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semantic-kitti.yaml
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semantic-kitti.yaml
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# This file is covered by the LICENSE file in the root of this project.
labels:
0 : "unlabeled"
1 : "outlier"
10: "car"
11: "bicycle"
13: "bus"
15: "motorcycle"
16: "on-rails"
18: "truck"
20: "other-vehicle"
30: "person"
31: "bicyclist"
32: "motorcyclist"
40: "road"
44: "parking"
48: "sidewalk"
49: "other-ground"
50: "building"
51: "fence"
52: "other-structure"
60: "lane-marking"
70: "vegetation"
71: "trunk"
72: "terrain"
80: "pole"
81: "traffic-sign"
99: "other-object"
252: "moving-car"
253: "moving-bicyclist"
254: "moving-person"
255: "moving-motorcyclist"
256: "moving-on-rails"
257: "moving-bus"
258: "moving-truck"
259: "moving-other-vehicle"
color_map: # bgr
0 : [0, 0, 0]
1 : [0, 0, 255]
10: [245, 150, 100]
11: [245, 230, 100]
13: [250, 80, 100]
15: [150, 60, 30]
16: [255, 0, 0]
18: [180, 30, 80]
20: [255, 0, 0]
30: [30, 30, 255]
31: [200, 40, 255]
32: [90, 30, 150]
40: [255, 0, 255]
44: [255, 150, 255]
48: [75, 0, 75]
49: [75, 0, 175]
50: [0, 200, 255]
51: [50, 120, 255]
52: [0, 150, 255]
60: [170, 255, 150]
70: [0, 175, 0]
71: [0, 60, 135]
72: [80, 240, 150]
80: [150, 240, 255]
81: [0, 0, 255]
99: [255, 255, 50]
252: [245, 150, 100]
256: [255, 0, 0]
253: [200, 40, 255]
254: [30, 30, 255]
255: [90, 30, 150]
257: [250, 80, 100]
258: [180, 30, 80]
259: [255, 0, 0]
content: # as a ratio with the total number of points
0: 0.018889854628292943
1: 0.0002937197336781505
10: 0.040818519255974316
11: 0.00016609538710764618
13: 2.7879693665067774e-05
15: 0.00039838616015114444
16: 0.0
18: 0.0020633612104619787
20: 0.0016218197275284021
30: 0.00017698551338515307
31: 1.1065903904919655e-08
32: 5.532951952459828e-09
40: 0.1987493871255525
44: 0.014717169549888214
48: 0.14392298360372
49: 0.0039048553037472045
50: 0.1326861944777486
51: 0.0723592229456223
52: 0.002395131480328884
60: 4.7084144280367186e-05
70: 0.26681502148037506
71: 0.006035012012626033
72: 0.07814222006271769
80: 0.002855498193863172
81: 0.0006155958086189918
99: 0.009923127583046915
252: 0.001789309418528068
253: 0.00012709999297008662
254: 0.00016059776092534436
255: 3.745553104802113e-05
256: 0.0
257: 0.00011351574470342043
258: 0.00010157861367183268
259: 4.3840131989471124e-05
# classes that are indistinguishable from single scan or inconsistent in
# ground truth are mapped to their closest equivalent
learning_map:
0 : 0 # "unlabeled"
1 : 0 # "outlier" mapped to "unlabeled" --------------------------mapped
10: 1 # "car"
11: 2 # "bicycle"
13: 5 # "bus" mapped to "other-vehicle" --------------------------mapped
15: 3 # "motorcycle"
16: 5 # "on-rails" mapped to "other-vehicle" ---------------------mapped
18: 4 # "truck"
20: 5 # "other-vehicle"
30: 6 # "person"
31: 7 # "bicyclist"
32: 8 # "motorcyclist"
40: 9 # "road"
44: 10 # "parking"
48: 11 # "sidewalk"
49: 12 # "other-ground"
50: 13 # "building"
51: 14 # "fence"
52: 0 # "other-structure" mapped to "unlabeled" ------------------mapped
60: 9 # "lane-marking" to "road" ---------------------------------mapped
70: 15 # "vegetation"
71: 16 # "trunk"
72: 17 # "terrain"
80: 18 # "pole"
81: 19 # "traffic-sign"
99: 0 # "other-object" to "unlabeled" ----------------------------mapped
252: 1 # "moving-car" to "car" ------------------------------------mapped
253: 7 # "moving-bicyclist" to "bicyclist" ------------------------mapped
254: 6 # "moving-person" to "person" ------------------------------mapped
255: 8 # "moving-motorcyclist" to "motorcyclist" ------------------mapped
256: 5 # "moving-on-rails" mapped to "other-vehicle" --------------mapped
257: 5 # "moving-bus" mapped to "other-vehicle" -------------------mapped
258: 4 # "moving-truck" to "truck" --------------------------------mapped
259: 5 # "moving-other"-vehicle to "other-vehicle" ----------------mapped
learning_map_inv: # inverse of previous map
0: 0 # "unlabeled", and others ignored
1: 10 # "car"
2: 11 # "bicycle"
3: 15 # "motorcycle"
4: 18 # "truck"
5: 20 # "other-vehicle"
6: 30 # "person"
7: 31 # "bicyclist"
8: 32 # "motorcyclist"
9: 40 # "road"
10: 44 # "parking"
11: 48 # "sidewalk"
12: 49 # "other-ground"
13: 50 # "building"
14: 51 # "fence"
15: 70 # "vegetation"
16: 71 # "trunk"
17: 72 # "terrain"
18: 80 # "pole"
19: 81 # "traffic-sign"
learning_ignore: # Ignore classes
0: True # "unlabeled", and others ignored
1: False # "car"
2: False # "bicycle"
3: False # "motorcycle"
4: False # "truck"
5: False # "other-vehicle"
6: False # "person"
7: False # "bicyclist"
8: False # "motorcyclist"
9: False # "road"
10: False # "parking"
11: False # "sidewalk"
12: False # "other-ground"
13: False # "building"
14: False # "fence"
15: False # "vegetation"
16: False # "trunk"
17: False # "terrain"
18: False # "pole"
19: False # "traffic-sign"
thing_class: # thing class in panoptic segmentation
0: False # "unlabeled", and others ignored
1: True # "car"
2: True # "bicycle"
3: True # "motorcycle"
4: True # "truck"
5: True # "other-vehicle"
6: True # "person"
7: True # "bicyclist"
8: True # "motorcyclist"
9: False # "road"
10: False # "parking"
11: False # "sidewalk"
12: False # "other-ground"
13: False # "building"
14: False # "fence"
15: False # "vegetation"
16: False # "trunk"
17: False # "terrain"
18: False # "pole"
19: False # "traffic-sign"
split: # sequence numbers
train:
- 0
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 9
- 10
valid:
- 8
test:
- 11
- 12
- 13
- 14
- 15
- 16
- 17
- 18
- 19
- 20
- 21