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calibration/0106_dataset.yaml ADDED
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+ # Dataset-specific calibration: 0106_HY_dataset
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+
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+ # Extrinsics: cam_to_lidar (actual; inverse of originally stored lidar_to_cam)
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+ rgb_cam_to_lidar:
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+ - [-0.10364097, 0.10970652, 0.98853059, 0.95891483]
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+ - [-0.99461404, -0.00848903, -0.10326713, -0.27301648]
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+ - [-0.00302048, -0.99388832, 0.10996262, -0.47535845]
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+ - [0.0, 0.0, 0.0, 1.0]
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+
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+ polar_cam_to_lidar:
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+ - [-0.09889617, 0.10958587, 0.98902986, 0.85242987]
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+ - [-0.9950968, -0.00800446, -0.09854544, -0.23196711]
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+ - [-0.00296596, -0.99390565, 0.10980748, -0.47771596]
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+ - [0.0, 0.0, 0.0, 1.0]
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+
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+ # cam_to_ego = lidar_to_ego @ cam_to_lidar
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+ rgb_cam_to_ego:
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+ - [-0.10376541, 0.09806621, 0.98970797, 2.40322995]
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+ - [-0.99448407, 0.00155009, -0.10436743, -0.26818806]
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+ - [-0.01185318, -0.99515824, 0.09734282, 0.97071231]
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+ - [0.0, 0.0, 0.0, 1.0]
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+
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+ polar_cam_to_ego:
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+ - [-0.0990205, 0.09794541, 0.99020585, 2.29673215]
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+ - [-0.99496734, 0.00203478, -0.09964464, -0.22711898]
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+ - [-0.01185906, -0.99516925, 0.09722954, 0.97001552]
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+ - [0.0, 0.0, 0.0, 1.0]
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+
calibration/0112_dataset.yaml ADDED
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+ # Dataset-specific calibration: 0112_HY_snow_dataset
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+
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+ # Extrinsics: cam_to_lidar (actual; inverse of originally stored lidar_to_cam)
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+ rgb_cam_to_lidar:
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+ - [-0.10899271, 0.1032307, 0.98865271, 0.88867919]
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+ - [-0.9940436, -0.00903365, -0.10857355, -0.23085548]
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+ - [-0.00235959, -0.994577, 0.10356744, -0.4816661]
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+ - [0.0, 0.0, 0.0, 1.0]
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+
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+ polar_cam_to_lidar:
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+ - [-0.10267413, 0.10328608, 0.98932292, 0.87775276]
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+ - [-0.99471574, -0.00838843, -0.10228695, -0.18059152]
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+ - [-0.00234892, -0.99457688, 0.10356876, -0.48303158]
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+ - [0.0, 0.0, 0.0, 1.0]
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+
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+ # cam_to_ego = lidar_to_ego @ cam_to_lidar
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+ rgb_cam_to_ego:
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+ - [-0.10910882, 0.09158293, 0.98975473, 2.33293175]
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+ - [-0.99392036, 0.00101248, -0.10960872, -0.22596757]
20
+ - [-0.01112398, -0.99577659, 0.09089325, 0.96565288]
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+ - [0.0, 0.0, 0.0, 1.0]
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+
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+ polar_cam_to_ego:
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+ - [-0.10279081, 0.09163837, 0.99042551, 2.32199546]
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+ - [-0.99459254, 0.00165763, -0.10332277, -0.17569484]
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+ - [-0.01119403, -0.9957706, 0.09095023, 0.96492304]
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+ - [0.0, 0.0, 0.0, 1.0]
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+
calibration/0119_1_dataset.yaml ADDED
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+ # Dataset-specific calibration: 0119_Gapyeong1_dataset
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+
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+ # Extrinsics: cam_to_lidar (actual; inverse of originally stored lidar_to_cam)
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+ rgb_cam_to_lidar:
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+ - [-0.10645938, 0.12582873, 0.98630843, 0.89996257]
6
+ - [-0.99425001, -0.02539172, -0.10400924, -0.23635732]
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+ - [0.01187353, -0.99168745, 0.12777471, -0.45743828]
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+ - [0.0, 0.0, 0.0, 1.0]
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+
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+ polar_cam_to_lidar:
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+ - [-0.09996328, 0.12412695, 0.98720322, 0.88815806]
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+ - [-0.99497365, -0.01898134, -0.09829436, -0.18333914]
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+ - [0.00645365, -0.99204525, 0.12536733, -0.4625416]
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+ - [0.0, 0.0, 0.0, 1.0]
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+
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+ # cam_to_ego = lidar_to_ego @ cam_to_lidar
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+ rgb_cam_to_ego:
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+ - [-0.10640924, 0.11421087, 0.98769436, 2.34449691]
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+ - [-0.99427051, -0.01537314, -0.10528936, -0.23171356]
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+ - [0.003076, -0.99331693, 0.11517163, 0.98969069]
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+ - [0.0, 0.0, 0.0, 1.0]
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+
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+ polar_cam_to_ego:
24
+ - [-0.09997728, 0.11250571, 0.98856147, 2.33263918]
25
+ - [-0.99493934, -0.00895978, -0.09955074, -0.17864913]
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+ - [-0.00242666, -0.99359004, 0.11281174, 0.98526148]
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+ - [0.0, 0.0, 0.0, 1.0]
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+
calibration/0119_2_dataset.yaml ADDED
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1
+ # Dataset-specific calibration: 0119_Gapyeong2_dataset
2
+
3
+ # Extrinsics: cam_to_lidar (actual; inverse of originally stored lidar_to_cam)
4
+ rgb_cam_to_lidar:
5
+ - [-0.10743233, 0.12310456, 0.98654669, 0.8984752]
6
+ - [-0.99408776, -0.02932867, -0.10452567, -0.23903197]
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+ - [0.01598376, -0.9919207, 0.12549356, -0.45896972]
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+ - [0.0, 0.0, 0.0, 1.0]
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+
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+ polar_cam_to_lidar:
11
+ - [-0.10190026, 0.12059578, 0.9874429, 0.88616108]
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+ - [-0.99472888, -0.02413575, -0.09963511, -0.18739036]
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+ - [0.01173385, -0.99236873, 0.12238595, -0.46474306]
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+ - [0.0, 0.0, 0.0, 1.0]
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+
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+ # cam_to_ego = lidar_to_ego @ cam_to_lidar
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+ rgb_cam_to_ego:
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+ - [-0.10733399, 0.11148384, 0.98790585, 2.34299151]
19
+ - [-0.99414979, -0.01930734, -0.1057827, -0.23437247]
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+ - [0.00719884, -0.99355805, 0.11288271, 0.98814979]
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+ - [0.0, 0.0, 0.0, 1.0]
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+
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+ polar_cam_to_ego:
24
+ - [-0.10185226, 0.10897059, 0.98876611, 2.33061623]
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+ - [-0.99474792, -0.01411042, -0.10086125, -0.18267771]
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+ - [0.00287815, -0.99392423, 0.10981432, 0.98304269]
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+ - [0.0, 0.0, 0.0, 1.0]
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+
calibration/0120_dataset.yaml ADDED
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1
+ # Dataset-specific calibration: 0120_Konkuk_dataset
2
+
3
+ # Extrinsics: cam_to_lidar (actual; inverse of originally stored lidar_to_cam)
4
+ rgb_cam_to_lidar:
5
+ - [-0.1062833, 0.12752302, 0.98610982, 0.90078718]
6
+ - [-0.99430345, -0.02217974, -0.10423022, -0.23471306]
7
+ - [0.0084964, -0.99154805, 0.12912049, -0.45666116]
8
+ - [0.0, 0.0, 0.0, 1.0]
9
+
10
+ polar_cam_to_lidar:
11
+ - [-0.105189, 0.12753263, 0.98622611, 0.88881664]
12
+ - [-0.9943548, -0.02769187, -0.10240623, -0.19171168]
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+ - [0.01416675, -0.99140817, 0.12969189, -0.45785844]
14
+ - [0.0, 0.0, 0.0, 1.0]
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+
16
+ # cam_to_ego = lidar_to_ego @ cam_to_lidar
17
+ rgb_cam_to_ego:
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+ - [-0.10627269, 0.11590694, 0.9875115, 2.3453307]
19
+ - [-0.99428983, -0.01216289, -0.10552392, -0.23007731]
20
+ - [-0.0003034, -0.99316493, 0.11651736, 0.99047469]
21
+ - [0.0, 0.0, 0.0, 1.0]
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+
23
+ polar_cam_to_ego:
24
+ - [-0.10511216, 0.11591764, 0.98763464, 2.33335164]
25
+ - [-0.99439845, -0.01767588, -0.10370588, -0.18706814]
26
+ - [0.00535306, -0.99308085, 0.11710578, 0.9898519]
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+ - [0.0, 0.0, 0.0, 1.0]
28
+
calibration/0124_dataset.yaml ADDED
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1
+ # Dataset-specific calibration: 0124_Konkuk_dataset
2
+
3
+ # Extrinsics: cam_to_lidar (actual; inverse of originally stored lidar_to_cam)
4
+ rgb_cam_to_lidar:
5
+ - [-0.10894914, 0.11710711, 0.98711031, 0.89531768]
6
+ - [-0.9940436, -0.00903366, -0.10857355, -0.23085549]
7
+ - [-0.00388113, -0.99303873, 0.11736109, -0.46921125]
8
+ - [0.0, 0.0, 0.0, 1.0]
9
+
10
+ polar_cam_to_lidar:
11
+ - [-0.10262456, 0.11889548, 0.98757408, 0.88523161]
12
+ - [-0.99471915, -0.01531945, -0.10145303, -0.18386262]
13
+ - [0.00298309, -0.99274909, 0.11980678, -0.46791266]
14
+ - [0.0, 0.0, 0.0, 1.0]
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+
16
+ # cam_to_ego = lidar_to_ego @ cam_to_lidar
17
+ rgb_cam_to_ego:
18
+ - [-0.10908306, 0.10547594, 0.98837387, 2.33971529]
19
+ - [-0.99390499, 0.00099694, -0.10974804, -0.22609337]
20
+ - [-0.01264588, -0.99440082, 0.10470357, 0.97802882]
21
+ - [0.0, 0.0, 0.0, 1.0]
22
+
23
+ polar_cam_to_ego:
24
+ - [-0.10267887, 0.10726689, 0.98886692, 2.32965012]
25
+ - [-0.99464981, -0.00529115, -0.10265293, -0.17911832]
26
+ - [-0.00586316, -0.99419561, 0.1072155, 0.97991991]
27
+ - [0.0, 0.0, 0.0, 1.0]
28
+
calibration/0129_1_dataset.yaml ADDED
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1
+ # Dataset-specific calibration: k-city_1_dataset
2
+
3
+ # Extrinsics: cam_to_lidar (actual; inverse of originally stored lidar_to_cam)
4
+ rgb_cam_to_lidar:
5
+ - [-0.11239576, 0.12227287, 0.98609736, 0.89695111]
6
+ - [-0.99364766, -0.00765578, -0.11223822, -0.23314208]
7
+ - [-0.00625843, -0.99242749, 0.12232419, -0.46494156]
8
+ - [0.0, 0.0, 0.0, 1.0]
9
+
10
+ polar_cam_to_lidar:
11
+ - [-0.10783066, 0.11885017, 0.98702504, 0.88427416]
12
+ - [-0.99416448, -0.00892003, -0.10746656, -0.18518051]
13
+ - [-0.00405224, -0.99283263, 0.119086, -0.46920157]
14
+ - [0.0, 0.0, 0.0, 1.0]
15
+
16
+ # cam_to_ego = lidar_to_ego @ cam_to_lidar
17
+ rgb_cam_to_ego:
18
+ - [-0.11255711, 0.11064847, 0.98741872, 2.34139829]
19
+ - [-0.99348509, 0.0023685, -0.11346247, -0.22842286]
20
+ - [-0.01497862, -0.99383616, 0.10964102, 0.98225587]
21
+ - [0.0, 0.0, 0.0, 1.0]
22
+
23
+ polar_cam_to_ego:
24
+ - [-0.1079667, 0.10722125, 0.98830889, 2.32867756]
25
+ - [-0.99402414, 0.00110847, -0.10865858, -0.18042306]
26
+ - [-0.01283128, -0.99421399, 0.10644049, 0.97862902]
27
+ - [0.0, 0.0, 0.0, 1.0]
28
+
calibration/0129_2_dataset.yaml ADDED
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1
+ # Dataset-specific calibration: k-city_2_dataset
2
+
3
+ # Extrinsics: cam_to_lidar (actual; inverse of originally stored lidar_to_cam)
4
+ rgb_cam_to_lidar:
5
+ - [-0.10717654, 0.12578404, 0.98623651, 0.89977962]
6
+ - [-0.99420228, -0.02270582, -0.10507824, -0.23572495]
7
+ - [0.00909278, -0.99175824, 0.12745481, -0.45812397]
8
+ - [0.0, 0.0, 0.0, 1.0]
9
+
10
+ polar_cam_to_lidar:
11
+ - [-0.10399084, 0.12408047, 0.98679322, 0.88742316]
12
+ - [-0.99434917, -0.03449996, -0.10038015, -0.19391392]
13
+ - [0.02150624, -0.99163267, 0.12693274, -0.45963055]
14
+ - [0.0, 0.0, 0.0, 1.0]
15
+
16
+ # cam_to_ego = lidar_to_ego @ cam_to_lidar
17
+ rgb_cam_to_ego:
18
+ - [-0.10715885, 0.11416562, 0.9876186, 2.34430602]
19
+ - [-0.99419469, -0.01268679, -0.10635503, -0.23107433]
20
+ - [0.00030439, -0.99336007, 0.11484181, 0.9890136]
21
+ - [0.0, 0.0, 0.0, 1.0]
22
+
23
+ polar_cam_to_ego:
24
+ - [-0.10382825, 0.11246251, 0.98816961, 2.33193735]
25
+ - [-0.99446695, -0.02448102, -0.10165213, -0.18925226]
26
+ - [0.01267785, -0.9933337, 0.11436072, 0.98807403]
27
+ - [0.0, 0.0, 0.0, 1.0]
28
+
calibration/0129_3_dataset.yaml ADDED
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1
+ # Dataset-specific calibration: k-city_3_dataset
2
+
3
+ # Extrinsics: cam_to_lidar (actual; inverse of originally stored lidar_to_cam)
4
+ rgb_cam_to_lidar:
5
+ - [-0.10892733, 0.12230501, 0.98648229, 0.89776218]
6
+ - [-0.9940446, -0.01769362, -0.10750017, -0.23490032]
7
+ - [0.00422319, -0.99229532, 0.12347076, -0.4624847]
8
+ - [0.0, 0.0, 0.0, 1.0]
9
+
10
+ polar_cam_to_lidar:
11
+ - [-0.10779974, 0.1257785, 0.98616961, 0.88752823]
12
+ - [-0.99417601, -0.01411387, -0.10680549, -0.18760231]
13
+ - [0.00040054, -0.99191841, 0.12653475, -0.46204083]
14
+ - [0.0, 0.0, 0.0, 1.0]
15
+
16
+ # cam_to_ego = lidar_to_ego @ cam_to_lidar
17
+ rgb_cam_to_ego:
18
+ - [-0.10896643, 0.11068116, 0.98781749, 2.34223784]
19
+ - [-0.99398785, -0.00766967, -0.10873647, -0.23020573]
20
+ - [-0.00454263, -0.99380577, 0.11083082, 0.98468523]
21
+ - [0.0, 0.0, 0.0, 1.0]
22
+
23
+ polar_cam_to_ego:
24
+ - [-0.10788369, 0.11415907, 0.98754077, 2.33201484]
25
+ - [-0.99408064, -0.00409409, -0.10807281, -0.18291694]
26
+ - [-0.00837942, -0.99343337, 0.11390517, 0.98572651]
27
+ - [0.0, 0.0, 0.0, 1.0]
28
+
calibration/0129_4_dataset.yaml ADDED
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1
+ # Dataset-specific calibration: k-city_road_dataset
2
+
3
+ # Extrinsics: cam_to_lidar (actual; inverse of originally stored lidar_to_cam)
4
+ rgb_cam_to_lidar:
5
+ - [-0.10891939, 0.12403691, 0.98626693, 0.89857154]
6
+ - [-0.9940436, -0.00903366, -0.10857355, -0.23085548]
7
+ - [-0.00464164, -0.99219697, 0.12424951, -0.46294936]
8
+ - [0.0, 0.0, 0.0, 1.0]
9
+
10
+ polar_cam_to_lidar:
11
+ - [-0.10783757, 0.11711717, 0.98723138, 0.88345391]
12
+ - [-0.99416448, -0.00892004, -0.10746655, -0.18518051]
13
+ - [-0.00386404, -0.99303855, 0.11736314, -0.4707442]
14
+ - [0.0, 0.0, 0.0, 1.0]
15
+
16
+ # cam_to_ego = lidar_to_ego @ cam_to_lidar
17
+ rgb_cam_to_ego:
18
+ - [-0.10906221, 0.1124149, 0.98761116, 2.34304209]
19
+ - [-0.99389731, 0.00098844, -0.10981761, -0.22615661]
20
+ - [-0.01340666, -0.99364022, 0.11160116, 0.984252]
21
+ - [0.0, 0.0, 0.0, 1.0]
22
+
23
+ polar_cam_to_ego:
24
+ - [-0.10797141, 0.10548601, 0.98849506, 2.32783934]
25
+ - [-0.99402604, 0.00111054, -0.10864117, -0.18040748]
26
+ - [-0.01264301, -0.99439961, 0.10471539, 0.97709614]
27
+ - [0.0, 0.0, 0.0, 1.0]
28
+
calibration/0202_dataset.yaml ADDED
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1
+ # Dataset-specific calibration: konkuk_dataset
2
+
3
+ # Extrinsics: cam_to_lidar (actual; inverse of originally stored lidar_to_cam)
4
+ rgb_cam_to_lidar:
5
+ - [-0.10720737, 0.11885571, 0.98709194, 0.89653675]
6
+ - [-0.99423232, -0.00885649, -0.10684755, -0.22930556]
7
+ - [-0.00404099, -0.99283255, 0.11908703, -0.46764089]
8
+ - [0.0, 0.0, 0.0, 1.0]
9
+
10
+ polar_cam_to_lidar:
11
+ - [-0.10783066, 0.11885017, 0.98702504, 0.88427416]
12
+ - [-0.99416448, -0.00892003, -0.10746656, -0.18518051]
13
+ - [-0.00405224, -0.99283263, 0.119086, -0.46920157]
14
+ - [0.0, 0.0, 0.0, 1.0]
15
+
16
+ # cam_to_ego = lidar_to_ego @ cam_to_lidar
17
+ rgb_cam_to_ego:
18
+ - [-0.10734335, 0.1072268, 0.98837586, 2.34095276]
19
+ - [-0.99409209, 0.001172, -0.10803964, -0.22455946]
20
+ - [-0.01282801, -0.99421333, 0.10644698, 0.9796004]
21
+ - [0.0, 0.0, 0.0, 1.0]
22
+
23
+ polar_cam_to_ego:
24
+ - [-0.1079667, 0.10722125, 0.98830889, 2.32867756]
25
+ - [-0.99402414, 0.00110847, -0.10865858, -0.18042306]
26
+ - [-0.01283128, -0.99421399, 0.10644049, 0.97862902]
27
+ - [0.0, 0.0, 0.0, 1.0]
28
+
calibration/0210_1_dataset.yaml ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Dataset-specific calibration: 0210_K-city_rainy_1_dataset
2
+
3
+ # Extrinsics: cam_to_lidar (actual; inverse of originally stored lidar_to_cam)
4
+ rgb_cam_to_lidar:
5
+ - [-0.10718474, 0.12405252, 0.98645488, 0.89897301]
6
+ - [-0.99423232, -0.0088565, -0.10684755, -0.22930557]
7
+ - [-0.00460227, -0.99219661, 0.12425377, -0.46294025]
8
+ - [0.0, 0.0, 0.0, 1.0]
9
+
10
+ polar_cam_to_lidar:
11
+ - [-0.10779974, 0.12577849, 0.98616961, 0.88752823]
12
+ - [-0.99416856, -0.01757623, -0.10636315, -0.18921399]
13
+ - [0.00387085, -0.9918631, 0.1269068, -0.46138317]
14
+ - [0.0, 0.0, 0.0, 1.0]
15
+
16
+ # cam_to_ego = lidar_to_ego @ cam_to_lidar
17
+ rgb_cam_to_ego:
18
+ - [-0.10732729, 0.11243053, 0.98779932, 2.34344378]
19
+ - [-0.99408642, 0.00116558, -0.10809183, -0.22460694]
20
+ - [-0.0133895, -0.99363826, 0.11162066, 0.98427207]
21
+ - [0.0, 0.0, 0.0, 1.0]
22
+
23
+ polar_cam_to_ego:
24
+ - [-0.10784309, 0.11415936, 0.98754517, 2.33202237]
25
+ - [-0.99410824, -0.00755666, -0.10763427, -0.1845351]
26
+ - [-0.00490938, -0.99341304, 0.11428165, 0.98636783]
27
+ - [0.0, 0.0, 0.0, 1.0]
28
+
calibration/0210_2_dataset.yaml ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Dataset-specific calibration: 0210_K-city_rainy_2_dataset
2
+
3
+ # Extrinsics: cam_to_lidar (actual; inverse of originally stored lidar_to_cam)
4
+ rgb_cam_to_lidar:
5
+ - [-0.11238769, 0.12400477, 0.98588202, 0.89776051]
6
+ - [-0.99365708, -0.00938788, -0.11202455, -0.23395321]
7
+ - [-0.00472034, -0.9921977, 0.12424077, -0.46296777]
8
+ - [0.0, 0.0, 0.0, 1.0]
9
+
10
+ polar_cam_to_lidar:
11
+ - [-0.10432984, 0.12580901, 0.9865386, 0.8881691]
12
+ - [-0.99453501, -0.00856566, -0.1040138, -0.18212174]
13
+ - [-0.00472014, -0.99197797, 0.1259828, -0.46300112]
14
+ - [0.0, 0.0, 0.0, 1.0]
15
+
16
+ # cam_to_ego = lidar_to_ego @ cam_to_lidar
17
+ rgb_cam_to_ego:
18
+ - [-0.11253105, 0.11238272, 0.98722585, 2.34223062]
19
+ - [-0.99351004, 0.00063426, -0.11326818, -0.22925384]
20
+ - [-0.01344087, -0.99364416, 0.11156208, 0.98421181]
21
+ - [0.0, 0.0, 0.0, 1.0]
22
+
23
+ polar_cam_to_ego:
24
+ - [-0.10447409, 0.11418943, 0.98790355, 2.33264496]
25
+ - [-0.99438788, 0.00145417, -0.10527583, -0.17742722]
26
+ - [-0.01354381, -0.99343725, 0.11337716, 0.98481417]
27
+ - [0.0, 0.0, 0.0, 1.0]
28
+
calibration/0318_dataset.yaml ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Dataset-specific calibration: 0318_K-city_dataset
2
+
3
+ # Extrinsics: cam_to_lidar (actual; inverse of originally stored lidar_to_cam)
4
+ rgb_cam_to_lidar:
5
+ - [-0.11237053, 0.12746743, 0.98544233, 0.8993711]
6
+ - [-0.99365708, -0.00938788, -0.11202455, -0.23395321]
7
+ - [-0.00511262, -0.9917588, 0.12768138, -0.45983118]
8
+ - [0.0, 0.0, 0.0, 1.0]
9
+
10
+ polar_cam_to_lidar:
11
+ - [-0.10779119, 0.12750963, 0.98594824, 0.888335]
12
+ - [-0.99416448, -0.00892003, -0.10746655, -0.18518051]
13
+ - [-0.00499308, -0.99175768, 0.12769478, -0.46146705]
14
+ - [0.0, 0.0, 0.0, 1.0]
15
+
16
+ # cam_to_ego = lidar_to_ego @ cam_to_lidar
17
+ rgb_cam_to_ego:
18
+ - [-0.112518476, 0.115850166, 0.986826453, 2.343877742]
19
+ - [-0.993506074, 0.000629822, -0.113302932, -0.229285517]
20
+ - [-0.013833311, -0.993245809, 0.115007493, 0.987329236]
21
+ - [ 0. , 0. , 0. , 1. ]
22
+
23
+ polar_cam_to_ego:
24
+ - [-0.107938248, 0.115892426, 0.98733293, 2.332828481]
25
+ - [-0.994014635, 0.001097612, -0.108745521, -0.180501172]
26
+ - [-0.013772481, -0.993240457, 0.115061004, 0.986315256]
27
+ - [ 0. , 0. , 0. , 1. ]
28
+
calibration/0327_dataset.yaml ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Dataset-specific calibration: 0327_kiapi_dataset
2
+
3
+ # Extrinsics: cam_to_lidar (actual; inverse of originally stored lidar_to_cam)
4
+ rgb_cam_to_lidar:
5
+ - [-0.11237053, 0.12746743, 0.98544233, 0.8993711]
6
+ - [-0.99365708, -0.00938788, -0.11202455, -0.23395321]
7
+ - [-0.00511262, -0.9917588, 0.12768138, -0.45983118]
8
+ - [0.0, 0.0, 0.0, 1.0]
9
+
10
+ polar_cam_to_lidar:
11
+ - [-0.10779119, 0.12750963, 0.98594824, 0.888335]
12
+ - [-0.99416448, -0.00892003, -0.10746655, -0.18518051]
13
+ - [-0.00499308, -0.99175768, 0.12769478, -0.46146705]
14
+ - [0.0, 0.0, 0.0, 1.0]
15
+
16
+ # cam_to_ego = lidar_to_ego @ cam_to_lidar
17
+ rgb_cam_to_ego:
18
+ - [-0.112518476, 0.115850166, 0.986826453, 2.343877742]
19
+ - [-0.993506074, 0.000629822, -0.113302932, -0.229285517]
20
+ - [-0.013833311, -0.993245809, 0.115007493, 0.987329236]
21
+ - [ 0. , 0. , 0. , 1. ]
22
+
23
+ polar_cam_to_ego:
24
+ - [-0.107938248, 0.115892426, 0.98733293, 2.332828481]
25
+ - [-0.994014635, 0.001097612, -0.108745521, -0.180501172]
26
+ - [-0.013772481, -0.993240457, 0.115061004, 0.986315256]
27
+ - [ 0. , 0. , 0. , 1. ]
28
+
labels.json ADDED
@@ -0,0 +1,1042 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "metadata": {
3
+ "dataset_name": "PRISM",
4
+ "version": "1.1.0",
5
+ "total_frames": 48792,
6
+ "description": "Frame-level classification labels for the PRISM dataset. Labels cover weather condition, road type, surface material, and surface state. For folders with homogeneous surfaces, only default_label is provided. For folders with surface transitions, ordered_segments lists each contiguous segment in chronological order. Short transition zones are excluded with exact timestamp boundaries.",
7
+ "label_usage": {
8
+ "step_1": "If frame timestamp t falls within any timestamp_override [ts_start, ts_end], use that override's label.",
9
+ "step_2": "Otherwise, if ordered_segments exists, determine the segment by cumulative frame_count offsets.",
10
+ "step_3": "Otherwise, use default_label."
11
+ },
12
+ "timestamp_unit": "Unix seconds with millisecond precision (e.g., 1770704845.634)",
13
+ "normalization_notes": {
14
+ "surface_material": "'ahsphalt' typo corrected to 'asphalt'; 'beigian' typo corrected to 'belgian_block'",
15
+ "surface_state": "'snow covered' normalized to 'snow_covered'"
16
+ }
17
+ },
18
+ "class_definitions": {
19
+ "weather": {
20
+ "clear": "No precipitation, good visibility",
21
+ "overcast": "Cloudy sky, no precipitation",
22
+ "rainy": "Active rainfall during collection",
23
+ "snowy": "Active snowfall during collection",
24
+ "foggy": "Reduced visibility due to fog"
25
+ },
26
+ "road_type": {
27
+ "urban": "City roads with intersections and traffic control",
28
+ "highway": "High-speed limited-access roads",
29
+ "rural": "Country roads outside urban areas",
30
+ "proving_ground": "Controlled test facility with specialty road profiles"
31
+ },
32
+ "surface_material": {
33
+ "asphalt": "Standard asphalt (bituminous) pavement",
34
+ "concrete": "Portland cement concrete pavement",
35
+ "belgian_block": "Cobblestone or interlocking paving block surface",
36
+ "gravel": "Loose gravel road surface",
37
+ "other": "Other surface types such as plastic speed bumps"
38
+ },
39
+ "surface_state": {
40
+ "dry": "No moisture present on the surface",
41
+ "damp": "Slight surface moisture with no standing water",
42
+ "wet": "Wet surface; standing water or active rain film possible",
43
+ "slush": "Partially melted snow or slush layer",
44
+ "snow_covered": "Surface covered by compacted or fresh snow"
45
+ }
46
+ },
47
+ "folders": {
48
+ "0106_dataset": {
49
+ "ordered_segments": [
50
+ {
51
+ "ts_start": "1767667361_605",
52
+ "ts_end": "1767667454_496",
53
+ "label": {
54
+ "weather": "clear",
55
+ "road_type": "urban",
56
+ "surface_material": "asphalt",
57
+ "surface_state": "dry"
58
+ }
59
+ }
60
+ ]
61
+ },
62
+ "0112_dataset": {
63
+ "ordered_segments": [
64
+ {
65
+ "ts_start": "1768200916_088",
66
+ "ts_end": "1768200990_782",
67
+ "label": {
68
+ "weather": "snowy",
69
+ "road_type": "urban",
70
+ "surface_material": "asphalt",
71
+ "surface_state": "snow_covered"
72
+ }
73
+ }
74
+ ]
75
+ },
76
+ "0119_1_dataset": {
77
+ "ordered_segments": [
78
+ {
79
+ "ts_start": "1768791654_524",
80
+ "ts_end": "1768791736_119",
81
+ "label": {
82
+ "weather": "overcast",
83
+ "road_type": "highway",
84
+ "surface_material": "asphalt",
85
+ "surface_state": "damp"
86
+ }
87
+ }
88
+ ]
89
+ },
90
+ "0119_2_dataset": {
91
+ "ordered_segments": [
92
+ {
93
+ "ts_start": "1768791794_516",
94
+ "ts_end": "1768791886_309",
95
+ "label": {
96
+ "weather": "overcast",
97
+ "road_type": "highway",
98
+ "surface_material": "asphalt",
99
+ "surface_state": "damp"
100
+ }
101
+ }
102
+ ]
103
+ },
104
+ "0120_dataset": {
105
+ "ordered_segments": [
106
+ {
107
+ "ts_start": "1768891166_060",
108
+ "ts_end": "1768891424_644",
109
+ "label": {
110
+ "weather": "clear",
111
+ "road_type": "urban",
112
+ "surface_material": "asphalt",
113
+ "surface_state": "dry"
114
+ }
115
+ }
116
+ ]
117
+ },
118
+ "0124_dataset": {
119
+ "ordered_segments": [
120
+ {
121
+ "ts_start": "1769223059_386",
122
+ "ts_end": "1769223287_575",
123
+ "label": {
124
+ "weather": "clear",
125
+ "road_type": "urban",
126
+ "surface_material": "asphalt",
127
+ "surface_state": "slush"
128
+ }
129
+ }
130
+ ]
131
+ },
132
+ "0128_1_dataset": {
133
+ "ordered_segments": [],
134
+ "ignored_frames": [
135
+ {
136
+ "ts_start": "1769586554_508",
137
+ "ts_end": "1769586600_597"
138
+ }
139
+ ]
140
+ },
141
+ "0128_2_dataset": {
142
+ "ordered_segments": [
143
+ {
144
+ "ts_start": "1769586754_988",
145
+ "ts_end": "1769586792_586",
146
+ "label": {
147
+ "weather": "clear",
148
+ "road_type": "proving_ground",
149
+ "surface_material": "concrete",
150
+ "surface_state": "snow_covered"
151
+ }
152
+ }
153
+ ],
154
+ "ignored_frames": [
155
+ {
156
+ "ts_start": "1769586743_507",
157
+ "ts_end": "1769586754_888"
158
+ }
159
+ ]
160
+ },
161
+ "0128_3_dataset": {
162
+ "ordered_segments": [
163
+ {
164
+ "ts_start": "1769587101_167",
165
+ "ts_end": "1769587148_464",
166
+ "label": {
167
+ "weather": "clear",
168
+ "road_type": "proving_ground",
169
+ "surface_material": "concrete",
170
+ "surface_state": "damp"
171
+ }
172
+ }
173
+ ],
174
+ "ignored_frames": [
175
+ {
176
+ "ts_start": "1769587094_478",
177
+ "ts_end": "1769587101_067"
178
+ }
179
+ ]
180
+ },
181
+ "0128_4_dataset": {
182
+ "ordered_segments": [
183
+ {
184
+ "ts_start": "1769587667_132",
185
+ "ts_end": "1769587750_327",
186
+ "label": {
187
+ "weather": "clear",
188
+ "road_type": "proving_ground",
189
+ "surface_material": "other",
190
+ "surface_state": "damp"
191
+ }
192
+ }
193
+ ],
194
+ "ignored_frames": [
195
+ {
196
+ "ts_start": "1769587645_534",
197
+ "ts_end": "1769587667_032"
198
+ }
199
+ ]
200
+ },
201
+ "0128_5_dataset": {
202
+ "ordered_segments": [
203
+ {
204
+ "ts_start": "1769587935_817",
205
+ "ts_end": "1769587949_517",
206
+ "label": {
207
+ "weather": "clear",
208
+ "road_type": "proving_ground",
209
+ "surface_material": "belgian_block",
210
+ "surface_state": "snow_covered"
211
+ }
212
+ },
213
+ {
214
+ "ts_start": "1769587950_316",
215
+ "ts_end": "1769587990_213",
216
+ "label": {
217
+ "weather": "clear",
218
+ "road_type": "proving_ground",
219
+ "surface_material": "belgian_block",
220
+ "surface_state": "damp"
221
+ }
222
+ },
223
+ {
224
+ "ts_start": "1769587997_213",
225
+ "ts_end": "1769588017_212",
226
+ "label": {
227
+ "weather": "clear",
228
+ "road_type": "proving_ground",
229
+ "surface_material": "belgian_block",
230
+ "surface_state": "damp"
231
+ }
232
+ }
233
+ ],
234
+ "ignored_frames": [
235
+ {
236
+ "ts_start": "1769587923_429",
237
+ "ts_end": "1769587935_717"
238
+ },
239
+ {
240
+ "ts_start": "1769587949_617",
241
+ "ts_end": "1769587950_216"
242
+ },
243
+ {
244
+ "ts_start": "1769587990_313",
245
+ "ts_end": "1769587997_113"
246
+ }
247
+ ]
248
+ },
249
+ "0128_6_dataset": {
250
+ "ordered_segments": [
251
+ {
252
+ "ts_start": "1769588187_002",
253
+ "ts_end": "1769588273_097",
254
+ "label": {
255
+ "weather": "clear",
256
+ "road_type": "proving_ground",
257
+ "surface_material": "concrete",
258
+ "surface_state": "wet"
259
+ }
260
+ }
261
+ ],
262
+ "ignored_frames": [
263
+ {
264
+ "ts_start": "1769588174_420",
265
+ "ts_end": "1769588186_902"
266
+ }
267
+ ]
268
+ },
269
+ "0128_7_dataset": {
270
+ "ordered_segments": [
271
+ {
272
+ "ts_start": "1769588445_087",
273
+ "ts_end": "1769588469_185",
274
+ "label": {
275
+ "weather": "clear",
276
+ "road_type": "proving_ground",
277
+ "surface_material": "other",
278
+ "surface_state": "damp"
279
+ }
280
+ }
281
+ ],
282
+ "ignored_frames": [
283
+ {
284
+ "ts_start": "1769588427_489",
285
+ "ts_end": "1769588444_987"
286
+ }
287
+ ]
288
+ },
289
+ "0129_1_dataset": {
290
+ "ordered_segments": [
291
+ {
292
+ "ts_start": "1769664717_817",
293
+ "ts_end": "1769664826_713",
294
+ "label": {
295
+ "weather": "clear",
296
+ "road_type": "urban",
297
+ "surface_material": "asphalt",
298
+ "surface_state": "damp"
299
+ }
300
+ }
301
+ ]
302
+ },
303
+ "0129_2_dataset": {
304
+ "ordered_segments": [
305
+ {
306
+ "ts_start": "1769665006_799",
307
+ "ts_end": "1769665053_495",
308
+ "label": {
309
+ "weather": "clear",
310
+ "road_type": "highway",
311
+ "surface_material": "asphalt",
312
+ "surface_state": "damp"
313
+ }
314
+ }
315
+ ]
316
+ },
317
+ "0129_3_dataset": {
318
+ "ordered_segments": [
319
+ {
320
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