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        ],
        "num_inputs": 3,
        "note": "原图细节比 GPT 正交化更重要，保留 direct 路线并提高步数。",
        "mesh_stats": {
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        "mesh_preview": "quality_optimization/chair/selected_highstep/mesh_preview.png",
        "raw_mesh": "quality_optimization/chair/selected_highstep/mesh_raw.obj",
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          "inputs/chair/chair_3.png",
          "inputs/chair/chair_1.png",
          "inputs/chair/chair_2.png",
          "inputs/chair/chair_3.png",
          "orthoviews/chair/front.png",
          "orthoviews/chair/left.png",
          "orthoviews/chair/right.png",
          "orthoviews/chair/back.png"
        ],
        "num_inputs": 10,
        "note": "原图重复 2 次，降低 GPT 重绘丢小物件的影响。",
        "mesh_stats": {
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        "raw_mesh": "quality_optimization/chair/weighted_hybrid_highstep/mesh_raw.obj",
        "raw_mesh_status": "ok"
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    },
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        "description": "前两轮每个 case 的最佳路线 + 24 step multidiffusion",
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          "orthoviews/monkey/right.png",
          "orthoviews/monkey/back.png"
        ],
        "num_inputs": 4,
        "note": "GPT 正交视图质量高，使用正交视图提高方向一致性。",
        "mesh_stats": {
          "vertices": 348194,
          "bbox_min": [
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          "faces": 696424
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        "mesh_video": "quality_optimization/monkey/selected_highstep/mesh_normal.mp4",
        "mesh_preview": "quality_optimization/monkey/selected_highstep/mesh_preview.png",
        "raw_mesh": "quality_optimization/monkey/selected_highstep/mesh_raw.obj",
        "raw_mesh_status": "ok"
      },
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        "description": "基于质量门控的加权输入 + 24 step multidiffusion",
        "mode": "multidiffusion",
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        "elapsed_sec": 11.14453649520874,
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          "orthoviews/monkey/front.png",
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          "orthoviews/monkey/right.png",
          "orthoviews/monkey/back.png"
        ],
        "num_inputs": 4,
        "note": "只用高质量 GPT 正交图。",
        "mesh_stats": {
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          "bbox_min": [
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        "mesh_video": "quality_optimization/monkey/weighted_hybrid_highstep/mesh_normal.mp4",
        "mesh_preview": "quality_optimization/monkey/weighted_hybrid_highstep/mesh_preview.png",
        "raw_mesh": "quality_optimization/monkey/weighted_hybrid_highstep/mesh_raw.obj",
        "raw_mesh_status": "ok"
      }
    },
    "robot": {
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        "variant": "selected_highstep",
        "description": "前两轮每个 case 的最佳路线 + 24 step multidiffusion",
        "mode": "multidiffusion",
        "steps": 24,
        "elapsed_sec": 6.406952142715454,
        "inputs": [
          "inputs/robot/robot_1.png",
          "inputs/robot/robot_2.png"
        ],
        "num_inputs": 2,
        "note": "GPT back 方向错误，优先信任原图。",
        "mesh_stats": {
          "vertices": 238808,
          "bbox_min": [
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        "mesh_video": "quality_optimization/robot/selected_highstep/mesh_normal.mp4",
        "mesh_preview": "quality_optimization/robot/selected_highstep/mesh_preview.png",
        "raw_mesh": "quality_optimization/robot/selected_highstep/mesh_raw.obj",
        "raw_mesh_status": "ok"
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        "description": "基于质量门控的加权输入 + 24 step multidiffusion",
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        "elapsed_sec": 21.468254566192627,
        "inputs": [
          "inputs/robot/robot_1.png",
          "inputs/robot/robot_2.png",
          "inputs/robot/robot_1.png",
          "inputs/robot/robot_2.png",
          "inputs/robot/robot_1.png",
          "inputs/robot/robot_2.png",
          "orthoviews/robot/front.png",
          "orthoviews/robot/left.png",
          "orthoviews/robot/right.png"
        ],
        "num_inputs": 9,
        "note": "原图重复 3 次，并排除错误 back 视图。",
        "mesh_stats": {
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        "mesh_video": "quality_optimization/robot/weighted_hybrid_highstep/mesh_normal.mp4",
        "mesh_preview": "quality_optimization/robot/weighted_hybrid_highstep/mesh_preview.png",
        "raw_mesh": "quality_optimization/robot/weighted_hybrid_highstep/mesh_raw.obj",
        "raw_mesh_status": "ok"
      }
    },
    "toolcar": {
      "selected_highstep": {
        "variant": "selected_highstep",
        "description": "前两轮每个 case 的最佳路线 + 24 step multidiffusion",
        "mode": "multidiffusion",
        "steps": 24,
        "elapsed_sec": 18.103885650634766,
        "inputs": [
          "inputs/toolcar/toolcar_1.png",
          "inputs/toolcar/toolcar_2.png",
          "inputs/toolcar/toolcar_3.png",
          "orthoviews/toolcar/front.png",
          "orthoviews/toolcar/left.png",
          "orthoviews/toolcar/right.png",
          "orthoviews/toolcar/back.png"
        ],
        "num_inputs": 7,
        "note": "原图细节和可信 GPT 正交约束互补。",
        "mesh_stats": {
          "vertices": 485086,
          "bbox_min": [
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        "mesh_video": "quality_optimization/toolcar/selected_highstep/mesh_normal.mp4",
        "mesh_preview": "quality_optimization/toolcar/selected_highstep/mesh_preview.png",
        "raw_mesh": "quality_optimization/toolcar/selected_highstep/mesh_raw.obj",
        "raw_mesh_status": "ok"
      },
      "weighted_hybrid_highstep": {
        "variant": "weighted_hybrid_highstep",
        "description": "基于质量门控的加权输入 + 24 step multidiffusion",
        "mode": "multidiffusion",
        "steps": 24,
        "elapsed_sec": 23.747543811798096,
        "inputs": [
          "inputs/toolcar/toolcar_1.png",
          "inputs/toolcar/toolcar_2.png",
          "inputs/toolcar/toolcar_3.png",
          "inputs/toolcar/toolcar_1.png",
          "inputs/toolcar/toolcar_2.png",
          "inputs/toolcar/toolcar_3.png",
          "orthoviews/toolcar/front.png",
          "orthoviews/toolcar/left.png",
          "orthoviews/toolcar/right.png",
          "orthoviews/toolcar/back.png"
        ],
        "num_inputs": 10,
        "note": "原图重复 2 次以保留部件细节，同时加入可信正交约束。",
        "mesh_stats": {
          "vertices": 455526,
          "bbox_min": [
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          "faces": 911248
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        "mesh_video": "quality_optimization/toolcar/weighted_hybrid_highstep/mesh_normal.mp4",
        "mesh_preview": "quality_optimization/toolcar/weighted_hybrid_highstep/mesh_preview.png",
        "raw_mesh": "quality_optimization/toolcar/weighted_hybrid_highstep/mesh_raw.obj",
        "raw_mesh_status": "ok"
      }
    },
    "flower": {
      "selected_highstep": {
        "variant": "selected_highstep",
        "description": "前两轮每个 case 的最佳路线 + 24 step multidiffusion",
        "mode": "multidiffusion",
        "steps": 24,
        "elapsed_sec": 18.314245462417603,
        "inputs": [
          "inputs/flower/flower_1.png",
          "inputs/flower/flower_2.png",
          "inputs/flower/flower_3.png",
          "inputs/flower/flower_4.png",
          "inputs/flower/flower_5.png",
          "inputs/flower/flower_6.png",
          "inputs/flower/flower_7.png",
          "inputs/flower/flower_8.png"
        ],
        "num_inputs": 8,
        "note": "GPT 四视图差异不足，排除 GPT 正交视图。",
        "mesh_stats": {
          "vertices": 425110,
          "bbox_min": [
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          "faces": 850688
        },
        "mesh_video": "quality_optimization/flower/selected_highstep/mesh_normal.mp4",
        "mesh_preview": "quality_optimization/flower/selected_highstep/mesh_preview.png",
        "raw_mesh": "quality_optimization/flower/selected_highstep/mesh_raw.obj",
        "raw_mesh_status": "ok"
      },
      "weighted_hybrid_highstep": {
        "variant": "weighted_hybrid_highstep",
        "description": "基于质量门控的加权输入 + 24 step multidiffusion",
        "mode": "multidiffusion",
        "steps": 24,
        "elapsed_sec": 18.138001441955566,
        "inputs": [
          "inputs/flower/flower_1.png",
          "inputs/flower/flower_2.png",
          "inputs/flower/flower_3.png",
          "inputs/flower/flower_4.png",
          "inputs/flower/flower_5.png",
          "inputs/flower/flower_6.png",
          "inputs/flower/flower_7.png",
          "inputs/flower/flower_8.png"
        ],
        "num_inputs": 8,
        "note": "GPT 花束视图不合格，完全回退到原图。",
        "mesh_stats": {
          "vertices": 425122,
          "bbox_min": [
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          "faces": 850732
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        "mesh_video": "quality_optimization/flower/weighted_hybrid_highstep/mesh_normal.mp4",
        "mesh_preview": "quality_optimization/flower/weighted_hybrid_highstep/mesh_preview.png",
        "raw_mesh": "quality_optimization/flower/weighted_hybrid_highstep/mesh_raw.obj",
        "raw_mesh_status": "ok"
      }
    }
  },
  "variants": {
    "selected_highstep": {
      "steps": 24,
      "mode": "multidiffusion",
      "description": "前两轮每个 case 的最佳路线 + 24 step multidiffusion"
    },
    "weighted_hybrid_highstep": {
      "steps": 24,
      "mode": "multidiffusion",
      "description": "基于质量门控的加权输入 + 24 step multidiffusion"
    }
  },
  "weighted_rules": {
    "chair": {
      "original_weight": 2,
      "gpt_views": [
        "front",
        "left",
        "right",
        "back"
      ],
      "gpt_weight": 1,
      "note": "原图重复 2 次，降低 GPT 重绘丢小物件的影响。"
    },
    "monkey": {
      "original_weight": 0,
      "gpt_views": [
        "front",
        "left",
        "right",
        "back"
      ],
      "gpt_weight": 1,
      "note": "只用高质量 GPT 正交图。"
    },
    "robot": {
      "original_weight": 3,
      "gpt_views": [
        "front",
        "left",
        "right"
      ],
      "gpt_weight": 1,
      "note": "原图重复 3 次，并排除错误 back 视图。"
    },
    "toolcar": {
      "original_weight": 2,
      "gpt_views": [
        "front",
        "left",
        "right",
        "back"
      ],
      "gpt_weight": 1,
      "note": "原图重复 2 次以保留部件细节，同时加入可信正交约束。"
    },
    "flower": {
      "original_weight": 1,
      "gpt_views": [],
      "gpt_weight": 0,
      "note": "GPT 花束视图不合格，完全回退到原图。"
    }
  }
}