"""SPU/SKU 数据库查询 + 底图/模特图资源查找(产品图生成流水线的数据层)。 数据关系(已核实 spu_sku.db): - SPU.code = 款号(如 DG004) - SKU.code = "款号-颜色编码"(如 DG004-BL01),SKU.color = 中文色名(黑/灰/...) - basemap 目录 = basemap/<款号>//xxx.jpg - material_library/<品类>/ 存放模特图 - SKU.img_url_2~5 = CDN 图 URL(底图/细节/模特图,仅作参考字段) """ import sqlite3 from pathlib import Path from typing import Any, Dict, List, Optional from PIL import Image # 支持的图片格式:模特图/底图均按此识别(png/jpg 等常见格式全覆盖;AVIF/GIF/TIFF 亦支持) IMG_EXTS = {".jpg", ".jpeg", ".png", ".webp", ".bmp", ".avif", ".gif", ".tiff", ".tif"} def _connect(db_path) -> sqlite3.Connection: conn = sqlite3.connect(str(db_path)) conn.row_factory = sqlite3.Row return conn def list_spus(db_path, country: Optional[str] = None) -> List[Dict[str, Any]]: """全部 SPU(可选按国家过滤)。""" conn = _connect(db_path) sql = "SELECT id, code, style, material, printing_type, target_audience, pattern, country, mark FROM SPU" params: list = [] if country: sql += " WHERE country = ?" params.append(country) sql += " ORDER BY code" rows = conn.execute(sql, params).fetchall() conn.close() return [dict(r) for r in rows] def list_colors(db_path, spu_code: str) -> List[Dict[str, Any]]: """款号 → 颜色列表(SKU.code 去重,附中文色名、CDN 底图 URL、最低价)。""" conn = _connect(db_path) rows = conn.execute( """SELECT s.code AS sku_code, s.color, s.img_url_2 AS img_url, MIN(s.price) AS price FROM SKU s JOIN SPU p ON s.spu_id = p.id WHERE p.code = ? GROUP BY s.code, s.color ORDER BY s.code""", (spu_code,)).fetchall() conn.close() return [dict(r) for r in rows] def _norm_name(s: str) -> str: """去空格(半角+全角)+ 小写,用于 SKU code 与文件夹名比较。""" return str(s or "").replace(" ", "").replace(" ", "").strip().lower() def find_basemap(basemap_root, spu_code: str, sku_code: str) -> Optional[Path]: """basemap/<款号>// 下第一张图片;无返回 None。 SKU code 与文件夹名比较时两边都去空格(兼容 db code 或文件夹名带空格)。 """ root = Path(basemap_root) / spu_code if not root.exists(): return None target = _norm_name(sku_code) if not target: return None d = root / sku_code if not (d.exists() and d.is_dir()): d = None for cand in sorted(root.iterdir()): if cand.is_dir() and _norm_name(cand.name) == target: d = cand break if d is None: return None for f in sorted(d.iterdir()): if f.is_file() and f.suffix.lower() in IMG_EXTS: return f return None def list_model_images(material_root, category: str = "T-shirt") -> List[Path]: """material_library/<品类>/ 下所有图片;无返回空列表。""" d = Path(material_root) / category if not d.exists(): return [] return [f for f in sorted(d.iterdir()) if f.is_file() and f.suffix.lower() in IMG_EXTS] def find_first_model_folder(material_root, preferred: Optional[str] = None): """material_library 下「第一个有图片的子目录」及其图片列表。 - preferred(如 config 的 model_category)优先:该目录有图就直接用; - 否则按子目录名排序,取第一个有图的目录; - 全空返回 (None, [])。 返回 (dir_name or None, images: List[Path])。 """ root = Path(material_root) if not root.exists(): return None, [] candidates = [] if preferred: d = root / preferred if d.is_dir(): candidates.append(d) candidates += [d for d in sorted(root.iterdir()) if d.is_dir()] seen = set() for d in candidates: if d in seen: continue seen.add(d) imgs = [f for f in sorted(d.iterdir()) if f.is_file() and f.suffix.lower() in IMG_EXTS] if imgs: return d.name, imgs return None, [] def image_ratio_ok(path, target_ratio: float = 3 / 4, tolerance: float = 0.06) -> bool: """图片宽高比是否接近目标比例(默认 3:4,相对容差 6%)。 相对容差:接受 [target*(1-tol), target*(1+tol)],对 3:4 即 0.705~0.795。 无法解析的图片(损坏/非标准)按不通过处理,避免坏图被当模特。 """ try: with Image.open(path) as im: w, h = im.size if w <= 0 or h <= 0: return False ratio = w / h lo = target_ratio * (1 - tolerance) hi = target_ratio * (1 + tolerance) return lo <= ratio <= hi except Exception: # noqa: BLE001 return False def _dir_images(d: Path, ratio: float, tolerance: float) -> List[Path]: """返回目录内满足比例过滤(默认3:4)的图片列表;目录不存在/无图片返回空。""" if d is None or not d.is_dir(): return [] imgs = [f for f in sorted(d.iterdir()) if f.is_file() and f.suffix.lower() in IMG_EXTS] if not imgs: return [] ok = [f for f in imgs if image_ratio_ok(f, ratio, tolerance)] if len(ok) < len(imgs): print(f"[product] 目录 {d.name}/ 过滤非 {int(ratio * 100)}:{int(ratio * 100) + 1} 比例:" f"{len(imgs)} → {len(ok)} 张") return ok def build_mark_sources(material_root, mark_dirs: Optional[Dict] = None, category: str = "T-shirt", mark: str = "1", ratio: float = 3 / 4, tolerance: float = 0.06) -> Dict[str, Any]: """按可配置的 mark→图源映射,返回指定 mark 的图源选择信息。 图源 = {"model": [Path...], "flat": [Path...]}(模特图 / 平铺图,各带英文键)。 从 config.product.mark_dirs 读 mark 对应的两个子目录名(model_dir/flat_dir), 在 material_library 下解析 → 过滤 3:4 → 返回「有图的文件夹」图片列表。 mark 未配置时回退 mark_dirs["1"];完全无配置则回退 category 默认目录。 返回结构:{"model": [imgs], "flat": [imgs]}。 """ root = Path(material_root) result: Dict[str, Any] = {"model": [], "flat": []} if not root.exists(): return result mcfg = mark_dirs or {} cfg = mcfg.get(str(mark)) or mcfg.get("1") or {} # 优先按 mark,其次回退默认 "1" model_name = str(cfg.get("model_dir") or "").strip() flat_name = str(cfg.get("flat_dir") or "").strip() if model_name: result["model"] = _dir_images(root / model_name, ratio, tolerance) if flat_name: result["flat"] = _dir_images(root / flat_name, ratio, tolerance) # 回退:某类目录未配置时,使用 category 默认目录补充模特图 if not result["model"] and not result["flat"]: d = root / category if d.is_dir(): result["model"] = _dir_images(d, ratio, tolerance) if not result["model"] and not result["flat"]: for sub in sorted(root.iterdir()): if not sub.is_dir(): continue imgs = _dir_images(sub, ratio, tolerance) if imgs: result["model"] = imgs break return result def first_available_sku(db_path, basemap_root, spu_code: str) -> Optional[str]: """返回该款号下第一个「本地有底图」的 SKU.code;无则 None。""" for c in list_colors(db_path, spu_code): if find_basemap(basemap_root, spu_code, c["sku_code"]) is not None: return c["sku_code"] return None