{"id":2387,"date":"2024-03-13T16:13:20","date_gmt":"2024-03-13T07:13:20","guid":{"rendered":"https:\/\/www.silicloud.com\/ja\/blog\/keras%e3%81%a7%e4%ba%8b%e5%89%8d%e3%81%ab%e8%a8%93%e7%b7%b4%e3%81%95%e3%82%8c%e3%81%9f%e3%83%a2%e3%83%87%e3%83%ab%e3%82%92%e4%bd%bf%e7%94%a8%e3%81%99%e3%82%8b%e6%96%b9%e6%b3%95%e3%81%af%e4%bd%95\/"},"modified":"2025-08-02T06:38:18","modified_gmt":"2025-08-01T21:38:18","slug":"keras%e3%81%a7%e4%ba%8b%e5%89%8d%e3%81%ab%e8%a8%93%e7%b7%b4%e3%81%95%e3%82%8c%e3%81%9f%e3%83%a2%e3%83%87%e3%83%ab%e3%82%92%e4%bd%bf%e7%94%a8%e3%81%99%e3%82%8b%e6%96%b9%e6%b3%95%e3%81%af%e4%bd%95","status":"publish","type":"post","link":"https:\/\/www.silicloud.com\/ja\/blog\/keras%e3%81%a7%e4%ba%8b%e5%89%8d%e3%81%ab%e8%a8%93%e7%b7%b4%e3%81%95%e3%82%8c%e3%81%9f%e3%83%a2%e3%83%87%e3%83%ab%e3%82%92%e4%bd%bf%e7%94%a8%e3%81%99%e3%82%8b%e6%96%b9%e6%b3%95%e3%81%af%e4%bd%95\/","title":{"rendered":"Keras\u3067\u4e8b\u524d\u306b\u8a13\u7df4\u3055\u308c\u305f\u30e2\u30c7\u30eb\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u306f\u4f55\u3067\u3059\u304b\uff1f"},"content":{"rendered":"<p>Keras\u3067\u4e8b\u524d\u5b66\u7fd2\u6e08\u307f\u30e2\u30c7\u30eb\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u306f2\u3064\u3042\u308a\u307e\u3059\uff1aKeras\u3067\u63d0\u4f9b\u3055\u308c\u3066\u3044\u308b\u4e8b\u524d\u5b66\u7fd2\u6e08\u307f\u30e2\u30c7\u30eb\uff08VGG16\u3001ResNet50\u3001InceptionV3\u306a\u3069\uff09\u3092\u4f7f\u7528\u3059\u308b\u304b\u3001\u4ed6\u306e\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\uff08TensorFlow\u3001PyTorch\u306a\u3069\uff09\u3067\u8a13\u7df4\u3055\u308c\u305f\u30e2\u30c7\u30eb\u3092\u4f7f\u7528\u3059\u308b\u304b\u3067\u3059\u3002<\/p>\n<ol>\n<li>Keras\u304c\u63d0\u4f9b\u3059\u308b\u4e8b\u524d\u5b66\u7fd2\u6e08\u307f\u30e2\u30c7\u30eb\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/li>\n<\/ol>\n<pre class=\"post-pre\"><code><span class=\"hljs-keyword\">from<\/span> keras.applications.vgg16 <span class=\"hljs-keyword\">import<\/span> VGG16\r\n<span class=\"hljs-keyword\">from<\/span> keras.applications.vgg16 <span class=\"hljs-keyword\">import<\/span> preprocess_input, decode_predictions\r\n<span class=\"hljs-keyword\">from<\/span> keras.preprocessing <span class=\"hljs-keyword\">import<\/span> image\r\n<span class=\"hljs-keyword\">import<\/span> numpy <span class=\"hljs-keyword\">as<\/span> np\r\n\r\n<span class=\"hljs-comment\"># \u52a0\u8f7d\u9884\u8bad\u7ec3\u7684VGG16\u6a21\u578b<\/span>\r\nmodel = VGG16(weights=<span class=\"hljs-string\">'imagenet'<\/span>)\r\n\r\n<span class=\"hljs-comment\"># \u52a0\u8f7d\u8981\u9884\u6d4b\u7684\u56fe\u7247\uff0c\u5e76\u8fdb\u884c\u9884\u5904\u7406<\/span>\r\nimg_path = <span class=\"hljs-string\">'path_to_your_image.jpg'<\/span>\r\nimg = image.load_img(img_path, target_size=(<span class=\"hljs-number\">224<\/span>, <span class=\"hljs-number\">224<\/span>))\r\nx = image.img_to_array(img)\r\nx = np.expand_dims(x, axis=<span class=\"hljs-number\">0<\/span>)\r\nx = preprocess_input(x)\r\n\r\n<span class=\"hljs-comment\"># \u9884\u6d4b\u56fe\u50cf\u7684\u7c7b\u522b<\/span>\r\npreds = model.predict(x)\r\npredictions = decode_predictions(preds, top=<span class=\"hljs-number\">3<\/span>)[<span class=\"hljs-number\">0<\/span>]\r\n<span class=\"hljs-keyword\">for<\/span> i, (imagenetID, label, score) <span class=\"hljs-keyword\">in<\/span> <span class=\"hljs-built_in\">enumerate<\/span>(predictions):\r\n    <span class=\"hljs-built_in\">print<\/span>(<span class=\"hljs-string\">\"{}. {}: {:.2f}%\"<\/span>.<span class=\"hljs-built_in\">format<\/span>(i + <span class=\"hljs-number\">1<\/span>, label, score * <span class=\"hljs-number\">100<\/span>))\r\n<\/code><\/pre>\n<ol>\n<li>\u4ed6\u306e\u6df1\u5c64\u5b66\u7fd2\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u3067\u8a13\u7df4\u3055\u308c\u305f\u30e2\u30c7\u30eb\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/li>\n<\/ol>\n<pre class=\"post-pre\"><code><span class=\"hljs-keyword\">import<\/span> tensorflow <span class=\"hljs-keyword\">as<\/span> tf\r\n<span class=\"hljs-keyword\">from<\/span> keras.applications.vgg16 <span class=\"hljs-keyword\">import<\/span> preprocess_input\r\n<span class=\"hljs-keyword\">from<\/span> keras.preprocessing <span class=\"hljs-keyword\">import<\/span> image\r\n<span class=\"hljs-keyword\">import<\/span> numpy <span class=\"hljs-keyword\">as<\/span> np\r\n\r\n<span class=\"hljs-comment\"># \u52a0\u8f7d\u5176\u4ed6\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\u4e2d\u8bad\u7ec3\u597d\u7684\u6a21\u578b<\/span>\r\nmodel = tf.keras.models.load_model(<span class=\"hljs-string\">'path_to_your_model.h5'<\/span>)\r\n\r\n<span class=\"hljs-comment\"># \u52a0\u8f7d\u8981\u9884\u6d4b\u7684\u56fe\u7247\uff0c\u5e76\u8fdb\u884c\u9884\u5904\u7406<\/span>\r\nimg_path = <span class=\"hljs-string\">'path_to_your_image.jpg'<\/span>\r\nimg = image.load_img(img_path, target_size=(<span class=\"hljs-number\">224<\/span>, <span class=\"hljs-number\">224<\/span>))\r\nx = image.img_to_array(img)\r\nx = np.expand_dims(x, axis=<span class=\"hljs-number\">0<\/span>)\r\nx = preprocess_input(x)\r\n\r\n<span class=\"hljs-comment\"># \u9884\u6d4b\u56fe\u50cf\u7684\u7c7b\u522b<\/span>\r\npreds = model.predict(x)\r\n<\/code><\/pre>\n<p>Keras\u3092\u4f7f\u3063\u3066\u3001\u753b\u50cf\u5206\u985e\u3084\u7269\u4f53\u691c\u51fa\u306a\u3069\u306e\u30bf\u30b9\u30af\u306b\u4e8b\u524d\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u6e08\u307f\u306e\u30e2\u30c7\u30eb\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u304c2\u3064\u3042\u308a\u307e\u3059\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Keras\u3067\u4e8b\u524d\u5b66\u7fd2\u6e08\u307f\u30e2\u30c7\u30eb\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u306f2\u3064\u3042\u308a\u307e\u3059\uff1aKeras\u3067\u63d0\u4f9b\u3055\u308c\u3066\u3044\u308b\u4e8b\u524d\u5b66\u7fd2\u6e08\u307f\u30e2\u30c7\u30eb\uff08VGG16\u3001ResNet50\u3001InceptionV3\u306a\u3069\uff09\u3092\u4f7f\u7528\u3059\u308b\u304b\u3001\u4ed6\u306e\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\uff08Te [&hellip;]<\/p>\n","protected":false},"author":8,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[26,61],"class_list":["post-2387","post","type-post","status-publish","format-standard","hentry","category-uncategorized","tag-26","tag-61"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.5 (Yoast SEO v21.5) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Keras\u3067\u4e8b\u524d\u306b\u8a13\u7df4\u3055\u308c\u305f\u30e2\u30c7\u30eb\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u306f\u4f55\u3067\u3059\u304b\uff1f - Blog - Silicon Cloud<\/title>\n<meta name=\"description\" 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