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July 19, 2024 16:01
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Download Mapillary images a JPGs
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import mercantile, mapbox_vector_tile, requests, json, os | |
from vt2geojson.tools import vt_bytes_to_geojson | |
# define an empty geojson as output | |
output= { "type": "FeatureCollection", "features": [] } | |
# vector tile endpoints -- change this in the API request to reference the correct endpoint | |
tile_coverage = 'mly1_public' | |
# tile layer depends which vector tile endpoints: | |
# 1. if map features or traffic signs, it will be "point" always | |
# 2. if looking for coverage, it will be "image" for points, "sequence" for lines, or "overview" for far zoom | |
tile_layer = "image" | |
# Mapillary access token -- user should provide their own | |
access_token = 'MLY|XXX' | |
# a bounding box in [east_lng,_south_lat,west_lng,north_lat] format | |
west, south, east, north = [-80.13423442840576,25.77376933762778,-80.1264238357544,25.788608487732198] | |
# get the list of tiles with x and y coordinates which intersect our bounding box | |
# MUST be at zoom level 14 where the data is available, other zooms currently not supported | |
tiles = list(mercantile.tiles(west, south, east, north, 14)) | |
# loop through list of tiles to get tile z/x/y to plug in to Mapillary endpoints and make request | |
for tile in tiles: | |
tile_url = 'https://tiles.mapillary.com/maps/vtp/{}/2/{}/{}/{}?access_token={}'.format(tile_coverage,tile.z,tile.x,tile.y,access_token) | |
response = requests.get(tile_url) | |
data = vt_bytes_to_geojson(response.content, tile.x, tile.y, tile.z,layer=tile_layer) | |
# push to output geojson object if yes | |
for feature in data['features']: | |
# get lng,lat of each feature | |
lng = feature['geometry']['coordinates'][0] | |
lat = feature['geometry']['coordinates'][1] | |
# ensure feature falls inside bounding box since tiles can extend beyond | |
if lng > west and lng < east and lat > south and lat < north: | |
# create a folder for each unique sequence ID to group images by sequence | |
sequence_id = feature['properties']['sequence_id'] | |
if not os.path.exists(sequence_id): | |
os.makedirs(sequence_id) | |
# request the URL of each image | |
image_id = feature['properties']['id'] | |
header = {'Authorization' : 'OAuth {}'.format(access_token)} | |
url = 'https://graph.mapillary.com/{}?fields=thumb_2048_url'.format(image_id) | |
r = requests.get(url, headers=header) | |
data = r.json() | |
image_url = data['thumb_2048_url'] | |
# save each image with ID as filename to directory by sequence ID | |
with open('{}/{}.jpg'.format(sequence_id, image_id), 'wb') as handler: | |
image_data = requests.get(image_url, stream=True).content | |
handler.write(image_data) | |
@cbeddow Are you able to download and view the point cloud supplied as sfm_cluster, among the "fields" associated with an individual image ?
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Well done!