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# This file is covered by the LICENSE file in the root of this project.
labels:
0 : "unlabeled"
1: "car"
2: "pick-up"
3: "truck"
4: "bus"
5: "bicycle"
6: "motorcycle"
7: "other-vehicle"
8: "road"
9: "sidewalk"
10: "parking"
11: "other-ground"
12: "female"
13: "male"
14: "kid"
15: "crowd" # multiple person that are very close
16: "bicyclist"
17: "motorcyclist"
18: "building"
19: "other-structure"
20: "vegetation"
21: "trunk"
22: "terrain"
23: "traffic-sign"
24: "pole"
25: "traffic-cone"
26: "fence"
27: "garbage-can"
28: "electric-box"
29: "table"
30: "chair"
31: "bench"
32: "other-object"
color_map: # bgr
0 : [0, 0, 0]
1 : [0, 0, 255]
2: [245, 150, 100]
3: [245, 230, 100]
4: [250, 80, 100]
5: [150, 60, 30]
6: [255, 0, 0]
7: [180, 30, 80]
8: [255, 0, 0]
9: [30, 30, 255]
10: [200, 40, 255]
11: [90, 30, 150]
12: [255, 0, 255]
13: [255, 150, 255]
14: [75, 0, 75]
15: [75, 0, 175]
16: [0, 200, 255]
17: [50, 120, 255]
18: [0, 150, 255]
19: [170, 255, 150]
20: [0, 175, 0]
21: [0, 60, 135]
22: [80, 240, 150]
23: [150, 240, 255]
24: [0, 0, 255]
25: [255, 255, 50]
26: [245, 150, 100]
27: [255, 0, 0]
28: [200, 40, 255]
29: [30, 30, 255]
30: [90, 30, 150]
31: [250, 80, 100]
32: [180, 30, 80]
# An example of class mapping from synlidar to semantickitti,
# classes that are indistinguishable from single scan or inconsistent in
# ground truth are mapped to their closest equivalent.
map_2_semantickitti:
0: 0 # "unlabeled"
1: 1 # "car"
2: 4 # "pick-up"
3: 4 # "truck"
4: 5 # "bus"
5: 2 # "bicycle"
6: 3 # "motorcycle"
7: 5 # "other-vehicle"
8: 9 # "road"
9: 11 # "sidewalk"
10: 10 # "parking"
11: 12 # "other-ground"
12: 6 # "female"
13: 6 # "male"
14: 6 # "kid"
15: 6 # "crowd"
16: 7 # "bicyclist"
17: 8 # "motorcyclist"
18: 13 # "building"
19: 0 # "other-structure"
20: 15 # "vegetation"
21: 16 # "trunk"
22: 17 # "terrain"
23: 19 # "traffic-sign"
24: 18 # "pole"
25: 0 # "traffic-cone"
26: 14 # "fence"
27: 0 # "garbage-can"
28: 0 # "electric-box"
29: 0 # "table"
30: 0 # "chair"
31: 0 # "bench"
32: 0 # "other-object"
# An example of class mapping from synlidar to semanticposs,
# classes that are indistinguishable from single scan or inconsistent in
# ground truth are mapped to their closest equivalent.
map_2_semanticposs:
0: 255 # "unlabeled"
1: 2 # "car"
2: 2
3: 2
4: 2
5: 11 # "bike"
6: 11
7: 255
8: 12 # "ground"
9: 12
10: 12
11: 12
12: 0 # "person"
13: 0
14: 0
15: 0
16: 1 # "rider"
17: 1
18: 8 # "building"
19: 255
20: 4 # "plant"
21: 3 # "trunk"
22: 4
23: 5 # "traffic-sign"
24: 6 # "pole"
25: 9 # "cone/stone"
26: 10 # "fence"
27: 7 # "trashcan"
28: 255
29: 255
30: 255
31: 255
32: 255
sequences: # sequence numbers
- 00
- 01
- 02
- 03
- 04
- 05
- 06
- 07
- 08
- 09
- 10
- 11
- 12
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