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Get_panos.py
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Get_panos.py
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from GPano import *
import GPano
from PIL import Image
from skimage import io
import numpy as np
import matplotlib.pyplot as plt
import glob
import json
import sqlite3
from tqdm import tqdm
gpano = GPano.GPano()
gsv = GPano.GSV_depthmap()
def test_getPanoJPGfrmArea():
print('started! ')
pts = gpano.readRoadSeedsPts_csv(r'D:\OneDrive_NJIT\OneDrive - NJIT\Research\sidewalk\Essex_county\road_seeds.csv')
# coords = GPano.GPano.readCoords_csv(GPano.GPano(),
# r'O:\OneDrive_NJIT\OneDrive - NJIT\Research\sidewalk\Essex_test\polygon_coords.csv')
coords = gpano.readCoords_csv(r'D:\OneDrive_NJIT\OneDrive - NJIT\Research\sidewalk\Essex_county\essex_vet.csv')
polygon = gpano.formPolygon(coords)
saved_path = r'G:\My Drive\Sidewalk_extraction\Essex\jsons'
random.shuffle(pts)
# self.gpano.getPanoJPGfrmArea(pts, saved_path, coords)
gpano.getPanoJPGfrmArea_mp('json_only', pts, saved_path, coords, Process_cnt=1)
#### Test for getPanoIDfrmLonlat()
def test_getPanosfrmLonlats_mp():
list_lonlat = pd.read_csv(r'K:\OneDrive_NJIT\OneDrive - NJIT\Research\House\maryland\merge.csv')
print(sys.getfilesystemencoding())
print(sys.getdefaultencoding())
mp_lonlat = mp.Manager().list()
ns = mp.Manager().Namespace()
ns.list_lonlat = list_lonlat
print(len(list_lonlat))
for idx, row in tqdm(list_lonlat[:].iterrows()):
mp_lonlat.append([row['Longitude'], row['Latitude'], str(row['ACCTID']) + '_' + str(row['class'])])
# mp_lonlat.append([row['Longitude'], row['Latitude'], str(row['ACCTID']) + '_' + str(row['class']))
# pass
print(len(mp_lonlat))
gpano.shootLonlats_mp(mp_lonlat, saved_path=r'J:\Maryland\MS_building\images2', Process_cnt=10)
def getPanoJPGs_philadelphia():
print('started! ')
pts = gpano.readRoadSeedsPts_csv(r'D:\OneDrive_NJIT\OneDrive - NJIT\Research\sidewalk\Essex_county\road_seeds.csv')
# coords = GPano.GPano.readCoords_csv(GPano.GPano(),
# r'O:\OneDrive_NJIT\OneDrive - NJIT\Research\sidewalk\Essex_test\polygon_coords.csv')
coords = gpano.readCoords_csv(r'D:\OneDrive_NJIT\OneDrive - NJIT\Research\sidewalk\Essex_county\essex_vet.csv')
polygon = gpano.formPolygon(coords)
saved_path = r'G:\My Drive\Sidewalk_extraction\Essex\jsons'
random.shuffle(pts)
# self.gpano.getPanoJPGfrmArea(pts, saved_path, coords)
gpano.getPanoJPGfrmArea_mp('json_only', pts, saved_path, coords, Process_cnt=1)
def getPanoJPGs_oceancity():
print('started! ')
pts = gpano.readRoadSeedsPts_csv(r'X:\My Drive\Research\StreetGraph\data\oceancity\road_ends.csv')
# coords = GPano.GPano.readCoords_csv(GPano.GPano(),
# r'O:\OneDrive_NJIT\OneDrive - NJIT\Research\sidewalk\Essex_test\polygon_coords.csv')
coords = gpano.readCoords_csv(r'X:\My Drive\Research\StreetGraph\data\oceancity\boudary_vertices.csv')
polygon = gpano.formPolygon(coords)
saved_path = r'X:\My Drive\Research\StreetGraph\data\oceancity\panos'
random.shuffle(pts)
# self.gpano.getPanoJPGfrmArea(pts, saved_path, coords)
gpano.getPanoJPGfrmArea_mp(None, pts, saved_path, coords, Process_cnt=5)
if __name__ == '__main__':
try:
# test_getPanoJPGfrmArea()
getPanoJPGs_oceancity()
except:
# test_getPanoJPGfrmArea()
getPanoJPGs_oceancity()