mirror of https://gitlab.com/bashrc2/epicyon
220 lines
8.4 KiB
Python
220 lines
8.4 KiB
Python
__filename__ = "city.py"
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__author__ = "Bob Mottram"
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__license__ = "AGPL3+"
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__version__ = "1.2.0"
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__maintainer__ = "Bob Mottram"
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__email__ = "bob@freedombone.net"
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__status__ = "Production"
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import os
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import datetime
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import random
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import math
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from random import randint
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# states which the simulated city dweller can be in
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PERSON_SLEEP = 0
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PERSON_WORK = 1
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PERSON_PLAY = 2
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PERSON_SHOP = 3
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PERSON_EVENING = 4
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PERSON_PARTY = 5
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def _getDecoyCamera(decoySeed: int) -> (str, str, int):
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"""Returns a decoy camera make and model which took the photo
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"""
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cameras = [
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["Apple", "iPhone SE"],
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["Apple", "iPhone XR"],
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["Apple", "iPhone 6"],
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["Apple", "iPhone 7"],
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["Apple", "iPhone 8"],
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["Apple", "iPhone 11"],
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["Apple", "iPhone 11 Pro"],
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["Apple", "iPhone 12"],
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["Apple", "iPhone 12 Mini"],
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["Apple", "iPhone 12 Pro Max"],
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["Samsung", "Galaxy Note 20 Ultra"],
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["Samsung", "Galaxy S20 Plus"],
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["Samsung", "Galaxy S20 FE 5G"],
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["Samsung", "Galaxy Z FOLD 2"],
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["Samsung", "Galaxy S10 Plus"],
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["Samsung", "Galaxy S10e"],
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["Samsung", "Galaxy Z Flip"],
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["Samsung", "Galaxy A51"],
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["Samsung", "Galaxy S10"],
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["Samsung", "Galaxy S10 Plus"],
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["Samsung", "Galaxy S10e"],
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["Samsung", "Galaxy S10 5G"],
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["Samsung", "Galaxy A60"],
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["Samsung", "Note 10"],
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["Samsung", "Note 10 Plus"],
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["Samsung", "Galaxy S21 Ultra"],
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["Samsung", "Galaxy Note 20 Ultra"],
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["Samsung", "Galaxy S21"],
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["Samsung", "Galaxy S21 Plus"],
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["Samsung", "Galaxy S20 FE"],
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["Samsung", "Galaxy Z Fold 2"],
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["Samsung", "Galaxy A52 5G"],
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["Samsung", "Galaxy A71 5G"],
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["Google", "Pixel 5"],
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["Google", "Pixel 4a"],
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["Google", "Pixel 4 XL"],
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["Google", "Pixel 3 XL"],
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["Google", "Pixel 4"],
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["Google", "Pixel 4a 5G"],
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["Google", "Pixel 3"],
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["Google", "Pixel 3a"]
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]
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randgen = random.Random(decoySeed)
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index = randgen.randint(0, len(cameras) - 1)
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serialNumber = randgen.randint(100000000000, 999999999999999999999999)
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return cameras[index][0], cameras[index][1], serialNumber
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def _getCityPulse(currTimeOfDay, decoySeed: int) -> (float, float):
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"""This simulates expected average patterns of movement in a city.
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Jane or Joe average lives and works in the city, commuting in
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and out of the central district for work. They have a unique
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life pattern, which machine learning can latch onto.
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This returns a polar coordinate for the simulated city dweller:
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Distance from the city centre is in the range 0.0 - 1.0
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Angle is in radians
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"""
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randgen = random.Random(decoySeed)
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variance = 3
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busyStates = (PERSON_WORK, PERSON_SHOP, PERSON_PLAY, PERSON_PARTY)
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dataDecoyState = PERSON_SLEEP
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weekday = currTimeOfDay.weekday()
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minHour = 7 + randint(0, variance)
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maxHour = 17 + randint(0, variance)
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if currTimeOfDay.hour > minHour:
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if currTimeOfDay.hour <= maxHour:
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if weekday < 5:
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dataDecoyState = PERSON_WORK
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elif weekday == 5:
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dataDecoyState = PERSON_SHOP
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else:
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dataDecoyState = PERSON_PLAY
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else:
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if weekday < 5:
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dataDecoyState = PERSON_EVENING
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else:
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dataDecoyState = PERSON_PARTY
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randgen2 = random.Random(decoySeed + dataDecoyState)
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angleRadians = \
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(randgen2.randint(0, 100000) / 100000) * 2 * math.pi
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# some people are quite random, others have more predictable habits
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decoyRandomness = randgen.randint(1, 3)
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# occasionally throw in a wildcard to keep the machine learning guessing
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if randint(0, 100) < decoyRandomness:
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distanceFromCityCenter = (randint(0, 100000) / 100000)
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angleRadians = (randint(0, 100000) / 100000) * 2 * math.pi
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else:
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# what consitutes the central district is fuzzy
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centralDistrictFuzz = (randgen.randint(0, 100000) / 100000) * 0.1
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busyRadius = 0.3 + centralDistrictFuzz
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if dataDecoyState in busyStates:
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# if we are busy then we're somewhere in the city center
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distanceFromCityCenter = \
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(randgen.randint(0, 100000) / 100000) * busyRadius
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else:
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# otherwise we're in the burbs
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distanceFromCityCenter = busyRadius + \
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((1.0 - busyRadius) * (randgen.randint(0, 100000) / 100000))
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return distanceFromCityCenter, angleRadians
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def spoofGeolocation(baseDir: str,
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city: str, currTime, decoySeed: int,
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citiesList: []) -> (float, float, str, str,
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str, str, int):
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"""Given a city and the current time spoofs the location
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for an image
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returns latitude, longitude, N/S, E/W,
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camera make, camera model, camera serial number
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"""
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locationsFilename = baseDir + '/custom_locations.txt'
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if not os.path.isfile(locationsFilename):
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locationsFilename = baseDir + '/locations.txt'
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manCityRadius = 0.1
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varianceAtLocation = 0.0004
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default_latitude = 51.8744
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default_longitude = 0.368333
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default_latdirection = 'N'
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default_longdirection = 'W'
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if citiesList:
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cities = citiesList
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else:
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if not os.path.isfile(locationsFilename):
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return (default_latitude, default_longitude,
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default_latdirection, default_longdirection,
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"", "", 0)
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cities = []
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with open(locationsFilename, "r") as f:
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cities = f.readlines()
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city = city.lower()
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for cityName in cities:
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if city in cityName.lower():
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cityFields = cityName.split(':')
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latitude = cityFields[1]
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longitude = cityFields[2]
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areaKm2 = 0
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if len(cityFields) > 3:
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areaKm2 = int(cityFields[3])
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latdirection = 'N'
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longdirection = 'E'
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if 'S' in latitude:
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latdirection = 'S'
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latitude = latitude.replace('S', '')
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if 'W' in longitude:
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longdirection = 'W'
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longitude = longitude.replace('W', '')
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latitude = float(latitude)
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longitude = float(longitude)
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# get the time of day at the city
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approxTimeZone = int(longitude / 15.0)
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if longdirection == 'E':
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approxTimeZone = -approxTimeZone
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currTimeAdjusted = currTime - \
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datetime.timedelta(hours=approxTimeZone)
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camMake, camModel, camSerialNumber = \
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_getDecoyCamera(decoySeed)
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# patterns of activity change in the city over time
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(distanceFromCityCenter, angleRadians) = \
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_getCityPulse(currTimeAdjusted, decoySeed)
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# The city radius value is in longitude and the reference
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# is Manchester. Adjust for the radius of the chosen city.
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if areaKm2 > 1:
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manRadius = math.sqrt(630 / math.pi)
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radius = math.sqrt(areaKm2 / math.pi)
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cityRadius = manCityRadius * manRadius / radius
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else:
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cityRadius = manCityRadius
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# Get the position within the city, with some randomness added
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latitude += \
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distanceFromCityCenter * cityRadius * math.cos(angleRadians)
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longitude += \
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distanceFromCityCenter * cityRadius * math.sin(angleRadians)
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# add a small amount of variance around the location
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fraction = randint(0, 100000) / 100000
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distanceFromLocation = fraction * fraction * varianceAtLocation
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fraction = randint(0, 100000) / 100000
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angleFromLocation = fraction * 2 * math.pi
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latitude += distanceFromLocation * math.cos(angleFromLocation)
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longitude += distanceFromLocation * math.sin(angleFromLocation)
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# gps locations aren't transcendental, so round to a fixed
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# number of decimal places
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latitude = int(latitude * 100000) / 100000.0
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longitude = int(longitude * 100000) / 100000.0
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return (latitude, longitude, latdirection, longdirection,
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camMake, camModel, camSerialNumber)
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return (default_latitude, default_longitude,
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default_latdirection, default_longdirection,
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"", "", 0)
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