mapillary.interface
#
mapillary.interfaceThis module implements the basic functionalities of the Mapillary Python SDK, a Python implementation of the Mapillary API v4. For more information, please check out https://www.mapillary.com/developer/api-documentation/
- Copyright: (c) 2021 Facebook
- License: MIT LICENSE
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mapillary.interface.feature_from_key(key: str, fields: list = [])Gets a map feature for the given key argument
Parameters
- key (int) – The map feature ID to which will be used to get the feature
* **fields** (*list*) – The fields to include. The field ‘geometry’ will always be includedso you do not need to specify it, or if you leave it off, it will still be returned.
Fields:
```1. first_seen_at - timestamp, timestamp of the least recent detection contributing to this feature2. last_seen_at - timestamp, timestamp of the most recent detection contributing to this feature3. object_value - string, what kind of map feature it is4. object_type - string, either a traffic_sign or point5. geometry - GeoJSON Point geometry6. images - list of IDs, which images this map feature was derivedfrom```
Refer to [https://www.mapillary.com/developer/api-documentation/#map-feature](https://www.mapillary.com/developer/api-documentation/#map-feature) for more details
Returns
A GeoJSON string that represents the queried feature
Return type
str
Usage:
>>> import mapillary as mly>>> mly.interface.set_access_token('MLY|XXX')>>> mly.interface.feature_from_key(... key='VALID_MAP_FEATURE_KEY',... fields=['object_value']... )
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mapillary.interface.get_detections_with_image_id(image_id: int, fields: list = [])Extracting all the detections within an image using an image key
Parameters
- image_id (int) – The image key as the argument
* **fields** (*list*) – The fields possible for the detection endpoint. Please see[https://www.mapillary.com/developer/api-documentation](https://www.mapillary.com/developer/api-documentation) for more information
Returns
The GeoJSON in response
Return type
dict
Usage:
>>> import mapillary as mly>>> mly.interface.set_access_token('CLIENT_TOKEN_HERE')>>> mly.interface.get_detections_with_image_id(image_id=1933525276802129)... {"data":[{"created_at":"2021-05-20T17:49:01+0000","geometry":... "GjUKBm1weS1vchIVEgIAABgDIg0JhiekKBoqAABKKQAPGgR0eXBlIgkKB3BvbHlnb24ogCB4AQ==","image"... :{"geometry":{"type":"Point","coordinates":[-97.743279722222,30.270651388889]},"id":... "1933525276802129"},"value":"regulatory--no-parking--g2","id":"1942105415944115"},... {"created_at":"2021-05-20T18:40:21+0000","geometry":... "GjYKBm1weS1vchIWEgIAABgDIg4J7DjqHxpWAADiAVUADxoEdHlwZSIJCgdwb2x5Z29uKIAgeAE=",... "image":{"geometry":{"type":"Point","coordinates":[-97.743279722222,30.270651388889]},... "id":"1933525276802129"},"value":"information--parking--g1","id":"1942144785940178"},... , ...}
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mapillary.interface.get_detections_with_map_feature_id(map_feature_id: str, fields: list = None)Extracting all detections made for a map feature key
Parameters
- map_feature_id (int) – A map feature key as the argument
* **fields** (*list*) – The fields possible for the detection endpoint. Please see[https://www.mapillary.com/developer/api-documentation](https://www.mapillary.com/developer/api-documentation) for more information
Returns
The GeoJSON in response
Return type
GeoJSON
Usage:
>>> import mapillary as mly>>> mly.interface.set_access_token('MLY|XXX')>>> mly.interface.get_detections_with_map_feature_id(map_feature_id='1933525276802129')... File "/home/saif/MLH/mapillary-python-sdk/mapillary/controller/rules/verify.py",... line 227, in valid_id... raise InvalidOptionError(... mly.models.exceptions.InvalidOptionError: InvalidOptionError: Given id value,... "Id: 1933525276802129, image: False" while possible id options, [Id is image_id... AND image is True, key is map_feature_id ANDimage is False]
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mapillary.interface.get_image_close_to(latitude=-122.1504711, longitude=37.485073, **kwargs)Function that takes a longitude, latitude as argument and outputs the near images. This makes an API call with the token set in set_access_token and returns a JSON object.
Parameters
- longitude (float or double) – The longitude
* **latitude** (*float** or **double*) – The latitude
* **kwargs.fields** (*list*) – A list of options, either as [‘all’], or a list of fields.See [https://www.mapillary.com/developer/api-documentation/](https://www.mapillary.com/developer/api-documentation/), under ‘Fields’ for more insight.
* **kwargs.zoom** (*int*) – The zoom level of the tiles to obtain, defaults to 14
* **kwargs.radius** (*float** or **int** or **double*) – The radius of the images obtained from a center center
* **kwargs.image_type** (*str*) – The tile image_type to be obtained, either as ‘flat’, ‘pano’(panoramic), or ‘both’. See [https://www.mapillary.com/developer/api-documentation/](https://www.mapillary.com/developer/api-documentation/) under‘image_type Tiles’ for more information
* **kwargs.min_captured_at** (*str*) – The min date. Format from ‘YYYY’, to ‘YYYY-MM-DDTHH:MM:SS’
* **kwargs.max_captured_at** (*str*) – The max date. Format from ‘YYYY’, to ‘YYYY-MM-DDTHH:MM:SS’
* **kwargs.org_id** (*int*) – The organization id, ID of the organization this image (or sets ofimages) belong to. It can be absent. Thus, default is -1 (None)
Returns
GeoJSON
Return type
dict
Usage:
>>> import mapillary as mly>>> mly.interface.set_access_token('CLIENT_TOKEN_HERE')>>> mly.interface.get_image_close_to(longitude=31, latitude=30)... {'type': 'FeatureCollection', 'features': [{'type': 'Feature','geometry': {'type': 'Point', 'coordinates': [30.9912246465683,29.99794091267283]}, 'properties': {'captured_at': 1621008070596,'compass_angle': 322.56726074219, 'id': 499412381300321, 'is_pano':False, 'sequence_id': '94afmyyhq85xd9bi8p44ve'}} ...
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mapillary.interface.get_image_looking_at(at: dict, **filters: dict)Function that takes two sets of latitude and longitude, where the 2nd set is the “looking at” location from 1st set’s perspective argument and outputs the near images. This makes an API call with the token set in set_access_token and returns a JSON object.
Parameters
at (dict) – The coordinate sets to where a certain point is being looked at
Format:
>>> {... 'lng': 'longitude',... 'lat': 'latitude'... }
* **filters.min_captured_at** (*str*) – The minimum date to filter till
* **filters.max_captured_at** (*str*) – The maximum date to filter upto
* **filters.radius** (*float*) – The radius that the geometry points will lie in
* **filters.image_type** (*str*) – Either ‘pano’, ‘flat’ or ‘all’
* **filters.organization_id** (*str*) – The organization to retrieve the data for
Returns
The GeoJSON response containing relevant features
Return type
GeoJSON
Usage:
>>> import mapillary as mly>>> mly.interface.set_access_token('MLY|XXX')>>> data = mly.interface.get_image_looking_at(... at={... 'lng': 12.955075073889,... 'lat': 48.053805939722,... },... radius = 5000,... )>>> data... {'type': 'FeatureCollection', 'features': [{'type': 'Feature', 'geometry': {'type':... 'Point', 'coordinates': [12.954479455947876, 48.05091893670834]}, 'properties':... {'captured_at': 1612606959408, 'compass_angle': 21.201110839844, 'id': 1199705400459580,... 'is_pano': False, 'sequence_id': 'qrrqtke4a6vtygyc7w8rzc'}}, ... }
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mapillary.interface.image_from_key(key: str, fields: list = None)Gets an image for the given key argument
Parameters
- key (int) – The image unique key which will be used for image retrieval
* **fields** (*list*) – The fields to include. The field ‘geometry’ will always be includedso you do not need to specify it, or if you leave it off, it will still be returned.
Fields,
1. altitude - float, original altitude from Exif
2. atomic_scale - float, scale of the SfM reconstruction around the image
3. camera_parameters - array of float, intrinsic camera parameters
4. camera_type - enum, type of camera projection (perspective, fisheye, or
spherical)
5. captured_at - timestamp, capture time
6. compass_angle - float, original compass angle of the image
7. computed_altitude - float, altitude after running image processing
8. computed_compass_angle - float, compass angle after running image processing
9. computed_geometry - GeoJSON Point, location after running image processing
10. computed_rotation - enum, corrected orientation of the image
11. exif_orientation - enum, orientation of the camera as given by the exif tag(see: [https://sylvana.net/jpegcrop/exif_orientation.html](https://sylvana.net/jpegcrop/exif_orientation.html))
12. geometry - GeoJSON Point geometry
13. height - int, height of the original image uploaded
14. thumb_256_url - string, URL to the 256px wide thumbnail
15. thumb_1024_url - string, URL to the 1024px wide thumbnail
16. thumb_2048_url - string, URL to the 2048px wide thumbnail
17. merge_cc - int, id of the connected component of images that were alignedtogether
18. mesh - { id: string, url: string } - URL to the mesh
19. quality_score - float, how good the image is (experimental)
20. sequence - string, ID of the sequence
21. sfm_cluster - { id: string, url: string } - URL to the point cloud
22. width - int, width of the original image uploaded
Refer to [https://www.mapillary.com/developer/api-documentation/#image](https://www.mapillary.com/developer/api-documentation/#image) for more details
Returns
A GeoJSON string that represents the queried image
Return type
str
Usage:
>>> import mapillary as mly>>> mly.interface.set_access_token('MLY|XXX')>>> mly.interface.image_from_key(... key='VALID_IMAGE_KEY',... fields=['captured_at', 'sfm_cluster', 'width']... )
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mapillary.interface.image_thumbnail(image_id: str, resolution: int = 1024)Gets the thumbnails of images from the API
Parameters
- image_id – Image key as the argument
* **resolution** – Option for the thumbnail size, with available resolutions:256, 1024, and 2048
Returns
A URL for the thumbnail
Return type
str
Usage:
>>> import mapillary as mly>>> mly.interface.set_access_token('MLY|XXX')>>> mly.interface.image_thumbnail(... image_id='IMAGE_ID_HERE', resolution=1024... )
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mapillary.interface.images_in_bbox(bbox: dict, **filters)Gets a complete list of images with custom filter within a BBox
Parameters
bbox (dict) – Bounding box coordinates
Format:
>>> {... 'west': 'BOUNDARY_FROM_WEST',... 'south': 'BOUNDARY_FROM_SOUTH',... 'east': 'BOUNDARY_FROM_EAST',... 'north': 'BOUNDARY_FROM_NORTH'... }
* **filters** (*dict*) – Different filters that may be applied to the output
Example filters:
```- max_captured_at- min_captured_at- image_type: pano, flat, or all- compass_angle- sequence_id- organization_id```
Returns
Output is a GeoJSON string that represents all the within a bbox after passing given filters
Return type
str
Usage:
>>> import mapillary as mly>>> mly.interface.set_access_token('MLY|XXX')>>> mly.interface.images_in_bbox(... bbox={... 'west': 'BOUNDARY_FROM_WEST',... 'south': 'BOUNDARY_FROM_SOUTH',... 'east': 'BOUNDARY_FROM_EAST',... 'north': 'BOUNDARY_FROM_NORTH'... },... max_captured_at='YYYY-MM-DD HH:MM:SS',... min_captured_at='YYYY-MM-DD HH:MM:SS',... image_type='pano',... compass_angle=(0, 360),... sequence_id='SEQUENCE_ID',... organization_id='ORG_ID'... )
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mapillary.interface.images_in_geojson(geojson: dict, **filters: dict)Extracts all images within a shape
Parameters
- geojson (dict) – A geojson as the shape acting as the query extent
* **filters** (*dict** (**kwargs**)*) – Different filters that may be applied to the output, defaults to {}
* **filters.max_captured_at** (*str*) – The max date. Format from ‘YYYY’, to ‘YYYY-MM-DDTHH:MM:SS’
* **filters.min_captured_at** (*str*) – The min date. Format from ‘YYYY’, to ‘YYYY-MM-DDTHH:MM:SS’
* **filters.image_type** (*str*) – The tile image_type to be obtained, either as ‘flat’, ‘pano’(panoramic), or ‘all’. See [https://www.mapillary.com/developer/api-documentation/](https://www.mapillary.com/developer/api-documentation/) under‘image_type Tiles’ for more information
* **filters.compass_angle** (*int*) – The compass angle of the image
* **filters.sequence_id** (*str*) – ID of the sequence this image belongs to
* **filters.organization_id** (*str*) – ID of the organization this image belongs to. It can be absent
Returns
A GeoJSON object
Return type
mapillary.models.geojson.GeoJSON
Usage:
>>> import mapillary as mly>>> from mapillary.models.geojson import GeoJSON>>> import json>>> mly.interface.set_access_token('MLY|YYY')>>> data = mly.interface.images_in_geojson(json.load(open('my_geojson.geojson', mode='r')))>>> open('output_geojson.geojson', mode='w').write(data.encode())
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mapillary.interface.images_in_shape(shape, **filters: dict)Extracts all images within a shape or polygon.
Format:
>>> {... "type": "FeatureCollection",... "features": [... {... "type": "Feature",... "properties": {},... "geometry": {... "type": "Polygon",... "coordinates": [... [... [... 7.2564697265625,... 43.69716905314008... ],... ...... ]... ]... }... }... ]... }
Parameters
- shape (dict) – A shape that describes features, formatted as a geojson
* **filters** (*dict** (**kwargs**)*) – Different filters that may be applied to the output, defaults to {}
* **filters.max_captured_at** (*str*) – The max date. Format from ‘YYYY’, to ‘YYYY-MM-DDTHH:MM:SS’
* **filters.min_captured_at** (*str*) – The min date. Format from ‘YYYY’, to ‘YYYY-MM-DDTHH:MM:SS’
* **filters.image_type** (*str*) – The tile image_type to be obtained, either as ‘flat’, ‘pano’(panoramic), or ‘all’. See [https://www.mapillary.com/developer/api-documentation/](https://www.mapillary.com/developer/api-documentation/) under‘image_type Tiles’ for more information
* **filters.compass_angle** (*int*) – The compass angle of the image
* **filters.sequence_id** (*str*) – ID of the sequence this image belongs to
* **filters.organization_id** (*str*) – ID of the organization this image belongs to. It can be absent
Returns
A GeoJSON object
Return type
mapillary.models.geojson.GeoJSON
Usage:
>>> import mapillary as mly>>> import json>>> mly.interface.set_access_token('MLY|XXX')>>> data = mly.interface.images_in_shape(json.load(open('polygon.geojson', mode='r')))>>> open('output_geojson.geojson', mode='w').write(data.encode())
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mapillary.interface.is_image_being_looked_at(at: Union[dict, Coordinates, list], **filters: dict)Function that two sets of coordinates and returns whether the image with coordinates of “at” is looked at or not by the image with coordinates of “looker”.
Parameters
at (Union[dict, mapillary.models.geojson.Coordinates, list**]) – The coordinate sets to where a certain point is being looked at
Format:
>>> at_dict = {... 'lng': 'longitude',... 'lat': 'latitude'... }>>> at_list = [12.954940544167, 48.0537894275]>>> from mapillary.models.geojson import Coordinates>>> at_coord: Coordinates = Coordinates(lng=12.954940544167, lat=48.0537894275)
Returns
True if the image is looked at, False otherwise
Return type
bool
Usage:
>>> import mapillary as mly>>> mly.interface.set_access_token('MLY|XXX')>>> mly.interface.is_image_being_looked_at(... at={... 'lng': 12.955075073889,... 'lat': 48.053805939722,... },... radius=50,... )... True>>> # OR>>> from mapillary.models.geojson import Coordinates>>> mly.interface.is_image_looked_at(... at=Coordinates(lng=11.954940544167, lat=46.0537894275),... radius=50,... )... True
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mapillary.interface.map_feature_points_in_bbox(bbox: dict, filter_values: list = None, **filters: dict)Extracts map feature points within a bounding box (bbox)
Parameters
bbox (dict) – bbox coordinates as the argument
Example:
>>> _ = {... 'west': 'BOUNDARY_FROM_WEST',... 'south': 'BOUNDARY_FROM_SOUTH',... 'east': 'BOUNDARY_FROM_EAST',... 'north': 'BOUNDARY_FROM_NORTH'... }
* **filter_values** (*list*) – a list of filter values supported by the API
Example:
```>>> _ = ['object--support--utility-pole', 'object--street-light']```
* **filters** (*dict*) – kwarg filters to be applied on the resulted GeoJSON
Chronological filters,
* *existed_at*: checks if a feature existed after a certain date depending on the time
it was first seen at.
* *existed_before*: filters out the features that existed after a given date
Returns
GeoJSON Object
Return type
dict
Usage:
>>> import mapillary as mly>>> mly.interface.set_access_token('MLY|XXX')>>> mly.interface.map_feature_points_in_bbox(... bbox={... 'west': 'BOUNDARY_FROM_WEST',... 'south': 'BOUNDARY_FROM_SOUTH',... 'east': 'BOUNDARY_FROM_EAST',... 'north': 'BOUNDARY_FROM_NORTH'... },... filter_values=['object--support--utility-pole', 'object--street-light'],... existed_at='YYYY-MM-DD HH:MM:SS',... existed_before='YYYY-MM-DD HH:MM:SS'... )
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mapillary.interface.map_features_in_geojson(geojson: dict, **filters: dict)Extracts all map features within a geojson’s boundaries
Parameters
- geojson (dict) – A geojson as the shape acting as the query extent
* **filters** (*dict** (**kwargs**)*) – Different filters that may be applied to the output, defaults to {}
* **filters.zoom** (*int*) – The zoom level of the tiles to obtain, defaults to 14
* **filters.max_captured_at** (*str*) – The max date. Format from ‘YYYY’, to ‘YYYY-MM-DDTHH:MM:SS’
* **filters.min_captured_at** (*str*) – The min date. Format from ‘YYYY’, to ‘YYYY-MM-DDTHH:MM:SS’
* **filters.image_type** (*str*) – The tile image_type to be obtained, either as ‘flat’, ‘pano’(panoramic), or ‘all’. See [https://www.mapillary.com/developer/api-documentation/](https://www.mapillary.com/developer/api-documentation/) under‘image_type Tiles’ for more information
* **filters.compass_angle** (*int*) – The compass angle of the image
* **filters.sequence_id** (*str*) – ID of the sequence this image belongs to
* **filters.organization_id** (*str*) – ID of the organization this image belongs to. It can be absent
Returns
A GeoJSON object
Return type
mapillary.models.geojson.GeoJSON
Usage:
>>> import mapillary as mly>>> import json>>> mly.interface.set_access_token('MLY|YYY')>>> data = mly.interface.map_features_in_geojson(... json.load(... open('my_geojson.geojson', mode='r')... )... )>>> open('output_geojson.geojson', mode='w').write(data.encode())
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mapillary.interface.map_features_in_shape(shape: dict, **filters: dict)Extracts all map features within a shape/polygon
Format:
>>> _ = {... "type": "FeatureCollection",... "features": [... {... "type": "Feature",... "properties": {},... "geometry": {... "type": "Polygon",... "coordinates": [... [... [... 7.2564697265625,... 43.69716905314008... ],... ...... ]... ]... }... }... ]... }
Parameters
- shape (dict) – A shape that describes features, formatted as a geojson
* **filters** (*dict** (**kwargs**)*) – Different filters that may be applied to the output, defaults to {}
* **filters.zoom** (*int*) – The zoom level of the tiles to obtain, defaults to 14
* **filters.max_captured_at** (*str*) – The max date. Format from ‘YYYY’, to ‘YYYY-MM-DDTHH:MM:SS’
* **filters.min_captured_at** (*str*) – The min date. Format from ‘YYYY’, to ‘YYYY-MM-DDTHH:MM:SS’
* **filters.image_type** (*str*) – The tile image_type to be obtained, either as ‘flat’, ‘pano’(panoramic), or ‘all’. See [https://www.mapillary.com/developer/api-documentation/](https://www.mapillary.com/developer/api-documentation/) under‘image_type Tiles’ for more information
* **filters.compass_angle** (*int*) – The compass angle of the image
* **filters.sequence_id** (*str*) – ID of the sequence this image belongs to
* **filters.organization_id** (*str*) – ID of the organization this image belongs to. It can be absent
Returns
A GeoJSON object
Return type
mapillary.models.geojson.GeoJSON
Usage:
>>> import mapillary as mly>>> import json>>> mly.interface.set_access_token('MLY|XXX')>>> data = mly.interface.map_features_in_shape(json.load(open('polygon.geojson', mode='r')))>>> open('output_geojson.geojson', mode='w').write(data.encode())
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mapillary.interface.save_locally(geojson_data: str, file_path: str = '/home/saif/Projects/mapillary-python-sdk/src/mapillary', file_name: str = None, extension: str = 'geojson')This function saves the geojson data locally as a file with the given file name, path, and format.
Parameters
- geojson_data (str) – The GeoJSON data to be stored
* **file_path** (*str*) – The path to save the data to. Defaults to the current directory path
* **file_name** (*str*) – The name of the file to be saved. Defaults to ‘geojson’
* **extension** (*str*) – The format to save the data as. Defaults to ‘geojson’
Note:
Allowed file format values at the moment are, - geojson - CSV
TODO: More file format will be supported further in developemtn TODO: Suggestions and help needed at mapillary/mapillary-python-sdk!
Returns
None
Return type
None
Usage:
>>> import mapillary as mly>>> mly.interface.set_access_token('MLY|XXX')>>> mly.interface.save_locally(... geojson_data=geojson_data,... file_path=os.path.dirname(os.path.realpath(__file__)),... file_name='test_geojson',... extension='geojson'... )>>> mly.interface.save_locally(... geojson_data=geojson_data,... file_path=os.path.dirname(os.path.realpath(__file__)),... file_name='local_geometries',... extension='csv'... )
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mapillary.interface.sequences_in_bbox(bbox: dict, **filters)Gets a complete list of all sequences of images that satisfy given filters within a BBox.
Parameters
bbox (dict) – Bounding box coordinates
Example:
>>> _ = {... 'west': 'BOUNDARY_FROM_WEST',... 'south': 'BOUNDARY_FROM_SOUTH',... 'east': 'BOUNDARY_FROM_EAST',... 'north': 'BOUNDARY_FROM_NORTH'... }
* **filters** (*dict*) – Different filters that may be applied to the output
Example filters:
```- max_captured_at- min_captured_at- image_type: pano, flat, or all- org_id```
Returns
Output is a GeoJSON string that contains all the filtered sequences within a bbox. Sequences would NOT be cut at BBox boundary, would select all sequences which are partially or entirely in BBox
Return type
str
Usage:
>>> import mapillary as mly>>> mly.interface.set_access_token('MLY|XXX')>>> mly.interface.sequences_in_bbox(... bbox={... 'west': 'BOUNDARY_FROM_WEST',... 'south': 'BOUNDARY_FROM_SOUTH',... 'east': 'BOUNDARY_FROM_EAST',... 'north': 'BOUNDARY_FROM_NORTH'... },... max_captured_at='YYYY-MM-DD HH:MM:SS',... min_captured_at='YYYY-MM-DD HH:MM:SS',... image_type='pano',... org_id='ORG_ID'... )
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mapillary.interface.set_access_token(token: str)A function allowing the user to set an access token for the session, which they can create at https://www.mapillary.com/dashboard/developers. Takes token as an argument and sets a global variable used by other functions making API requests. For more information what the details of authentication, please check out the blog post at Mapillary. https://blog.mapillary.com/update/2021/06/23/getting-started-with-the-new-mapillary-api-v4.html
Parameters
token (str) – The token itself that would be set and accessed globally. Must be obtained
Returns
None
Return type
None
Usage:
>>> import mapillary as mly>>> mly.interface.set_access_token('CLIENT_TOKEN_HERE')
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mapillary.interface.traffic_signs_in_bbox(bbox: dict, filter_values: list = None, **filters: dict)Extracts traffic signs within a bounding box (bbox)
Parameters
bbox (dict) – bbox coordinates as the argument
Example:
>>> {... 'west': 'BOUNDARY_FROM_WEST',... 'south': 'BOUNDARY_FROM_SOUTH',... 'east': 'BOUNDARY_FROM_EAST',... 'north': 'BOUNDARY_FROM_NORTH'... }
* **filter_values** (*list*) – a list of filter values supported by the API,
Example:
```>>> ['regulatory--advisory-maximum-speed-limit--g1', 'regulatory--atvs-permitted--g1']```
* **filters** (*dict*) – kwarg filters to be applied on the resulted GeoJSON
Chronological filters,
* *existed_at*: checks if a feature existed after a certain date depending on the time
it was first seen at.
* *existed_before*: filters out the features that existed after a given date
Returns
GeoJSON Object
Return type
dict
Usage:
>>> import mapillary as mly>>> mly.interface.set_access_token('MLY|XXX')>>> mly.interface.traffic_signs_in_bbox(... bbox={... 'west': 'BOUNDARY_FROM_WEST',... 'south': 'BOUNDARY_FROM_SOUTH',... 'east': 'BOUNDARY_FROM_EAST',... 'north': 'BOUNDARY_FROM_NORTH'... },... filter_values=[... 'regulatory--advisory-maximum-speed-limit--g1',... 'regulatory--atvs-permitted--g1'... ],... existed_at='YYYY-MM-DD HH:MM:SS',... existed_before='YYYY-MM-DD HH:MM:SS'... )
#
Module contents#
mapillary.initThis module imports the necessary parts of the SDK
- Copyright: (c) 2021 Facebook
- License: MIT LICENSE