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SSCBench / configs /waymo.yaml
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# This file is covered by the LICENSE file in the root of this project.
nbr_classes: 15
learning_map:
0 : 0 # "unlabeled"
1 : 0 # "outlier" mapped to "unlabeled" --------------------------mapped
10: 1 # "car"
11: 2 # "bicycle"
13: 1 # "bus"
15: 3 # "motorcycle"
16: 1 # "on-rails" mapped to "other-vehicle" ---------------------mapped
18: 1 # "truck"
20: 1 # "other-vehicle"
30: 4 # "person"
31: 5 # "bicyclist"
32: 5 # "motorcyclist"
40: 6 # "road"
44: 0 # "parking" ---ignore
48: 7 # "sidewalk"
49: 8 # "other-ground"
50: 9 # "building"
51: 0 # "fence" ---ignore
52: 0 # "other-structure" ---ignore
60: 6 # "lane-marking" mapped to "road"
70: 10 # "vegetation"
71: 11 # "trunk"
72: 0 # "terrain" ---ignore
80: 12 # "pole"
81: 13 # "traffic-sign"
99: 14 # "other-object"
252: 1 # "moving-car" to "car" ------------------------------------mapped
253: 5 # "moving-bicyclist" to "bicyclist" ------------------------mapped
254: 4 # "moving-person" to "person" ------------------------------mapped
255: 5 # "moving-motorcyclist" to "motorcyclist" ------------------mapped
256: 1 # "moving-on-rails" mapped to "other-vehicle" --------------mapped
257: 1 # "moving-bus" mapped to "bus" -------------------mapped
258: 1 # "moving-truck" to "truck" --------------------------------mapped
259: 1 # "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: 30 # "person"
5: 31 # "bicyclist" + "motorcyclist"
6: 40 # "road" + "lane marking"
7: 48 # "sidewalk"
8: 49 # "other-ground"
9: 50 # "building"
10: 70 # "vegetation"
11: 71 # "trunk"
12: 80 # "pole"
13: 81 # "traffic-sign"
14: 99 # "other-object"
learning_ignore: # Ignore classes
0: True # "unlabeled", and others ignored
1: False
2: False
3: False
4: False
5: False
6: False
7: False
8: False
9: False
10: False
11: False
12: False
13: False
14: False
#UNIFIED
# nbr_classes: 11
# learning_map:
# 0 : 0 # "unlabeled"
# 1 : 0 # "outlier" mapped to "unlabeled" --------------------------mapped
# 10: 1 # "car"
# 11: 2 # "bicycle"
# 13: 1 # "bus"
# 15: 3 # "motorcycle"
# 16: 1 # "on-rails" mapped to "other-vehicle" ---------------------mapped
# 18: 1 # "truck"
# 20: 1 # "other-vehicle"
# 30: 4 # "person"
# 31: 0 # "bicyclist" mapped to "unlabeled" --------------------------mapped
# 32: 0 # "motorcyclist" mapped to "unlabeled" --------------------------mapped
# 40: 5 # "road"
# 44: 0 # "parking" ---ignore
# 48: 6 # "sidewalk"
# 49: 7 # "other-ground"
# 50: 8 # "building"
# 51: 0 # "fence" ---ignore
# 52: 0 # "other-structure" ---ignore
# 60: 6 # "lane-marking" mapped to "road" --------------------------mapped
# 70: 9 # "vegetation"
# 71: 9 # "trunk" mapped to "vegetation" --------------------------mapped
# 72: 0 # "terrain" ---ignore
# 80: 10 # "pole" mapped to "other obejct" --------------------------mapped
# 81: 10 # "traffic-sign" mapped to "other object" --------------------------mapped
# 99: 10 # "other-object"
# 252: 1 # "moving-car" to "car" ------------------------------------mapped
# 253: 0 # "moving-bicyclist" to "unlabeled" ------------------------mapped
# 254: 4 # "moving-person" to "person" ------------------------------mapped
# 255: 0 # "moving-motorcyclist" to "unlabeled" ------------------mapped
# 256: 1 # "moving-on-rails" mapped to "car" --------------mapped
# 257: 1 # "moving-bus" mapped to "car" -------------------mapped
# 258: 1 # "moving-truck" to "car" --------------------------------mapped
# 259: 1 # "moving-other"-vehicle to "car" ----------------mapped
# learning_map_inv: # inverse of previous map
# 0: 0 # "unlabeled", and others ignored
# 1: 10 # "car"
# 2: 11 # "bicycle"
# 3: 15 # "motorcycle"
# 4: 30 # "person"
# 5: 40 # "road"
# 6: 48 # "sidewalk"
# 7: 49 # "other-ground"
# 8: 50 # "building"
# 9: 70 # "vegetation"
# 10: 99 # "other-object"
# learning_ignore: # Ignore classes
# 0: True # "unlabeled", and others ignored
# 1: False
# 2: False
# 3: False
# 4: False
# 5: False
# 6: False
# 7: False
# 8: False
# 9: False
# 10: False
grid_dims: [256, 32, 256] # (W, H, D)
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