引入3d模型
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107
art-agent/backend/scripts/test_frame_extract.py
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107
art-agent/backend/scripts/test_frame_extract.py
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"""Phase 2 验收脚本：独立验证 combined_video 抽帧 + 左右切分逻辑。
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不需要再跑一次 Trellis（省钱），直接用 generated/ 下已有的
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`trellis_combined_*.mp4` 做验证。
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用法（在 backend 目录激活 venv 之后）：
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python scripts/test_frame_extract.py
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python scripts/test_frame_extract.py generated/trellis_combined_211176d3940b.mp4
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成功标准：
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- 退出码 0
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- 打印的 color_png / normal_png 均为 /generated/view_xxx.png
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- 到 backend/generated/ 能看到 6 对 color + normal 文件（12 张）且尺寸接近正方形
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- 目视检查：每组 color 图按 0/60/120/180/240/300° 依次环绕建筑一圈
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"""
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import asyncio
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import json
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import sys
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from pathlib import Path
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_BACKEND_ROOT = Path(__file__).resolve().parent.parent
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if str(_BACKEND_ROOT) not in sys.path:
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sys.path.insert(0, str(_BACKEND_ROOT))
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from dotenv import load_dotenv # noqa: E402
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load_dotenv(_BACKEND_ROOT / ".env", override=True)
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from app.services import video_frame_extractor # noqa: E402
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from app.services.image_gen import GENERATED_DIR # noqa: E402
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def _pick_default_video() -> str:
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candidates = sorted(
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GENERATED_DIR.glob("trellis_combined_*.mp4"),
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key=lambda p: p.stat().st_mtime,
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reverse=True,
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)
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if not candidates:
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raise FileNotFoundError(
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"generated/ 下找不到 trellis_combined_*.mp4；请先跑一次 Phase 1 "
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"（scripts/test_trellis.py）或显式传入视频路径"
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)
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return f"/generated/{candidates[0].name}"
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async def main() -> int:
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video_arg = sys.argv[1] if len(sys.argv) > 1 else _pick_default_video()
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# 允许传相对路径或纯文件名
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if not video_arg.startswith("/generated/"):
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if video_arg.startswith("generated/"):
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video_arg = "/" + video_arg.replace("\\", "/")
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elif not video_arg.startswith("/") and not Path(video_arg).is_absolute():
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# 如果只给了个文件名，假定在 generated/ 下
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if (GENERATED_DIR / video_arg).exists():
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video_arg = f"/generated/{video_arg}"
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print(f"[test_frame_extract] 输入视频：{video_arg}")
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print("[test_frame_extract] 抽取 6 视角：az=[0,60,120,180,240,300]，el 全 0")
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azimuths = [0, 60, 120, 180, 240, 300]
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elevations = [0] * len(azimuths)
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frames = await video_frame_extractor.extract_by_azimuth(
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combined_video_path=video_arg,
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azimuths=azimuths,
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elevations=elevations,
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total_rotation_deg=360,
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)
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print("[test_frame_extract] 抽帧结果：")
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print(json.dumps(frames, ensure_ascii=False, indent=2))
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# 简单完整性校验
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all_exist = True
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for f in frames:
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for key in ("color_png", "normal_png"):
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rel = f.get(key)
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if not rel:
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print(f"[test_frame_extract] 警告：帧 az={f['az']} 缺少 {key}")
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all_exist = False
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continue
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local = GENERATED_DIR / Path(rel).name
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size = local.stat().st_size if local.exists() else -1
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status = "OK" if size > 0 else "MISSING"
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print(f" [{status}] az={f['az']:3d} {key}: {rel} ({size} bytes)")
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if size <= 0:
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all_exist = False
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if not all_exist:
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print("[test_frame_extract] 部分文件缺失，判定失败")
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return 1
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print(
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f"[test_frame_extract] 成功：共 {len(frames)} 个视角，"
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f"color+normal 合计 {len(frames) * 2} 张已落盘到 {GENERATED_DIR}"
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)
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print(
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"[test_frame_extract] 请目视检查：打开 generated/ 下任意 view_*_color.png，"
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"确认 az=0 正面、az=180 背面、其余按顺序环绕；normal 帧应为蓝紫调法线图。"
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)
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return 0
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if __name__ == "__main__":
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sys.exit(asyncio.run(main()))
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167
art-agent/backend/scripts/test_style_restore.py
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167
art-agent/backend/scripts/test_style_restore.py
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"""Phase 3 / Checkpoint 3 验收脚本：独立验证 Stage 3 风格还原链路。
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复用 Phase 2 已抽出的 normal 帧，无需再跑 Trellis（省 $0.041）。
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默认会挑最新一组 view_*_el0_normal.png 作为结构参考，并让用户指定原图。
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用法（在 backend 目录激活 venv 后）：
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# 1. 全 6 帧批量重绘（~6 × $0.07 ≈ $0.42）
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python scripts/test_style_restore.py <原图路径>
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# 2. 只跑一帧做快速冒烟（便宜 ~$0.07）
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python scripts/test_style_restore.py <原图路径> --single
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# 3. 手动指定 normal 帧前缀（不指定时用最新一组）
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python scripts/test_style_restore.py <原图路径> --prefix view_xxxxxxxx
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成功标准：
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- 退出码 0
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- 打印的每一帧都返回 success=True 且 url 以 /generated/restyled_ 开头
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- 打开 generated/restyled_* 图片，目视检查：风格与原图一致、视角符合 az 标注
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"""
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from __future__ import annotations
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import argparse
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import asyncio
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import json
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import sys
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from pathlib import Path
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_BACKEND_ROOT = Path(__file__).resolve().parent.parent
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if str(_BACKEND_ROOT) not in sys.path:
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sys.path.insert(0, str(_BACKEND_ROOT))
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from dotenv import load_dotenv # noqa: E402
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load_dotenv(_BACKEND_ROOT / ".env", override=True)
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from app.services import style_restorer # noqa: E402
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from app.services.image_gen import GENERATED_DIR # noqa: E402
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def _pick_latest_normal_group() -> tuple[str, list[dict]]:
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"""在 generated/ 下挑一组最新的 view_<prefix>_az*_el0_normal.png，按 az 排好序。
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返回 (prefix, frames)，frames = [{az, el, normal_png, color_png}, ...]
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"""
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all_normals = sorted(
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GENERATED_DIR.glob("view_*_el0_normal.png"),
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key=lambda p: p.stat().st_mtime,
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reverse=True,
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)
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if not all_normals:
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raise FileNotFoundError(
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"generated/ 下找不到 view_*_el0_normal.png；请先跑 scripts/test_frame_extract.py"
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)
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# 最新文件的 prefix：view_<8hex>_az...
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latest_name = all_normals[0].name
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# 形如 view_63731b77_az0_el0_normal.png → prefix = view_63731b77
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parts = latest_name.split("_")
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prefix = "_".join(parts[:2])
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return prefix, _load_group_by_prefix(prefix)
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def _load_group_by_prefix(prefix: str) -> list[dict]:
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normals = sorted(GENERATED_DIR.glob(f"{prefix}_az*_el0_normal.png"))
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if not normals:
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raise FileNotFoundError(f"找不到前缀为 {prefix} 的 normal 帧")
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frames = []
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for n in normals:
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# 从文件名解析 az：view_63731b77_az120_el0_normal.png → az=120
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tokens = n.stem.split("_")
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az = 0
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el = 0
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for t in tokens:
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if t.startswith("az"):
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try:
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az = int(t[2:])
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except ValueError:
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pass
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elif t.startswith("el"):
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try:
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el = int(t[2:])
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except ValueError:
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pass
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color = n.with_name(n.name.replace("_normal.png", "_color.png"))
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frames.append({
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"az": az,
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"el": el,
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"normal_png": f"/generated/{n.name}",
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"color_png": f"/generated/{color.name}" if color.exists() else None,
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"frame_idx": -1,
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})
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frames.sort(key=lambda f: f["az"])
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return frames
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async def main() -> int:
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parser = argparse.ArgumentParser()
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parser.add_argument("original", help="用户原图路径（本地相对/绝对路径均可）")
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parser.add_argument("--prefix", default=None, help="normal 帧的文件名前缀（如 view_63731b77）")
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parser.add_argument("--single", action="store_true", help="只跑第一帧做快速冒烟")
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parser.add_argument("--scale", type=float, default=None, help="覆盖 IP-Adapter 权重（0-1）")
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parser.add_argument("--cn-scale", type=float, default=None, help="覆盖 ControlNet 权重（0-1）")
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args = parser.parse_args()
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original = args.original
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original_path = Path(original)
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if not original_path.is_absolute():
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original_path = (_BACKEND_ROOT / original).resolve()
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if not original_path.exists():
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print(f"[test_style_restore] 原图不存在：{original_path}")
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return 2
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if args.prefix:
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frames = _load_group_by_prefix(args.prefix)
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prefix = args.prefix
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else:
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prefix, frames = _pick_latest_normal_group()
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if args.single:
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frames = frames[:1]
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override_params = {}
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if args.scale is not None:
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override_params["scale"] = args.scale
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if args.cn_scale is not None:
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override_params["controlnet_conditioning_scale"] = args.cn_scale
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print(f"[test_style_restore] 原图：{original_path}")
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print(f"[test_style_restore] normal 帧组 prefix={prefix}，共 {len(frames)} 帧")
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print(f"[test_style_restore] 角度列表：{[f['az'] for f in frames]}")
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if override_params:
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print(f"[test_style_restore] 覆盖参数：{override_params}")
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print(
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f"[test_style_restore] 预计耗时 ~{72}s × {len(frames)}，"
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f"成本 ~${0.07 * len(frames):.2f}（并发 3 实际会更快）"
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)
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results = await style_restorer.restore_batch(
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original_image=str(original_path),
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frames=frames,
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params=override_params or None,
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concurrency=3,
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)
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print("[test_style_restore] 重绘结果：")
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print(json.dumps(results, ensure_ascii=False, indent=2))
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ok = sum(1 for r in results if r.get("success"))
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print(f"[test_style_restore] 成功 {ok}/{len(results)} 帧")
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if ok == 0:
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print("[test_style_restore] 全军覆没，判定失败")
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return 1
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if ok < len(results):
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print("[test_style_restore] 部分帧失败，视为部分通过；请检查上方错误信息")
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return 0
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print(
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"[test_style_restore] 全部成功；请目视检查 generated/restyled_* 图片："
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"风格应贴近原图、视角按 az 顺序环绕。"
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)
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return 0
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if __name__ == "__main__":
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sys.exit(asyncio.run(main()))
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72
art-agent/backend/scripts/test_trellis.py
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72
art-agent/backend/scripts/test_trellis.py
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@@ -0,0 +1,72 @@
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"""Phase 1 验收脚本：直接调用 Trellis，验证 .glb + color_video + normal_video 能下到本地。
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用法（在 backend 目录激活 venv 之后）：
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python scripts/test_trellis.py uploads/0e6fd7e47a524bb9ad18de0b72495e0e.png
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不带参数时会尝试使用 uploads/ 下最新的 png 作为测试图。
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成功标准：
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- 退出码 0
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- 终端打印 glb_path / color_video_path / normal_video_path 均为 /generated/ 开头
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- 实际到 backend/generated/ 目录能看到 3 个文件且 size > 0
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"""
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import asyncio
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import json
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import sys
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from pathlib import Path
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# 允许直接 `python scripts/test_trellis.py` 跑
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_BACKEND_ROOT = Path(__file__).resolve().parent.parent
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if str(_BACKEND_ROOT) not in sys.path:
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sys.path.insert(0, str(_BACKEND_ROOT))
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# .env 加载（复用项目 main.py 的习惯）
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from dotenv import load_dotenv # noqa: E402
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load_dotenv(_BACKEND_ROOT / ".env", override=True)
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from app.services import mesh_generator # noqa: E402
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def _pick_default_image() -> str:
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uploads = _BACKEND_ROOT / "uploads"
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pngs = sorted(uploads.glob("*.png"), key=lambda p: p.stat().st_mtime, reverse=True)
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if not pngs:
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raise FileNotFoundError(f"uploads/ 下没有 png 文件，请显式传入图片路径")
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return str(pngs[0].relative_to(_BACKEND_ROOT)).replace("\\", "/")
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async def main() -> int:
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image_arg = sys.argv[1] if len(sys.argv) > 1 else _pick_default_image()
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# 规范化成 / 开头的 "本地相对 URL" 以便 to_data_uri 识别
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if not image_arg.startswith("/") and not image_arg.startswith("data:") and not image_arg.startswith("http"):
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image_arg = "/" + image_arg.lstrip("./").replace("\\", "/")
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print(f"[test_trellis] 输入图：{image_arg}")
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print("[test_trellis] 开始调用 Trellis（预计 ~30s 起）...")
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result = await mesh_generator.generate_with_trellis(image_arg)
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print("[test_trellis] Trellis 返回：")
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print(json.dumps(result, ensure_ascii=False, indent=2))
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if not result.get("success"):
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print("[test_trellis] 失败：", result.get("error"))
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return 1
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generated_dir = _BACKEND_ROOT / "generated"
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for key in ("glb_path", "color_video_path", "normal_video_path"):
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rel = result.get(key)
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if not rel:
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print(f"[test_trellis] 警告：缺少 {key}")
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continue
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local = generated_dir / Path(rel).name
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size = local.stat().st_size if local.exists() else -1
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print(f"[test_trellis] {key}: {rel} (本地大小: {size} bytes)")
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return 0
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if __name__ == "__main__":
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sys.exit(asyncio.run(main()))
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Block a user