python提取照片坐標(biāo)信息的實例代碼

更新時間：2019年08月14日 10:16:20 作者：張景源

這篇文章主要介紹了python提取照片坐標(biāo)信息的實例代碼，文中給大家提到了Python利用exifread庫來解析照片的經(jīng)緯度，通過實例代碼給大家介紹的非常詳細(xì)，具有一定的參考借鑒價值,需要的朋友可以參考下

python提取照片坐標(biāo)信息的代碼如下所示：

from PIL import Image
from PIL.ExifTags import TAGS
import os
output="Z://result.csv"
out=open(output,'a')
out.write('lat,lon\n')
fpath="Z://iphonephoto"
for item in os.walk(fpath):
 ob=item[2]
 for i in ob:
  name=fpath+'/'+str(i)
  ret={}
  try:
   img=Image.open(name)
   if hasattr(img,'_getexif'):
    exifinfo=img._getexif()
    if exifinfo !=None:
     for tag,value in exifinfo.items():
      decoded=TAGS.get(tag,tag)
      ret[decoded]=value
      N1 = ret['GPSInfo'][2][0][0]
      N2 = ret['GPSInfo'][2][1][0]
      N3 = ret['GPSInfo'][2][2][0]
      N=int(N1)+int(N2)*(1.0/60)+int(N3)*(1.0/360000)
      E1 = ret['GPSInfo'][4][0][0]
      E2 = ret['GPSInfo'][4][1][0]
      E3 = ret['GPSInfo'][4][2][0]
      E=int(E1)+int(E2)*(1.0/60)+int(E3)*(1.0/360000)
      out.write(str(N)+','+str(E)+'\n')
  except:
   pass
out.close()

PS：Python小列子-讀取照片位置

Python exifread

Python利用exifread庫來解析照片的經(jīng)緯度，對接百度地圖API顯示拍攝地點。

import exifread
import re
import json
import requests
def latitude_and_longitude_convert_to_decimal_system(*arg):
 """
 經(jīng)緯度轉(zhuǎn)為小數(shù), 作者嘗試適用于iphone6、ipad2以上的拍照的照片，
 :param arg:
 :return: 十進(jìn)制小數(shù)
 """
 return float(arg[0]) + ((float(arg[1]) + (float(arg[2].split('/')[0]) / float(arg[2].split('/')[-1]) / 60)) / 60)
def find_GPS_image(pic_path):
 GPS = {}
 date = ''
 with open(pic_path, 'rb') as f:
  tags = exifread.process_file(f)
  for tag, value in tags.items():
   if re.match('GPS GPSLatitudeRef', tag):
    GPS['GPSLatitudeRef'] = str(value)
   elif re.match('GPS GPSLongitudeRef', tag):
    GPS['GPSLongitudeRef'] = str(value)
   elif re.match('GPS GPSAltitudeRef', tag):
    GPS['GPSAltitudeRef'] = str(value)
   elif re.match('GPS GPSLatitude', tag):
    try:
     match_result = re.match('\[(\w*),(\w*),(\w.*)/(\w.*)\]', str(value)).groups()
     GPS['GPSLatitude'] = int(match_result[0]), int(match_result[1]), int(match_result[2])
    except:
     deg, min, sec = [x.replace(' ', '') for x in str(value)[1:-1].split(',')]
     GPS['GPSLatitude'] = latitude_and_longitude_convert_to_decimal_system(deg, min, sec)
   elif re.match('GPS GPSLongitude', tag):
    try:
     match_result = re.match('\[(\w*),(\w*),(\w.*)/(\w.*)\]', str(value)).groups()
     GPS['GPSLongitude'] = int(match_result[0]), int(match_result[1]), int(match_result[2])
    except:
     deg, min, sec = [x.replace(' ', '') for x in str(value)[1:-1].split(',')]
     GPS['GPSLongitude'] = latitude_and_longitude_convert_to_decimal_system(deg, min, sec)
   elif re.match('GPS GPSAltitude', tag):
    GPS['GPSAltitude'] = str(value)
   elif re.match('.*Date.*', tag):
    date = str(value)
 return {'GPS_information': GPS, 'date_information': date}
def find_address_from_GPS(GPS):
 print(GPS)
 """
 使用Geocoding API把經(jīng)緯度坐標(biāo)轉(zhuǎn)換為結(jié)構(gòu)化地址。
 :param GPS:
 :return:
 """
 secret_key = 'xxxxxxxxxxxxxxxxxxxx'    # 百度地圖創(chuàng)應(yīng)用的秘鑰 
 if not GPS['GPS_information']:
  return '該照片無GPS信息'
 lat, lng = GPS['GPS_information']['GPSLatitude'], GPS['GPS_information']['GPSLongitude']
 baidu_map_api = "http://api.map.baidu.com/geocoder/v2/?ak={0}&callback=renderReverse&location={1},{2}s&output=json&pois=0".format(
  secret_key, lat, lng)
 response = requests.get(baidu_map_api)
 content = response.text.replace("renderReverse&&renderReverse(", "")[:-1]
 baidu_map_address = json.loads(content)
 formatted_address = baidu_map_address["result"]["formatted_address"]
 # province = baidu_map_address["result"]["addressComponent"]["province"]
 # city = baidu_map_address["result"]["addressComponent"]["city"]
 # district = baidu_map_address["result"]["addressComponent"]["district"]
 return formatted_address
GPS_info = find_GPS_image(pic_path='lllll.jpg')  # 照片
address = find_address_from_GPS(GPS=GPS_info)
print(address)

總結(jié)

以上所述是小編給大家介紹的python提取照片坐標(biāo)信息的實例代碼 ,希望對大家有所幫助，如果大家有任何疑問請給我留言，小編會及時回復(fù)大家的。在此也非常感謝大家對腳本之家網(wǎng)站的支持！
如果你覺得本文對你有幫助，歡迎轉(zhuǎn)載，煩請注明出處，謝謝！

您可能感興趣的文章: