The COCO pretrained models only have 80 classes. But `ultralytics` also provides pretrained models on the OIv7 image dataset that has 600 classes. You can check the list of classes in the link:
It sees squirrels as cats or bears !! Presumably the model knows nothing about red squirrels....
ultralytics/cfg/datasets/coco.yaml
# Classes
names:
0: person
1: bicycle
2: car
3: motorcycle
4: airplane
5: bus
6: train
7: truck
8: boat
9: traffic light
10: fire hydrant
11: stop sign
12: parking meter
13: bench
14: bird
15: cat
16: dog
17: horse
18: sheep
19: cow
20: elephant
21: bear
22: zebra
23: giraffe
24: backpack
25: umbrella
26: handbag
27: tie
28: suitcase
29: frisbee
30: skis
31: snowboard
32: sports ball
33: kite
34: baseball bat
35: baseball glove
36: skateboard
37: surfboard
38: tennis racket
39: bottle
40: wine glass
41: cup
42: fork
43: knife
44: spoon
45: bowl
46: banana
47: apple
48: sandwich
49: orange
50: broccoli
51: carrot
52: hot dog
53: pizza
54: donut
55: cake
56: chair
57: couch
58: potted plant
59: bed
60: dining table
61: toilet
62: tv
63: laptop
64: mouse
65: remote
66: keyboard
67: cell phone
68: microwave
69: oven
70: toaster
71: sink
72: refrigerator
73: book
74: clock
75: vase
76: scissors
77: teddy bear
78: hair drier
79: toothbrush
Hopefully in future it will be easier to train it....
https://docs.ultralytics.com/datasets/d ... images-v7/
To load the oiv7 trained models, you just add -oiv7 suffix to the original model name.
Code:
from ultralytics import YOLO, ASSETSmodel = YOLO("yolov8n-oiv7.pt")Statistics: Posted by Y-T-G — Tue Oct 22, 2024 1:09 pm