3218485270
b7f429db89
1) 模板导出：识别「基码表-胸围」填 sku.bust（多个胸围列都填）；申报价格模糊匹配多列统一按加价后价格填写；详情图文不再拼接 img_url_2；SPU 款式来源统一填「现货款」；商品产地国家简称映射（沙特→沙特阿拉伯） 2) 模特性别分组：model_features 按男女分组，按模板类目含男/女固定取对应性别模特（含 Pinterest 模式 pipeline） 3) 三合一提示词：去掉 DESIGN CONTENT 四要素描述（设计已由设计稿提供） 4) 生图尺寸：全部改为读 config 不再硬编码（设计图 compose.design_size / 合成图 compose.size / 种草图 seed_shot.size）
151 lines
7.3 KiB
Python
151 lines
7.3 KiB
Python
"""种草图（Seed Shot）生成。
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- 模板：configs/seed_shot_templates.yaml（可自定义，占位符 [商品名称]/[材质]/[模特特征]）
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- 模特特征：configs/model_features.yaml（可自定义，随机取一条）
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- 生成：以 product 合成图（图1）为参考，img2img 生成 N 张种草图（保留衣服外观、换场景/模特）
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- 占位替换：[商品名称]→cn_title（缺省回退 topic）；[材质]→SPU.material；[模特特征]→随机
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"""
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import random
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from pathlib import Path
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from typing import Any, Dict, List, Optional
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import yaml
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from graph.paths import project_root
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def _load_yaml(rel: str) -> Dict[str, Any]:
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for root in (project_root(),):
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p = root / rel
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if p.exists():
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try:
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return yaml.safe_load(p.read_text(encoding="utf-8")) or {}
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except Exception as e: # noqa: BLE001
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print(f"[seed_shot] 读取 {rel} 失败: {e}")
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return {}
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def load_templates() -> List[Dict[str, str]]:
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"""种草图提示词模板列表（无配置时给内置兜底）。"""
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data = _load_yaml("configs/seed_shot_templates.yaml")
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tpls = data.get("seed_shot_templates") or []
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if not tpls:
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tpls = [{
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"name": "default",
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"prompt": (
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"【最高优先级约束】请严格保留参考图1中模特所穿衣服的完整外观，包括其原有的颜色、"
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"印花图案、版型款式、材质纹理与缝线细节，绝对禁止对衣服本身进行任何形式的修改、"
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"重新设计、变色或改变图案。仅提取这件[商品名称]，将其穿在一位[模特特征]的身上。"
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"全身动态抓拍构图，行走在阳光斑驳的城市林荫道上，微微低头微笑，凸显[材质]的透气与百搭。"
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"徕卡Q2摄影质感，高对比度色彩，35mm镜头，f/1.7大光圈，8k分辨率。"
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),
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}]
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return [{"name": str(t.get("name", "default")), "prompt": str(t.get("prompt", ""))}
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for t in tpls if t.get("prompt")]
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def load_model_features(gender: Optional[str] = None) -> List[str]:
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"""模特特征列表（无配置时给内置兜底）。
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gender: "male"/"female" 时只返回对应性别；None/其他 返回全部（指定性别组为空时回退全部）。"""
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data = _load_yaml("configs/model_features.yaml")
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mf = data.get("model_features") or []
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feats: List[str] = []
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if isinstance(mf, dict):
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if gender and gender in mf:
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feats = [str(f) for f in mf[gender] if str(f).strip()]
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if not feats:
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feats = [str(f) for g in mf.values() for f in g if str(f).strip()]
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else:
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feats = [str(f) for f in mf if str(f).strip()]
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if not feats:
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feats = ["20岁清新少女，素颜通透感", "25岁都市职场女性，干练气质"]
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return feats
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def read_template_category(template_path: str) -> str:
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"""读取模版「类目」表头对应的值（如 服装、鞋靴和珠宝饰品>男士时尚>男装>男装上衣、T恤、衬衫>男装T恤）。
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遍历所有 sheet（类目表头可能在「模版」等 sheet），找到即返回其下一行同列值。"""
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try:
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import openpyxl
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wb = openpyxl.load_workbook(template_path, data_only=True, read_only=True)
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try:
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for ws in wb.worksheets:
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rows = [r for r in ws.iter_rows(min_row=1, max_row=5, values_only=True)]
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for ri, row in enumerate(rows):
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for ci, v in enumerate(row):
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if v is not None and str(v).strip() == "类目":
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if ri + 1 < len(rows):
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val = rows[ri + 1][ci]
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return str(val or "").strip()
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finally:
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wb.close()
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except Exception as e: # noqa: BLE001
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print(f"[seed_shot] 读取模版类目失败: {e}")
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return ""
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def gender_from_category(category: str) -> Optional[str]:
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"""类目含「男」→ male；含「女」→ female；都不含 → None（全部随机）。"""
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if "男" in category:
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return "male"
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if "女" in category:
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return "female"
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return None
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def load_style_features() -> List[str]:
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"""服装风格列表（style_features.yaml，随机取一条替换 [服装风格]；无配置时内置兜底）。"""
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data = _load_yaml("configs/style_features.yaml")
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feats = [str(f) for f in (data.get("style_features") or []) if str(f).strip()]
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if not feats:
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feats = ["极简基础款风格，干净纯粹，无过多繁复装饰",
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"日系City Boy/Girl风，微宽松版型，注重舒适度与层次感"]
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return feats
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def render_prompt(template_prompt: str, cn_title: str, material: str, model_feature: str,
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style_feature: str = "") -> str:
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"""占位替换：[商品名称]/[材质]/[模特特征]/[服装风格]"""
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out = template_prompt.replace("[商品名称]", (cn_title or "").strip() or "这件衣服")
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out = out.replace("[材质]", (material or "").strip() or "面料")
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out = out.replace("[模特特征]", (model_feature or "").strip() or "模特")
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out = out.replace("[服装风格]", (style_feature or "").strip() or "日常休闲风")
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return out
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def generate_seed_shots(image_backend, base_image: str, cn_title: str, material: str,
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count: int, out_dir: str, negative: str = "",
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size: str = "1536x2048", prefix: str = "",
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gender: Optional[str] = None) -> List[str]:
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"""生成 count 张种草图（img2img，图1=合成图）。返回产物路径列表。
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size: 种草图统一 1536x2048（与合成图一致）。
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prefix: 货号前缀（对应产品货号，命名 {prefix}_{随机4位}.png，不覆盖旧文件）。
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gender: "male"/"female" 时只从对应性别模特特征随机；None 全部随机。
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占位符 [商品名称]/[材质]/[模特特征]/[服装风格] 均随机组合（模板/模特/服装风格各随机取一条）。"""
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templates = load_templates()
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features = load_model_features(gender=gender)
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style_features = load_style_features()
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out = Path(out_dir)
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out.mkdir(parents=True, exist_ok=True)
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paths: List[str] = []
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for i in range(count):
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tpl = random.choice(templates)
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feat = random.choice(features)
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style_feat = random.choice(style_features)
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prompt = render_prompt(tpl["prompt"], cn_title, material, feat, style_feat)
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# 命名：{货号}_{随机4位}.png（按货号命名，随机4位避免自增序号/覆盖）
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while True:
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rand4 = f"{random.randint(0, 9999):04d}"
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out_path = str(out / f"{prefix}_{rand4}.png" if prefix
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else out / f"seed_{rand4}.png")
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if not Path(out_path).exists():
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break
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try:
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image_backend.print(prompt, base_image, out_path, negative, size=size)
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paths.append(out_path)
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print(f"[seed_shot] 已生成种草图 {i + 1}/{count}: {out_path}"
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f"（模板={tpl['name']}，模特={feat[:14]}…，风格={style_feat[:14]}…）")
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except Exception as e: # noqa: BLE001
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print(f"[seed_shot] 种草图 {i + 1} 生成失败: {e}")
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return paths
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