updated blog

Author: mynguy

images/movieGradleImg2.JPG

@@ -52,7 +52,24 @@ <h1>My Nguyen Blog</h1>
     <ul class="posts-list">
 
         <li class="posts-list-item">
-          <a class="posts-list-item-title" href="http://mynguy.github.io/posts/post6/">Journey into Computer Vision and Machine Learning Part III</a>
+          <a class="posts-list-item-title" href="http://mynguy.github.io/posts/post6/">Unveiling the New Features of movieGradle: A Multi-Modular Movie Library Application</a>
+          <span class="posts-list-item-description">
+            <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="icon icon-calendar">
+  <title>calendar</title>
+  <rect x="3" y="4" width="18" height="18" rx="2" ry="2"></rect><line x1="16" y1="2" x2="16" y2="6"></line><line x1="8" y1="2" x2="8" y2="6"></line><line x1="3" y1="10" x2="21" y2="10"></line>
+</svg>
+            Jul 17, 2023
+            <span class="posts-list-item-separator">-</span>
+            <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="icon icon-clock">
+  <title>clock</title>
+  <circle cx="12" cy="12" r="10"></circle><polyline points="12 6 12 12 16 14"></polyline>
+</svg>
+            2 min read
+          </span>
+        </li>
+      
+        <li class="posts-list-item">
+          <a class="posts-list-item-title" href="http://mynguy.github.io/posts/cv3/">Journey into Computer Vision and Machine Learning Part III</a>
           <span class="posts-list-item-description">
             <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="icon icon-calendar">
   <title>calendar</title>
@@ -154,7 +171,7 @@ <h1>My Nguyen Blog</h1>
         </li>
 
         <li class="posts-list-item">
-          <a class="posts-list-item-title" href="http://mynguy.github.io/posts/cv1/">Embarking on a Journey into Computer Vision and Machine Learning</a>
+          <a class="posts-list-item-title" href="http://mynguy.github.io/posts/cv1/">Journey into Computer Vision and Machine Learning Part I</a>
           <span class="posts-list-item-description">
             <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="icon icon-calendar">
   <title>calendar</title>

index.html

@@ -6,13 +6,23 @@
     <description>Recent content on My Nguyen Blog</description>
     <generator>Hugo -- gohugo.io</generator>
     <language>en-us</language>
-    <lastBuildDate>Tue, 06 Jun 2023 14:13:20 -0400</lastBuildDate><atom:link href="http://mynguy.github.io/index.xml" rel="self" type="application/rss+xml" />
+    <lastBuildDate>Mon, 17 Jul 2023 16:40:33 -0400</lastBuildDate><atom:link href="http://mynguy.github.io/index.xml" rel="self" type="application/rss+xml" />
     <item>
-      <title>Journey into Computer Vision and Machine Learning Part III</title>
+      <title>Unveiling the New Features of movieGradle: A Multi-Modular Movie Library Application</title>
       <link>http://mynguy.github.io/posts/post6/</link>
-      <pubDate>Tue, 06 Jun 2023 14:13:20 -0400</pubDate>
+      <pubDate>Mon, 17 Jul 2023 16:40:33 -0400</pubDate>
 
       <guid>http://mynguy.github.io/posts/post6/</guid>
+      <description>Today&amp;rsquo;s blog post brings an exciting update on my movieGradle project, a multi-modular movie library application focused on serialization and deserialization. Since my last blog update, I&amp;rsquo;ve been diligently working on creating a user-friendly GUI for the app. This involved adjusting my FXML files, utilizing Scenebuilder, and implementing various buttons and features in the code. Let&amp;rsquo;s dive into the breakdown of the latest features:
+Serialization and Deserialization: The application now allows users to serialize their movie library data into both CSV and binary formats.</description>
+    </item>
+    
+    <item>
+      <title>Journey into Computer Vision and Machine Learning Part III</title>
+      <link>http://mynguy.github.io/posts/cv3/</link>
+      <pubDate>Tue, 06 Jun 2023 14:13:20 -0400</pubDate>
+      
+      <guid>http://mynguy.github.io/posts/cv3/</guid>
       <description>It has been an eventful month since my last update on our computer vision and machine learning project. Our team has made significant progress, particularly in understanding and utilizing YOLOv8 to train and create powerful computer vision models. In this blog post, I will share the latest developments in our project, including our transition to Roboflow, a user-friendly software platform that has provided us with invaluable resources for training and deploying models.</description>
     </item>
 
@@ -55,14 +65,14 @@
     <item>
       <title>Exploring Serialization and Deserialization in Java: A Movie Serialization Project</title>
       <link>http://mynguy.github.io/posts/post2/</link>
-      <pubDate>Mon, 24 Apr 2023 22:11:47 -0400</pubDate>
+      <pubDate>Mon, 24 Apr 2023 15:33:01 -0400</pubDate>
 
       <guid>http://mynguy.github.io/posts/post2/</guid>
-      <description>In this blog post, I will share my experience working on a serialization and deserialization Java project assigned to me by Dr. Bowring. The project aimed to enhance my understanding of these processes and improve my coding skills. I chose to create a simple movie serialization project, where I serialized and deserialized movie objects containing information such as name, genre, and release date. Throughout the project, I encountered various challenges and sought to improve the code&amp;rsquo;s dynamism, organization, and user-friendliness based on Dr.</description>
+      <description>In this blog post, I will share my experience working on a serialization and deserialization Java project assigned to me by Dr. Bowring. The project aimed to enhance my understanding of these processes and improve my coding skills. I chose to create a simple movie serialization project, where I serialized and deserialized movie objects containing information such as name, genre, and release date. Throughout the project, I encountered various challenges and sought to improve the code’s dynamism, organization, and user-friendliness based on Dr.</description>
     </item>
 
     <item>
-      <title>Embarking on a Journey into Computer Vision and Machine Learning</title>
+      <title>Journey into Computer Vision and Machine Learning Part I</title>
       <link>http://mynguy.github.io/posts/cv1/</link>
       <pubDate>Sun, 09 Apr 2023 19:28:43 -0400</pubDate>
 

index.xml

@@ -1,7 +1,7 @@
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   <head>
-    <title>Embarking on a Journey into Computer Vision and Machine Learning // My Nguyen Blog</title>
+    <title>Journey into Computer Vision and Machine Learning Part I // My Nguyen Blog</title>
     <link rel="shortcut icon" href="/favicon.ico" />
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     <meta name="generator" content="Hugo 0.111.3">
@@ -12,11 +12,11 @@
 
 
     <meta name="twitter:card" content="summary"/>
-<meta name="twitter:title" content="Embarking on a Journey into Computer Vision and Machine Learning"/>
+<meta name="twitter:title" content="Journey into Computer Vision and Machine Learning Part I"/>
 <meta name="twitter:description" content="I recently had an initial meeting with a family friend who introduced a fascinating project idea that combines computer vision and machine learning. While my knowledge in the field of computer vision is limited, I felt a surge of anticipation at the prospect of diving into this realm and learning more.
 Our first day together was dedicated to setting up our work environments, establishing meeting schedules, and determining the framework for our project."/>
 
-    <meta property="og:title" content="Embarking on a Journey into Computer Vision and Machine Learning" />
+    <meta property="og:title" content="Journey into Computer Vision and Machine Learning Part I" />
 <meta property="og:description" content="I recently had an initial meeting with a family friend who introduced a fascinating project idea that combines computer vision and machine learning. While my knowledge in the field of computer vision is limited, I felt a surge of anticipation at the prospect of diving into this realm and learning more.
 Our first day together was dedicated to setting up our work environments, establishing meeting schedules, and determining the framework for our project." />
 <meta property="og:type" content="article" />
@@ -53,7 +53,7 @@
 
   <article class="post">
     <header class="post-header">
-      <h1 class ="post-title">Embarking on a Journey into Computer Vision and Machine Learning</h1>
+      <h1 class ="post-title">Journey into Computer Vision and Machine Learning Part I</h1>
       <div class="post-meta">
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           <svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="icon icon-calendar">

posts/cv1/index.html

@@ -71,13 +71,13 @@ <h1 class ="post-title">Journey into Computer Vision and Machine Learning Part I
     </header>
     <div class="post-content">
       <p>Welcome to the second part of our ongoing journey into computer vision and machine learning. In this blog post, I am thrilled to provide an update on our progress in learning annotation techniques for creating segmentation masks in instance segmentation. Instance segmentation, which involves detecting object outlines, has been a central focus of our exploration. Over the past month, our dedicated team has been working together, utilizing CVAT as our annotation tool, to produce datasets enriched with segmentation masks. Our ultimate objective is to accurately detect specific objects in alignment with our project&rsquo;s goals.</p>
-<p><strong>Learning Annotation Techniques with CVAT:</strong>
+<p><strong>Learning Annotation Techniques with CVAT:</strong>    <br>
 In our pursuit of instance segmentation, we have diligently learned annotation techniques using the versatile tool, CVAT. This robust annotation toolset has equipped us with the necessary skills to create precise segmentation masks. Through collaborative efforts and continuous learning, we have mastered the art of outlining and labeling objects of interest in our datasets. These segmentation masks play a crucial role in training our models to accurately detect and analyze objects.</p>
 <p>With the aid of CVAT, we have made significant strides in producing datasets brimming with detailed segmentation masks. These masks provide invaluable information about object boundaries and outlines within the images. By leveraging these datasets, we are poised to train our models to identify and classify specific objects with enhanced precision and accuracy. Our project&rsquo;s overarching goal revolves around detecting and analyzing these objects, and the creation of these high-quality datasets marks a significant milestone in our journey.</p>
-<p><strong>Overcoming Challenges:</strong>
+<p><strong>Overcoming Challenges:</strong>    <br>
 Throughout our exploration, we encountered a challenge related to the conversion of segmentation masks to polygons. The tutorial and training materials we found online provided scripts that were designed to work with one class projects only. To address this limitation, I took the initiative to develop my own version of the script capable of handling multiple classes. The code is readily available on my GitHub repository, specifically tailored for users of CVAT who are annotating for segmentation in YOLOv8 format. I encourage you to explore and utilize this code for your own projects.</p>
 <p>In our pursuit of efficient annotation, we have embraced cutting-edge technology. Thanks to Meta AI, annotation has become significantly faster and more streamlined through the use of SAM (Segment Anything), an innovative solution that employs AI to automate the annotation process. SAM has revolutionized the way we annotate and has resulted in cleaner and more efficient dataset creation. This remarkable advancement has accelerated our progress and enabled us to focus on further aspects of our project.</p>
-<p><strong>Future Prospects and Continued Progress:</strong>
+<p><strong>Future Prospects and Continued Progress:</strong>     <br>
 As we forge ahead in our computer vision and machine learning journey, we remain passionate about the incredible possibilities that instance segmentation holds. Our expertise in annotation techniques, bolstered by the powerful capabilities of CVAT and our customized conversion script, empowers us to unlock new levels of object detection accuracy. Additionally, the integration of Meta AI&rsquo;s SAM has transformed the annotation process, elevating our efficiency and productivity. We are excited to continue this journey and share more updates in the future.</p>
 
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