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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 7bd2e7697a3cb5f74ff05bd718babdb927f8b60d) 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 1870, in _prepare_split_single writer.write_table(table) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 622, 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 1415, 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 991, in stream_convert_to_parquet builder._prepare_split( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1741, 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 1872, 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 7bd2e7697a3cb5f74ff05bd718babdb927f8b60d) 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.
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