sidewalk-cv-assets19/add_data_to_meta.py at master · ProjectSidewalk/sidewalk-cv-assets19 · GitHub

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# Galen Weld, April 2019
# Use this to add metadata to existing sidecars

# before running, make sure to check:
# 1) that you have the correct city center point defined
# 2) that you have the correct shapefile for that city loaded into the label-intersection-proximity code

import sys
import os
label_intersection_dir = '/mnt/c/Users/gweld/sidewalk/label-intersection-proximity'
sys.path.append( label_intersection_dir )
from intersection_proximity import compute_proximity

from GSVutils.utils import add_metadata, extract_pano_lat_lng

from math import sin, cos, atan2, radians, degrees, sqrt


# DEFINE THE CENTER OF WASHINGTON DC HERE
dc_lat, dc_lng = 38.8977, -77.0366
# this is the middle of the White House

# DEFINE THE CENTER OF NEWBERG HERE
nb_lat, nb_lng = 45.3003, -122.9755

# DEFINTE THE CENTER OF SEATTLE HERE
sea_lat, sea_lng = 	47.6062, -122.3350

center = (sea_lat, sea_lng)


def calc_bearing_and_distance_between_points(lat1, lng1, lat2=center[0], lng2=center[1]):
	''' returns a tuple of the bearing and distance between
		two latitude and longitude points'''
	lat1 = radians(lat1)
	lng1 = radians(lng1)
	lat2 = radians(lat2)
	lng2 = radians(lng2)

	delta_lat = abs( lat2-lat1 )
	delta_lng = abs( lng2-lng1 )

	# let's calculate the bearing
	# https://www.igismap.com/formula-to-find-bearing-or-heading-angle-between-two-points-latitude-longitude/
	x = cos(lat2) * sin( delta_lng )
	y = cos(lat1) * sin(lat2) - sin(lat1) * cos(lat2) * cos(delta_lng)
	#print("x:{},y:{}".format(x,y))
	bearing = degrees( atan2(x,y) )

	# let's calculate the distance
	# https://andrew.hedges.name/experiments/haversine/
	R = 3961 #miles
	# this value is approximately correct for the area around Washington DC
	a = (sin(delta_lat/2))**2 + cos(lat1) * cos(lat2) * (sin(delta_lng/2))**2
	c = 2 * atan2( sqrt(a), sqrt(1-a) )
	dist = R * c #where R is the radius of the Earth

	return bearing, dist


def helper(input_dict):
	#print(input_dict)
	pano_id = input_dict[u'pano id']

	err = False

	try:
		lat, lng = extract_pano_lat_lng(pano_id, '/mnt/g/scrapes_dump_seattle')
	except Exception as e:
		print(e)
		lat = float('nan')
		lng = float('nan')
		err = True
	input_dict[u'latitude']  = lat
	input_dict[u'longitude'] = lng

	try:
		distance, middleness = compute_proximity(lat, lng)
	except Exception as e:
		print(e)
		distance   = float('nan')
		middleness = float('nan')
		err = True
	input_dict[u'dist to intersection'] = distance
	input_dict[u'block middleness']     = middleness

	try:
		bearing, distance = calc_bearing_and_distance_between_points(lat, lng)
	except Exception as e:
		print(e)
		bearing  = float('nan')
		distance = float('nan')
		err = True
	input_dict[u'bearing to cbd'] = bearing
	input_dict[u'dist to cbd']    = distance
	return input_dict, err

#add_metadata('/mnt/c/Users/gweld/sidewalk/sidewalk_ml/baby_ds', helper)
#add_metadata('/mnt/e/new_old_dataset', helper, "/mnt/e/new_metadata_files_for_cc")
add_metadata('/mnt/g/seattle_center_crops_researchers/', helper, verbose=True)

# let's do this for ground truth
#add_metadata('/mnt/c/Users/gweld/sidewalk/sidewalk_ml/sliding_window/ground_truth_crops', helper)
# if not os.path.isdir('/mnt/g/newberg_new_cc_meta/partitioned/'):
# 	os.mkdir('/mnt/g/newberg_new_cc_meta/partitioned/')
# add_metadata('/mnt/g/newberg_cc_researchers_partitioned', helper, '/mnt/g/newberg_new_cc_meta/partitioned')