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Eduardo Ottone 51bba0f5e8 Major upgrade: Flexible multi-class detection from 80 COCO classes

- Removed restrictive filtering - now detects 79/80 classes by default
- Added granular control: exclude_person, exclude_animals, exclude_vehicles
- Added min_confidence parameter for quality control
- Created COCO_CLASSES.md reference with all 80 detectable classes
- Better logging showing included/excluded classes and counts
- Can detect: furniture, electronics, food, accessories, sports equipment, etc.
- Default: Only excludes person (79 classes available)
- Much more flexible for diverse object detection scenarios
- Perfect for extracting multiple objects from rich scenes

2025-08-22 13:52:45 -07:00

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COCO Dataset Classes Reference

The YOLOv8 Object Detection Node can detect 80 different object classes from the COCO dataset. Here's the complete list:

🧑‍🤝‍🧑 People

0: person

🚗 Vehicles

1: bicycle
2: car
3: motorcycle
4: airplane
5: bus
6: train
7: truck
8: boat

🚦 Traffic & Outdoor

9: traffic light
10: fire hydrant
11: stop sign
12: parking meter
13: bench

🐾 Animals

14: bird
15: cat
16: dog
17: horse
18: sheep
19: cow
20: elephant
21: bear
22: zebra
23: giraffe

🎒 Accessories & Bags

24: backpack
25: umbrella
26: handbag
27: tie
28: suitcase

⚽ Sports & Recreation

29: frisbee
30: skis
31: snowboard
32: sports ball
33: kite
34: baseball bat
35: baseball glove
36: skateboard
37: surfboard
38: tennis racket

🍽️ Kitchen & Dining

39: bottle
40: wine glass
41: cup
42: fork
43: knife
44: spoon
45: bowl

🍎 Food

46: banana
47: apple
48: sandwich
49: orange
50: broccoli
51: carrot
52: hot dog
53: pizza
54: donut
55: cake

🏠 Furniture

56: chair
57: couch
58: potted plant
59: bed
60: dining table
61: toilet

💻 Electronics

62: tv
63: laptop
64: mouse
65: remote
66: keyboard
67: cell phone

🔌 Appliances

68: microwave
69: oven
70: toaster
71: sink
72: refrigerator

📚 Personal Items

73: book
74: clock
75: vase
76: scissors
77: teddy bear
78: hair drier
79: toothbrush

🎛️ Filter Controls

Current Default Settings:

✅ All 80 classes enabled by default
❌ exclude_person: True (only excludes person)
❌ exclude_animals: False (animals included)
❌ exclude_vehicles: False (vehicles included)

Available Filters:

exclude_person: Skip person detection
exclude_animals: Skip all animals (classes 14-23)
exclude_vehicles: Skip all vehicles (classes 1-8)
min_confidence: Minimum confidence for any detection (0.1-0.9)

Examples:

Detect Everything (79 classes):

exclude_person: True
exclude_animals: False
exclude_vehicles: False
Result: All objects except people

Objects Only (69 classes):

exclude_person: True
exclude_animals: True
exclude_vehicles: False
Result: No people or animals, includes vehicles

Pure Objects (61 classes):

exclude_person: True
exclude_animals: True
exclude_vehicles: True
Result: Only furniture, electronics, food, accessories

Everything (80 classes):

exclude_person: False
exclude_animals: False
exclude_vehicles: False
Result: Detect absolutely everything including people

💡 Pro Tips:

Lower confidence (0.1-0.3) = more detections, some false positives
Higher confidence (0.5-0.8) = fewer but more accurate detections
Check console output to see which classes are being excluded
Use padding to get more context around detected objects
Adjust max_size based on your output needs (128-1024px)

Perfect for detecting multiple objects from a rich set of 80 different classes! 🎯

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