YOLOS Coco Labels mismatch
Hey,I’m using the transformer library YOLOS model and wanted to write my own id2label function for a quick look-up without the need of loading the model.I assume it was trained on COCO and therefore used this class list here:github.comamikelive/coco-labels/blob/master/coco-labels-2014_2017.txtperson
bicycle
car
motorcycle
airplane
bus
train
truck
boat
traffic light
fire hydrant
stop sign
parking meter
bench
bird
cat
dog
horse
sheep
cowThis file has been truncated.show originalBut I got a bit suspicious when Ties got classiefied as Snowboards repeatedly, so I printed the labels directly from the YOLOS config and got this list which is a bit off:1: person
2: bicycle
3: car
4: motorcycle
5: airplane
6: bus
7: train
8: truck
9: boat
10: traffic light
11: fire hydrant
12: N/A
13: stop sign
14: parking meter
15: bench
16: bird
17: cat
18: dog
19: horse
20: sheep
21: cow
22: elephant
23: bear
24: zebra
25: giraffe
26: N/A
27: backpack
28: umbrella
29: N/A
30: N/A
31: handbag
32: tie
33: suitcase
34: frisbee
35: skis
36: snowboard
37: sports ball
38: kite
39: baseball bat
40: baseball glove
41: skateboard
42: surfboard
43: tennis racket
44: bottle
45: N/A
46: wine glass
47: cup
48: fork
49: knife
50: spoon
51: bowl
52: banana
53: apple
54: sandwich
55: orange
56: broccoli
57: carrot
58: hot dog
59: pizza
60: donut
61: cake
62: chair
63: couch
64: potted plant
65: bed
66: N/A
67: dining table
68: N/A
69: N/A
70: toilet
71: N/A
72: tv
73: laptop
74: mouse
75: remote
76: keyboard
77: cell phone
78: microwave
79: oven
80: toaster
81: sink
82: refrigerator
83: N/A
84: book
85: clock
86: vase
87: scissors
88: teddy bear
89: hair drier
90: toothbrushWhy is that and why are some indices apparently skipped (theN/As) ?Maybe@nielsrknows an answer to that?
2024-01-16T11:57:31Z
Not sure if this is still relevant with the latest version of the library, but probably you missed reading theoriginal article. From 91 object categories in the original paper, only 80 categories were provided in the dataset.This leaves 11 categories not represented in the released dataset, which you saw as N/A in the YOLO model.