/ Sobel\u30a8\u30c3\u30b8\u691c\u51fa\n    cv::Mat sobel_x, sobel_y, sobel_combined;\n    cv::Sobel(gray, sobel_x, CV_64F, 1, 0, 3);\n    cv::Sobel(gray, sobel_y, CV_64F, 0, 1, 3);\n\n    \/\/ Sobel\u306e\u7d50\u679c\u3092\u5408\u6210\n    cv::convertScaleAbs(sobel_x, sobel_x);\n    cv::convertScaleAbs(sobel_y, sobel_y);\n    cv::addWeighted(sobel_x, 0.5, sobel_y, 0.5, 0, sobel_combined);\n\n    \/\/ Canny\u30a8\u30c3\u30b8\u691c\u51fa\n    cv::Mat canny;\n    cv::Canny(gray, canny, 50, 150);\n\n    \/\/ Laplacian\u30a8\u30c3\u30b8\u691c\u51fa\n    cv::Mat laplacian;\n    cv::Laplacian(gray, laplacian, CV_64F);\n    cv::convertScaleAbs(laplacian, laplacian);\n\n    \/\/ \u7d50\u679c\u306e\u8868\u793a\n    cv::imshow(\"Original\", image);\n    cv::imshow(\"Sobel Edge Detection\", sobel_combined);\n    cv::imshow(\"Canny Edge Detection\", canny);\n    cv::imshow(\"Laplacian Edge Detection\", laplacian);\n\n    cv::waitKey(0);\n    return 0;\n}<\/pre>\n\n\n\n<p>\u5404\u30a8\u30c3\u30b8\u691c\u51fa\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306e\u7279\u5fb4\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Sobel\u30d5\u30a3\u30eb\u30bf<\/strong><\/li>\n<\/ol>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u7e26\u65b9\u5411\u3068\u6a2a\u65b9\u5411\u306e\u52fe\u914d\u3092\u500b\u5225\u306b\u8a08\u7b97<\/li>\n\n\n\n<li>\u30a8\u30c3\u30b8\u306e\u65b9\u5411\u6027\u3092\u691c\u51fa\u53ef\u80fd<\/li>\n\n\n\n<li>\u30ce\u30a4\u30ba\u306b\u6bd4\u8f03\u7684\u5f37\u3044<\/li>\n<\/ul>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Canny\u30a8\u30c3\u30b8\u691c\u51fa<\/strong><\/li>\n<\/ol>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u30ce\u30a4\u30ba\u9664\u53bb\u3001\u52fe\u914d\u8a08\u7b97\u3001\u975e\u6700\u5927\u5024\u6291\u5236\u3001\u30d2\u30b9\u30c6\u30ea\u30b7\u30b9\u95be\u5024\u51e6\u7406\u3092\u542b\u3080<\/li>\n\n\n\n<li>\u7cbe\u5ea6\u306e\u9ad8\u3044\u30a8\u30c3\u30b8\u691c\u51fa\u304c\u53ef\u80fd<\/li>\n\n\n\n<li>\u30d1\u30e9\u30e1\u30fc\u30bf\u8abf\u6574\u304c\u5fc5\u8981<\/li>\n<\/ul>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Laplacian\u30d5\u30a3\u30eb\u30bf<\/strong><\/li>\n<\/ol>\n\n\n\n<ul class=\"wp-block-list\">\n<li>2\u6b21\u5fae\u5206\u3092\u5229\u7528\u3057\u305f\u30a8\u30c3\u30b8\u691c\u51fa<\/li>\n\n\n\n<li>\u30a8\u30c3\u30b8\u3092\u3088\u308a\u7d30\u304f\u691c\u51fa<\/li>\n\n\n\n<li>\u30ce\u30a4\u30ba\u306b\u654f\u611f<\/li>\n<\/ul>\n\n\n\n<p>\u5b9f\u88c5\u306e\u30dd\u30a4\u30f3\u30c8\uff1a<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u30b0\u30ec\u30fc\u30b9\u30b1\u30fc\u30eb\u5909\u63db\u3092\u524d\u51e6\u7406\u3068\u3057\u3066\u884c\u3046<\/li>\n\n\n\n<li>\u9069\u5207\u306a\u95be\u5024\u306e\u8a2d\u5b9a\u304c\u91cd\u8981<\/li>\n\n\n\n<li>\u7528\u9014\u306b\u5fdc\u3058\u3066\u9069\u5207\u306a\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3092\u9078\u629e<\/li>\n\n\n\n<li>\u5fc5\u8981\u306b\u5fdc\u3058\u3066\u30ce\u30a4\u30ba\u9664\u53bb\u3092\u8ffd\u52a0<\/li>\n<\/ul>\n\n\n\n<p>\u3053\u308c\u3089\u306e\u57fa\u672c\u7684\u306a\u753b\u50cf\u51e6\u7406\u6280\u8853\u3092\u7d44\u307f\u5408\u308f\u305b\u308b\u3053\u3068\u3067\u3001\u3088\u308a\u9ad8\u5ea6\u306a\u753b\u50cf\u51e6\u7406\u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3\u306e\u958b\u767a\u304c\u53ef\u80fd\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"i-8\">\u5b9f\u8df5\u7684\u306aOpenCV C++ \u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"i-9\">\u9854\u691c\u51fa\u30b7\u30b9\u30c6\u30e0\u306e\u5b9f\u88c5\u65b9\u6cd5<\/h3>\n\n\n\n<p>OpenCV\u306e\u9854\u691c\u51fa\u6a5f\u80fd\u3092\u4f7f\u7528\u3057\u305f\u5b9f\u8df5\u7684\u306a\u5b9f\u88c5\u4f8b\u3092\u793a\u3057\u307e\u3059\uff1a<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">#include &lt;opencv2\/opencv.hpp&gt;\n#include &lt;iostream&gt;\n\nclass FaceDetector {\nprivate:\n    cv::CascadeClassifier face_cascade;\n    double scale_factor;\n    int min_neighbors;\n\npublic:\n    FaceDetector(const std::string&amp; cascade_path = \"haarcascade_frontalface_default.xml\",\n                 double scale = 1.1,\n                 int neighbors = 3) : scale_factor(scale), min_neighbors(neighbors) {\n        \/\/ \u30ab\u30b9\u30b1\u30fc\u30c9\u5206\u985e\u5668\u306e\u8aad\u307f\u8fbc\u307f\n        if (!face_cascade.load(cascade_path)) {\n            throw std::runtime_error(\"\u30ab\u30b9\u30b1\u30fc\u30c9\u5206\u985e\u5668\u306e\u8aad\u307f\u8fbc\u307f\u306b\u5931\u6557\u3057\u307e\u3057\u305f\u3002\");\n        }\n    }\n\n    std::vector&lt;cv::Rect&gt; detectFaces(const cv::Mat&amp; frame) {\n        std::vector&lt;cv::Rect&gt; faces;\n        cv::Mat gray;\n\n        \/\/ \u30b0\u30ec\u30fc\u30b9\u30b1\u30fc\u30eb\u5909\u63db\n        cv::cvtColor(frame, gray, cv::COLOR_BGR2GRAY);\n\n        \/\/ \u30b3\u30f3\u30c8\u30e9\u30b9\u30c8\u8abf\u6574\n        cv::equalizeHist(gray, gray);\n\n        \/\/ \u9854\u691c\u51fa\u306e\u5b9f\u884c\n        face_cascade.detectMultiScale(gray, faces, scale_factor, min_neighbors, 0,\n                                    cv::Size(30, 30));\n        return faces;\n    }\n\n    void drawFaces(cv::Mat&amp; frame, const std::vector&lt;cv::Rect&gt;&amp; faces) {\n        for (const auto&amp; face : faces) {\n            \/\/ \u691c\u51fa\u3055\u308c\u305f\u9854\u3092\u77e9\u5f62\u3067\u56f2\u3080\n            cv::rectangle(frame, face, cv::Scalar(255, 0, 0), 2);\n\n            \/\/ \u9854\u306e\u4e2d\u5fc3\u306b\u70b9\u3092\u63cf\u753b\n            cv::Point center(face.x + face.width\/2, face.y + face.height\/2);\n            cv::circle(frame, center, 3, cv::Scalar(0, 255, 0), -1);\n        }\n    }\n};\n\nint main() {\n    try {\n        cv::VideoCapture cap(0); \/\/ \u30ab\u30e1\u30e9\u306e\u521d\u671f\u5316\n        if (!cap.isOpened()) {\n            throw std::runtime_error(\"\u30ab\u30e1\u30e9\u3092\u958b\u3051\u307e\u305b\u3093\u3067\u3057\u305f\u3002\");\n        }\n\n        FaceDetector detector;\n        cv::Mat frame;\n\n        while (true) {\n            cap &gt;&gt; frame;\n            if (frame.empty()) break;\n\n            \/\/ \u9854\u691c\u51fa\n            auto faces = detector.detectFaces(frame);\n\n            \/\/ \u691c\u51fa\u7d50\u679c\u306e\u63cf\u753b\n            detector.drawFaces(frame, faces);\n\n            \/\/ \u691c\u51fa\u3055\u308c\u305f\u9854\u306e\u6570\u3092\u8868\u793a\n            cv::putText(frame, \"Faces: \" + std::to_string(faces.size()),\n                       cv::Point(10, 30), cv::FONT_HERSHEY_SIMPLEX, 1,\n                       cv::Scalar(0, 255, 0), 2);\n\n            cv::imshow(\"Face Detection\", frame);\n\n            if (cv::waitKey(1) == 27) break; \/\/ ESC\u30ad\u30fc\u3067\u7d42\u4e86\n        }\n    }\n    catch (const std::exception&amp; e) {\n        std::cerr &lt;&lt; \"\u30a8\u30e9\u30fc: \" &lt;&lt; e.what() &lt;&lt; std::endl;\n        return -1;\n    }\n\n    return 0;\n}<\/pre>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"i-10\">\u52d5\u753b\u51e6\u7406\u306e\u52b9\u7387\u7684\u306a\u30c6\u30af\u30cb\u30c3\u30af\u5b9f\u88c5<\/h3>\n\n\n\n<p>\u52b9\u7387\u7684\u306a\u52d5\u753b\u51e6\u7406\u306e\u305f\u3081\u306e\u5b9f\u88c5\u4f8b\u3092\u793a\u3057\u307e\u3059\uff1a<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">#include &lt;opencv2\/opencv.hpp&gt;\n#include &lt;queue&gt;\n#include &lt;thread&gt;\n#include &lt;mutex&gt;\n#include &lt;condition_variable&gt;\n\nclass VideoProcessor {\nprivate:\n    std::queue&lt;cv::Mat&gt; frame_queue;\n    std::mutex mutex;\n    std::condition_variable cond;\n    bool stop_flag;\n\n    \/\/ \u30d5\u30ec\u30fc\u30e0\u51e6\u7406\u7528\u306e\u95a2\u6570\n    cv::Mat processFrame(const cv::Mat&amp; frame) {\n        cv::Mat processed;\n\n        \/\/ \u30ea\u30b5\u30a4\u30ba\u306b\u3088\u308b\u51e6\u7406\u306e\u52b9\u7387\u5316\n        cv::resize(frame, processed, cv::Size(), 0.5, 0.5);\n\n        \/\/ \u30ce\u30a4\u30ba\u9664\u53bb\n        cv::GaussianBlur(processed, processed, cv::Size(5, 5), 0);\n\n        \/\/ \u30b3\u30f3\u30c8\u30e9\u30b9\u30c8\u5f37\u8abf\n        cv::convertScaleAbs(processed, processed, 1.2, 10);\n\n        return processed;\n    }\n\npublic:\n    VideoProcessor() : stop_flag(false) {}\n\n    void start(const std::string&amp; video_path) {\n        cv::VideoCapture cap(video_path);\n        if (!cap.isOpened()) {\n            throw std::runtime_error(\"\u30d3\u30c7\u30aa\u30d5\u30a1\u30a4\u30eb\u3092\u958b\u3051\u307e\u305b\u3093\u3067\u3057\u305f\u3002\");\n        }\n\n        \/\/ \u51e6\u7406\u30b9\u30ec\u30c3\u30c9\u306e\u958b\u59cb\n        std::thread process_thread(&amp;VideoProcessor::processFrames, this);\n\n        cv::Mat frame;\n        while (true) {\n            cap &gt;&gt; frame;\n            if (frame.empty()) break;\n\n            {\n                std::lock_guard&lt;std::mutex&gt; lock(mutex);\n                frame_queue.push(frame.clone());\n            }\n            cond.notify_one();\n        }\n\n        \/\/ \u7d42\u4e86\u51e6\u7406\n        stop_flag = true;\n        cond.notify_one();\n        process_thread.join();\n    }\n\n    void processFrames() {\n        while (true) {\n            cv::Mat frame;\n            {\n                std::unique_lock&lt;std::mutex&gt; lock(mutex);\n                cond.wait(lock, [this] {\n                    return !frame_queue.empty() || stop_flag;\n                });\n\n                if (stop_flag &amp;&amp; frame_queue.empty()) break;\n\n                frame = frame_queue.front();\n                frame_queue.pop();\n            }\n\n            \/\/ \u30d5\u30ec\u30fc\u30e0\u51e6\u7406\n            cv::Mat processed = processFrame(frame);\n\n            \/\/ \u51e6\u7406\u7d50\u679c\u306e\u8868\u793a\n            cv::imshow(\"Processed Video\", processed);\n            cv::waitKey(1);\n        }\n    }\n};<\/pre>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"i-11\">\u7269\u4f53\u8ffd\u8de1\u30b7\u30b9\u30c6\u30e0\u306e\u5b9f\u88c5\u4f8b<\/h3>\n\n\n\n<p>KCF\u30c8\u30e9\u30c3\u30ab\u30fc\u3092\u4f7f\u7528\u3057\u305f\u7269\u4f53\u8ffd\u8de1\u30b7\u30b9\u30c6\u30e0\u306e\u5b9f\u88c5\u4f8b\u3092\u793a\u3057\u307e\u3059\uff1a<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">#include &lt;opencv2\/opencv.hpp&gt;\n#include &lt;opencv2\/tracking.hpp&gt;\n\nclass ObjectTracker {\nprivate:\n    cv::Ptr&lt;cv::Tracker&gt; tracker;\n    cv::Rect2d bbox;\n    bool tracking_initialized;\n\npublic:\n    ObjectTracker() : tracking_initialized(false) {\n        \/\/ KCF\u30c8\u30e9\u30c3\u30ab\u30fc\u306e\u521d\u671f\u5316\n        tracker = cv::TrackerKCF::create();\n    }\n\n    bool initializeTracker(const cv::Mat&amp; frame, const cv::Rect2d&amp; initial_bbox) {\n        bbox = initial_bbox;\n        if (tracker-&gt;init(frame, bbox)) {\n            tracking_initialized = true;\n            return true;\n        }\n        return false;\n    }\n\n    bool updateTracker(const cv::Mat&amp; frame) {\n        if (!tracking_initialized) return false;\n\n        if (tracker-&gt;update(frame, bbox)) {\n            \/\/ \u8ffd\u8de1\u7d50\u679c\u306e\u63cf\u753b\n            cv::rectangle(frame, bbox, cv::Scalar(255, 0, 0), 2);\n\n            \/\/ \u8ffd\u8de1\u5bfe\u8c61\u306e\u4e2d\u5fc3\u5ea7\u6a19\u3092\u8a08\u7b97\n            cv::Point2d center(bbox.x + bbox.width\/2, bbox.y + bbox.height\/2);\n            cv::circle(frame, center, 3, cv::Scalar(0, 255, 0), -1);\n\n            \/\/ \u8ffd\u8de1\u60c5\u5831\u306e\u8868\u793a\n            std::string info = \"Position: (\" + \n                             std::to_string(int(center.x)) + \", \" +\n                             std::to_string(int(center.y)) + \")\";\n            cv::putText(frame, info, cv::Point(10, 30),\n                       cv::FONT_HERSHEY_SIMPLEX, 0.8,\n                       cv::Scalar(0, 255, 0), 2);\n\n            return true;\n        }\n        return false;\n    }\n};\n\nint main() {\n    cv::VideoCapture cap(0);\n    if (!cap.isOpened()) {\n        std::cerr &lt;&lt; \"\u30ab\u30e1\u30e9\u3092\u958b\u3051\u307e\u305b\u3093\u3067\u3057\u305f\u3002\" &lt;&lt; std::endl;\n        return -1;\n    }\n\n    ObjectTracker tracker;\n    cv::Mat frame;\n    cv::Rect2d bbox;\n\n    \/\/ \u6700\u521d\u306e\u30d5\u30ec\u30fc\u30e0\u3067\u8ffd\u8de1\u5bfe\u8c61\u3092\u9078\u629e\n    cap &gt;&gt; frame;\n    bbox = cv::selectROI(frame);\n\n    if (tracker.initializeTracker(frame, bbox)) {\n        while (true) {\n            cap &gt;&gt; frame;\n            if (frame.empty()) break;\n\n            if (tracker.updateTracker(frame)) {\n                cv::imshow(\"Object Tracking\", frame);\n            }\n\n            if (cv::waitKey(1) == 27) break;\n        }\n    }\n\n    return 0;\n}<\/pre>\n\n\n\n<p>\u5b9f\u88c5\u306e\u30dd\u30a4\u30f3\u30c8\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u9854\u691c\u51fa\u30b7\u30b9\u30c6\u30e0<\/strong><\/li>\n<\/ol>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u30ab\u30b9\u30b1\u30fc\u30c9\u5206\u985e\u5668\u306e\u9069\u5207\u306a\u9078\u629e\u3068\u8a2d\u5b9a<\/li>\n\n\n\n<li>\u30b9\u30b1\u30fc\u30eb\u30d5\u30a1\u30af\u30bf\u30fc\u3068minNeighbors\u306e\u8abf\u6574<\/li>\n\n\n\n<li>\u4f8b\u5916\u51e6\u7406\u306e\u5b9f\u88c5<\/li>\n<\/ul>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u52d5\u753b\u51e6\u7406<\/strong><\/li>\n<\/ol>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u30de\u30eb\u30c1\u30b9\u30ec\u30c3\u30c9\u306b\u3088\u308b\u51e6\u7406\u306e\u52b9\u7387\u5316<\/li>\n\n\n\n<li>\u30d5\u30ec\u30fc\u30e0\u30ad\u30e5\u30fc\u306e\u9069\u5207\u306a\u7ba1\u7406<\/li>\n\n\n\n<li>\u30e1\u30e2\u30ea\u4f7f\u7528\u91cf\u306e\u6700\u9069\u5316<\/li>\n<\/ul>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u7269\u4f53\u8ffd\u8de1<\/strong><\/li>\n<\/ol>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u9069\u5207\u306a\u30c8\u30e9\u30c3\u30ab\u30fc\u306e\u9078\u629e<\/li>\n\n\n\n<li>\u8ffd\u8de1\u72b6\u614b\u306e\u7ba1\u7406<\/li>\n\n\n\n<li>\u8ffd\u8de1\u5931\u6557\u6642\u306e\u5bfe\u5fdc<\/li>\n<\/ul>\n\n\n\n<p>\u3053\u308c\u3089\u306e\u5b9f\u88c5\u4f8b\u306f\u3001\u5b9f\u969b\u306e\u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3\u958b\u767a\u306b\u304a\u3044\u3066\u57fa\u790e\u3068\u306a\u308b\u90e8\u5206\u3067\u3059\u3002\u7528\u9014\u306b\u5fdc\u3058\u3066\u9069\u5207\u306b\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"i-12\">OpenCV C++\u306e\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u6700\u9069\u5316<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"i-13\">\u30e1\u30e2\u30ea\u4f7f\u7528\u91cf\u306e\u6700\u9069\u5316\u624b\u6cd5<\/h3>\n\n\n\n<p>OpenCV C++\u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3\u306e\u30e1\u30e2\u30ea\u4f7f\u7528\u3092\u6700\u9069\u5316\u3059\u308b\u4e3b\u8981\u306a\u624b\u6cd5\u3092\u89e3\u8aac\u3057\u307e\u3059\uff1a<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">#include &lt;opencv2\/opencv.hpp&gt;\n\nclass MemoryOptimizedProcessor {\nprivate:\n    \/\/ \u30e1\u30e2\u30ea\u30d7\u30fc\u30eb\u306e\u7ba1\u7406\n    std::vector&lt;cv::Mat&gt; mat_pool;\n\npublic:\n    \/\/ ROI\uff08Region of Interest\uff09\u3092\u4f7f\u7528\u3057\u305f\u52b9\u7387\u7684\u306a\u51e6\u7406\n    cv::Mat processWithROI(const cv::Mat&amp; input) {\n        \/\/ \u5fc5\u8981\u306a\u9818\u57df\u306e\u307f\u3092\u51e6\u7406\n        cv::Rect roi(input.cols\/4, input.rows\/4, \n                    input.cols\/2, input.rows\/2);\n        cv::Mat roi_mat = input(roi);\n\n        \/\/ ROI\u4e0a\u3067\u76f4\u63a5\u51e6\u7406\u3092\u5b9f\u884c\n        cv::GaussianBlur(roi_mat, roi_mat, cv::Size(5, 5), 0);\n        return input;\n    }\n\n    \/\/ \u30e1\u30e2\u30ea\u306e\u518d\u5229\u7528\n    cv::Mat getReuseableMat(const cv::Size&amp; size, int type) {\n        for (auto&amp; mat : mat_pool) {\n            if (mat.size() == size &amp;&amp; mat.type() == type) {\n                mat.setTo(cv::Scalar(0));  \/\/ \u5185\u5bb9\u3092\u30af\u30ea\u30a2\n                return mat;\n            }\n        }\n\n        \/\/ \u65b0\u3057\u3044Mat\u3092\u4f5c\u6210\n        cv::Mat new_mat(size, type);\n        mat_pool.push_back(new_mat);\n        return new_mat;\n    }\n\n    \/\/ \u30e1\u30e2\u30ea\u30ea\u30fc\u30af\u3092\u9632\u3050\u305f\u3081\u306e\u660e\u793a\u7684\u306a\u89e3\u653e\n    void releaseMemory() {\n        for (auto&amp; mat : mat_pool) {\n            mat.release();\n        }\n        mat_pool.clear();\n        cv::destroyAllWindows();\n    }\n};<\/pre>\n\n\n\n<p>\u30e1\u30e2\u30ea\u6700\u9069\u5316\u306e\u30d9\u30b9\u30c8\u30d7\u30e9\u30af\u30c6\u30a3\u30b9\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>ROI\u306e\u6d3b\u7528\u306b\u3088\u308b\u4e0d\u8981\u306a\u30e1\u30e2\u30ea\u78ba\u4fdd\u306e\u56de\u907f<\/li>\n\n\n\n<li>\u30e1\u30e2\u30ea\u30d7\u30fc\u30eb\u306b\u3088\u308b\u30e1\u30e2\u30ea\u306e\u518d\u5229\u7528<\/li>\n\n\n\n<li>\u9069\u5207\u306a\u30bf\u30a4\u30df\u30f3\u30b0\u3067\u306e\u30e1\u30e2\u30ea\u89e3\u653e<\/li>\n\n\n\n<li>\u753b\u50cf\u30b5\u30a4\u30ba\u306e\u9069\u5207\u306a\u9078\u629e<\/li>\n<\/ol>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"i-14\">\u51e6\u7406\u901f\u5ea6\u3092\u5411\u4e0a\u3055\u305b\u308b\u30c6\u30af\u30cb\u30c3\u30af\u5b9f\u88c5<\/h3>\n\n\n\n<p>\u51e6\u7406\u901f\u5ea6\u3092\u5411\u4e0a\u3055\u305b\u308b\u305f\u3081\u306e\u5177\u4f53\u7684\u306a\u5b9f\u88c5\u4f8b\u3092\u793a\u3057\u307e\u3059\uff1a<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">#include &lt;opencv2\/opencv.hpp&gt;\n#include &lt;chrono&gt;\n\nclass OptimizedImageProcessor {\nprivate:\n    \/\/ \u30eb\u30c3\u30af\u30a2\u30c3\u30d7\u30c6\u30fc\u30d6\u30eb\u306e\u4e8b\u524d\u8a08\u7b97\n    cv::Mat createLUT(const std::function&lt;uchar(uchar)&gt;&amp; func) {\n        cv::Mat lut(1, 256, CV_8U);\n        for (int i = 0; i &lt; 256; i++) {\n            lut.at&lt;uchar&gt;(i) = func(i);\n        }\n        return lut;\n    }\n\npublic:\n    \/\/ \u6700\u9069\u5316\u3055\u308c\u305f\u753b\u50cf\u51e6\u7406\u306e\u5b9f\u88c5\n    cv::Mat processOptimized(const cv::Mat&amp; input) {\n        \/\/ \u753b\u50cf\u306e\u30d5\u30a9\u30fc\u30de\u30c3\u30c8\u6700\u9069\u5316\n        cv::Mat optimized;\n        input.convertTo(optimized, CV_8UC1);\n\n        \/\/ SIMD\u547d\u4ee4\u306e\u6d3b\u7528\n        cv::Mat result;\n        cv::parallel_for_(cv::Range(0, optimized.rows), [&amp;](const cv::Range&amp; range) {\n            for (int r = range.start; r &lt; range.end; r++) {\n                auto* ptr = optimized.ptr&lt;uchar&gt;(r);\n                for (int c = 0; c &lt; optimized.cols; c++) {\n                    ptr[c] = cv::saturate_cast&lt;uchar&gt;(ptr[c] * 1.5);\n                }\n            }\n        });\n\n        return result;\n    }\n\n    \/\/ \u30eb\u30c3\u30af\u30a2\u30c3\u30d7\u30c6\u30fc\u30d6\u30eb\u3092\u4f7f\u7528\u3057\u305f\u9ad8\u901f\u5316\n    cv::Mat applyLUT(const cv::Mat&amp; input) {\n        \/\/ \u30ac\u30f3\u30de\u88dc\u6b63\u7528\u306eLUT\u3092\u4f5c\u6210\n        auto gamma_correction = [](uchar x) -&gt; uchar {\n            return cv::saturate_cast&lt;uchar&gt;(pow(x \/ 255.0, 0.5) * 255.0);\n        };\n        cv::Mat lut = createLUT(gamma_correction);\n\n        cv::Mat result;\n        cv::LUT(input, lut, result);\n        return result;\n    }\n};<\/pre>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"i-15\">\u4e26\u5217\u51e6\u7406\u306b\u3088\u308b\u9ad8\u901f\u5316\u306e\u5b9f\u88c5\u65b9\u6cd5<\/h3>\n\n\n\n<p>OpenCV\u3068C++\u306e\u4e26\u5217\u51e6\u7406\u6a5f\u80fd\u3092\u7d44\u307f\u5408\u308f\u305b\u305f\u9ad8\u901f\u5316\u306e\u5b9f\u88c5\u4f8b\uff1a<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">#include &lt;opencv2\/opencv.hpp&gt;\n#include &lt;thread&gt;\n#include &lt;future&gt;\n\nclass ParallelProcessor {\nprivate:\n    int num_threads;\n\npublic:\n    ParallelProcessor(int threads = std::thread::hardware_concurrency())\n        : num_threads(threads) {}\n\n    \/\/ \u753b\u50cf\u3092\u5206\u5272\u3057\u3066\u4e26\u5217\u51e6\u7406\n    cv::Mat processParallel(const cv::Mat&amp; input) {\n        cv::Mat result = input.clone();\n        std::vector&lt;std::future&lt;void&gt;&gt; futures;\n\n        int rows_per_thread = input.rows \/ num_threads;\n\n        for (int i = 0; i &lt; num_threads; i++) {\n            int start_row = i * rows_per_thread;\n            int end_row = (i == num_threads - 1) ? input.rows \n                                                : start_row + rows_per_thread;\n\n            futures.push_back(std::async(std::launch::async,\n                [this, &amp;result, start_row, end_row]() {\n                    processPortion(result, start_row, end_row);\n                }));\n        }\n\n        \/\/ \u3059\u3079\u3066\u306e\u30b9\u30ec\u30c3\u30c9\u306e\u5b8c\u4e86\u3092\u5f85\u6a5f\n        for (auto&amp; future : futures) {\n            future.wait();\n        }\n\n        return result;\n    }\n\n    \/\/ OpenCV\u306e\u7d44\u307f\u8fbc\u307f\u4e26\u5217\u51e6\u7406\u306e\u6d3b\u7528\n    cv::Mat processWithOpenCVParallel(const cv::Mat&amp; input) {\n        cv::Mat result = input.clone();\n\n        cv::parallel_for_(cv::Range(0, input.rows),\n            [&amp;](const cv::Range&amp; range) {\n                for (int r = range.start; r &lt; range.end; r++) {\n                    auto* ptr = result.ptr&lt;uchar&gt;(r);\n                    for (int c = 0; c &lt; result.cols; c++) {\n                        \/\/ \u4e26\u5217\u51e6\u7406\u53ef\u80fd\u306a\u64cd\u4f5c\u3092\u5b9f\u884c\n                        ptr[c] = cv::saturate_cast&lt;uchar&gt;(ptr[c] * 1.2);\n                    }\n                }\n            });\n\n        return result;\n    }\n\nprivate:\n    void processPortion(cv::Mat&amp; image, int start_row, int end_row) {\n        for (int r = start_row; r &lt; end_row; r++) {\n            auto* ptr = image.ptr&lt;uchar&gt;(r);\n            for (int c = 0; c &lt; image.cols; c++) {\n                \/\/ \u753b\u50cf\u51e6\u7406\u64cd\u4f5c\u3092\u5b9f\u884c\n                ptr[c] = cv::saturate_cast&lt;uchar&gt;(ptr[c] * 1.2);\n            }\n        }\n    }\n};<\/pre>\n\n\n\n<p>\u6700\u9069\u5316\u306e\u30ad\u30fc\u30dd\u30a4\u30f3\u30c8\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u30e1\u30e2\u30ea\u6700\u9069\u5316<\/strong><\/li>\n<\/ol>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u30e1\u30e2\u30ea\u30d7\u30fc\u30eb\u306e\u4f7f\u7528<\/li>\n\n\n\n<li>ROI\u306e\u6d3b\u7528<\/li>\n\n\n\n<li>\u9069\u5207\u306a\u30c7\u30fc\u30bf\u578b\u306e\u9078\u629e<\/li>\n\n\n\n<li>\u30e1\u30e2\u30ea\u30ea\u30fc\u30af\u306e\u9632\u6b62<\/li>\n<\/ul>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u51e6\u7406\u901f\u5ea6\u306e\u6700\u9069\u5316<\/strong><\/li>\n<\/ol>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u30eb\u30c3\u30af\u30a2\u30c3\u30d7\u30c6\u30fc\u30d6\u30eb\u306e\u6d3b\u7528<\/li>\n\n\n\n<li>SIMD\u547d\u4ee4\u306e\u5229\u7528<\/li>\n\n\n\n<li>\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306e\u52b9\u7387\u5316<\/li>\n\n\n\n<li>\u30ad\u30e3\u30c3\u30b7\u30e5\u306e\u52b9\u7387\u7684\u306a\u5229\u7528<\/li>\n<\/ul>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u4e26\u5217\u51e6\u7406\u306e\u6700\u9069\u5316<\/strong><\/li>\n<\/ol>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u30de\u30eb\u30c1\u30b9\u30ec\u30c3\u30c9\u51e6\u7406<\/li>\n\n\n\n<li>OpenCV\u306e\u4e26\u5217\u51e6\u7406\u6a5f\u80fd\u306e\u6d3b\u7528<\/li>\n\n\n\n<li>\u9069\u5207\u306a\u30bf\u30b9\u30af\u5206\u5272<\/li>\n\n\n\n<li>\u30b9\u30ec\u30c3\u30c9\u9593\u306e\u540c\u671f\u7ba1\u7406<\/li>\n<\/ul>\n\n\n\n<p>\u3053\u308c\u3089\u306e\u6700\u9069\u5316\u30c6\u30af\u30cb\u30c3\u30af\u3092\u9069\u5207\u306b\u7d44\u307f\u5408\u308f\u305b\u308b\u3053\u3068\u3067\u3001OpenCV\u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3\u306e\u6027\u80fd\u3092\u5927\u5e45\u306b\u5411\u4e0a\u3055\u305b\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"i-16\">OpenCV C++\u306e\u5b9f\u52d9\u3067\u306e\u6d3b\u7528\u4e8b\u4f8b<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"i-17\">\u7523\u696d\u7528\u753b\u50cf\u691c\u67fb\u30b7\u30b9\u30c6\u30e0\u306e\u5b9f\u88c5\u4f8b<\/h3>\n\n\n\n<p>\u88fd\u9020\u30e9\u30a4\u30f3\u4e0a\u3067\u306e\u88fd\u54c1\u691c\u67fb\u30b7\u30b9\u30c6\u30e0\u306e\u5b9f\u88c5\u4f8b\u3092\u793a\u3057\u307e\u3059\uff1a<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">#include &lt;opencv2\/opencv.hpp&gt;\n\nclass QualityInspectionSystem {\nprivate:\n    \/\/ \u691c\u67fb\u30d1\u30e9\u30e1\u30fc\u30bf\n    struct InspectionParams {\n        double threshold;\n        double min_area;\n        double max_area;\n        double allowed_deviation;\n    };\n\n    InspectionParams params;\n    cv::Mat reference_image;\n\npublic:\n    QualityInspectionSystem(const cv::Mat&amp; ref_image, \n                           const InspectionParams&amp; inspection_params)\n        : reference_image(ref_image), params(inspection_params) {}\n\n    struct InspectionResult {\n        bool passed;\n        std::vector&lt;cv::Rect&gt; defect_areas;\n        double quality_score;\n    };\n\n    InspectionResult inspectProduct(const cv::Mat&amp; product_image) {\n        InspectionResult result;\n\n        \/\/ \u753b\u50cf\u306e\u4f4d\u7f6e\u5408\u308f\u305b\n        cv::Mat aligned_image;\n        alignImages(product_image, aligned_image);\n\n        \/\/ \u5dee\u5206\u691c\u51fa\n        cv::Mat diff;\n        cv::absdiff(reference_image, aligned_image, diff);\n\n        \/\/ \u6b20\u9665\u691c\u51fa\n        cv::Mat binary;\n        cv::threshold(diff, binary, params.threshold, 255, cv::THRESH_BINARY);\n\n        \/\/ \u6b20\u9665\u9818\u57df\u306e\u691c\u51fa\n        std::vector&lt;std::vector&lt;cv::Point&gt;&gt; contours;\n        cv::findContours(binary, contours, cv::RETR_EXTERNAL, \n                        cv::CHAIN_APPROX_SIMPLE);\n\n        \/\/ \u6b20\u9665\u306e\u8a55\u4fa1\n        result.defect_areas.clear();\n        result.quality_score = 100.0;\n\n        for (const auto&amp; contour : contours) {\n            double area = cv::contourArea(contour);\n            if (area &gt; params.min_area &amp;&amp; area &lt; params.max_area) {\n                result.defect_areas.push_back(cv::boundingRect(contour));\n                result.quality_score -= area * params.allowed_deviation;\n            }\n        }\n\n        result.passed = result.quality_score &gt;= 90.0;\n        return result;\n    }\n\nprivate:\n    void alignImages(const cv::Mat&amp; input, cv::Mat&amp; output) {\n        \/\/ \u7279\u5fb4\u70b9\u691c\u51fa\u3068\u30de\u30c3\u30c1\u30f3\u30b0\n        cv::Ptr&lt;cv::Feature2D&gt; detector = cv::SIFT::create();\n        std::vector&lt;cv::KeyPoint&gt; keypoints1, keypoints2;\n        cv::Mat descriptors1, descriptors2;\n\n        detector-&gt;detectAndCompute(reference_image, cv::noArray(), \n                                 keypoints1, descriptors1);\n        detector-&gt;detectAndCompute(input, cv::noArray(), \n                                 keypoints2, descriptors2);\n\n        \/\/ \u4f4d\u7f6e\u5408\u308f\u305b\u5909\u63db\u884c\u5217\u306e\u8a08\u7b97\n        cv::Ptr&lt;cv::DescriptorMatcher&gt; matcher = \n            cv::DescriptorMatcher::create(cv::DescriptorMatcher::FLANNBASED);\n        std::vector&lt;std::vector&lt;cv::DMatch&gt;&gt; knn_matches;\n        matcher-&gt;knnMatch(descriptors1, descriptors2, knn_matches, 2);\n\n        \/\/ \u753b\u50cf\u306e\u5909\u63db\n        cv::Mat homography = cv::findHomography(keypoints2, keypoints1, \n                                              cv::RANSAC);\n        cv::warpPerspective(input, output, homography, \n                           reference_image.size());\n    }\n};<\/pre>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"i-18\">\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\u30b7\u30b9\u30c6\u30e0\u3067\u306e\u6d3b\u7528\u65b9\u6cd5<\/h3>\n\n\n\n<p>\u76e3\u8996\u30ab\u30e1\u30e9\u30b7\u30b9\u30c6\u30e0\u306b\u304a\u3051\u308b\u7570\u5e38\u691c\u77e5\u306e\u5b9f\u88c5\u4f8b\uff1a<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">#include &lt;opencv2\/opencv.hpp&gt;\n#include &lt;queue&gt;\n\nclass SecurityMonitoringSystem {\nprivate:\n    cv::Ptr&lt;cv::BackgroundSubtractor&gt; bg_subtractor;\n    std::queue&lt;cv::Mat&gt; motion_history;\n    int history_size;\n    double motion_threshold;\n\npublic:\n    SecurityMonitoringSystem(int history = 30, double threshold = 0.02)\n        : history_size(history), motion_threshold(threshold) {\n        bg_subtractor = cv::createBackgroundSubtractorMOG2();\n    }\n\n    struct SecurityAlert {\n        bool motion_detected;\n        cv::Rect motion_area;\n        double motion_magnitude;\n        cv::Mat event_frame;\n    };\n\n    SecurityAlert processFrame(const cv::Mat&amp; frame) {\n        SecurityAlert alert;\n        alert.motion_detected = false;\n\n        \/\/ \u80cc\u666f\u5dee\u5206\n        cv::Mat fg_mask;\n        bg_subtractor-&gt;apply(frame, fg_mask);\n\n        \/\/ \u30e2\u30fc\u30b7\u30e7\u30f3\u691c\u51fa\n        cv::Mat motion_mask;\n        cv::threshold(fg_mask, motion_mask, 128, 255, cv::THRESH_BINARY);\n\n        \/\/ \u30ce\u30a4\u30ba\u9664\u53bb\n        cv::erode(motion_mask, motion_mask, cv::getStructuringElement(\n            cv::MORPH_RECT, cv::Size(3, 3)));\n        cv::dilate(motion_mask, motion_mask, cv::getStructuringElement(\n            cv::MORPH_RECT, cv::Size(3, 3)));\n\n        \/\/ \u30e2\u30fc\u30b7\u30e7\u30f3\u9818\u57df\u306e\u691c\u51fa\n        std::vector&lt;std::vector&lt;cv::Point&gt;&gt; contours;\n        cv::findContours(motion_mask, contours, cv::RETR_EXTERNAL, \n                        cv::CHAIN_APPROX_SIMPLE);\n\n        \/\/ \u30e2\u30fc\u30b7\u30e7\u30f3\u306e\u8a55\u4fa1\n        for (const auto&amp; contour : contours) {\n            double area = cv::contourArea(contour);\n            if (area &gt; frame.total() * motion_threshold) {\n                alert.motion_detected = true;\n                alert.motion_area = cv::boundingRect(contour);\n                alert.motion_magnitude = area \/ frame.total();\n                frame.copyTo(alert.event_frame);\n                break;\n            }\n        }\n\n        return alert;\n    }\n};<\/pre>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"i-19\">\u533b\u7642\u753b\u50cf\u51e6\u7406\u3067\u306e\u5fdc\u7528\u6280\u8853<\/h3>\n\n\n\n<p>\u533b\u7642\u753b\u50cf\u306e\u89e3\u6790\u30b7\u30b9\u30c6\u30e0\u306e\u5b9f\u88c5\u4f8b\uff1a<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">#include &lt;opencv2\/opencv.hpp&gt;\n\nclass MedicalImageAnalyzer {\nprivate:\n    struct AnalysisParams {\n        double contrast_alpha;\n        double brightness_beta;\n        int smooth_kernel_size;\n    };\n\n    AnalysisParams params;\n\npublic:\n    MedicalImageAnalyzer(const AnalysisParams&amp; analysis_params)\n        : params(analysis_params) {}\n\n    struct AnalysisResult {\n        cv::Mat enhanced_image;\n        cv::Mat segmented_image;\n        std::vector&lt;cv::Rect&gt; regions_of_interest;\n        double abnormality_score;\n    };\n\n    AnalysisResult analyzeMedicalImage(const cv::Mat&amp; medical_image) {\n        AnalysisResult result;\n\n        \/\/ \u753b\u50cf\u306e\u524d\u51e6\u7406\n        cv::Mat processed;\n        medical_image.convertTo(processed, -1, \n                              params.contrast_alpha, params.brightness_beta);\n\n        \/\/ \u30ce\u30a4\u30ba\u9664\u53bb\n        cv::GaussianBlur(processed, processed, \n                        cv::Size(params.smooth_kernel_size, \n                                params.smooth_kernel_size), 0);\n\n        \/\/ \u753b\u50cf\u30bb\u30b0\u30e1\u30f3\u30c6\u30fc\u30b7\u30e7\u30f3\n        cv::Mat gray;\n        cv::cvtColor(processed, gray, cv::COLOR_BGR2GRAY);\n\n        cv::Mat binary;\n        cv::threshold(gray, binary, 0, 255, \n                     cv::THRESH_BINARY | cv::THRESH_OTSU);\n\n        \/\/ \u95a2\u5fc3\u9818\u57df\u306e\u691c\u51fa\n        std::vector&lt;std::vector&lt;cv::Point&gt;&gt; contours;\n        cv::findContours(binary, contours, cv::RETR_EXTERNAL, \n                        cv::CHAIN_APPROX_SIMPLE);\n\n        \/\/ \u7d50\u679c\u306e\u751f\u6210\n        processed.copyTo(result.enhanced_image);\n        binary.copyTo(result.segmented_image);\n\n        result.abnormality_score = 0.0;\n        for (const auto&amp; contour : contours) {\n            double area = cv::contourArea(contour);\n            if (area &gt; 100) {  \/\/ \u6700\u5c0f\u9762\u7a4d\u3067\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\n                result.regions_of_interest.push_back(\n                    cv::boundingRect(contour));\n                result.abnormality_score += area \/ binary.total();\n            }\n        }\n\n        return result;\n    }\n};<\/pre>\n\n\n\n<p>\u5b9f\u52d9\u3067\u306e\u6d3b\u7528\u306b\u304a\u3051\u308b\u91cd\u8981\u306a\u30dd\u30a4\u30f3\u30c8\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u7523\u696d\u7528\u753b\u50cf\u691c\u67fb<\/strong><\/li>\n<\/ol>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u9ad8\u7cbe\u5ea6\u306a\u4f4d\u7f6e\u5408\u308f\u305b<\/li>\n\n\n\n<li>\u30ed\u30d0\u30b9\u30c8\u306a\u6b20\u9665\u691c\u51fa<\/li>\n\n\n\n<li>\u30ea\u30a2\u30eb\u30bf\u30a4\u30e0\u51e6\u7406\u3078\u306e\u5bfe\u5fdc<\/li>\n\n\n\n<li>\u691c\u67fb\u57fa\u6e96\u306e\u67d4\u8edf\u306a\u8a2d\u5b9a<\/li>\n<\/ul>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u30bb\u30ad\u30e5\u30ea\u30c6\u30a3\u30b7\u30b9\u30c6\u30e0<\/strong><\/li>\n<\/ol>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u52b9\u7387\u7684\u306a\u52d5\u4f53\u691c\u77e5<\/li>\n\n\n\n<li>\u8aa4\u691c\u77e5\u306e\u4f4e\u6e1b<\/li>\n\n\n\n<li>\u30a4\u30d9\u30f3\u30c8\u306e\u9069\u5207\u306a\u8a18\u9332<\/li>\n\n\n\n<li>\u30a2\u30e9\u30fc\u30c8\u6a5f\u80fd\u306e\u5b9f\u88c5<\/li>\n<\/ul>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u533b\u7642\u753b\u50cf\u51e6\u7406<\/strong><\/li>\n<\/ol>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u753b\u8cea\u306e\u6700\u9069\u5316<\/li>\n\n\n\n<li>\u6b63\u78ba\u306a\u30bb\u30b0\u30e1\u30f3\u30c6\u30fc\u30b7\u30e7\u30f3<\/li>\n\n\n\n<li>\u7570\u5e38\u691c\u51fa\u306e\u7cbe\u5ea6\u5411\u4e0a<\/li>\n\n\n\n<li>\u8a3a\u65ad\u652f\u63f4\u60c5\u5831\u306e\u63d0\u4f9b<\/li>\n<\/ul>\n\n\n\n<p>\u3053\u308c\u3089\u306e\u5b9f\u88c5\u4f8b\u306f\u3001\u5b9f\u969b\u306e\u696d\u52d9\u306b\u304a\u3044\u3066\u57fa\u790e\u3068\u306a\u308b\u90e8\u5206\u3067\u3059\u3002\u5b9f\u969b\u306e\u904b\u7528\u3067\u306f\u3001\u3088\u308a\u8a73\u7d30\u306a\u8981\u4ef6\u306b\u5fdc\u3058\u3066\u30ab\u30b9\u30bf\u30de\u30a4\u30ba\u304c\u5fc5\u8981\u3067\u3059\u3002<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"i-20\">OpenCV C++ \u3067\u306e\u30c8\u30e9\u30d6\u30eb\u30b7\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"i-21\">\u4e00\u822c\u7684\u306a\u30a8\u30e9\u30fc\u3068\u305d\u306e\u89e3\u6c7a\u65b9\u6cd5<\/h3>\n\n\n\n<p>OpenCV C++\u958b\u767a\u3067\u983b\u7e41\u306b\u906d\u9047\u3059\u308b\u30a8\u30e9\u30fc\u3068\u305d\u306e\u89e3\u6c7a\u65b9\u6cd5\u3092\u793a\u3057\u307e\u3059\uff1a<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">#include &lt;opencv2\/opencv.hpp&gt;\n#include &lt;iostream&gt;\n#include &lt;string&gt;\n\nclass OpenCVErrorHandler {\nprivate:\n    static void errorCallback(int status, const char* func_name,\n                            const char* err_msg, const char* file_name,\n                            int line, void* userdata) {\n        \/\/ \u30a8\u30e9\u30fc\u60c5\u5831\u306e\u51fa\u529b\n        std::cerr &lt;&lt; \"OpenCV Error:\" &lt;&lt; std::endl\n                  &lt;&lt; \"Status: \" &lt;&lt; status &lt;&lt; std::endl\n                  &lt;&lt; \"Function: \" &lt;&lt; func_name &lt;&lt; std::endl\n                  &lt;&lt; \"Message: \" &lt;&lt; err_msg &lt;&lt; std::endl\n                  &lt;&lt; \"File: \" &lt;&lt; file_name &lt;&lt; std::endl\n                  &lt;&lt; \"Line: \" &lt;&lt; line &lt;&lt; std::endl;\n    }\n\npublic:\n    static void registerHandler() {\n        cv::redirectError(errorCallback);\n    }\n\n    static bool validateImage(const cv::Mat&amp; image) {\n        if (image.empty()) {\n            throw std::runtime_error(\"\u753b\u50cf\u304c\u7a7a\u3067\u3059\");\n        }\n        if (image.depth() != CV_8U &amp;&amp; image.depth() != CV_8S) {\n            throw std::runtime_error(\"\u30b5\u30dd\u30fc\u30c8\u3055\u308c\u3066\u3044\u306a\u3044\u753b\u50cf\u30d5\u30a9\u30fc\u30de\u30c3\u30c8\u3067\u3059\");\n        }\n        return true;\n    }\n\n    static void checkMemoryUsage(const cv::Mat&amp; image) {\n        size_t memory_usage = image.total() * image.elemSize();\n        std::cout &lt;&lt; \"\u30e1\u30e2\u30ea\u4f7f\u7528\u91cf: \" &lt;&lt; memory_usage \/ 1024.0 \/ 1024.0 \n                  &lt;&lt; \" MB\" &lt;&lt; std::endl;\n\n        if (memory_usage &gt; 1024 * 1024 * 1024) {  \/\/ 1GB\u4ee5\u4e0a\n            std::cout &lt;&lt; \"\u8b66\u544a: \u5927\u304d\u306a\u30e1\u30e2\u30ea\u4f7f\u7528\u91cf\u3092\u691c\u51fa\" &lt;&lt; std::endl;\n        }\n    }\n};\n\n\/\/ \u30a8\u30e9\u30fc\u30cf\u30f3\u30c9\u30ea\u30f3\u30b0\u306e\u5b9f\u88c5\u4f8b\nclass ErrorHandlingExample {\npublic:\n    static void demonstrateErrorHandling() {\n        try {\n            \/\/ \u753b\u50cf\u8aad\u307f\u8fbc\u307f\u306e\u30a8\u30e9\u30fc\u30cf\u30f3\u30c9\u30ea\u30f3\u30b0\n            cv::Mat image = cv::imread(\"non_existent.jpg\");\n            if (image.empty()) {\n                throw std::runtime_error(\"\u753b\u50cf\u306e\u8aad\u307f\u8fbc\u307f\u306b\u5931\u6557\u3057\u307e\u3057\u305f\");\n            }\n\n            \/\/ \u753b\u50cf\u51e6\u7406\u306e\u30a8\u30e9\u30fc\u30cf\u30f3\u30c9\u30ea\u30f3\u30b0\n            cv::Mat result;\n            if (!processImage(image, result)) {\n                throw std::runtime_error(\"\u753b\u50cf\u51e6\u7406\u306b\u5931\u6557\u3057\u307e\u3057\u305f\");\n            }\n\n        } catch (const cv::Exception&amp; e) {\n            std::cerr &lt;&lt; \"OpenCV\u30a8\u30e9\u30fc: \" &lt;&lt; e.what() &lt;&lt; std::endl;\n        } catch (const std::exception&amp; e) {\n            std::cerr &lt;&lt; \"\u4e00\u822c\u30a8\u30e9\u30fc: \" &lt;&lt; e.what() &lt;&lt; std::endl;\n        }\n    }\n\nprivate:\n    static bool processImage(const cv::Mat&amp; input, cv::Mat&amp; output) {\n        try {\n            if (!OpenCVErrorHandler::validateImage(input)) {\n                return false;\n            }\n\n            \/\/ \u753b\u50cf\u51e6\u7406\u306e\u5b9f\u884c\n            cv::GaussianBlur(input, output, cv::Size(3, 3), 0);\n            return true;\n\n        } catch (...) {\n            return false;\n        }\n    }\n};<\/pre>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"i-22\">\u30c7\u30d0\u30c3\u30b0\u30c6\u30af\u30cb\u30c3\u30af\u3068\u30d9\u30b9\u30c8\u30d7\u30e9\u30af\u30c6\u30a3\u30b9<\/h3>\n\n\n\n<p>\u52b9\u679c\u7684\u306a\u30c7\u30d0\u30c3\u30b0\u306e\u305f\u3081\u306e\u5b9f\u88c5\u4f8b\u3092\u793a\u3057\u307e\u3059\uff1a<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">#include &lt;opencv2\/opencv.hpp&gt;\n\nclass OpenCVDebugger {\npublic:\n    \/\/ \u753b\u50cf\u60c5\u5831\u306e\u8a73\u7d30\u8868\u793a\n    static void printMatInfo(const cv::Mat&amp; mat, const std::string&amp; name) {\n        std::cout &lt;&lt; \"========== \" &lt;&lt; name &lt;&lt; \" ==========\" &lt;&lt; std::endl;\n        std::cout &lt;&lt; \"\u30b5\u30a4\u30ba: \" &lt;&lt; mat.size() &lt;&lt; std::endl;\n        std::cout &lt;&lt; \"\u30c1\u30e3\u30f3\u30cd\u30eb\u6570: \" &lt;&lt; mat.channels() &lt;&lt; std::endl;\n        std::cout &lt;&lt; \"\u30c7\u30fc\u30bf\u578b: \" &lt;&lt; mat.type() &lt;&lt; std::endl;\n        std::cout &lt;&lt; \"\u9023\u7d9a\u6027: \" &lt;&lt; (mat.isContinuous() ? \"\u9023\u7d9a\" : \"\u4e0d\u9023\u7d9a\") \n                  &lt;&lt; std::endl;\n    }\n\n    \/\/ \u30d4\u30af\u30bb\u30eb\u5024\u306e\u7bc4\u56f2\u30c1\u30a7\u30c3\u30af\n    static void checkPixelRange(const cv::Mat&amp; mat) {\n        double min_val, max_val;\n        cv::minMaxLoc(mat, &amp;min_val, &amp;max_val);\n\n        std::cout &lt;&lt; \"\u30d4\u30af\u30bb\u30eb\u5024\u306e\u7bc4\u56f2:\" &lt;&lt; std::endl;\n        std::cout &lt;&lt; \"\u6700\u5c0f\u5024: \" &lt;&lt; min_val &lt;&lt; std::endl;\n        std::cout &lt;&lt; \"\u6700\u5927\u5024: \" &lt;&lt; max_val &lt;&lt; std::endl;\n    }\n\n    \/\/ \u51e6\u7406\u6642\u9593\u306e\u8a08\u6e2c\n    static void measureProcessingTime(const std::function&lt;void()&gt;&amp; func) {\n        auto start = std::chrono::high_resolution_clock::now();\n        func();\n        auto end = std::chrono::high_resolution_clock::now();\n\n        auto duration = std::chrono::duration_cast&lt;std::chrono::milliseconds&gt;\n                       (end - start);\n        std::cout &lt;&lt; \"\u51e6\u7406\u6642\u9593: \" &lt;&lt; duration.count() &lt;&lt; \"ms\" &lt;&lt; std::endl;\n    }\n\n    \/\/ \u30c7\u30d0\u30c3\u30b0\u7528\u306e\u753b\u50cf\u8868\u793a\n    static void showDebugImage(const cv::Mat&amp; image, \n                             const std::string&amp; window_name) {\n        cv::namedWindow(window_name, cv::WINDOW_NORMAL);\n        cv::imshow(window_name, image);\n        cv::waitKey(1);\n    }\n};<\/pre>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"i-23\">\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u554f\u984c\u306e\u8a3a\u65ad\u3068\u6539\u5584\u65b9\u6cd5<\/h3>\n\n\n\n<p>\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u306e\u554f\u984c\u3092\u8a3a\u65ad\u3057\u6539\u5584\u3059\u308b\u305f\u3081\u306e\u5b9f\u88c5\u4f8b\uff1a<\/p>\n\n\n\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\" data-enlighter-theme=\"\" data-enlighter-highlight=\"\" data-enlighter-linenumbers=\"\" data-enlighter-lineoffset=\"\" data-enlighter-title=\"\" data-enlighter-group=\"\">#include &lt;opencv2\/opencv.hpp&gt;\n#include &lt;vector&gt;\n#include &lt;chrono&gt;\n\nclass PerformanceAnalyzer {\npublic:\n    struct PerformanceMetrics {\n        double processing_time_ms;\n        size_t memory_usage_bytes;\n        int fps;\n    };\n\n    \/\/ \u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u8a08\u6e2c\u306e\u5b9f\u88c5\n    static PerformanceMetrics measurePerformance(\n        const std::function&lt;void()&gt;&amp; func) {\n        PerformanceMetrics metrics;\n\n        \/\/ \u30e1\u30e2\u30ea\u4f7f\u7528\u91cf\u306e\u8a08\u6e2c\u958b\u59cb\n        size_t initial_memory = getCurrentMemoryUsage();\n\n        \/\/ \u51e6\u7406\u6642\u9593\u306e\u8a08\u6e2c\n        auto start = std::chrono::high_resolution_clock::now();\n        func();\n        auto end = std::chrono::high_resolution_clock::now();\n\n        \/\/ \u30e1\u30e2\u30ea\u4f7f\u7528\u91cf\u306e\u8a08\u6e2c\u7d42\u4e86\n        size_t final_memory = getCurrentMemoryUsage();\n\n        \/\/ \u30e1\u30c8\u30ea\u30af\u30b9\u306e\u8a08\u7b97\n        metrics.processing_time_ms = \n            std::chrono::duration_cast&lt;std::chrono::milliseconds&gt;\n            (end - start).count();\n        metrics.memory_usage_bytes = final_memory - initial_memory;\n        metrics.fps = metrics.processing_time_ms &gt; 0 ? \n            1000 \/ metrics.processing_time_ms : 0;\n\n        return metrics;\n    }\n\n    \/\/ \u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u6700\u9069\u5316\u306e\u30a2\u30c9\u30d0\u30a4\u30b9\n    static void suggestOptimizations(const PerformanceMetrics&amp; metrics) {\n        std::cout &lt;&lt; \"\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u5206\u6790\u7d50\u679c:\" &lt;&lt; std::endl;\n\n        if (metrics.processing_time_ms &gt; 100) {\n            std::cout &lt;&lt; \"\u51e6\u7406\u6642\u9593\u304c\u9577\u3059\u304e\u307e\u3059\u3002\u4ee5\u4e0b\u3092\u691c\u8a0e\u3057\u3066\u304f\u3060\u3055\u3044\uff1a\"\n                      &lt;&lt; std::endl;\n            std::cout &lt;&lt; \"- \u753b\u50cf\u30b5\u30a4\u30ba\u306e\u7e2e\u5c0f\" &lt;&lt; std::endl;\n            std::cout &lt;&lt; \"- ROI\u306e\u4f7f\u7528\" &lt;&lt; std::endl;\n            std::cout &lt;&lt; \"- \u4e26\u5217\u51e6\u7406\u306e\u5c0e\u5165\" &lt;&lt; std::endl;\n        }\n\n        if (metrics.memory_usage_bytes &gt; 1024 * 1024 * 100) {  \/\/ 100MB\n            std::cout &lt;&lt; \"\u30e1\u30e2\u30ea\u4f7f\u7528\u91cf\u304c\u591a\u3059\u304e\u307e\u3059\u3002\u4ee5\u4e0b\u3092\u691c\u8a0e\u3057\u3066\u304f\u3060\u3055\u3044\uff1a\"\n                      &lt;&lt; std::endl;\n            std::cout &lt;&lt; \"- \u30e1\u30e2\u30ea\u306e\u518d\u5229\u7528\" &lt;&lt; std::endl;\n            std::cout &lt;&lt; \"- \u4e0d\u8981\u306a\u30b3\u30d4\u30fc\u306e\u524a\u9664\" &lt;&lt; std::endl;\n            std::cout &lt;&lt; \"- \u30b9\u30c8\u30ea\u30fc\u30df\u30f3\u30b0\u51e6\u7406\u306e\u5c0e\u5165\" &lt;&lt; std::endl;\n        }\n\n        if (metrics.fps &lt; 30) {\n            std::cout &lt;&lt; \"\u30d5\u30ec\u30fc\u30e0\u30ec\u30fc\u30c8\u304c\u4f4e\u3059\u304e\u307e\u3059\u3002\u4ee5\u4e0b\u3092\u691c\u8a0e\u3057\u3066\u304f\u3060\u3055\u3044\uff1a\"\n                      &lt;&lt; std::endl;\n            std::cout &lt;&lt; \"- \u51e6\u7406\u306e\u8efd\u91cf\u5316\" &lt;&lt; std::endl;\n            std::cout &lt;&lt; \"- GPU\u306e\u6d3b\u7528\" &lt;&lt; std::endl;\n            std::cout &lt;&lt; \"- \u30de\u30eb\u30c1\u30b9\u30ec\u30c3\u30c9\u5316\" &lt;&lt; std::endl;\n        }\n    }\n\nprivate:\n    static size_t getCurrentMemoryUsage() {\n        \/\/ \u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u4f9d\u5b58\u306e\u30e1\u30e2\u30ea\u4f7f\u7528\u91cf\u53d6\u5f97\n        \/\/ \u3053\u306e\u5b9f\u88c5\u306f\u7c21\u7565\u5316\u3055\u308c\u3066\u3044\u307e\u3059\n        return 0;\n    }\n};<\/pre>\n\n\n\n<p>\u30c8\u30e9\u30d6\u30eb\u30b7\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0\u306e\u30d9\u30b9\u30c8\u30d7\u30e9\u30af\u30c6\u30a3\u30b9\uff1a<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u30a8\u30e9\u30fc\u30cf\u30f3\u30c9\u30ea\u30f3\u30b0<\/strong><\/li>\n<\/ol>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u9069\u5207\u306a\u4f8b\u5916\u51e6\u7406\u306e\u5b9f\u88c5<\/li>\n\n\n\n<li>\u30a8\u30e9\u30fc\u30e1\u30c3\u30bb\u30fc\u30b8\u306e\u660e\u78ba\u306a\u8a18\u9332<\/li>\n\n\n\n<li>\u30a8\u30e9\u30fc\u767a\u751f\u6642\u306e\u9069\u5207\u306a\u30ea\u30ab\u30d0\u30ea\u30fc<\/li>\n\n\n\n<li>\u30b7\u30b9\u30c6\u30de\u30c6\u30a3\u30c3\u30af\u306a\u30a8\u30e9\u30fc\u30c1\u30a7\u30c3\u30af<\/li>\n<\/ul>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u30c7\u30d0\u30c3\u30b0\u30c6\u30af\u30cb\u30c3\u30af<\/strong><\/li>\n<\/ol>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u6bb5\u968e\u7684\u306a\u30c7\u30d0\u30c3\u30b0\u51fa\u529b<\/li>\n\n\n\n<li>\u753b\u50cf\u51e6\u7406\u306e\u4e2d\u9593\u7d50\u679c\u306e\u78ba\u8a8d<\/li>\n\n\n\n<li>\u51e6\u7406\u6642\u9593\u306e\u8a08\u6e2c\u3068\u5206\u6790<\/li>\n\n\n\n<li>\u30e1\u30e2\u30ea\u4f7f\u7528\u91cf\u306e\u30e2\u30cb\u30bf\u30ea\u30f3\u30b0<\/li>\n<\/ul>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u6539\u5584<\/strong><\/li>\n<\/ol>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u30dc\u30c8\u30eb\u30cd\u30c3\u30af\u306e\u7279\u5b9a<\/li>\n\n\n\n<li>\u30e1\u30e2\u30ea\u4f7f\u7528\u306e\u6700\u9069\u5316<\/li>\n\n\n\n<li>\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306e\u52b9\u7387\u5316<\/li>\n\n\n\n<li>\u4e26\u5217\u51e6\u7406\u306e\u6d3b\u7528<\/li>\n<\/ul>\n\n\n\n<p>\u3053\u308c\u3089\u306e\u30c4\u30fc\u30eb\u3068\u6280\u8853\u3092\u6d3b\u7528\u3059\u308b\u3053\u3068\u3067\u3001OpenCV C++\u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3\u306e\u958b\u767a\u3068\u4fdd\u5b88\u3092\u52b9\u7387\u7684\u306b\u884c\u3046\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Warning: Undefined array key &#8220;is_admin&#8221; in \/home\/xs392991\/dexall.co.jp\/public_html\/articles\/wp-content\/themes\/ &#8230; <\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5],"tags":[],"class_list":{"0":"post-1753","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-cpp","7":"nothumb"},"_links":{"self":[{"href":"https:\/\/dexall.co.jp\/articles\/index.php?rest_route=\/wp\/v2\/posts\/1753","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dexall.co.jp\/articles\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/dexall.co.jp\/articles\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/dexall.co.jp\/articles\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/dexall.co.jp\/articles\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1753"}],"version-history":[{"count":1,"href":"https:\/\/dexall.co.jp\/articles\/index.php?rest_route=\/wp\/v2\/posts\/1753\/revisions"}],"predecessor-version":[{"id":1754,"href":"https:\/\/dexall.co.jp\/articles\/index.php?rest_route=\/wp\/v2\/posts\/1753\/revisions\/1754"}],"wp:attachment":[{"href":"https:\/\/dexall.co.jp\/articles\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1753"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/dexall.co.jp\/articles\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1753"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/dexall.co.jp\/articles\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1753"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}