Datasets:
erenzhou
/
AirSpatial

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The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 2 new columns ({'question', 'qtype'}) and 7 missing columns ({'width', 'length', 'type', 'height', 'distance', 'color', 'depth'}).

This happened while the json dataset builder was generating data using

hf://datasets/erenzhou/AirSpatial/airspatial_rec_train.jsonl (at revision b40a1766a8a05d9ce3b5d2612fd2b5071565afa9)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 644, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              question_id: int64
              qtype: string
              image_id: string
              bbox: list<item: int64>
                child 0, item: int64
              poly: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              bbox_3d: list<item: double>
                child 0, item: double
              pitch_angle: string
              AGL: string
              question: string
              dataset: string
              to
              {'question_id': Value('int64'), 'image_id': Value('string'), 'bbox': List(Value('int64')), 'poly': List(List(Value('int64'))), 'bbox_3d': List(Value('float64')), 'AGL': Value('string'), 'pitch_angle': Value('string'), 'color': Value('string'), 'type': Value('string'), 'distance': Value('string'), 'depth': Value('string'), 'length': Value('string'), 'width': Value('string'), 'height': Value('string'), 'dataset': Value('string')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1456, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1055, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 894, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 970, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1702, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1833, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 2 new columns ({'question', 'qtype'}) and 7 missing columns ({'width', 'length', 'type', 'height', 'distance', 'color', 'depth'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/erenzhou/AirSpatial/airspatial_rec_train.jsonl (at revision b40a1766a8a05d9ce3b5d2612fd2b5071565afa9)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

question_id
int64
image_id
string
bbox
list
poly
list
bbox_3d
list
AGL
string
pitch_angle
string
color
string
type
string
distance
string
depth
string
length
string
width
string
height
string
dataset
string
0
0be3ceba-DJI_0001.JPG
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40
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airspatial
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0be3ceba-DJI_0001.JPG
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40
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black
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airspatial
3
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[ 2488, 1124, 2805, 1490 ]
[ [ 2622, 1490 ], [ 2488, 1402 ], [ 2671, 1124 ], [ 2805, 1212 ] ]
[ 9.3, 2.6, 40, 4.8, 2.3, 1.6, -56.7 ]
40
90
brown
suv
41.2
40.0
4508
1836
1610
airspatial
4
1e571650-DJI_0002.JPG
[ 1485, 385, 1803, 722 ]
[ [ 1605, 722 ], [ 1485, 622 ], [ 1684, 385 ], [ 1803, 485 ] ]
[ -5.1, -8.2, 40, 4.5, 2.2, 1.6, -50.1 ]
40
90
blue
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airspatial
5
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[ 1283, 252, 1641, 641 ]
[ [ 1417, 641 ], [ 1283, 533 ], [ 1506, 252 ], [ 1641, 359 ] ]
[ -7.7, -9.8, 40, 5.2, 2.5, 1.5, -51.5 ]
40
90
white
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4865
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airspatial
6
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[ 2793, 1317, 3119, 1674 ]
[ [ 2925, 1674 ], [ 2793, 1574 ], [ 2986, 1317 ], [ 3119, 1417 ] ]
[ 13.8, 5.3, 40, 4.6, 2.4, 1.6, -53 ]
40
90
pink
subcompact
42.6
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4125
1770
1570
airspatial
7
1e571650-DJI_0002.JPG
[ 3527, 1787, 3890, 2190 ]
[ [ 3684, 2190 ], [ 3527, 2080 ], [ 3733, 1787 ], [ 3890, 1897 ] ]
[ 24.6, 12.5, 40, 5.2, 2.8, 1.4, -54.8 ]
40
90
black
mid-size
48.6
40.0
4980
1862
1449
airspatial
8
f777b190-DJI_0003.JPG
[ 2468, 846, 2858, 1199 ]
[ [ 2565, 1199 ], [ 2468, 1075 ], [ 2761, 846 ], [ 2858, 970 ] ]
[ 9.6, -1.5, 40, 5.4, 2.3, 1.7, -38 ]
40
90
white
mpv
41.2
40.0
4861
1820
1712
airspatial
9
f777b190-DJI_0003.JPG
[ 1228, 1559, 1512, 1896 ]
[ [ 1345, 1896 ], [ 1228, 1822 ], [ 1395, 1559 ], [ 1512, 1634 ] ]
[ -9.1, 8.7, 40, 4.5, 2, 1.5, -57.5 ]
40
90
white
subcompact
41.9
40.0
4300
1735
1504
airspatial
10
f777b190-DJI_0003.JPG
[ 2616, 974, 2968, 1341 ]
[ [ 2745, 1341 ], [ 2616, 1229 ], [ 2840, 974 ], [ 2968, 1086 ] ]
[ 11.4, 0.5, 40, 4.9, 2.5, 1.5, -48.8 ]
40
90
brown
compact
41.6
40.0
4609
1798
1464
airspatial
11
f777b190-DJI_0003.JPG
[ 302, 0, 664, 240 ]
[ [ 618, 0 ], [ 664, 127 ], [ 347, 240 ], [ 302, 113 ] ]
[ -21.9, -14.5, 40, 4.8, 2, 1.5, -19.7 ]
40
90
white
suv
47.8
40.0
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1545
airspatial
12
f777b190-DJI_0003.JPG
[ 902, 1786, 1209, 2177 ]
[ [ 1078, 1786 ], [ 1209, 1859 ], [ 1033, 2177 ], [ 902, 2105 ] ]
[ -13.6, 12.4, 40, 5.2, 2.2, 1.4, -61 ]
40
90
black
mid-size
44.0
40.0
4975
1866
1447
airspatial
13
f777b190-DJI_0003.JPG
[ 3522, 1858, 3899, 2200 ]
[ [ 3621, 2200 ], [ 3522, 2070 ], [ 3800, 1858 ], [ 3899, 1988 ] ]
[ 24.7, 13, 40, 5, 2.3, 1.8, -37.3 ]
40
90
gray
suv
48.8
40.0
4965
1930
1750
airspatial
14
f777b190-DJI_0003.JPG
[ 3210, 1607, 3586, 2003 ]
[ [ 3342, 2003 ], [ 3210, 1888 ], [ 3453, 1607 ], [ 3586, 1722 ] ]
[ 20.2, 9.8, 40, 5.4, 2.5, 1.5, -49.1 ]
40
90
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45.9
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1520
airspatial
15
f777b190-DJI_0003.JPG
[ -66, 1964, 198, 2272 ]
[ [ 54, 2272 ], [ -66, 2198 ], [ 78, 1964 ], [ 198, 2039 ] ]
[ -27.9, 14.3, 40, 4, 2, 1.3, -58.2 ]
40
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4395
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airspatial
16
f777b190-DJI_0003.JPG
[ 856, 2151, 1028, 2310 ]
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40
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17
f777b190-DJI_0003.JPG
[ 1711, 1763, 2038, 2125 ]
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[ -1.8, 11.8, 40, 4.8, 2.3, 1.7, -53.1 ]
40
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airspatial
18
e3f83fff-DJI_0004.JPG
[ 1836, 897, 2134, 1261 ]
[ [ 1974, 1261 ], [ 1836, 1185 ], [ 1996, 897 ], [ 2134, 974 ] ]
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40
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e3f83fff-DJI_0004.JPG
[ 2711, 1084, 2999, 1465 ]
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40
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20
e3f83fff-DJI_0004.JPG
[ 3188, 468, 3516, 860 ]
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[ 19.5, -6.6, 40, 5.2, 2.3, 1.5, -58.1 ]
40
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white
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airspatial
21
e3f83fff-DJI_0004.JPG
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[ [ 3038, 725 ], [ 3181, 804 ], [ 3005, 1121 ], [ 2863, 1042 ] ]
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e3f83fff-DJI_0004.JPG
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airspatial
23
e3f83fff-DJI_0004.JPG
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27
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f1238d03-DJI_0007.JPG
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a020f163-DJI_0008.JPG
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a020f163-DJI_0008.JPG
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40
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[ 2193, 549, 2580, 842 ]
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90
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suv
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airspatial
51
a020f163-DJI_0008.JPG
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airspatial
52
a020f163-DJI_0008.JPG
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airspatial
53
a020f163-DJI_0008.JPG
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suv
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4350
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airspatial
54
a020f163-DJI_0008.JPG
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airspatial
55
a020f163-DJI_0008.JPG
[ 2223, 736, 2600, 1032 ]
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airspatial
56
a020f163-DJI_0008.JPG
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airspatial
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a020f163-DJI_0008.JPG
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airspatial
58
a020f163-DJI_0008.JPG
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airspatial
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bd1ff5b3-DJI_0009.JPG
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airspatial
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bd1ff5b3-DJI_0009.JPG
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airspatial
61
bd1ff5b3-DJI_0009.JPG
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bd1ff5b3-DJI_0009.JPG
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airspatial
63
bd1ff5b3-DJI_0009.JPG
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90
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airspatial
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bd1ff5b3-DJI_0009.JPG
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airspatial
65
bd1ff5b3-DJI_0009.JPG
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90
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airspatial
66
bd1ff5b3-DJI_0009.JPG
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40
90
black
suv
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40.0
4895
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1754
airspatial
67
bd1ff5b3-DJI_0009.JPG
[ 2275, 1872, 2650, 2152 ]
[ [ 2337, 2152 ], [ 2275, 1995 ], [ 2588, 1872 ], [ 2650, 2029 ] ]
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40
90
black
crossover
42.5
40.0
4600
1855
1680
airspatial
68
bd1ff5b3-DJI_0009.JPG
[ 2177, 1326, 2575, 1606 ]
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[ 5.4, 4.9, 40, 5.4, 2, 1.5, -23.9 ]
40
90
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4975
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airspatial
69
bd1ff5b3-DJI_0009.JPG
[ 2210, 1696, 2585, 1955 ]
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40
90
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airspatial
70
bd1ff5b3-DJI_0009.JPG
[ 1837, -126, 2209, 162 ]
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40
90
black
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40.0
4948
1836
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airspatial
71
bd1ff5b3-DJI_0009.JPG
[ 2332, 2048, 2726, 2340 ]
[ [ 2396, 2340 ], [ 2332, 2180 ], [ 2662, 2048 ], [ 2726, 2207 ] ]
[ 7.6, 15.4, 40, 5.1, 2.5, 1.8, -21.8 ]
40
90
white
suv
43.5
40.0
4965
1930
1750
airspatial
72
8eaba8ed-DJI_0010.JPG
[ 2514, 1082, 2914, 1369 ]
[ [ 2575, 1369 ], [ 2514, 1232 ], [ 2853, 1082 ], [ 2914, 1218 ] ]
[ 10.3, 1.5, 40, 5.3, 2.2, 1.5, -24 ]
40
90
black
mid-size
41.3
40.0
4948
1836
1469
airspatial
73
8eaba8ed-DJI_0010.JPG
[ 2576, 1247, 2959, 1536 ]
[ [ 2641, 1536 ], [ 2576, 1392 ], [ 2894, 1247 ], [ 2959, 1391 ] ]
[ 11.1, 3.8, 40, 5, 2.3, 1.5, -24.4 ]
40
90
white
compact
41.7
40.0
4678
1806
1474
airspatial
74
8eaba8ed-DJI_0010.JPG
[ 2681, 1802, 3061, 2092 ]
[ [ 2748, 2092 ], [ 2681, 1937 ], [ 2994, 1802 ], [ 3061, 1957 ] ]
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40
90
red
compact
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40.0
4570
1775
1445
airspatial
75
8eaba8ed-DJI_0010.JPG
[ 2410, 677, 2831, 994 ]
[ [ 2479, 994 ], [ 2410, 861 ], [ 2762, 677 ], [ 2831, 810 ] ]
[ 9, -4.2, 40, 5.7, 2.2, 1.5, -27.6 ]
40
90
black
full-size
41.2
40.0
5320
1945
1488
airspatial
76
8eaba8ed-DJI_0010.JPG
[ 2587, 1446, 2993, 1739 ]
[ [ 2649, 1739 ], [ 2587, 1591 ], [ 2931, 1446 ], [ 2993, 1594 ] ]
[ 11.4, 6.8, 40, 5.4, 2.3, 1.5, -22.8 ]
40
90
black
mid-size
42.1
40.0
4996
1866
1472
airspatial
77
8eaba8ed-DJI_0010.JPG
[ 2622, 1616, 3013, 1902 ]
[ [ 2683, 1902 ], [ 2622, 1744 ], [ 2952, 1616 ], [ 3013, 1774 ] ]
[ 11.8, 9.1, 40, 5.1, 2.4, 1.4, -21.2 ]
40
90
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4778
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1437
airspatial
78
8eaba8ed-DJI_0010.JPG
[ 2714, 1993, 3081, 2272 ]
[ [ 2777, 2272 ], [ 2714, 2139 ], [ 3017, 1993 ], [ 3081, 2126 ] ]
[ 12.9, 14.5, 40, 4.9, 2.1, 1.5, -25.7 ]
40
90
black
sedan
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40.0
4800
1875
1460
airspatial
79
8eaba8ed-DJI_0010.JPG
[ 2907, 2172, 3115, 2339 ]
[ [ 2950, 2339 ], [ 2907, 2257 ], [ 3073, 2172 ], [ 3115, 2254 ] ]
[ 14.6, 16.3, 40, 2.7, 1.3, 1.5, -27.2 ]
40
90
golden
mid-size
45.6
40.0
4996
1866
1472
airspatial
80
c041fff3-DJI_0011.JPG
[ 2360, 1425, 2544, 1559 ]
[ [ 2388, 1559 ], [ 2360, 1491 ], [ 2515, 1425 ], [ 2544, 1494 ] ]
[ 13, 10.6, 80, 4.9, 2.1, 1.4, -22.7 ]
80
90
red
compact
81.7
80.0
4570
1775
1445
airspatial
81
c041fff3-DJI_0011.JPG
[ 2334, 1334, 2517, 1459 ]
[ [ 2359, 1459 ], [ 2334, 1394 ], [ 2492, 1334 ], [ 2517, 1399 ] ]
[ 12.3, 7.8, 80, 4.9, 2, 1.4, -20.7 ]
80
90
red
mid-size
81.3
80.0
4778
1850
1437
airspatial
82
c041fff3-DJI_0011.JPG
[ 2369, 1503, 2556, 1648 ]
[ [ 2403, 1648 ], [ 2369, 1569 ], [ 2523, 1503 ], [ 2556, 1582 ] ]
[ 13.4, 13, 80, 4.8, 2.5, 1.5, -23.3 ]
80
90
black
sedan
82.1
80.0
4800
1875
1460
airspatial
83
c041fff3-DJI_0011.JPG
[ 2311, 1147, 2492, 1282 ]
[ [ 2340, 1282 ], [ 2311, 1215 ], [ 2462, 1147 ], [ 2492, 1214 ] ]
[ 11.6, 2.6, 80, 4.8, 2.1, 1.5, -24.1 ]
80
90
white
compact
80.9
80.0
4678
1806
1474
airspatial
84
c041fff3-DJI_0011.JPG
[ 2396, 1595, 2590, 1738 ]
[ [ 2427, 1738 ], [ 2396, 1662 ], [ 2559, 1595 ], [ 2590, 1671 ] ]
[ 14.2, 15.6, 80, 5.1, 2.4, 1.5, -22.2 ]
80
90
golden
mid-size
82.7
80.0
4996
1866
1472
airspatial
85
c041fff3-DJI_0011.JPG
[ 2314, 1245, 2508, 1385 ]
[ [ 2344, 1385 ], [ 2314, 1314 ], [ 2478, 1245 ], [ 2508, 1316 ] ]
[ 11.9, 5.5, 80, 5.1, 2.2, 1.5, -22.9 ]
80
90
black
mid-size
81.1
80.0
4996
1866
1472
airspatial
86
c041fff3-DJI_0011.JPG
[ 2403, 1683, 2593, 1835 ]
[ [ 2440, 1835 ], [ 2403, 1755 ], [ 2556, 1683 ], [ 2593, 1763 ] ]
[ 14.4, 18.3, 80, 4.9, 2.5, 1.7, -25.3 ]
80
90
white
crossover
83.3
80.0
4703
1866
1680
airspatial
87
c041fff3-DJI_0011.JPG
[ 2274, 1057, 2467, 1199 ]
[ [ 2305, 1199 ], [ 2274, 1133 ], [ 2436, 1057 ], [ 2467, 1123 ] ]
[ 10.7, 0.1, 80, 5.1, 2.1, 1.5, -25.2 ]
80
90
black
mid-size
80.7
80.0
4948
1836
1469
airspatial
88
c041fff3-DJI_0011.JPG
[ 2443, 1769, 2639, 1912 ]
[ [ 2473, 1912 ], [ 2443, 1837 ], [ 2608, 1769 ], [ 2639, 1844 ] ]
[ 15.6, 20.6, 80, 5.2, 2.3, 1.5, -22.4 ]
80
90
red
mid-size
84.1
80.0
4975
1910
1495
airspatial
89
c041fff3-DJI_0011.JPG
[ 2519, 2124, 2717, 2272 ]
[ [ 2552, 2272 ], [ 2519, 2198 ], [ 2684, 2124 ], [ 2717, 2198 ] ]
[ 17.8, 31, 80, 5.2, 2.3, 1.8, -24.2 ]
80
90
white
suv
87.6
80.0
4965
1930
1750
airspatial
90
c041fff3-DJI_0011.JPG
[ 2218, 859, 2427, 1015 ]
[ [ 2253, 1015 ], [ 2218, 946 ], [ 2392, 859 ], [ 2427, 929 ] ]
[ 9.3, -5.4, 80, 5.6, 2.2, 1.5, -26.4 ]
80
90
black
full-size
80.7
80.0
5320
1945
1488
airspatial
91
c041fff3-DJI_0011.JPG
[ 2493, 2034, 2683, 2179 ]
[ [ 2526, 2179 ], [ 2493, 2101 ], [ 2650, 2034 ], [ 2683, 2112 ] ]
[ 17, 28.3, 80, 4.9, 2.4, 1.7, -23 ]
80
90
black
crossover
86.5
80.0
4600
1855
1680
airspatial
92
c041fff3-DJI_0011.JPG
[ 2459, 1863, 2656, 2000 ]
[ [ 2487, 2000 ], [ 2459, 1929 ], [ 2629, 1863 ], [ 2656, 1934 ] ]
[ 16.1, 23.3, 80, 5.2, 2.2, 1.8, -21.2 ]
80
90
black
suv
84.9
80.0
4895
1896
1754
airspatial
93
c041fff3-DJI_0011.JPG
[ 2463, 1947, 2658, 2083 ]
[ [ 2491, 2083 ], [ 2463, 2015 ], [ 2630, 1947 ], [ 2658, 2015 ] ]
[ 16.2, 25.7, 80, 5.2, 2.1, 1.5, -22.2 ]
80
90
black
mid-size
85.6
80.0
4882
1820
1461
airspatial
94
e9508d5b-DJI_0012.JPG
[ 1825, 458, 2006, 592 ]
[ [ 1854, 592 ], [ 1825, 518 ], [ 1977, 458 ], [ 2006, 533 ] ]
[ -2.4, -17.3, 80, 4.7, 2.3, 1.6, -21.2 ]
80
90
blue
suv
81.9
80.0
4498
1848
1614
airspatial
95
e9508d5b-DJI_0012.JPG
[ 1681, 6, 1886, 168 ]
[ [ 1720, 168 ], [ 1681, 84 ], [ 1846, 6 ], [ 1886, 90 ] ]
[ -6.2, -29.9, 80, 5.3, 2.7, 1.7, -25.2 ]
80
90
red
suv
85.6
80.0
4870
1950
1725
airspatial
96
e9508d5b-DJI_0012.JPG
[ 1717, 103, 1913, 251 ]
[ [ 1751, 251 ], [ 1717, 174 ], [ 1879, 103 ], [ 1913, 180 ] ]
[ -5.3, -27.3, 80, 5.1, 2.4, 1.4, -23.6 ]
80
90
white
mid-size
84.7
80.0
4724
1848
1430
airspatial
97
e9508d5b-DJI_0012.JPG
[ 1816, 370, 1994, 501 ]
[ [ 1844, 501 ], [ 1816, 426 ], [ 1966, 370 ], [ 1994, 445 ] ]
[ -2.7, -19.9, 80, 4.6, 2.3, 1.6, -20.6 ]
80
90
blue
suv
82.5
80.0
4350
1815
1620
airspatial
98
e9508d5b-DJI_0012.JPG
[ 1947, 815, 2128, 950 ]
[ [ 1977, 950 ], [ 1947, 879 ], [ 2099, 815 ], [ 2128, 886 ] ]
[ 1.1, -7, 80, 4.7, 2.2, 1.6, -22.9 ]
80
90
black
suv
80.3
80.0
4641
1883
1638
airspatial
99
e9508d5b-DJI_0012.JPG
[ 2251, 1546, 2437, 1687 ]
[ [ 2284, 1687 ], [ 2251, 1615 ], [ 2404, 1546 ], [ 2437, 1617 ] ]
[ 9.9, 14.2, 80, 4.8, 2.3, 1.5, -24.6 ]
80
90
white
compact
81.8
80.0
4791
1801
1465
airspatial
End of preview.