[Object Detection] COCO Category 91 vs 80

 

 

COCO 데이터 세트 논문에 나와있는 클래스의 개수는 91이다.

Darknet 프레임워크에 나와있는 클래스의 개수는 80개이다.

 

COCO 데이터 세트의 2014 데이터와 2017 데이터 이름은 같으며, 

단지, Paper 와의 약소한 차이인 누락된 클래스가 있다. 

 

 

누락된 클래스 11개 

• stop sign
• hat
• shoe
• eye glasses
• plate
• mirror
• window
• desk
• door
• blender
• hair brush

 

 

또한 참고로 COCO 주석인 json 파일에서 stop sign 에 대한 주석이 빠지면서 생긴 문제인지

train 및 val 의 이미지 개수와 annotation 개수의 차이가 다소 있다. 

 

• train2017 : 118,287 장
• annotation (train2017) : 117,266
• val2017 : 5,000장
• annotation (val2017) : 4,952 

 

 

 

COCO 클래스 목록

ID	Object (Paper)	Object (2014)	Object (2017)	Super Category
1	person	person	person	person
2	bicycle	bicycle	bicycle	vehicle
3	car	car	car	vehicle
4	motorcycle	motorcycle	motorcycle	vehicle
5	airplane	airplane	airplane	vehicle
6	bus	bus	bus	vehicle
7	train	train	train	vehicle
8	truck	truck	truck	vehicle
9	boat	boat	boat	vehicle
10	traffic light	traffic light	traffic light	outdoor
11	fire hydrant	fire hydrant	fire hydrant	outdoor
12	street sign	-	-	outdoor
13	stop sign	stop sign	stop sign	outdoor
14	parking meter	parking meter	parking meter	outdoor
15	bench	bench	bench	outdoor
16	bird	bird	bird	animal
17	cat	cat	cat	animal
18	dog	dog	dog	animal
19	horse	horse	horse	animal
20	sheep	sheep	sheep	animal
21	cow	cow	cow	animal
22	elephant	elephant	elephant	animal
23	bear	bear	bear	animal
24	zebra	zebra	zebra	animal
25	giraffe	giraffe	giraffe	animal
26	hat	-	-	accessory
27	backpack	backpack	backpack	accessory
28	umbrella	umbrella	umbrella	accessory
29	shoe	-	-	accessory
30	eye glasses	-	-	accessory
31	handbag	handbag	handbag	accessory
32	tie	tie	tie	accessory
33	suitcase	suitcase	suitcase	accessory
34	frisbee	frisbee	frisbee	sports
35	skis	skis	skis	sports
36	snowboard	snowboard	snowboard	sports
37	sports ball	sports ball	sports ball	sports
38	kite	kite	kite	sports
39	baseball bat	baseball bat	baseball bat	sports
40	baseball glove	baseball glove	baseball glove	sports
41	skateboard	skateboard	skateboard	sports
42	surfboard	surfboard	surfboard	sports
43	tennis racket	tennis racket	tennis racket	sports
44	bottle	bottle	bottle	kitchen
45	plate	-	-	kitchen
46	wine glass	wine glass	wine glass	kitchen
47	cup	cup	cup	kitchen
48	fork	fork	fork	kitchen
49	knife	knife	knife	kitchen
50	spoon	spoon	spoon	kitchen
51	bowl	bowl	bowl	kitchen
52	banana	banana	banana	food
53	apple	apple	apple	food
54	sandwich	sandwich	sandwich	food
55	orange	orange	orange	food
56	broccoli	broccoli	broccoli	food
57	carrot	carrot	carrot	food
58	hot dog	hot dog	hot dog	food
59	pizza	pizza	pizza	food
60	donut	donut	donut	food
61	cake	cake	cake	food
62	chair	chair	chair	furniture
63	couch	couch	couch	furniture
64	potted plant	potted plant	potted plant	furniture
65	bed	bed	bed	furniture
66	mirror	-	-	furniture
67	dining table	dining table	dining table	furniture
68	window	-	-	furniture
69	desk	-	-	furniture
70	toilet	toilet	toilet	furniture
71	door	-	-	furniture
72	tv	tv	tv	electronic
73	laptop	laptop	laptop	electronic
74	mouse	mouse	mouse	electronic
75	remote	remote	remote	electronic
76	keyboard	keyboard	keyboard	electronic
77	cell phone	cell phone	cell phone	electronic
78	microwave	microwave	microwave	appliance
79	oven	oven	oven	appliance
80	toaster	toaster	toaster	appliance
81	sink	sink	sink	appliance
82	refrigerator	refrigerator	refrigerator	appliance
83	blender	-	-	appliance
84	book	book	book	indoor
85	clock	clock	clock	indoor
86	vase	vase	vase	indoor
87	scissors	scissors	scissors	indoor
88	teddy bear	teddy bear	teddy bear	indoor
89	hair drier	hair drier	hair drier	indoor
90	toothbrush	toothbrush	toothbrush	indoor
91	hair brush	-	-	indoor

 

 

 

 

 

그리고 참고로

COCO 2017 train 데이터는 COCO 2014 trainval 데이터와 같고,

COCO 2017 val 데이터는 COCO 2014 minival 데이터와 같다. 

 

 

참고자료 1 : 

https://tech.amikelive.com/node-718/what-object-categories-labels-are-in-coco-dataset/

What Object Categories / Labels Are In COCO Dataset?

참고자료 2 : 

https://github.com/mks0601/TF-SimpleHumanPose/issues/4

where can I get human_detection.json of MPII? · Issue #4 · mks0601/TF-SimpleHumanPose