| # 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 | |