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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 1 new columns ({'lighting_condition'}) and 1 missing columns ({'glare'}). This happened while the csv dataset builder was generating data using hf://datasets/NUS-UAL/global-streetscapes/manual_labels/train/lighting_condition.csv (at revision f32c31dffab66fec8a032cd2ee17c6610eb301c3) 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 1869, in _prepare_split_single writer.write_table(table) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 580, 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 2292, in table_cast return cast_table_to_schema(table, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in cast_table_to_schema raise CastError( datasets.table.CastError: Couldn't cast uuid: string source: string orig_id: int64 lighting_condition: string url: string label_method: string city: string city_id: int64 country: string continent: string lat: double lon: double datetime_local: string sequence_index: int64 sequence_id: string split: string img_path: string -- schema metadata -- pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2225 to {'uuid': Value(dtype='string', id=None), 'source': Value(dtype='string', id=None), 'orig_id': Value(dtype='int64', id=None), 'glare': Value(dtype='string', id=None), 'url': Value(dtype='string', id=None), 'label_method': Value(dtype='string', id=None), 'city': Value(dtype='string', id=None), 'city_id': Value(dtype='int64', id=None), 'country': Value(dtype='string', id=None), 'continent': Value(dtype='string', id=None), 'lat': Value(dtype='float64', id=None), 'lon': Value(dtype='float64', id=None), 'datetime_local': Value(dtype='string', id=None), 'sequence_index': Value(dtype='int64', id=None), 'sequence_id': Value(dtype='string', id=None), 'split': Value(dtype='string', id=None), 'img_path': Value(dtype='string', id=None)} 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 1387, in compute_config_parquet_and_info_response parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet( File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in stream_convert_to_parquet builder._prepare_split( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1740, 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 1871, 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 1 new columns ({'lighting_condition'}) and 1 missing columns ({'glare'}). This happened while the csv dataset builder was generating data using hf://datasets/NUS-UAL/global-streetscapes/manual_labels/train/lighting_condition.csv (at revision f32c31dffab66fec8a032cd2ee17c6610eb301c3) 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)
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uuid
string | source
string | orig_id
int64 | glare
string | url
string | label_method
string | city
string | city_id
int64 | country
string | continent
string | lat
float64 | lon
float64 | datetime_local
string | sequence_index
int64 | sequence_id
string | split
string | img_path
string |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1978a821-d39f-4d98-8d8b-a9975d497385 | Mapillary | 976,482,762,890,327 | no | https://www.mapillary.com/app/?pKey=976482762890327&focus=photo | random sample and manual label | Tarazona de Aragón | 1,724,796,233 | Spain | Europe | 41.790652 | -1.766745 | 2018-08-05 11:33:53.319000+02:00 | 12 | J63JR0B5QM6pfhxWwj9IWA | train | img/3/1978a821-d39f-4d98-8d8b-a9975d497385.jpeg |
12731198-74b8-448e-bec8-faa96b024a2c | Mapillary | 246,917,197,222,492 | no | https://www.mapillary.com/app/?pKey=246917197222492&focus=photo | random sample and manual label | Tarazona de Aragón | 1,724,796,233 | Spain | Europe | 41.785087 | -1.766823 | 2017-07-02 14:03:01.745000+02:00 | 33 | eo1Pec9DyI5lxwa4KhvwXw | train | img/6/12731198-74b8-448e-bec8-faa96b024a2c.jpeg |
ad798a8c-649a-4ff8-b9a2-f2932dc228ff | Mapillary | 2,970,430,033,242,379 | no | https://www.mapillary.com/app/?pKey=2970430033242379&focus=photo | random sample and manual label | Tarazona de Aragón | 1,724,796,233 | Spain | Europe | 41.790926 | -1.766326 | 2016-11-01 16:57:17.295000+01:00 | 35 | K-ILLX1_HQqfj3Z1pNCB9Q | train | img/3/ad798a8c-649a-4ff8-b9a2-f2932dc228ff.jpeg |
2d1f6cba-f083-4308-ae6d-35402709ac4e | Mapillary | 568,930,494,081,380 | no | https://www.mapillary.com/app/?pKey=568930494081380&focus=photo | random sample and manual label | Tarazona de Aragón | 1,724,796,233 | Spain | Europe | 41.784608 | -1.762885 | 2017-07-02 14:03:25.934000+02:00 | 57 | eo1Pec9DyI5lxwa4KhvwXw | train | img/5/2d1f6cba-f083-4308-ae6d-35402709ac4e.jpeg |
ba75d911-58e3-4319-ba02-75b8f5af8837 | Mapillary | 457,198,638,702,420 | no | https://www.mapillary.com/app/?pKey=457198638702420&focus=photo | random sample and manual label | Tarazona de Aragón | 1,724,796,233 | Spain | Europe | 41.784535 | -1.760188 | 2017-07-02 14:03:46.049000+02:00 | 77 | eo1Pec9DyI5lxwa4KhvwXw | train | img/3/ba75d911-58e3-4319-ba02-75b8f5af8837.jpeg |
83bfeed5-c3fd-4972-bd5c-dc8d99f5eff9 | Mapillary | 3,431,244,766,975,759 | no | https://www.mapillary.com/app/?pKey=3431244766975759&focus=photo | random sample and manual label | Tarazona de Aragón | 1,724,796,233 | Spain | Europe | 41.78455 | -1.760757 | 2017-07-02 14:03:42.029000+02:00 | 73 | eo1Pec9DyI5lxwa4KhvwXw | train | img/2/83bfeed5-c3fd-4972-bd5c-dc8d99f5eff9.jpeg |
32de4a41-4471-4e82-a7d2-52303eba3dab | Mapillary | 292,827,205,713,670 | no | https://www.mapillary.com/app/?pKey=292827205713670&focus=photo | random sample and manual label | Tarazona de Aragón | 1,724,796,233 | Spain | Europe | 41.790525 | -1.75981 | 2016-11-01 12:00:15.479000+01:00 | 396 | 19cpum69akigj5podygolw | train | img/4/32de4a41-4471-4e82-a7d2-52303eba3dab.jpeg |
52a51d9d-1d73-4656-a32c-c0bd08af8e22 | Mapillary | 893,070,377,931,574 | no | https://www.mapillary.com/app/?pKey=893070377931574&focus=photo | random sample and manual label | Tarazona de Aragón | 1,724,796,233 | Spain | Europe | 41.789633 | -1.767905 | 2016-11-01 12:01:27.281000+01:00 | 431 | 19cpum69akigj5podygolw | train | img/3/52a51d9d-1d73-4656-a32c-c0bd08af8e22.jpeg |
e5933b92-9815-4b62-b66a-e0399cddf780 | Mapillary | 569,454,580,702,017 | no | https://www.mapillary.com/app/?pKey=569454580702017&focus=photo | random sample and manual label | Tarazona de Aragón | 1,724,796,233 | Spain | Europe | 41.790759 | -1.766591 | 2018-08-05 11:33:52.184000+02:00 | 11 | J63JR0B5QM6pfhxWwj9IWA | train | img/6/e5933b92-9815-4b62-b66a-e0399cddf780.jpeg |
df44af56-3592-4b6f-af2b-2c88a37cec74 | Mapillary | 289,703,232,821,034 | no | https://www.mapillary.com/app/?pKey=289703232821034&focus=photo | random sample and manual label | Tarazona de Aragón | 1,724,796,233 | Spain | Europe | 41.785076 | -1.766477 | 2017-07-02 14:03:03.764000+02:00 | 35 | eo1Pec9DyI5lxwa4KhvwXw | train | img/6/df44af56-3592-4b6f-af2b-2c88a37cec74.jpeg |
fdd50149-4736-4946-8fcd-e066c56f6ac9 | Mapillary | 971,359,846,736,761 | no | https://www.mapillary.com/app/?pKey=971359846736761&focus=photo | random sample and manual label | Tarazona de Aragón | 1,724,796,233 | Spain | Europe | 41.790066 | -1.767521 | 2016-11-01 16:57:08.387000+01:00 | 26 | K-ILLX1_HQqfj3Z1pNCB9Q | train | img/3/fdd50149-4736-4946-8fcd-e066c56f6ac9.jpeg |
141fd713-5bbc-48ce-a95d-8ec503919be5 | Mapillary | 825,568,588,354,414 | no | https://www.mapillary.com/app/?pKey=825568588354414&focus=photo | random sample and manual label | Tarazona de Aragón | 1,724,796,233 | Spain | Europe | 41.784521 | -1.760031 | 2017-07-02 14:03:47.115000+02:00 | 78 | eo1Pec9DyI5lxwa4KhvwXw | train | img/3/141fd713-5bbc-48ce-a95d-8ec503919be5.jpeg |
5eb9a153-81c2-437c-a7c2-494ab474dad2 | Mapillary | 270,036,261,481,904 | no | https://www.mapillary.com/app/?pKey=270036261481904&focus=photo | random sample and manual label | Tarazona de Aragón | 1,724,796,233 | Spain | Europe | 41.784555 | -1.76113 | 2017-07-02 14:03:39.031000+02:00 | 70 | eo1Pec9DyI5lxwa4KhvwXw | train | img/1/5eb9a153-81c2-437c-a7c2-494ab474dad2.jpeg |
6707bb77-44cd-41bb-bebc-83fea443d9db | Mapillary | 825,708,831,675,475 | no | https://www.mapillary.com/app/?pKey=825708831675475&focus=photo | random sample and manual label | Tarazona de Aragón | 1,724,796,233 | Spain | Europe | 41.791134 | -1.766039 | 2016-11-01 16:57:19.262000+01:00 | 37 | K-ILLX1_HQqfj3Z1pNCB9Q | train | img/6/6707bb77-44cd-41bb-bebc-83fea443d9db.jpeg |
0ef75504-f5c2-4c86-811d-39aca429291f | Mapillary | 373,767,707,225,320 | no | https://www.mapillary.com/app/?pKey=373767707225320&focus=photo | random sample and manual label | Tarazona de Aragón | 1,724,796,233 | Spain | Europe | 41.790222 | -1.767087 | 2016-11-01 12:01:18.774000+01:00 | 427 | 19cpum69akigj5podygolw | train | img/4/0ef75504-f5c2-4c86-811d-39aca429291f.jpeg |
42e8c905-c180-4cf7-99ba-f8195aeb3be5 | Mapillary | 146,806,674,059,957 | no | https://www.mapillary.com/app/?pKey=146806674059957&focus=photo | random sample and manual label | Tarazona de Aragón | 1,724,796,233 | Spain | Europe | 41.790896 | -1.761716 | 2016-11-01 12:00:25.840000+01:00 | 401 | 19cpum69akigj5podygolw | train | img/5/42e8c905-c180-4cf7-99ba-f8195aeb3be5.jpeg |
84807902-c117-49cf-857d-d63541ed137b | Mapillary | 798,385,614,447,860 | no | https://www.mapillary.com/app/?pKey=798385614447860&focus=photo | random sample and manual label | Tarazona de Aragón | 1,724,796,233 | Spain | Europe | 41.790222 | -1.767342 | 2018-08-05 11:33:58.213000+02:00 | 16 | J63JR0B5QM6pfhxWwj9IWA | train | img/5/84807902-c117-49cf-857d-d63541ed137b.jpeg |
1dacc914-cd74-4970-9a89-20b440c2ea5c | Mapillary | 304,339,664,403,173 | no | https://www.mapillary.com/app/?pKey=304339664403173&focus=photo | random sample and manual label | Tarazona de Aragón | 1,724,796,233 | Spain | Europe | 41.784861 | -1.764948 | 2017-07-02 14:03:12.794000+02:00 | 44 | eo1Pec9DyI5lxwa4KhvwXw | train | img/4/1dacc914-cd74-4970-9a89-20b440c2ea5c.jpeg |
b6516ab0-da81-4fe9-8d42-cb77c9937bf2 | Mapillary | 215,515,886,644,180 | no | https://www.mapillary.com/app/?pKey=215515886644180&focus=photo | random sample and manual label | Tarazona de Aragón | 1,724,796,233 | Spain | Europe | 41.784752 | -1.764151 | 2017-07-02 14:03:17.798000+02:00 | 49 | eo1Pec9DyI5lxwa4KhvwXw | train | img/6/b6516ab0-da81-4fe9-8d42-cb77c9937bf2.jpeg |
e19781ee-c0b7-40a0-8357-8f8abbb4bece | Mapillary | 207,663,590,941,956 | no | https://www.mapillary.com/app/?pKey=207663590941956&focus=photo | random sample and manual label | Tarazona de Aragón | 1,724,796,233 | Spain | Europe | 41.790154 | -1.767386 | 2016-11-01 16:57:09.421000+01:00 | 27 | K-ILLX1_HQqfj3Z1pNCB9Q | train | img/3/e19781ee-c0b7-40a0-8357-8f8abbb4bece.jpeg |
7680f8b9-6b9b-48c7-ab73-e18537ec7336 | Mapillary | 1,107,543,566,418,319 | no | https://www.mapillary.com/app/?pKey=1107543566418319&focus=photo | random sample and manual label | Northallerton | 1,826,697,671 | United Kingdom | Europe | 54.326377 | -1.400904 | 2018-05-23 15:26:02.529000+01:00 | 630 | 924f2559-43c3-478e-b52a-bad0a1e78967 | train | img/6/7680f8b9-6b9b-48c7-ab73-e18537ec7336.jpeg |
f4a6495c-9899-4b87-913c-58f044135562 | Mapillary | 157,589,106,369,935 | no | https://www.mapillary.com/app/?pKey=157589106369935&focus=photo | random sample and manual label | Northallerton | 1,826,697,671 | United Kingdom | Europe | 54.326032 | -1.399915 | 2018-05-23 15:25:58.529000+01:00 | 626 | 924f2559-43c3-478e-b52a-bad0a1e78967 | train | img/6/f4a6495c-9899-4b87-913c-58f044135562.jpeg |
65a28401-03df-4ed8-8fa3-825255be0fa2 | Mapillary | 487,109,565,864,184 | no | https://www.mapillary.com/app/?pKey=487109565864184&focus=photo | random sample and manual label | Northallerton | 1,826,697,671 | United Kingdom | Europe | 54.326308 | -1.400644 | 2018-05-23 15:26:01.529000+01:00 | 629 | 924f2559-43c3-478e-b52a-bad0a1e78967 | train | img/4/65a28401-03df-4ed8-8fa3-825255be0fa2.jpeg |
10bf6ad1-a3bc-4281-a2a0-56e51172c365 | Mapillary | 313,601,323,534,233 | no | https://www.mapillary.com/app/?pKey=313601323534233&focus=photo | random sample and manual label | Northallerton | 1,826,697,671 | United Kingdom | Europe | 54.325386 | -1.39644 | 2018-05-23 15:25:44.530000+01:00 | 612 | 924f2559-43c3-478e-b52a-bad0a1e78967 | train | img/2/10bf6ad1-a3bc-4281-a2a0-56e51172c365.jpeg |
3b60ab1b-1e73-48e0-9583-2a15a8d44321 | Mapillary | 246,478,903,924,447 | no | https://www.mapillary.com/app/?pKey=246478903924447&focus=photo | random sample and manual label | Northallerton | 1,826,697,671 | United Kingdom | Europe | 54.325788 | -1.39916 | 2018-05-23 15:25:55.529000+01:00 | 623 | 924f2559-43c3-478e-b52a-bad0a1e78967 | train | img/4/3b60ab1b-1e73-48e0-9583-2a15a8d44321.jpeg |
29200d65-7724-4b15-83b8-54a525f5596f | Mapillary | 862,169,824,334,527 | no | https://www.mapillary.com/app/?pKey=862169824334527&focus=photo | random sample and manual label | Northallerton | 1,826,697,671 | United Kingdom | Europe | 54.326443 | -1.401146 | 2018-05-23 15:26:03.529000+01:00 | 631 | 924f2559-43c3-478e-b52a-bad0a1e78967 | train | img/5/29200d65-7724-4b15-83b8-54a525f5596f.jpeg |
ea70082a-9ec4-4ece-8504-5084f3883471 | Mapillary | 802,672,190,683,499 | no | https://www.mapillary.com/app/?pKey=802672190683499&focus=photo | random sample and manual label | Northallerton | 1,826,697,671 | United Kingdom | Europe | 54.325657 | -1.398363 | 2018-05-23 15:25:52.529000+01:00 | 620 | 924f2559-43c3-478e-b52a-bad0a1e78967 | train | img/3/ea70082a-9ec4-4ece-8504-5084f3883471.jpeg |
ed24d625-9831-472c-bf70-4ee5384d9a05 | Mapillary | 183,449,380,312,477 | no | https://www.mapillary.com/app/?pKey=183449380312477&focus=photo | random sample and manual label | Northallerton | 1,826,697,671 | United Kingdom | Europe | 54.324945 | -1.39567 | 2018-05-23 15:25:40.529000+01:00 | 608 | 924f2559-43c3-478e-b52a-bad0a1e78967 | train | img/2/ed24d625-9831-472c-bf70-4ee5384d9a05.jpeg |
0db6166d-2c15-43f3-b102-c2333d330c1d | Mapillary | 1,410,685,509,292,358 | no | https://www.mapillary.com/app/?pKey=1410685509292358&focus=photo | random sample and manual label | Northallerton | 1,826,697,671 | United Kingdom | Europe | 54.326226 | -1.400373 | 2018-05-23 15:26:00.529000+01:00 | 628 | 924f2559-43c3-478e-b52a-bad0a1e78967 | train | img/5/0db6166d-2c15-43f3-b102-c2333d330c1d.jpeg |
adb29d75-518b-4624-be5c-6d7f0aefceb8 | Mapillary | 490,878,362,031,890 | no | https://www.mapillary.com/app/?pKey=490878362031890&focus=photo | random sample and manual label | Northallerton | 1,826,697,671 | United Kingdom | Europe | 54.32548 | -1.396653 | 2018-05-23 15:25:45.530000+01:00 | 613 | 924f2559-43c3-478e-b52a-bad0a1e78967 | train | img/2/adb29d75-518b-4624-be5c-6d7f0aefceb8.jpeg |
8cfedd0e-2bf6-49d0-97e7-939270bd4d65 | Mapillary | 148,004,727,295,582 | no | https://www.mapillary.com/app/?pKey=148004727295582&focus=photo | random sample and manual label | Northallerton | 1,826,697,671 | United Kingdom | Europe | 54.32568 | -1.398631 | 2018-05-23 15:25:53.529000+01:00 | 621 | 924f2559-43c3-478e-b52a-bad0a1e78967 | train | img/6/8cfedd0e-2bf6-49d0-97e7-939270bd4d65.jpeg |
91e8af0b-52f8-4c4e-9a96-58e0ba496091 | Mapillary | 152,595,283,499,193 | no | https://www.mapillary.com/app/?pKey=152595283499193&focus=photo | random sample and manual label | Northallerton | 1,826,697,671 | United Kingdom | Europe | 54.32517 | -1.396052 | 2018-05-23 15:25:42.530000+01:00 | 610 | 924f2559-43c3-478e-b52a-bad0a1e78967 | train | img/4/91e8af0b-52f8-4c4e-9a96-58e0ba496091.jpeg |
1341eb2b-86a3-4039-8a92-ac643cf4d663 | Mapillary | 589,254,562,463,489 | no | https://www.mapillary.com/app/?pKey=589254562463489&focus=photo | random sample and manual label | Northallerton | 1,826,697,671 | United Kingdom | Europe | 54.325053 | -1.395853 | 2018-05-23 15:25:41.530000+01:00 | 609 | 924f2559-43c3-478e-b52a-bad0a1e78967 | train | img/1/1341eb2b-86a3-4039-8a92-ac643cf4d663.jpeg |
51f94ad7-64ae-423b-b0c0-7f6c38707673 | Mapillary | 1,893,685,710,795,509 | no | https://www.mapillary.com/app/?pKey=1893685710795509&focus=photo | random sample and manual label | Northallerton | 1,826,697,671 | United Kingdom | Europe | 54.325874 | -1.399415 | 2018-05-23 15:25:56.529000+01:00 | 624 | 924f2559-43c3-478e-b52a-bad0a1e78967 | train | img/3/51f94ad7-64ae-423b-b0c0-7f6c38707673.jpeg |
34b5765b-d540-40a9-97a9-040fac67fe9b | Mapillary | 144,570,840,982,973 | no | https://www.mapillary.com/app/?pKey=144570840982973&focus=photo | random sample and manual label | Northallerton | 1,826,697,671 | United Kingdom | Europe | 54.325657 | -1.398095 | 2018-05-23 15:25:51.529000+01:00 | 619 | 924f2559-43c3-478e-b52a-bad0a1e78967 | train | img/1/34b5765b-d540-40a9-97a9-040fac67fe9b.jpeg |
344cfc79-e839-4a25-b8bf-a1683c399431 | Mapillary | 589,979,889,071,874 | no | https://www.mapillary.com/app/?pKey=589979889071874&focus=photo | random sample and manual label | Northallerton | 1,826,697,671 | United Kingdom | Europe | 54.326109 | -1.400153 | 2018-05-23 15:25:59.529000+01:00 | 627 | 924f2559-43c3-478e-b52a-bad0a1e78967 | train | img/2/344cfc79-e839-4a25-b8bf-a1683c399431.jpeg |
23671806-354f-4e4a-b562-d45d8599d558 | Mapillary | 1,187,015,858,408,081 | no | https://www.mapillary.com/app/?pKey=1187015858408081&focus=photo | random sample and manual label | Diego de Almagro | 1,152,585,849 | Chile | South America | -26.94132 | -69.027472 | 2020-03-08 11:34:15.824000-03:00 | 93 | b1a10y0215fx4lcq05cbs9 | train | img/1/23671806-354f-4e4a-b562-d45d8599d558.jpeg |
fc4d27cb-96fe-4216-95a6-2d3788988130 | Mapillary | 776,308,026,609,745 | no | https://www.mapillary.com/app/?pKey=776308026609745&focus=photo | random sample and manual label | Diego de Almagro | 1,152,585,849 | Chile | South America | -26.940172 | -69.026643 | 2020-03-08 11:34:24.848000-03:00 | 101 | b1a10y0215fx4lcq05cbs9 | train | img/2/fc4d27cb-96fe-4216-95a6-2d3788988130.jpeg |
078b3e17-1958-4311-b0cd-9a56e7f2ff38 | Mapillary | 2,834,691,673,447,367 | no | https://www.mapillary.com/app/?pKey=2834691673447367&focus=photo | random sample and manual label | Diego de Almagro | 1,152,585,849 | Chile | South America | -26.940408 | -69.026814 | 2020-03-08 11:34:22.661000-03:00 | 99 | b1a10y0215fx4lcq05cbs9 | train | img/4/078b3e17-1958-4311-b0cd-9a56e7f2ff38.jpeg |
3e6c47c0-0037-4975-9543-e1a0976bf9de | Mapillary | 137,476,115,036,772 | no | https://www.mapillary.com/app/?pKey=137476115036772&focus=photo | random sample and manual label | Diego de Almagro | 1,152,585,849 | Chile | South America | -26.941014 | -69.027254 | 2020-03-08 11:34:18.031000-03:00 | 95 | b1a10y0215fx4lcq05cbs9 | train | img/4/3e6c47c0-0037-4975-9543-e1a0976bf9de.jpeg |
d860cf05-a360-4944-84f7-74119e951c6a | Mapillary | 372,993,500,804,918 | no | https://www.mapillary.com/app/?pKey=372993500804918&focus=photo | random sample and manual label | Diego de Almagro | 1,152,585,849 | Chile | South America | -26.939852 | -69.026421 | 2020-03-08 11:34:28.193000-03:00 | 104 | b1a10y0215fx4lcq05cbs9 | train | img/2/d860cf05-a360-4944-84f7-74119e951c6a.jpeg |
525eab8e-a252-4c1d-83ae-718122ca07ba | Mapillary | 314,245,133,403,370 | no | https://www.mapillary.com/app/?pKey=314245133403370&focus=photo | random sample and manual label | Diego de Almagro | 1,152,585,849 | Chile | South America | -26.941928 | -69.027908 | 2020-03-08 11:34:11.384000-03:00 | 89 | b1a10y0215fx4lcq05cbs9 | train | img/5/525eab8e-a252-4c1d-83ae-718122ca07ba.jpeg |
ec6b0fee-1c3b-4a5e-ab39-f541bace672b | Mapillary | 162,337,479,174,809 | no | https://www.mapillary.com/app/?pKey=162337479174809&focus=photo | random sample and manual label | Diego de Almagro | 1,152,585,849 | Chile | South America | -26.940679 | -69.027012 | 2020-03-08 11:34:20.488000-03:00 | 97 | b1a10y0215fx4lcq05cbs9 | train | img/1/ec6b0fee-1c3b-4a5e-ab39-f541bace672b.jpeg |
e42c10e5-5c50-4fa4-bbeb-87e18c5b3ca9 | Mapillary | 222,493,512,641,912 | no | https://www.mapillary.com/app/?pKey=222493512641912&focus=photo | random sample and manual label | Diego de Almagro | 1,152,585,849 | Chile | South America | -26.940539 | -69.02691 | 2020-03-08 11:34:21.558000-03:00 | 98 | b1a10y0215fx4lcq05cbs9 | train | img/3/e42c10e5-5c50-4fa4-bbeb-87e18c5b3ca9.jpeg |
63cefc7c-6a45-4323-a0bb-4ef592a90959 | Mapillary | 673,607,083,434,957 | no | https://www.mapillary.com/app/?pKey=673607083434957&focus=photo | random sample and manual label | Diego de Almagro | 1,152,585,849 | Chile | South America | -26.941472 | -69.027581 | 2020-03-08 11:34:14.721000-03:00 | 92 | b1a10y0215fx4lcq05cbs9 | train | img/1/63cefc7c-6a45-4323-a0bb-4ef592a90959.jpeg |
8c71ae95-4477-4c21-a10b-2b3b823499e7 | Mapillary | 226,839,982,132,294 | no | https://www.mapillary.com/app/?pKey=226839982132294&focus=photo | random sample and manual label | Diego de Almagro | 1,152,585,849 | Chile | South America | -26.942077 | -69.028012 | 2020-03-08 11:34:10.293000-03:00 | 88 | b1a10y0215fx4lcq05cbs9 | train | img/2/8c71ae95-4477-4c21-a10b-2b3b823499e7.jpeg |
f7ff7c33-0b00-4f3f-9a5d-1623dbc2588c | Mapillary | 328,364,788,704,472 | no | https://www.mapillary.com/app/?pKey=328364788704472&focus=photo | random sample and manual label | Diego de Almagro | 1,152,585,849 | Chile | South America | -26.939951 | -69.02649 | 2020-03-08 11:34:27.079000-03:00 | 103 | b1a10y0215fx4lcq05cbs9 | train | img/3/f7ff7c33-0b00-4f3f-9a5d-1623dbc2588c.jpeg |
a33226c8-6791-4226-b884-c2d9db0c306f | Mapillary | 1,062,304,020,965,452 | no | https://www.mapillary.com/app/?pKey=1062304020965452&focus=photo | random sample and manual label | Diego de Almagro | 1,152,585,849 | Chile | South America | -26.940862 | -69.027145 | 2020-03-08 11:34:19.118000-03:00 | 96 | b1a10y0215fx4lcq05cbs9 | train | img/6/a33226c8-6791-4226-b884-c2d9db0c306f.jpeg |
b90c5bff-9294-4b02-aeba-24ae97cbbf45 | Mapillary | 386,487,156,034,164 | no | https://www.mapillary.com/app/?pKey=386487156034164&focus=photo | random sample and manual label | Diego de Almagro | 1,152,585,849 | Chile | South America | -26.939673 | -69.026289 | 2020-03-08 11:34:30.383000-03:00 | 106 | b1a10y0215fx4lcq05cbs9 | train | img/4/b90c5bff-9294-4b02-aeba-24ae97cbbf45.jpeg |
ad74f76a-1733-44d9-ae3c-346f7b0f7530 | Mapillary | 566,971,930,934,876 | no | https://www.mapillary.com/app/?pKey=566971930934876&focus=photo | random sample and manual label | Diego de Almagro | 1,152,585,849 | Chile | South America | -26.940057 | -69.026562 | 2020-03-08 11:34:25.986000-03:00 | 102 | b1a10y0215fx4lcq05cbs9 | train | img/2/ad74f76a-1733-44d9-ae3c-346f7b0f7530.jpeg |
08f90444-f6e7-4e22-a3e2-b7334e59ac0e | Mapillary | 1,179,928,785,792,813 | no | https://www.mapillary.com/app/?pKey=1179928785792813&focus=photo | random sample and manual label | Diego de Almagro | 1,152,585,849 | Chile | South America | -26.941623 | -69.027689 | 2020-03-08 11:34:13.619000-03:00 | 91 | b1a10y0215fx4lcq05cbs9 | train | img/5/08f90444-f6e7-4e22-a3e2-b7334e59ac0e.jpeg |
e796e615-8e7a-48e4-b24f-57871b0bca80 | Mapillary | 2,230,769,243,726,162 | no | https://www.mapillary.com/app/?pKey=2230769243726162&focus=photo | random sample and manual label | Diego de Almagro | 1,152,585,849 | Chile | South America | -26.941771 | -69.027796 | 2020-03-08 11:34:12.533000-03:00 | 90 | b1a10y0215fx4lcq05cbs9 | train | img/1/e796e615-8e7a-48e4-b24f-57871b0bca80.jpeg |
ca2d565f-d567-4b96-a5bb-7b481e0faae3 | Mapillary | 299,381,561,741,730 | no | https://www.mapillary.com/app/?pKey=299381561741730&focus=photo | random sample and manual label | Diego de Almagro | 1,152,585,849 | Chile | South America | -26.939763 | -69.026355 | 2020-03-08 11:34:29.280000-03:00 | 105 | b1a10y0215fx4lcq05cbs9 | train | img/4/ca2d565f-d567-4b96-a5bb-7b481e0faae3.jpeg |
10a3d5c8-7b4d-471b-8252-26620849b96a | Mapillary | 472,341,480,694,575 | no | https://www.mapillary.com/app/?pKey=472341480694575&focus=photo | random sample and manual label | Diego de Almagro | 1,152,585,849 | Chile | South America | -26.941168 | -69.027364 | 2020-03-08 11:34:16.927000-03:00 | 94 | b1a10y0215fx4lcq05cbs9 | train | img/1/10a3d5c8-7b4d-471b-8252-26620849b96a.jpeg |
9c3c8431-e002-4156-aa01-97578a51a6c8 | Mapillary | 2,989,949,317,912,042 | no | https://www.mapillary.com/app/?pKey=2989949317912042&focus=photo | random sample and manual label | Diego de Almagro | 1,152,585,849 | Chile | South America | -26.940284 | -69.026724 | 2020-03-08 11:34:23.798000-03:00 | 100 | b1a10y0215fx4lcq05cbs9 | train | img/4/9c3c8431-e002-4156-aa01-97578a51a6c8.jpeg |
d91aa51d-698c-4640-b7a9-2d2d9a81dceb | Mapillary | 445,746,653,393,222 | no | https://www.mapillary.com/app/?pKey=445746653393222&focus=photo | random sample and manual label | Zevenaar | 1,528,993,139 | Netherlands | Europe | 51.939453 | 6.056633 | 2017-01-25 14:32:28+01:00 | 362 | r6Yg1awvf9r55_7BzKhbHw | train | img/2/d91aa51d-698c-4640-b7a9-2d2d9a81dceb.jpeg |
66ca0c7e-06e5-4d0d-8f84-d207bddb1de7 | Mapillary | 1,991,049,161,070,737 | no | https://www.mapillary.com/app/?pKey=1991049161070737&focus=photo | random sample and manual label | La Banda | 1,032,317,566 | Argentina | South America | -27.755321 | -64.267196 | 2019-12-07 19:20:56.809000-03:00 | 57 | rrmvd772t0ugqagqe8nkli | train | img/3/66ca0c7e-06e5-4d0d-8f84-d207bddb1de7.jpeg |
6513e96e-964a-47fa-8936-04f6bb78a056 | Mapillary | 140,759,084,706,540 | no | https://www.mapillary.com/app/?pKey=140759084706540&focus=photo | random sample and manual label | Santiago del Estero | 1,032,492,280 | Argentina | South America | -27.755931 | -64.267466 | 2019-12-07 19:20:50.882000-03:00 | 54 | rrmvd772t0ugqagqe8nkli | train | img/5/6513e96e-964a-47fa-8936-04f6bb78a056.jpeg |
eb72852c-7403-4bf4-b997-4eb495457504 | Mapillary | 328,315,691,972,787 | no | https://www.mapillary.com/app/?pKey=328315691972787&focus=photo | random sample and manual label | Santiago del Estero | 1,032,492,280 | Argentina | South America | -27.756539 | -64.267856 | 2019-12-07 19:20:44.887000-03:00 | 51 | rrmvd772t0ugqagqe8nkli | train | img/5/eb72852c-7403-4bf4-b997-4eb495457504.jpeg |
d4128464-7f65-49ad-8baa-40fbe4416dc5 | Mapillary | 194,211,242,443,515 | no | https://www.mapillary.com/app/?pKey=194211242443515&focus=photo | random sample and manual label | La Banda | 1,032,317,566 | Argentina | South America | -27.755134 | -64.267141 | 2019-12-07 19:20:58.858000-03:00 | 58 | rrmvd772t0ugqagqe8nkli | train | img/3/d4128464-7f65-49ad-8baa-40fbe4416dc5.jpeg |
0c907f6a-eacc-4a7e-8a1f-7e1c8f60dd33 | Mapillary | 794,360,608,140,867 | no | https://www.mapillary.com/app/?pKey=794360608140867&focus=photo | random sample and manual label | Santiago del Estero | 1,032,492,280 | Argentina | South America | -27.756364 | -64.267737 | 2019-12-07 19:20:46.735000-03:00 | 52 | rrmvd772t0ugqagqe8nkli | train | img/1/0c907f6a-eacc-4a7e-8a1f-7e1c8f60dd33.jpeg |
0dcb1428-bfdd-49be-87e3-8e27366d6a6a | Mapillary | 396,201,244,889,620 | no | https://www.mapillary.com/app/?pKey=396201244889620&focus=photo | random sample and manual label | La Banda | 1,032,317,566 | Argentina | South America | -27.755734 | -64.267361 | 2019-12-07 19:20:52.712000-03:00 | 55 | rrmvd772t0ugqagqe8nkli | train | img/4/0dcb1428-bfdd-49be-87e3-8e27366d6a6a.jpeg |
fc096580-70d5-45ad-954f-f1510253e1db | Mapillary | 466,867,207,712,589 | no | https://www.mapillary.com/app/?pKey=466867207712589&focus=photo | random sample and manual label | Santiago del Estero | 1,032,492,280 | Argentina | South America | -27.756153 | -64.267602 | 2019-12-07 19:20:48.809000-03:00 | 53 | rrmvd772t0ugqagqe8nkli | train | img/4/fc096580-70d5-45ad-954f-f1510253e1db.jpeg |
a8a1f331-7991-4999-b7a2-bdae2a67b356 | Mapillary | 4,290,765,970,980,868 | no | https://www.mapillary.com/app/?pKey=4290765970980868&focus=photo | random sample and manual label | La Banda | 1,032,317,566 | Argentina | South America | -27.755524 | -64.267264 | 2019-12-07 19:20:54.743000-03:00 | 56 | rrmvd772t0ugqagqe8nkli | train | img/5/a8a1f331-7991-4999-b7a2-bdae2a67b356.jpeg |
6553f862-a7e1-4ee2-902d-78b3cf4950a6 | Mapillary | 177,212,604,287,368 | no | https://www.mapillary.com/app/?pKey=177212604287368&focus=photo | random sample and manual label | Lavāsān | 1,364,266,184 | Iran | Asia | 36.175699 | 51.314296 | 2019-07-03 22:26:58.272000+04:30 | 312 | p8dkgr1jyss78nbi3z9jy6 | train | img/5/6553f862-a7e1-4ee2-902d-78b3cf4950a6.jpeg |
efae1f6b-cc95-4298-88c9-f0bb989b9359 | Mapillary | 490,550,372,186,873 | no | https://www.mapillary.com/app/?pKey=490550372186873&focus=photo | random sample and manual label | Lavāsān | 1,364,266,184 | Iran | Asia | 36.175471 | 51.314505 | 2019-07-03 22:26:55.948000+04:30 | 296 | p8dkgr1jyss78nbi3z9jy6 | train | img/3/efae1f6b-cc95-4298-88c9-f0bb989b9359.jpeg |
0cbf16e4-7c28-4630-a210-f074ac4fc57f | Mapillary | 492,847,705,290,269 | no | https://www.mapillary.com/app/?pKey=492847705290269&focus=photo | random sample and manual label | Lavāsān | 1,364,266,184 | Iran | Asia | 36.176811 | 51.314602 | 2019-07-03 22:27:06.048000+04:30 | 378 | p8dkgr1jyss78nbi3z9jy6 | train | img/2/0cbf16e4-7c28-4630-a210-f074ac4fc57f.jpeg |
929cd75e-d14b-4d09-a60f-fac1c2d00c69 | Mapillary | 802,422,840,388,852 | no | https://www.mapillary.com/app/?pKey=802422840388852&focus=photo | random sample and manual label | Lavāsān | 1,364,266,184 | Iran | Asia | 36.176136 | 51.314257 | 2019-07-03 22:27:01.546000+04:30 | 337 | p8dkgr1jyss78nbi3z9jy6 | train | img/6/929cd75e-d14b-4d09-a60f-fac1c2d00c69.jpeg |
7b122b5e-092e-4c97-a612-59873c760dce | Mapillary | 465,823,671,377,372 | no | https://www.mapillary.com/app/?pKey=465823671377372&focus=photo | random sample and manual label | Lavāsān | 1,364,266,184 | Iran | Asia | 36.174634 | 51.315115 | 2019-07-03 22:26:48.605000+04:30 | 241 | p8dkgr1jyss78nbi3z9jy6 | train | img/1/7b122b5e-092e-4c97-a612-59873c760dce.jpeg |
4adffbff-55a5-4d8f-aae2-415b6166fc39 | Mapillary | 287,701,232,792,827 | no | https://www.mapillary.com/app/?pKey=287701232792827&focus=photo | random sample and manual label | Lavāsān | 1,364,266,184 | Iran | Asia | 36.176991 | 51.314614 | 2019-07-03 22:27:06.648000+04:30 | 388 | p8dkgr1jyss78nbi3z9jy6 | train | img/3/4adffbff-55a5-4d8f-aae2-415b6166fc39.jpeg |
ac62c362-018d-4f43-bc18-81b3f486b756 | Mapillary | 797,326,607,870,365 | no | https://www.mapillary.com/app/?pKey=797326607870365&focus=photo | random sample and manual label | Lavāsān | 1,364,266,184 | Iran | Asia | 36.1761 | 51.314243 | 2018-12-05 09:17:25.422000+03:30 | 39 | ki0cdixivdofra56yj6dvw | train | img/6/ac62c362-018d-4f43-bc18-81b3f486b756.jpeg |
bfaa9b3e-83ca-43a9-9f4d-ded2b3f433f7 | Mapillary | 832,471,700,683,937 | no | https://www.mapillary.com/app/?pKey=832471700683937&focus=photo | random sample and manual label | Lavāsān | 1,364,266,184 | Iran | Asia | 36.174745 | 51.315052 | 2019-07-03 22:26:49.415000+04:30 | 248 | p8dkgr1jyss78nbi3z9jy6 | train | img/5/bfaa9b3e-83ca-43a9-9f4d-ded2b3f433f7.jpeg |
fdf17967-046e-4fb8-9bfc-bf696ab37278 | Mapillary | 1,837,012,539,793,453 | no | https://www.mapillary.com/app/?pKey=1837012539793453&focus=photo | random sample and manual label | Lavāsān | 1,364,266,184 | Iran | Asia | 36.177316 | 51.314895 | 2019-07-03 22:27:09.160000+04:30 | 414 | p8dkgr1jyss78nbi3z9jy6 | train | img/1/fdf17967-046e-4fb8-9bfc-bf696ab37278.jpeg |
4da54df9-2c83-4598-aa43-288401221c0e | Mapillary | 225,768,142,245,135 | no | https://www.mapillary.com/app/?pKey=225768142245135&focus=photo | random sample and manual label | Lavāsān | 1,364,266,184 | Iran | Asia | 36.175652 | 51.31433 | 2019-07-03 22:26:57.829000+04:30 | 309 | p8dkgr1jyss78nbi3z9jy6 | train | img/5/4da54df9-2c83-4598-aa43-288401221c0e.jpeg |
53657d0e-9568-40f3-890f-0dce48dce0e4 | Mapillary | 938,627,560,272,189 | no | https://www.mapillary.com/app/?pKey=938627560272189&focus=photo | random sample and manual label | Lavāsān | 1,364,266,184 | Iran | Asia | 36.176398 | 51.314338 | 2019-07-03 22:27:03.282000+04:30 | 352 | p8dkgr1jyss78nbi3z9jy6 | train | img/4/53657d0e-9568-40f3-890f-0dce48dce0e4.jpeg |
9e788c80-353f-41c6-8d69-649e34f87b69 | Mapillary | 157,854,502,950,885 | no | https://www.mapillary.com/app/?pKey=157854502950885&focus=photo | random sample and manual label | Lavāsān | 1,364,266,184 | Iran | Asia | 36.175699 | 51.314318 | 2018-12-07 11:55:10.007000+03:30 | 234 | 8DL_SUCXSFS6V28z86I05g | train | img/4/9e788c80-353f-41c6-8d69-649e34f87b69.jpeg |
a8e609ac-c05d-46e5-b054-a6118753c110 | Mapillary | 371,005,134,311,065 | no | https://www.mapillary.com/app/?pKey=371005134311065&focus=photo | random sample and manual label | Lavāsān | 1,364,266,184 | Iran | Asia | 36.174738 | 51.315098 | 2018-12-07 11:55:01.707000+03:30 | 230 | 8DL_SUCXSFS6V28z86I05g | train | img/6/a8e609ac-c05d-46e5-b054-a6118753c110.jpeg |
ec75d0cd-5cb7-4456-8673-db6d9c9a5059 | Mapillary | 506,001,950,758,557 | no | https://www.mapillary.com/app/?pKey=506001950758557&focus=photo | random sample and manual label | Lavāsān | 1,364,266,184 | Iran | Asia | 36.175288 | 51.314623 | 2019-07-03 22:26:54.372000+04:30 | 284 | p8dkgr1jyss78nbi3z9jy6 | train | img/5/ec75d0cd-5cb7-4456-8673-db6d9c9a5059.jpeg |
f6d28c50-583f-48ec-b5cc-b433feeb6255 | Mapillary | 1,241,267,469,624,826 | no | https://www.mapillary.com/app/?pKey=1241267469624826&focus=photo | random sample and manual label | Lavāsān | 1,364,266,184 | Iran | Asia | 36.177414 | 51.315082 | 2019-07-03 22:27:10.539000+04:30 | 425 | p8dkgr1jyss78nbi3z9jy6 | train | img/1/f6d28c50-583f-48ec-b5cc-b433feeb6255.jpeg |
a7182672-b3aa-4095-b284-fd028601dbee | Mapillary | 334,357,738,032,528 | no | https://www.mapillary.com/app/?pKey=334357738032528&focus=photo | random sample and manual label | Debrecen | 1,348,460,698 | Hungary | Europe | 47.529854 | 21.639075 | 2017-12-02 13:36:08.161000+01:00 | 592 | 6zpr8o7931caqflwdwvqyh | train | img/6/a7182672-b3aa-4095-b284-fd028601dbee.jpeg |
639f1218-842f-40fb-8e92-7c6e951ec665 | Mapillary | 956,566,868,345,917 | no | https://www.mapillary.com/app/?pKey=956566868345917&focus=photo | random sample and manual label | West Haven | 1,840,004,852 | United States | North America | 41.275093 | -72.969314 | 2021-07-11 06:03:56.697000-04:00 | 379 | T9fD17IVwsiJFXevk2zOQC | train | img/5/639f1218-842f-40fb-8e92-7c6e951ec665.jpeg |
35d17b46-ac0a-4dea-a680-3ac2429b79fd | Mapillary | 2,971,229,786,468,848 | no | https://www.mapillary.com/app/?pKey=2971229786468848&focus=photo | random sample and manual label | Marmagao | 1,356,764,529 | India | Asia | 15.409954 | 73.794828 | 2019-03-20 10:31:29.489000+05:30 | 334 | hRHJfe-vSpW09EHd-mZdfw | train | img/5/35d17b46-ac0a-4dea-a680-3ac2429b79fd.jpeg |
d9928106-88a5-4aef-b941-2ae883b94c11 | Mapillary | 1,904,562,149,694,398 | no | https://www.mapillary.com/app/?pKey=1904562149694398&focus=photo | random sample and manual label | Brandon | 1,840,014,151 | United States | North America | 27.937607 | -82.307736 | 2014-08-22 10:57:19.266000-04:00 | 35 | W2d4fILDRvmCNFGYAdZRMA | train | img/1/d9928106-88a5-4aef-b941-2ae883b94c11.jpeg |
39b5fc03-d89d-46e2-9570-267c8adf6722 | Mapillary | 295,566,248,851,356 | no | https://www.mapillary.com/app/?pKey=295566248851356&focus=photo | random sample and manual label | Hanau | 1,276,550,409 | Germany | Europe | 50.129585 | 8.913147 | 2014-05-10 12:10:08+02:00 | 7 | T4fa3llpBHUx4tssFSKY8g | train | img/4/39b5fc03-d89d-46e2-9570-267c8adf6722.jpeg |
7f439743-bb56-4432-bb69-41526862a9f0 | Mapillary | 1,060,462,924,871,678 | no | https://www.mapillary.com/app/?pKey=1060462924871678&focus=photo | random sample and manual label | Gravatá | 1,076,214,495 | Brazil | South America | -8.196656 | -35.556843 | 2022-05-09 12:55:41.750000-03:00 | 196 | NAFJRE5ibGt3SxhkcPu7zp | train | img/6/7f439743-bb56-4432-bb69-41526862a9f0.jpeg |
0fc9c547-6889-4d9f-a824-63fac7c5c487 | Mapillary | 532,858,918,093,055 | no | https://www.mapillary.com/app/?pKey=532858918093055&focus=photo | random sample and manual label | Kansas City | 1,840,008,535 | United States | North America | 39.120784 | -94.564594 | 2018-10-06 15:59:41.631000-05:00 | 354 | pwvgr0x6j7t98r5mgz10iu | train | img/2/0fc9c547-6889-4d9f-a824-63fac7c5c487.jpeg |
ed93f81e-49f7-4c45-a0a7-37e9c2b1c55d | Mapillary | 278,652,547,253,159 | no | https://www.mapillary.com/app/?pKey=278652547253159&focus=photo | random sample and manual label | Hanau | 1,276,550,409 | Germany | Europe | 50.127292 | 8.909284 | 2014-06-03 13:02:29+02:00 | 105 | 0IX5Le4znvAsThyCpr-lEA | train | img/4/ed93f81e-49f7-4c45-a0a7-37e9c2b1c55d.jpeg |
8f9ea558-cfad-468b-a3bf-5ec694a20c8f | Mapillary | 494,139,672,000,209 | no | https://www.mapillary.com/app/?pKey=494139672000209&focus=photo | random sample and manual label | Dearborn | 1,840,003,969 | United States | North America | 42.310621 | -83.226446 | 2017-11-07 14:10:02.085000-05:00 | 137 | ji1xns2yADqHzy0QSbo5qA | train | img/6/8f9ea558-cfad-468b-a3bf-5ec694a20c8f.jpeg |
8449bd63-b4d9-4bc1-ab45-96100e1aca13 | Mapillary | 303,878,937,877,062 | no | https://www.mapillary.com/app/?pKey=303878937877062&focus=photo | random sample and manual label | Cancún | 1,484,010,310 | Mexico | North America | 21.154357 | -86.84377 | 2020-09-22 08:04:17-05:00 | 168 | brm2czcd21tfc961qqzijc | train | img/5/8449bd63-b4d9-4bc1-ab45-96100e1aca13.jpeg |
c022c452-038a-4996-8528-7124b5850487 | Mapillary | 985,639,815,306,934 | no | https://www.mapillary.com/app/?pKey=985639815306934&focus=photo | random sample and manual label | Helsinki | 1,246,177,997 | Finland | Europe | 60.184795 | 24.933316 | 2018-07-16 17:38:29+03:00 | 781 | bGfHXwPiEbBpwhBGdy5AJQ | train | img/6/c022c452-038a-4996-8528-7124b5850487.jpeg |
161f0b09-9d27-40e8-bafb-a81c649b8395 | Mapillary | 525,030,598,525,906 | no | https://www.mapillary.com/app/?pKey=525030598525906&focus=photo | random sample and manual label | Monterrey | 1,484,559,591 | Mexico | North America | 25.66423 | -100.302681 | 2020-03-02 11:38:57.590000-06:00 | 1 | 4h7wwyp75397fq9fhb3wd5 | train | img/1/161f0b09-9d27-40e8-bafb-a81c649b8395.jpeg |
5765de71-a626-4fb7-a958-1b2f8f520db9 | Mapillary | 222,088,019,335,040 | no | https://www.mapillary.com/app/?pKey=222088019335040&focus=photo | random sample and manual label | Monterrey | 1,484,559,591 | Mexico | North America | 25.670965 | -100.30215 | 2020-02-27 11:09:03.590000-06:00 | 50 | dsr0e3fpbmebuqdok7gkzn | train | img/5/5765de71-a626-4fb7-a958-1b2f8f520db9.jpeg |
d92e7d05-743b-4aa5-902f-6b912298aa3f | Mapillary | 255,923,762,987,787 | no | https://www.mapillary.com/app/?pKey=255923762987787&focus=photo | random sample and manual label | Moscow | 1,643,318,494 | Russia | Europe | 55.762155 | 37.624172 | 2020-08-04 09:00:31.320000+03:00 | 64 | 8nltapnyqijt9gy0c1godw | train | img/2/d92e7d05-743b-4aa5-902f-6b912298aa3f.jpeg |
5069bc14-817d-4903-be63-1838451fc02a | Mapillary | 3,831,013,896,997,692 | no | https://www.mapillary.com/app/?pKey=3831013896997692&focus=photo | random sample and manual label | Orléans | 1,250,441,405 | France | Europe | 47.906371 | 1.910022 | 2020-09-18 17:45:32.734000+02:00 | 498 | emszjijqrfe4q6j92z272e | train | img/3/5069bc14-817d-4903-be63-1838451fc02a.jpeg |
5358d5b0-e8fc-47db-b358-6653357aa028 | Mapillary | 513,854,883,289,741 | no | https://www.mapillary.com/app/?pKey=513854883289741&focus=photo | random sample and manual label | Philadelphia | 1,840,000,673 | United States | North America | 40.000272 | -75.142429 | 2018-08-28 15:11:24.296000-04:00 | 238 | 6pwhicb6bibv8pgtug1hwa | train | img/5/5358d5b0-e8fc-47db-b358-6653357aa028.jpeg |
688e8214-a78f-4a64-9367-75b058d1ac10 | Mapillary | 781,757,492,512,428 | no | https://www.mapillary.com/app/?pKey=781757492512428&focus=photo | random sample and manual label | Redmond | 1,840,019,835 | United States | North America | 47.670803 | -122.106836 | 2018-07-31 08:10:42.582000-07:00 | 117 | 1px35d4t4rxujmfm37mcw5 | train | img/2/688e8214-a78f-4a64-9367-75b058d1ac10.jpeg |
c1a438cb-f031-44e6-a880-994a1b0a066e | Mapillary | 794,251,901,520,558 | no | https://www.mapillary.com/app/?pKey=794251901520558&focus=photo | random sample and manual label | Amsterdam | 1,528,355,309 | Netherlands | Europe | 52.373592 | 4.881508 | 2017-03-04 16:55:00.575000+01:00 | 458 | I92ZRcEgYjCcSPgPuVZyUA | train | img/6/c1a438cb-f031-44e6-a880-994a1b0a066e.jpeg |
00de81fc-d5d7-463b-82f2-0ab1b9f2f6d3 | Mapillary | 155,626,406,521,648 | no | https://www.mapillary.com/app/?pKey=155626406521648&focus=photo | random sample and manual label | Donostia | 1,724,910,555 | Spain | Europe | 43.31852 | -1.979218 | 2020-04-23 08:44:48.736000+02:00 | 56 | 8stts5inztcuh3yilgzlei | train | img/3/00de81fc-d5d7-463b-82f2-0ab1b9f2f6d3.jpeg |
6c8d3fca-d9da-4e41-8aad-608b13a5a810 | Mapillary | 520,744,618,938,239 | no | https://www.mapillary.com/app/?pKey=520744618938239&focus=photo | random sample and manual label | Zemun | 1,688,453,076 | Serbia | Europe | 44.851804 | 20.395619 | 2019-01-29 14:34:04+01:00 | 16 | nMqJT1fl2h4sIFuUhOk8ig | train | img/5/6c8d3fca-d9da-4e41-8aad-608b13a5a810.jpeg |
84ae4416-6642-4110-9e04-43e43684a610 | Mapillary | 181,639,447,171,385 | no | https://www.mapillary.com/app/?pKey=181639447171385&focus=photo | random sample and manual label | Moscow | 1,643,318,494 | Russia | Europe | 55.757615 | 37.628496 | 2020-09-02 14:06:54.965000+03:00 | 195 | fbhgwys31ahzkkmgj2e1yl | train | img/4/84ae4416-6642-4110-9e04-43e43684a610.jpeg |
End of preview.