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convert.py
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convert.py
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import pandas as pd
import os
import utm
### config
utm_zone = 17
utm_band = 'T'
Mia_pre = 'MIA'
Pit_pre = 'PIT'
Mia = 'Miami'
Pit = 'Pittsburgh'
piz_utm_x = 583710.0070
piz_utm_y = 4477259.9999
mia_utm_x = 580560.0088
mia_utm_y = 2850959.9999
# df = pd.read_csv('1.csv')
# if df['CITY_NAME'][1]=='MIA':
# CITY = Mia
# else:
# CITY = Pit
# mean_x = piz_utm_x+df['X'].mean()
# mean_y = piz_utm_y+df['Y'].mean()
# pair = utm.to_latlon(mean_x, mean_y, utm_zone, utm_band)
# loc = "%s,UT(%f,%f)" % (CITY,pair[0],pair[1])
# df['Location'] = loc
# df.to_csv('1.csv')
filePath = "G:\\IdeaProject\\spadas\\dataset\\argoverse\\"
errfilename = "convertErr_id.txt"
#relativePath = 'train/data/'
for root, dirs, files in os.walk(filePath):
for f in files:
try:
lats=[]
lons=[]
df = pd.read_csv(filePath+f)
for row in df.itertuples():
if df['CITY_NAME'][1]=='MIA':
CITY = Mia
x = mia_utm_x+getattr(row, 'X')
y = mia_utm_y+getattr(row, 'Y')
else:
CITY = Pit
x = piz_utm_x+getattr(row, 'X')
y = piz_utm_y+getattr(row, 'Y')
pair = utm.to_latlon(x, y, utm_zone, utm_band)
lats.append(pair[0])
lons.append(pair[1])
#loc = "%s" % (CITY)
#df['Location'] = loc
df['latitude'] = lats
df['longitude'] = lons
df.drop(columns=["Location"])
# index参数解决多出来一列
df.to_csv(filePath+f,index=False)
print("ok")
except Exception as inst :
# with open(errfilename,'a') as obj:
# obj.write(f+"\n")
print(inst)
continue