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{
  "id": "88708ef5-88e4-4f81-a3ca-d91702b86c2a",
  "type": "general",
  "status": "completed",
  "title": "YOLOv8 Architecture Explorer",
  "description": "YOLOv8 anchor-free architecture with decoupled head details",
  "context": {
    "output": "<div style=\"background:#030712;color:#f3f4f6;padding:24px;border-radius:16px;font-family:system-ui,-apple-system,sans-serif;\"><div style=\"text-align:center;margin-bottom:24px;\"><h1 style=\"font-size:1.8rem;font-weight:bold;margin:0 0 8px 0;background:linear-gradient(to right,#60a5fa,#a78bfa,#fbbf24);-webkit-background-clip:text;-webkit-text-fill-color:transparent;background-clip:text;\">YOLO Architecture Explorer</h1><p style=\"color:#9ca3af;margin:0;\">Compare detection head designs across versions</p></div><div style=\"display:flex;justify-content:center;gap:8px;margin-bottom:24px;flex-wrap:wrap;\"><span style=\"background:#1f2937;color:#9ca3af;padding:8px 16px;border-radius:8px;\">YOLOv5</span><span style=\"background:#1f2937;color:#9ca3af;padding:8px 16px;border-radius:8px;\">YOLOv7</span><span style=\"background:#8b5cf6;color:#fff;padding:8px 16px;border-radius:8px;font-weight:500;box-shadow:0 4px 6px rgba(139,92,246,0.3);transform:scale(1.05);\">YOLOv8</span><span style=\"background:#1f2937;color:#9ca3af;padding:8px 16px;border-radius:8px;\">YOLOX</span></div><div style=\"background:#111827;border-radius:16px;border:1px solid #1f2937;overflow:hidden;\"><div style=\"padding:16px;border-bottom:1px solid #1f2937;background:rgba(139,92,246,0.1);\"><div style=\"display:flex;align-items:center;justify-content:space-between;flex-wrap:wrap;gap:12px;\"><div style=\"display:flex;align-items:center;gap:12px;\"><div style=\"width:12px;height:12px;border-radius:50%;background:#8b5cf6;\"></div><span style=\"font-size:1.25rem;font-weight:bold;\">YOLOv8</span><span style=\"color:#6b7280;\">(2023)</span></div><div style=\"display:flex;gap:16px;font-size:0.9rem;flex-wrap:wrap;\"><div><span style=\"color:#6b7280;\">Approach:</span> <span style=\"background:rgba(139,92,246,0.3);color:#8b5cf6;padding:2px 8px;border-radius:4px;font-weight:500;\">Anchor-free</span></div><div><span style=\"color:#6b7280;\">Head:</span> <span style=\"background:rgba(139,92,246,0.3);color:#8b5cf6;padding:2px 8px;border-radius:4px;font-weight:500;\">Decoupled</span></div></div></div></div><div style=\"display:flex;border-bottom:1px solid #1f2937;\"><div style=\"flex:1;padding:12px;text-align:center;border-bottom:2px solid #8b5cf6;color:#8b5cf6;font-weight:500;font-size:0.9rem;\">Architecture</div><div style=\"flex:1;padding:12px;text-align:center;color:#6b7280;font-size:0.9rem;\">Parameters</div><div style=\"flex:1;padding:12px;text-align:center;color:#6b7280;font-size:0.9rem;\">Strengths</div></div><div style=\"padding:24px;\"><div style=\"display:flex;gap:16px;align-items:flex-start;margin-bottom:24px;flex-wrap:wrap;\"><div style=\"flex:1;min-width:100px;\"><div style=\"background:#8b5cf6;color:#fff;padding:6px 12px;border-radius:6px;text-align:center;font-size:0.75rem;font-weight:600;margin-bottom:8px;\">BACKBONE</div><div style=\"border:1px solid #8b5cf6;color:#8b5cf6;background:rgba(139,92,246,0.1);padding:8px;border-radius:6px;text-align:center;font-size:0.8rem;margin-bottom:4px;\">CBS</div><div style=\"border:1px solid #8b5cf6;color:#8b5cf6;background:rgba(139,92,246,0.1);padding:8px;border-radius:6px;text-align:center;font-size:0.8rem;margin-bottom:4px;\">C2f</div><div style=\"border:1px solid #8b5cf6;color:#8b5cf6;background:rgba(139,92,246,0.1);padding:8px;border-radius:6px;text-align:center;font-size:0.8rem;\">SPPF</div></div><div style=\"display:flex;align-items:center;color:#4b5563;font-size:1.2rem;\">→</div><div style=\"flex:1;min-width:100px;\"><div style=\"background:#8b5cf6;color:#fff;padding:6px 12px;border-radius:6px;text-align:center;font-size:0.75rem;font-weight:600;margin-bottom:8px;\">NECK</div><div style=\"border:1px solid #8b5cf6;color:#8b5cf6;background:rgba(139,92,246,0.1);padding:8px;border-radius:6px;text-align:center;font-size:0.8rem;margin-bottom:4px;\">Upsample</div><div style=\"border:1px solid #8b5cf6;color:#8b5cf6;background:rgba(139,92,246,0.1);padding:8px;border-radius:6px;text-align:center;font-size:0.8rem;margin-bottom:4px;\">C2f</div><div style=\"border:1px solid #8b5cf6;color:#8b5cf6;background:rgba(139,92,246,0.1);padding:8px;border-radius:6px;text-align:center;font-size:0.8rem;\">Concat</div></div><div style=\"display:flex;align-items:center;color:#4b5563;font-size:1.2rem;\">→</div><div style=\"flex:1;min-width:100px;\"><div style=\"background:#8b5cf6;color:#fff;padding:6px 12px;border-radius:6px;text-align:center;font-size:0.75rem;font-weight:600;margin-bottom:8px;\">HEAD</div><div style=\"border:1px solid #8b5cf6;color:#8b5cf6;background:rgba(139,92,246,0.1);padding:8px;border-radius:6px;text-align:center;font-size:0.8rem;margin-bottom:4px;\">Decoupled (cls + reg)</div><div style=\"border:1px solid #8b5cf6;color:#8b5cf6;background:rgba(139,92,246,0.1);padding:8px;border-radius:6px;text-align:center;font-size:0.8rem;\">DFL Loss</div></div></div><div style=\"background:rgba(31,41,55,0.5);border-radius:12px;padding:16px;\"><h3 style=\"color:#8b5cf6;font-weight:600;margin:0 0 8px 0;font-size:0.95rem;\">Detection Head Details</h3><p style=\"color:#9ca3af;font-size:0.9rem;line-height:1.6;margin:0;\">YOLOv8 pioneered <strong style=\"color:#a78bfa;\">anchor-free detection</strong> in the YOLO family with a fully <strong style=\"color:#a78bfa;\">decoupled head</strong>. Classification and regression are separate branches, eliminating the coupling that slowed earlier versions. Uses <strong style=\"color:#a78bfa;\">Distribution Focal Loss (DFL)</strong> for bounding box regression, predicting distributions over box coordinates instead of direct values—this improves localization accuracy.</p></div></div></div><div style=\"background:#111827;border-radius:12px;padding:16px;margin-top:16px;border:1px solid #1f2937;\"><h3 style=\"color:#8b5cf6;font-weight:600;margin:0 0 12px 0;\">Model Variants</h3><div style=\"display:grid;grid-template-columns:repeat(5,1fr);gap:8px;\"><div style=\"background:#1f2937;padding:12px;border-radius:8px;text-align:center;\"><div style=\"color:#6b7280;font-size:0.7rem;text-transform:uppercase;margin-bottom:4px;\">Nano</div><div style=\"color:#8b5cf6;font-weight:bold;font-family:monospace;\">3.2M</div></div><div style=\"background:#1f2937;padding:12px;border-radius:8px;text-align:center;\"><div style=\"color:#6b7280;font-size:0.7rem;text-transform:uppercase;margin-bottom:4px;\">Small</div><div style=\"color:#8b5cf6;font-weight:bold;font-family:monospace;\">11.2M</div></div><div style=\"background:#1f2937;padding:12px;border-radius:8px;text-align:center;\"><div style=\"color:#6b7280;font-size:0.7rem;text-transform:uppercase;margin-bottom:4px;\">Medium</div><div style=\"color:#8b5cf6;font-weight:bold;font-family:monospace;\">25.9M</div></div><div style=\"background:#1f2937;padding:12px;border-radius:8px;text-align:center;\"><div style=\"color:#6b7280;font-size:0.7rem;text-transform:uppercase;margin-bottom:4px;\">Large</div><div style=\"color:#8b5cf6;font-weight:bold;font-family:monospace;\">43.7M</div></div><div style=\"background:#1f2937;padding:12px;border-radius:8px;text-align:center;\"><div style=\"color:#6b7280;font-size:0.7rem;text-transform:uppercase;margin-bottom:4px;\">XLarge</div><div style=\"color:#8b5cf6;font-weight:bold;font-family:monospace;\">68.2M</div></div></div></div><div style=\"background:#111827;border-radius:12px;padding:16px;margin-top:16px;border:1px solid #1f2937;\"><h3 style=\"color:#8b5cf6;font-weight:600;margin:0 0 12px 0;\">Key Strengths</h3><div style=\"display:grid;gap:8px;\"><div style=\"display:flex;align-items:center;gap:12px;padding:10px;background:rgba(139,92,246,0.1);border-radius:8px;\"><div style=\"width:28px;height:28px;border-radius:50%;background:#8b5cf6;display:flex;align-items:center;justify-content:center;font-weight:bold;font-size:0.8rem;\">1</div><span style=\"color:#e0e0e0;\">Anchor-free simplicity - no anchor tuning needed</span></div><div style=\"display:flex;align-items:center;gap:12px;padding:10px;background:rgba(139,92,246,0.1);border-radius:8px;\"><div style=\"width:28px;height:28px;border-radius:50%;background:#8b5cf6;display:flex;align-items:center;justify-content:center;font-weight:bold;font-size:0.8rem;\">2</div><span style=\"color:#e0e0e0;\">Decoupled head - faster convergence, better accuracy</span></div><div style=\"display:flex;align-items:center;gap:12px;padding:10px;background:rgba(139,92,246,0.1);border-radius:8px;\"><div style=\"width:28px;height:28px;border-radius:50%;background:#8b5cf6;display:flex;align-items:center;justify-content:center;font-weight:bold;font-size:0.8rem;\">3</div><span style=\"color:#e0e0e0;\">Unified CLI - single interface for train/val/predict/export</span></div><div style=\"display:flex;align-items:center;gap:12px;padding:10px;background:rgba(139,92,246,0.1);border-radius:8px;\"><div style=\"width:28px;height:28px;border-radius:50%;background:#8b5cf6;display:flex;align-items:center;justify-content:center;font-weight:bold;font-size:0.8rem;\">4</div><span style=\"color:#e0e0e0;\">Task versatility - detection, segmentation, pose, classification</span></div></div></div><div style=\"display:grid;grid-template-columns:1fr 1fr;gap:16px;margin-top:16px;\"><div style=\"background:#111827;border-radius:12px;padding:16px;border:1px solid #1f2937;\"><h3 style=\"color:#9ca3af;font-size:0.9rem;font-weight:600;margin:0 0 8px 0;\">vs YOLOv5</h3><p style=\"color:#6b7280;font-size:0.8rem;margin:0;line-height:1.5;\">Drops anchors entirely. C2f replaces C3 for better gradient flow. Decoupled head vs coupled. Better small object detection.</p></div><div style=\"background:#111827;border-radius:12px;padding:16px;border:1px solid #1f2937;\"><h3 style=\"color:#9ca3af;font-size:0.9rem;font-weight:600;margin:0 0 8px 0;\">vs YOLOv7</h3><p style=\"color:#6b7280;font-size:0.8rem;margin:0;line-height:1.5;\">Simpler architecture (no E-ELAN). No auxiliary heads needed. Faster training. Easier deployment with unified API.</p></div></div></div>",
    "requestedAt": "2026-01-07T02:40:00.000Z",
    "requestId": "62ab1638-81cf-46c8-be24-ee6b1d547205",
    "choices": [
      {
        "label": "View YOLOv7",
        "value": "Show me the YOLOv7 architecture with auxiliary heads",
        "primary": true
      },
      {
        "label": "View YOLOX",
        "value": "Show me YOLOX - the first anchor-free YOLO"
      },
      {
        "label": "Compare all",
        "value": "Create a side-by-side comparison table of all 4 YOLO versions"
      }
    ],
    "turnTiming": {
      "totalMs": 53366,
      "ttfeMs": 56,
      "thinkingMs": 53310,
      "toolExecutionMs": 0,
      "toolCallCount": 0,
      "thinkingPct": 100,
      "toolsPct": 0,
      "ttfePct": 0
    }
  },
  "createdBy": "claude",
  "createdAt": "2026-01-06T23:03:19.689Z",
  "updatedAt": "2026-01-06T23:03:24.872Z",
  "requestId": "62ab1638-81cf-46c8-be24-ee6b1d547205",
  "scope": "vibetools",
  "tags": [
    "demo",
    "yolo",
    "architecture",
    "v8"
  ],
  "targetUser": "claude"
}