0: unlabeled
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: street sign Removed from COCO.
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: hat Removed from COCO.
27: backpack
28: umbrella
29: shoe Removed from COCO.
30: eye glasses Removed from COCO.
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: plate Removed from COCO.
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: mirror Removed from COCO.
67: dining table
68: window Removed from COCO.
69: desk Removed from COCO.
70: toilet
71: door Removed from COCO.
72: tv
73: laptop
74: mouse
75: remote
76: keyboard
77: cell phone
78: microwave
79: oven
80: toaster
81: sink
82: refrigerator
83: blender Removed from COCO.
84: book
85: clock
86: vase
87: scissors
88: teddy bear
89: hair drier
90: toothbrush
91: hair brush Removed from COCO.
92: banner
93: blanket
94: branch
95: bridge
96: building-other
97: bush
98: cabinet
99: cage
100: cardboard
101: carpet
102: ceiling-other
103: ceiling-tile
104: cloth
105: clothes
106: clouds
107: counter
108: cupboard
109: curtain
110: desk-stuff
111: dirt
112: door-stuff
113: fence
114: floor-marble
115: floor-other
116: floor-stone
117: floor-tile
118: floor-wood
119: flower
120: fog
121: food-other
122: fruit
123: furniture-other
124: grass
125: gravel
126: ground-other
127: hill
128: house
129: leaves
130: light
131: mat
132: metal
133: mirror-stuff
134: moss
135: mountain
136: mud
137: napkin
138: net
139: paper
140: pavement
141: pillow
142: plant-other
143: plastic
144: platform
145: playingfield
146: railing
147: railroad
148: river
149: road
150: rock
151: roof
152: rug
153: salad
154: sand
155: sea
156: shelf
157: sky-other
158: skyscraper
159: snow
160: solid-other
161: stairs
162: stone
163: straw
164: structural-other
165: table
166: tent
167: textile-other
168: towel
169: tree
170: vegetable
171: wall-brick
172: wall-concrete
173: wall-other
174: wall-panel
175: wall-stone
176: wall-tile
177: wall-wood
178: water-other
179: waterdrops
180: window-blind
181: window-other
182: wood原本183个类（0号无标签），其中11个被移除，还剩下172个类。
那么id映射关系应该是除去这些被移除的类，放到这个映射表中去找到对应的类别。
比如天空原本是157，减去11后（不一定所有的都减去11，要看它们的位置），就是146，还有一个0号，那么预测图天空的像素值就是145，当然这是将171作为类别数的情况，如果172做为类别数训练，应该不用减1。
