fix:

index.xml

@@ -11,7 +11,7 @@
     <lastBuildDate>Wed, 07 Aug 2024 15:12:28 +0800</lastBuildDate>
     <atom:link href="/index.xml" rel="self" type="application/rss+xml" />
     <item>
-      <title>YOLO8</title>
+      <title>yolo8</title>
       <link>/posts/yolo8/</link>
       <pubDate>Wed, 07 Aug 2024 15:12:28 +0800</pubDate>
       <guid>/posts/yolo8/</guid>

posts/YOLO8/index.html

@@ -7,7 +7,7 @@
 <meta name="viewport" content="width=device-width, initial-scale=1">
 
 
-<title>YOLO8 | sincebyte</title>
+<title>yolo8 | sincebyte</title>
 
 <meta name="generator" content="Hugo Eureka 0.9.3" />
 <link rel="stylesheet" href="../../css/eureka.min.bf8dd3d6872fb704aafb8bcb973df1d5fc347fc34c9b7f4ed33052a953b06f8be99f29d44e29d0a4c6c01988203b5fd4.css">
@@ -89,7 +89,7 @@
       "item":"/posts/"},{
       "@type": "ListItem",
       "position": 2 ,
-      "name":"YOLO8",
+      "name":"yolo8",
       "item":"/posts/yolo8/"}]
 }
 </script>
@@ -104,7 +104,7 @@
         "@type": "WebPage",
         "@id": "/posts/yolo8/"
     },
-    "headline": "YOLO8 | sincebyte","datePublished": "2024-08-07T15:12:28+08:00",
+    "headline": "yolo8 | sincebyte","datePublished": "2024-08-07T15:12:28+08:00",
     "dateModified": "2024-08-07T15:12:28+08:00",
     "wordCount":  178 ,
     "publisher": {
@@ -117,7 +117,7 @@
         },
     "description": "\u003cp\u003eUltralytics YOLOv8 和 Darknet 是与 YOLO（You Only Look Once）目标检测模型相关的两个不同实现。它的主要特点是将目标检测问题视为回归问题，直接在图像上预测边界框和类别。\u003c\/p\u003e"
 }
-</script><meta property="og:title" content="YOLO8 | sincebyte" />
+</script><meta property="og:title" content="yolo8 | sincebyte" />
 <meta property="og:type" content="article" />
 
 
@@ -249,7 +249,7 @@
       class=" bg-secondary-bg col-span-2 rounded px-6 py-8 lg:col-span-6"
     >
       <article class="prose">
-  <h1 class="mb-4">YOLO8</h1>
+  <h1 class="mb-4">yolo8</h1>
 
   <div
   class="text-tertiary-text not-prose mt-2 flex flex-row flex-wrap items-center"

posts/h2-usage/index.html

@@ -364,7 +364,7 @@ <h2 id="ejc-connection">ejc Connection</h2>
         <span class="text-primary-text block font-bold"
           >Previous</span
         >
-        <a href="../../posts/yolo8/" class="block">YOLO8</a>
+        <a href="../../posts/yolo8/" class="block">yolo8</a>
 
     </div>
     <div class="mt-4 md:mt-0 md:text-right">

posts/index.html

@@ -89,7 +89,7 @@
     "itemListElement":[{
             "@type":"ListItem",
             "position":  1 ,
-            "name": "YOLO8",
+            "name": "yolo8",
             "description": "\u003cp\u003eUltralytics YOLOv8 和 Darknet 是与 YOLO（You Only Look Once）目标检测模型相关的两个不同实现。它的主要特点是将目标检测问题视为回归问题，直接在图像上预测边界框和类别。\u003c/p\u003e",
             "url": "/posts/yolo8/"
         },{
@@ -337,7 +337,7 @@ <h1>Posts</h1>
   <div class="w-full ">
     <div class="prose">
   <a href="../posts/yolo8/" class="no-underline">
-    <h3 class="mt-0">YOLO8</h3>
+    <h3 class="mt-0">yolo8</h3>
   </a>
 
     Ultralytics YOLOv8 和 Darknet 是与 YOLO（You Only Look Once）目标检测模型相关的两个不同实现。它的主要特点是将目标检测问题视为回归问题，直接在图像上预测边界框和类别。

posts/index.xml

@@ -11,7 +11,7 @@
     <lastBuildDate>Wed, 07 Aug 2024 15:12:28 +0800</lastBuildDate>
     <atom:link href="/posts/index.xml" rel="self" type="application/rss+xml" />
     <item>
-      <title>YOLO8</title>
+      <title>yolo8</title>
       <link>/posts/yolo8/</link>
       <pubDate>Wed, 07 Aug 2024 15:12:28 +0800</pubDate>
       <guid>/posts/yolo8/</guid>

tags/ai/index.html

@@ -104,7 +104,7 @@
     "itemListElement":[{
             "@type":"ListItem",
             "position":  1 ,
-            "name": "YOLO8",
+            "name": "yolo8",
             "description": "\u003cp\u003eUltralytics YOLOv8 和 Darknet 是与 YOLO（You Only Look Once）目标检测模型相关的两个不同实现。它的主要特点是将目标检测问题视为回归问题，直接在图像上预测边界框和类别。\u003c/p\u003e",
             "url": "/posts/yolo8/"
         }
@@ -238,7 +238,7 @@ <h1>Ai</h1>
   <div class="w-full ">
     <div class="prose">
   <a href="../../posts/yolo8/" class="no-underline">
-    <h3 class="mt-0">YOLO8</h3>
+    <h3 class="mt-0">yolo8</h3>
   </a>
 
     Ultralytics YOLOv8 和 Darknet 是与 YOLO（You Only Look Once）目标检测模型相关的两个不同实现。它的主要特点是将目标检测问题视为回归问题，直接在图像上预测边界框和类别。

tags/ai/index.xml

@@ -11,7 +11,7 @@
     <lastBuildDate>Wed, 07 Aug 2024 15:12:28 +0800</lastBuildDate>
     <atom:link href="/tags/ai/index.xml" rel="self" type="application/rss+xml" />
     <item>
-      <title>YOLO8</title>
+      <title>yolo8</title>
       <link>/posts/yolo8/</link>
       <pubDate>Wed, 07 Aug 2024 15:12:28 +0800</pubDate>
       <guid>/posts/yolo8/</guid>

tags/python/index.html

@@ -104,7 +104,7 @@
     "itemListElement":[{
             "@type":"ListItem",
             "position":  1 ,
-            "name": "YOLO8",
+            "name": "yolo8",
             "description": "\u003cp\u003eUltralytics YOLOv8 和 Darknet 是与 YOLO（You Only Look Once）目标检测模型相关的两个不同实现。它的主要特点是将目标检测问题视为回归问题，直接在图像上预测边界框和类别。\u003c/p\u003e",
             "url": "/posts/yolo8/"
         },{
@@ -244,7 +244,7 @@ <h1>Python</h1>
   <div class="w-full ">
     <div class="prose">
   <a href="../../posts/yolo8/" class="no-underline">
-    <h3 class="mt-0">YOLO8</h3>
+    <h3 class="mt-0">yolo8</h3>
   </a>
 
     Ultralytics YOLOv8 和 Darknet 是与 YOLO（You Only Look Once）目标检测模型相关的两个不同实现。它的主要特点是将目标检测问题视为回归问题，直接在图像上预测边界框和类别。

tags/python/index.xml

@@ -11,7 +11,7 @@
     <lastBuildDate>Wed, 07 Aug 2024 15:12:28 +0800</lastBuildDate>
     <atom:link href="/tags/python/index.xml" rel="self" type="application/rss+xml" />
     <item>
-      <title>YOLO8</title>
+      <title>yolo8</title>
       <link>/posts/yolo8/</link>
       <pubDate>Wed, 07 Aug 2024 15:12:28 +0800</pubDate>
       <guid>/posts/yolo8/</guid>