# ======================================================================= # Objects365 V2 – 365 classes (id 1~365) · MMYOLO Helper Module # 경로: /data/ltb/mmyolo/objects365_classes.py # 작성: 2025-06-27 # ======================================================================= from __future__ import annotations import random import numpy as np # ----------------------------------------------------------------------- # 1) 클래스 목록 (id 순서, 길이 = 365) # ----------------------------------------------------------------------- OBJECTS365_CLASSES: tuple[str, ...] = ( # 1 – 20 "Person", "Sneakers", "Chair", "Other Shoes", "Hat", "Car", "Lamp", "Glasses", "Bottle", "Desk", "Cup", "Street Lights", "Cabinet/Shelf", "Handbag/Satchel", "Bracelet", "Plate", "Picture/Frame", "Helmet", "Book", "Gloves", # 21 – 40 "Storage box", "Boat", "Leather Shoes", "Flower", "Bench", "Potted Plant", "Bowl/Basin", "Flag", "Pillow", "Boots", "Vase", "Microphone", "Necklace", "Ring", "SUV", "Wine Glass", "Belt", "Moniter/TV", "Backpack", "Umbrella", # 41 – 60 "Traffic Light", "Speaker", "Watch", "Tie", "Trash bin Can", "Slippers", "Bicycle", "Stool", "Barrel/Bucket", "Van", "Couch", "Sandals", "Basket", "Drum", "Pen/Pencil", "Bus", "Wild Bird", "High Heels", "Motorcycle", "Guitar", # 61 – 80 "Carpet", "Cell Phone", "Bread", "Camera", "Canned", "Truck", "Traffic cone", "Cymbal", "Lifesaver", "Towel", "Stuffed Toy", "Candle", "Sailboat", "Laptop", "Awning", "Bed", "Faucet", "Tent", "Horse", "Mirror", # 81 – 100 "Power outlet", "Sink", "Apple", "Air Conditioner", "Knife", "Hockey Stick", "Paddle", "Pickup Truck", "Fork", "Traffic Sign", "Ballon", "Tripod", "Dog", "Spoon", "Clock", "Pot", "Cow", "Cake", "Dinning Table", "Sheep", # 101 – 120 "Hanger", "Blackboard/Whiteboard", "Napkin", "Other Fish", "Orange/Tangerine", "Toiletry", "Keyboard", "Tomato", "Lantern", "Machinery Vehicle", "Fan", "Green Vegetables", "Banana", "Baseball Glove", "Airplane", "Mouse", "Train", "Pumpkin", "Soccer", "Skiboard", # 121 – 140 "Luggage", "Nightstand", "Tea pot", "Telephone", "Trolley", "Head Phone", "Sports Car", "Stop Sign", "Dessert", "Scooter", "Stroller", "Crane", "Remote", "Refrigerator", "Oven", "Lemon", "Duck", "Baseball Bat", "Surveillance Camera", "Cat", # 141 – 160 "Jug", "Broccoli", "Piano", "Pizza", "Elephant", "Skateboard", "Surfboard", "Gun", "Skating and Skiing shoes", "Gas stove", "Donut", "Bow Tie", "Carrot", "Toilet", "Kite", "Strawberry", "Other Balls", "Shovel", "Pepper", "Computer Box", # 161 – 180 "Toilet Paper", "Cleaning Products", "Chopsticks", "Microwave", "Pigeon", "Baseball", "Cutting/Chopping Board", "Coffee Table", "Side Table", "Scissors", "Marker", "Pie", "Ladder", "Snowboard", "Cookies", "Radiator", "Fire Hydrant", "Basketball", "Zebra", "Grape", # 181 – 200 "Giraffe", "Potato", "Sausage", "Tricycle", "Violin", "Egg", "Fire Extinguisher", "Candy", "Fire Truck", "Billards", "Converter", "Bathtub", "Wheelchair", "Golf Club", "Briefcase", "Cucumber", "Cigar/Cigarette", "Paint Brush", "Pear", "Heavy Truck", # 201 – 220 "Hamburger", "Extractor", "Extention Cord", "Tong", "Tennis Racket", "Folder", "American Football", "Earphone", "Mask", "Kettle", "Tennis", "Ship", "Swing", "Coffee Machine", "Slide", "Carriage", "Onion", "Green beans", "Projector", "Frisbee", # 221 – 240 "Washing Machine/Drying Machine", "Chicken", "Printer", "Watermelon", "Saxophone", "Tissue", "Toothbrush", "Ice cream", "Hotair Ballon", "Cello", "French Fries", "Scale", "Trophy", "Cabbage", "Hot dog", "Blender", "Peach", "Rice", "Wallet/Purse", "Volleyball", # 241 – 260 "Deer", "Goose", "Tape", "Tablet", "Cosmetics", "Trumpet", "Pineapple", "Golf Ball", "Ambulance", "Parking meter", "Mango", "Key", "Hurdle", "Fishing Rod", "Medal", "Flute", "Brush", "Penguin", "Megaphone", "Corn", # 261 – 280 "Lettuce", "Garlic", "Swan", "Helicopter", "Green Onion", "Sandwich", "Nuts", "Speed Limit Sign", "Induction Cooker", "Broom", "Trombone", "Plum", "Rickshaw", "Goldfish", "Kiwi Fruit", "Router/Modem", "Poker Card", "Toaster", "Shrimp", "Sushi", # 281 – 300 "Cheese", "Notepaper", "Cherry", "Pliers", "CD", "Pasta", "Hammer", "Cue", "Avocado", "Hamimelon", "Flask", "Mushroom", "Screwdriver", "Soap", "Recorder", "Bear", "Eggplant", "Board Eraser", "Coconut", "Tape Measure/Ruler", # 301 – 320 "Pig", "Showerhead", "Globe", "Chips", "Steak", "Crosswalk Sign", "Stapler", "Camel", "Formula 1", "Pomegranate", "Dishwasher", "Crab", "Hoverboard", "Meat Ball", "Rice Cooker", "Tuba", "Calculator", "Papaya", "Antelope", "Parrot", # 321 – 340 "Seal", "Butterfly", "Dumbbell", "Donkey", "Lion", "Urinal", "Dolphin", "Electric Drill", "Hair Dryer", "Egg Tart", "Jellyfish", "Treadmill", "Lighter", "Grapefruit", "Game Board", "Mop", "Radish", "Baozi", "Target", "French", # 341 – 360 "Spring Rolls", "Monkey", "Rabbit", "Pencil Case", "Yak", "Red Cabbage", "Binoculars", "Asparagus", "Barbell", "Scallop", "Noodles", "Comb", "Dumpling", "Oyster", "Table Tennis Paddle", "Cosmetics Brush/Eyeliner Pencil", "Chainsaw", "Eraser", "Lobster", "Durian", # 361 – 365 "Okra", "Lipstick", "Cosmetics Mirror", "Curling", "Table Tennis" ) # ----------------------------------------------------------------------- # 2) 팔레트 (고정 난수 – 시각화 용도) # ----------------------------------------------------------------------- random.seed(42) PALETTE: list[tuple[int, int, int]] = [ tuple(np.random.randint(0, 255, 3).tolist()) for _ in range(len(OBJECTS365_CLASSES)) ] # ----------------------------------------------------------------------- # 3) 보조 사전 & METAINFO # ----------------------------------------------------------------------- ID2NAME = {i + 1: n for i, n in enumerate(OBJECTS365_CLASSES)} # COCO id는 1-based NAME2ID = {v: k for k, v in ID2NAME.items()} METAINFO = dict(classes=OBJECTS365_CLASSES, palette=PALETTE) # --------------------------- 디버그 실행 ------------------------------- if __name__ == "__main__": print(f"총 클래스 : {len(OBJECTS365_CLASSES)}") print(f"예시 1~5 : {OBJECTS365_CLASSES[:5]}") print(f"팔레트 길이: {len(PALETTE)}")