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      <title>棋子检测方案升级：YOLO 目标检测替代传统 ROI 阈值</title>
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      <description>Phase: P1 升级 — 棋子识别方案演进 | 依赖: P0 棋盘矫正 目标: 用 YOLO 深度学习模型替代 ROI 双阈值方案，提升棋子检测准确率和光照鲁棒性。 0. 升级背景 当前的 ROI 双阈值</description>
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      <title>Part 0: 基础视觉系统 —— 从摄像头到棋盘矫正</title>
      <link>https://logmagic.top/courses/go-board-assistant/part0-foundation/</link>
      <pubDate>Mon, 11 May 2026 00:00:00 +0000</pubDate>
      
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      <description>完成摄像头采集、棋盘检测、透视矫正三大基础模块，为后续棋子识别和 AI 对弈打下视觉地基</description>
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      <title>Part 1: 规则引擎 &#43; 虚拟棋盘 —— 从检测到对弈</title>
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      <pubDate>Mon, 11 May 2026 00:00:00 +0000</pubDate>
      
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      <title>Qt6 安卓开发环境部署完全指南</title>
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      <description>从零到 APK：在 Ubuntu 20.04 上搭建 Qt6 Android 交叉编译环境，覆盖 JDK、Android SDK/NDK、Qt6 for Android 安装，以及 CMake 配置、交叉编译、APK 打包全流程</description>
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      <title>棋子检测系统设计：ROI 双阈值 &#43; 帧差法落子识别</title>
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      <pubDate>Mon, 11 May 2026 00:00:00 +0000</pubDate>
      
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      <description>Phase: P1 — 棋子识别 + 局面感知 | 依赖: P0 棋盘矫正 输入: 透视矫正后的 600×600 正方形棋盘图，已知 361 个交点像素坐标 输出: 19×19 局面字符串 (B/W/.) + 落</description>
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      <title>Qt6 中的 OpenGL 编程 — 从 QOpenGLWidget 开始</title>
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      <description>Qt6 的 OpenGL 模块和 Qt5 有微妙差别，这篇文章帮你避开最常见的坑</description>
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