| """ |
| Object Mapper — Synonym normalization for bridging YOLO labels |
| and natural-language user commands. |
| |
| YOLO may detect "cup" while the user says "mug". This module provides |
| a mapping layer and fuzzy-match helper to reconcile the two vocabularies. |
| """ |
|
|
| import logging |
| from difflib import SequenceMatcher |
|
|
| logger = logging.getLogger(__name__) |
|
|
| |
| |
| |
| SYNONYM_MAP: dict[str, str] = { |
| |
| |
| |
| |
|
|
| |
| "human": "person", |
| "worker": "person", |
| "operator": "person", |
| "man": "person", |
| "woman": "person", |
| "people": "person", |
| "employee": "person", |
| "technician": "person", |
|
|
| |
| "bike": "bicycle", |
| "cycle": "bicycle", |
|
|
| |
| "automobile": "car", |
| "vehicle": "car", |
| "sedan": "car", |
|
|
| |
| "motorbike": "motorcycle", |
| "scooter": "motorcycle", |
|
|
| |
| "van": "truck", |
| "lorry": "truck", |
| "pickup": "truck", |
|
|
| |
| "ship": "boat", |
| "vessel": "boat", |
| "canoe": "boat", |
|
|
| |
| "signal": "traffic light", |
| "stoplight": "traffic light", |
|
|
| |
| "bag": "backpack", |
| "rucksack": "backpack", |
| "knapsack": "backpack", |
|
|
| |
| "parasol": "umbrella", |
|
|
| |
| "purse": "handbag", |
| "clutch": "handbag", |
|
|
| |
| "briefcase": "suitcase", |
| "toolbox": "suitcase", |
| "case": "suitcase", |
| "luggage": "suitcase", |
| "tool box": "suitcase", |
|
|
| |
| "water bottle": "bottle", |
| "flask": "bottle", |
| "jug": "bottle", |
| "canteen": "bottle", |
| "container": "bottle", |
|
|
| |
| "goblet": "wine glass", |
| "chalice": "wine glass", |
| "glass": "wine glass", |
|
|
| |
| "mug": "cup", |
| "teacup": "cup", |
| "coffee cup": "cup", |
| "tumbler": "cup", |
|
|
| |
| "prong": "fork", |
|
|
| |
| "blade": "knife", |
| "wrench": "knife", |
| "spanner": "knife", |
| "screwdriver": "knife", |
| "tool": "knife", |
|
|
| |
| "ladle": "spoon", |
| "scoop": "spoon", |
|
|
| |
| "tray": "bowl", |
| "dish": "bowl", |
| "plate": "bowl", |
| "bin": "bowl", |
| "basket": "bowl", |
|
|
| |
| "fruit": "apple", |
|
|
| |
| "sub": "sandwich", |
| "burger": "sandwich", |
| "wrap": "sandwich", |
|
|
| |
| "pie": "pizza", |
|
|
| |
| "pastry": "cake", |
| "dessert": "cake", |
|
|
| |
| "seat": "chair", |
| "stool": "chair", |
| "office chair": "chair", |
|
|
| |
| "sofa": "couch", |
| "loveseat": "couch", |
| "settee": "couch", |
|
|
| |
| "mattress": "bed", |
| "cot": "bed", |
|
|
| |
| "desk": "dining table", |
| "table": "dining table", |
| "workbench": "dining table", |
| "bench": "dining table", |
| "counter": "dining table", |
|
|
| |
| "monitor": "tv", |
| "screen": "tv", |
| "display": "tv", |
| "television": "tv", |
|
|
| |
| "notebook": "laptop", |
| "computer": "laptop", |
| "macbook": "laptop", |
|
|
| |
| "trackpad": "mouse", |
|
|
| |
| "controller": "remote", |
| "remote control": "remote", |
|
|
| |
| "keypad": "keyboard", |
|
|
| |
| "mobile": "cell phone", |
| "phone": "cell phone", |
| "smartphone": "cell phone", |
| "iphone": "cell phone", |
| "handset": "cell phone", |
| "scanner": "cell phone", |
|
|
| |
| "microwave oven": "microwave", |
|
|
| |
| "stove": "oven", |
| "furnace": "oven", |
|
|
| |
| "fridge": "refrigerator", |
| "cooler": "refrigerator", |
| "freezer": "refrigerator", |
|
|
| |
| "notebook paper": "book", |
| "manual": "book", |
| "textbook": "book", |
| "binder": "book", |
|
|
| |
| "watch": "clock", |
| "timer": "clock", |
|
|
| |
| "pot": "vase", |
| "planter": "vase", |
| "jar": "vase", |
|
|
| |
| "cutter": "scissors", |
| "shears": "scissors", |
| "clipper": "scissors", |
| "pliers": "scissors", |
| "wire cutter": "scissors", |
|
|
| |
| "stuffed animal": "teddy bear", |
| "plush": "teddy bear", |
| "toy": "teddy bear", |
|
|
| |
| "plant": "potted plant", |
| "houseplant": "potted plant", |
| "flower": "potted plant", |
|
|
| |
| |
| |
| "damaged part": "knife", |
| "defective part": "knife", |
| "component": "knife", |
| "metal part": "knife", |
| "part": "knife", |
| "piece": "knife", |
|
|
| "red bin": "bowl", |
| "blue bin": "bowl", |
| "sorting bin": "bowl", |
| "reject bin": "bowl", |
| "accept bin": "bowl", |
|
|
| "circuit board": "keyboard", |
| "pcb": "keyboard", |
| "board": "keyboard", |
|
|
| "hard hat": "sports ball", |
| "helmet": "sports ball", |
| "safety hat": "sports ball", |
|
|
| "gloves": "backpack", |
| "safety gloves": "backpack", |
|
|
| "pallet": "suitcase", |
| "crate": "suitcase", |
| "carton": "suitcase", |
| "box": "suitcase", |
|
|
| "hand truck": "bicycle", |
| "dolly": "bicycle", |
| "cart": "bicycle", |
|
|
| "forklift": "truck", |
|
|
| "clipboard": "book", |
| "blueprint": "book", |
|
|
| "stethoscope": "tie", |
| "syringe": "toothbrush", |
| "safety goggles": "wine glass", |
| "goggles": "wine glass", |
|
|
| "oil can": "bottle", |
| "spray can": "bottle", |
| "battery": "suitcase", |
| "car battery": "suitcase", |
|
|
| "multimeter": "cell phone", |
| "meter": "cell phone", |
| "soldering iron": "knife", |
| "magnifying lamp": "clock", |
| } |
|
|
|
|
|
|
| def normalize_label(label: str) -> str: |
| """ |
| Normalize a label using the synonym map. |
| |
| Args: |
| label: Raw label string (from user command or YOLO). |
| |
| Returns: |
| The canonical label if a synonym exists, otherwise the |
| original label lowercased and stripped. |
| """ |
| cleaned = label.strip().lower() |
| return SYNONYM_MAP.get(cleaned, cleaned) |
|
|
|
|
| def _similarity(a: str, b: str) -> float: |
| """Return a 0-1 similarity score between two strings.""" |
| return SequenceMatcher(None, a.lower(), b.lower()).ratio() |
|
|
|
|
| def find_best_match( |
| query: str, |
| detected_labels: list[str], |
| threshold: float = 0.4, |
| ) -> str | None: |
| """ |
| Find the best matching detected label for a user query term. |
| |
| Strategy: |
| 1. Exact match after normalization. |
| 2. Substring containment check. |
| 3. Fuzzy similarity above *threshold*. |
| |
| Args: |
| query: The term from the user command (e.g. "mug"). |
| detected_labels: Labels returned by the vision detector. |
| threshold: Minimum similarity score for fuzzy matching. |
| |
| Returns: |
| The best matching label, or ``None`` if no match is found. |
| """ |
| normalized_query = normalize_label(query) |
| normalized_detected = {normalize_label(lbl): lbl for lbl in detected_labels} |
|
|
| |
| if normalized_query in normalized_detected: |
| logger.info( |
| "Exact match: '%s' → '%s'", |
| query, |
| normalized_detected[normalized_query], |
| ) |
| return normalized_detected[normalized_query] |
|
|
| |
| for norm_lbl, orig_lbl in normalized_detected.items(): |
| if normalized_query in norm_lbl or norm_lbl in normalized_query: |
| logger.info( |
| "Substring match: '%s' → '%s'", query, orig_lbl |
| ) |
| return orig_lbl |
|
|
| |
| best_score = 0.0 |
| best_label: str | None = None |
| for norm_lbl, orig_lbl in normalized_detected.items(): |
| score = _similarity(normalized_query, norm_lbl) |
| if score > best_score: |
| best_score = score |
| best_label = orig_lbl |
|
|
| if best_label and best_score >= threshold: |
| logger.info( |
| "Fuzzy match: '%s' → '%s' (score=%.2f)", |
| query, |
| best_label, |
| best_score, |
| ) |
| return best_label |
|
|
| logger.warning("No match found for query '%s'", query) |
| return None |
|
|
