streetscape

1 Get metadata of street view image from Mapillary

1.1 search data using a bounding box

bbox <- c(-83.751812,42.272984,-83.741255,42.279716)
data <- streetscape::strview_searchByGeo(bbox = bbox,
                                         epsg = 2253,
                                         token = "")

1.2 search data using a proximity given coordinates in degree

data <- streetscape::strview_searchByGeo(x = -83.743460634278,
                                         y = 42.277848830294,
                                         r = 100,
                                         epsg = 2253,
                                         token = "")

1.3 search data with filters

# check supported filters
streetscape::available_filter()
# only search for 360-degree street views
data <- streetscape::strview_searchByGeo(bbox = bbox,
                                         epsg = 2253,
                                         token = "",
                                         is_pano = TRUE)

1.4 search the nearest data given coordinates in degree (within a 10m buffer)

data <- streetscape::strview_search_nnb(
  x = -83.743460634278,
  y = 42.277848830294,
  epsg = 2253,
  token = '')

1.5 batch search data using OSM road line

bbox <- c(-83.752041,42.274896,-83.740711,42.281945)
data <- streetscape::strview_search_osm(
        bbox = bbox,
        epsg = 2253,
        token = '',
        size = 100)

2 Calculate the Green View Index

data$gvi()

3 Extract semantic segmentation

streetviewdata <- streetscape::scdataframe
# calculate the percentage of each segmentation
data$decodeDetection()
data$data$segmentation[[1]]
# extract the semantic segmentation of a street view
mask <- streetviewdata$get_mask(1)

4 Visualize the data in maps

map1 <- data$mapPreview('meta')
print(map1)
# assume that one has run data$gvi() and data$decodeDetection()
map2 <- data$mapPreview('seg')
print(map2)
map3 <- data$mapPreview('gvi')
print(map3)

5 Download data

# download street view images
data$download_data(path = 'path/to/download', items = 'image')
# download images and masks in sf format
data$download_data(path = 'path/to/download', items = c('image', 'mask'))

6 Generate Qualtrics survey text file

# general survey for understanding subjective perception from streetviews
questions <- c('1. To what extent you feel pleasant if you were in this environment', 
              '2. To what extent you feel safe if you were in this environment')
choices <- list(c('Unpleasant','Less pleasant', 'Pleasant', 'More pleasant'), 
                c('Unsafe', 'Less safe','Safe','Safer'))
header <- "Please review the following picture(s):"
streetscape::strview2rate(data, header, questions, choices, file = 'folder/filename')

# pair-wised comparison survey for ranking some specific property (such as perceived safety) of street views
questions <- c('which one is more beautiful?', 'which one is safer?')
streetscape::strview2pwc(data, k=1, header, questions, file = 'folder/filename')