"""未知菜品待学习：持久化存储与管理。""" import os import json import shutil import threading import datetime import numpy as np # 新未知图与库内已有 pending 特征相似度 ≥ 此值则不入待学习库 PENDING_DEDUP_SIMILARITY = 0.90 class PendingLearningStore: STATUS_PENDING = "pending" STATUS_LEARNED = "learned" STATUS_IGNORED = "ignored" def __init__(self, base_dir): self.base_dir = base_dir self.pending_dir = os.path.join(base_dir, "pending_images") self.data_file = os.path.join(base_dir, "pending_learning.json") self.lock = threading.Lock() self._items = [] self._next_id = 1 os.makedirs(self.pending_dir, exist_ok=True) self._load() def _load(self): if not os.path.exists(self.data_file): return try: with open(self.data_file, "r", encoding="utf-8") as f: data = json.load(f) self._items = data.get("items", []) self._next_id = data.get("next_id", 1) for item in self._items: if item.get("id") is None: continue self._next_id = max(self._next_id, item["id"] + 1) except Exception as e: print(f"加载待学习库失败: {e}") self._items = [] self._next_id = 1 def _save(self): try: with open(self.data_file, "w", encoding="utf-8") as f: json.dump({"next_id": self._next_id, "items": self._items}, f, ensure_ascii=False, indent=2) except Exception as e: print(f"保存待学习库失败: {e}") def _find_pending_by_path(self, image_path): norm = os.path.normcase(os.path.abspath(image_path)) for item in self._items: if item.get("status") != self.STATUS_PENDING: continue stored = item.get("source_path") or item.get("image_path") if stored and os.path.normcase(os.path.abspath(stored)) == norm: return item return None def _is_similar_pending(self, feature, threshold=PENDING_DEDUP_SIMILARITY): """若与任一 pending 特征相似度 ≥ threshold，返回 (item, sim)；否则 (None, 0)。""" feat = np.asarray(feature, dtype=np.float32).reshape(-1) best_item = None best_sim = 0.0 for item in self._items: if item.get("status") != self.STATUS_PENDING: continue stored = item.get("feature") if stored is None: continue other = np.asarray(stored, dtype=np.float32).reshape(-1) if other.shape != feat.shape: continue sim = float(np.dot(feat, other)) if sim >= threshold and sim >= best_sim: best_sim = sim best_item = item return best_item, best_sim def add(self, image_path, feature, suggested_category=None, score=None, reason=None): if not image_path or not os.path.exists(image_path): return None feature = np.asarray(feature, dtype=np.float32) new_sug = (suggested_category or "").strip() with self.lock: existing = self._find_pending_by_path(image_path) if existing: old_sug = (existing.get("suggested_category") or "").strip() # 同一路径但建议菜名已变：视为新的未知菜，不覆盖旧记录 if old_sug and new_sug and old_sug != new_sug: existing = None else: existing["suggested_category"] = suggested_category or existing.get("suggested_category") existing["score"] = score if score is not None else existing.get("score") existing["feature"] = feature.tolist() existing["capture_time"] = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S") if reason: existing["reason"] = reason # 刷新图片副本，避免源文件被覆盖后内容过期 try: dest = existing.get("image_path") if dest and dest.startswith(self.pending_dir): shutil.copy2(image_path, dest) except Exception: pass self._save() return existing["id"] # 与库内已有图相似度 ≥ 0.90 → 不加入待学习库 similar, sim = self._is_similar_pending(feature, PENDING_DEDUP_SIMILARITY) if similar is not None: print( f"[pending] skip add (sim={sim:.3f}≥{PENDING_DEDUP_SIMILARITY:.2f} " f"vs #{similar.get('id')})" ) return None pending_id = self._next_id self._next_id += 1 stamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S") ext = os.path.splitext(image_path)[1] or ".jpeg" dest_name = f"pending_{stamp}_{pending_id}{ext}" dest_path = os.path.join(self.pending_dir, dest_name) try: shutil.copy2(image_path, dest_path) except Exception as e: print(f"复制待学习图片失败: {e}") dest_path = image_path item = { "id": pending_id, "image_path": dest_path, "source_path": image_path, "feature": feature.tolist(), "suggested_category": suggested_category, "score": float(score) if score is not None else None, "status": self.STATUS_PENDING, "capture_time": datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"), "learned_category": None, "reason": reason, } self._items.append(item) self._save() return pending_id def get(self, pending_id): for item in self._items: if item.get("id") == pending_id: return item.copy() return None def get_list(self, status=STATUS_PENDING): rows = [] for item in self._items: if item.get("status") != status: continue row = item.copy() feat = row.get("feature") if feat is not None: row["feature"] = np.array(feat, dtype=np.float32) rows.append(row) rows.sort(key=lambda x: x.get("capture_time", ""), reverse=True) return rows def count(self, status=STATUS_PENDING): return sum(1 for item in self._items if item.get("status") == status) def mark_learned(self, pending_id, category): with self.lock: for item in self._items: if item.get("id") == pending_id: item["status"] = self.STATUS_LEARNED item["learned_category"] = category item["learn_time"] = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S") self._save() return True return False def update_suggestion(self, pending_id, suggested_category=None, score=None): """刷新仍待处理项的建议菜名 / 相似度（不改 status）。""" with self.lock: for item in self._items: if item.get("id") != pending_id: continue if item.get("status") != self.STATUS_PENDING: return False if suggested_category is not None: item["suggested_category"] = suggested_category if score is not None: item["score"] = float(score) self._save() return True return False def _unlink_image(self, item): """删除 pending_images 下的本地图（仅限本库目录，防误删）。""" path = item.get("image_path") if not path: return try: abs_path = os.path.abspath(path) if not abs_path.startswith(os.path.abspath(self.pending_dir)): return if os.path.exists(abs_path): os.remove(abs_path) except Exception as e: print(f"删除待学习图片失败: {e}") def mark_ignored(self, pending_id, remove_image=True): """忽略一条：删除图片并从库中移除（不再只改 status 留尸）。""" with self.lock: for idx, item in enumerate(self._items): if item.get("id") != pending_id: continue if remove_image: self._unlink_image(item) del self._items[idx] self._save() return True return False def ignore_all_pending(self, remove_image=True): """忽略全部 pending：删图 + 从库移除，只写盘一次。返回删除条数。""" with self.lock: kept = [] removed = 0 for item in self._items: if item.get("status") == self.STATUS_PENDING: if remove_image: self._unlink_image(item) removed += 1 else: kept.append(item) if removed: self._items = kept self._save() return removed def delete(self, pending_id, remove_image=True): with self.lock: for idx, item in enumerate(self._items): if item.get("id") != pending_id: continue if remove_image: self._unlink_image(item) del self._items[idx] self._save() return True return False def clear_all(self): with self.lock: for item in self._items: self._unlink_image(item) self._items = [] self._next_id = 1 self._save()