这篇文章主要介绍了用python找出那些被“标记”的照片的相关资料,需要的朋友可以参考下
源码传送门
环境准备
下面的两个第三方模块都可以直接通过pip快速安装，这里使用py36作为运行环境。
python3.6
requests
exifread
思路
遍历目录
拉取数据集合
遍历集合取得exif
exif信息整理，并获取实体地址
拷贝文件到结果样本目录
生成json报告文件
基础知识
下面是现今相片中会存在与GPS相关的关键字，大牛亦可一比带过~ [参考]
{
"GPSVersionID": "GPS版本",
"GPSLatitudeRef": "南北纬",
"GPSLatitude": "纬度",
"GPSLongitudeRef": "东西经",
"GPSLongitude": "经度",
"GPSAltitudeRef": "海拔参照值",
"GPSAltitude": "海拔",
"GPSTimeStamp": "GPS时间戳",
"GPSSatellites": "测量的卫星",
"GPSStatus": "接收器状态",
"GPSMeasureMode": "测量模式",
"GPSDOP": "测量精度",
"GPSSpeedRef": "速度单位",
"GPSSpeed": "GPS接收器速度",
"GPSTrackRef": "移动方位参照",
"GPSTrack": "移动方位",
"GPSImgDirectionRef": "图像方位参照",
"GPSImgDirection": "图像方位",
"GPSMapDatum": "地理测量资料",
"GPSDestLatitudeRef": "目标纬度参照",
"GPSDestLatitude": "目标纬度",
"GPSDestLongitudeRef": "目标经度参照",
"GPSDestLongitude": "目标经度",
"GPSDestBearingRef": "目标方位参照",
"GPSDestBearing": "目标方位",
"GPSDestDistanceRef": "目标距离参照",
"GPSDestDistance": "目标距离",
"GPSProcessingMethod": "GPS处理方法名",
"GPSAreaInformation": "GPS区功能变数名",
"GPSDateStamp": "GPS日期",
"GPSDifferential": "GPS修正"
}初始化
考虑到exifread的模块中有大量的logging输出，这里将它的level级别调到最高。 然后下边的KEY是某站在高德地图API的时候遗留下来的 我也很尴尬。。就当福利了
import os import time import json import random import logging import requests import exifread logging.basicConfig(level=logging.CRITICAL) KEY = "169d2dd7829fe45690fabec812d05bc3"
主逻辑函数
def main():
# 预设后缀列表
types = ["bmp", "jpg", "tiff", "gif", "png"]
#结果数据集合
picex = []
# 文件存储路径
saves = "$" + input("| SavePath: ").strip()
# 文件搜索路径 并遍历所有文件返回文件路径列表
pools = jpgwalk(input("| FindPath: "), types)
#存储目录
savep = "%s/%s" % (os.getcwd().replace("\\", "/"), saves)
if savep in pools:
pools.remove(savep)
# 遍历数据集并获取exif信息
for path in pools:
res = getEXIF(path)
if res:
picex.append(res)
# 结果报告
print("| Result %s" % len(picex))
# 如果存在结果 保存结果到json并讲相关图片复制到该目录下
if picex:
#创建目录
if not os.path.exists(saves):
os.mkdir(saves)
#生成一个4格缩进的json文件
with open("%s/%s.json" % (saves, saves), "wb") as f:
f.write(json.dumps(picex, ensure_ascii=False, indent=4).encode("utf8"))
#copy图像到该目录
for item in picex:
source_path = item["Filename"]
with open("%s/%s" % (saves, source_path.split("/")[-1]), "wb") as f_in:
with open(source_path, "rb") as f_out:
f_in.write(f_out.read())遍历方法
遍历指定及其所有下级目录，并返回全部的图片的路径集合，这里要注意的是每次扫描后的拷贝行为都会生成缓存，所以通过指定 $ 来避开。
# 获取指导目录全部的图片路径
def jpgwalk(path, types):
_start = time.time()
_pools = []
# 遍历该目录 并判断files后缀 如符合规则则拼接路径
for _root, _dirs, _files in os.walk(path):
_pools.extend([_root.replace("\\", "/") + "/" +
_item for _item in _files if _item.split(".")[-1].lower() in types and "$" not in _root])
#报告消耗时间
print("| Find %s \n| Time %.3fs" % (len(_pools), time.time() - _start))
return _pools经纬度格式化
度分秒转浮点，方便api调用查询，因为存在一些诡异的数据比如 1/0，所以默认返回0
def cg(i): try: _ii = [float(eval(x)) for x in i[1:][:-1].split(', ')] _res = _ii[0] + _ii[1] / 60 + _ii[2] / 3600 return _res except ZeropisionError: return 0
EXIF信息整理
考虑到大部分的设备还未开始支持朝向、速度、测量依据等关键字，这里暂时只使用比较常见的，如有需要的朋友可以自行添加。毕竟得到的信息越多对社工有更大的帮助。
def getEXIF(filepath):
#基础关键字
_showlist = [
'GPS GPSDOP',
'GPS GPSMeasureMode',
'GPS GPSAltitudeRef',
'GPS GPSAltitude',
'Image Software',
'Image Model',
'Image Make'
]
#GPS关键字
_XYlist = ["GPS GPSLatitude", "GPS GPSLongitude"]
#时间关键字
_TimeList = ["EXIF DateTimeOrigina", "Image DateTime", "GPS GPSDate"]
#初始化结果字典
_infos = {
'Filename': filepath
}
with open(filepath, "rb") as _files:
_tags = None
# 尝试去的EXIF信息
try:
_tags = exifread.process_file(_files)
except KeyError:
return
# 判断是否存在地理位置信息
_tagkeys = _tags.keys()
if _tags and len(set(_tagkeys) & set(_XYlist)) == 2 and cg(str(_tags["GPS GPSLongitude"])) != 0.0:
for _item in sorted(_tagkeys):
if _item in _showlist:
_infos[_item.split()[-1]] = str(_tags[_item]).strip()
# 经纬度取值
_infos["GPS"] = (cg(str(_tags["GPS GPSLatitude"])) * float(1.0 if str(_tags.get("GPS GPSLatitudeRef", "N")) == "N" else -1.0),
cg(str(_tags["GPS GPSLongitude"])) * float(1.0 if str(_tags.get("GPS GPSLongitudeRef", "E")) == "E" else -1.0))
# 获取实体地址
_infos["address"] = address(_infos["GPS"])
# 获取照片海拔高度
if "GPS GPSAltitudeRef" in _tagkeys:
try:
_infos["GPSAltitude"] = eval(_infos["GPSAltitude"])
except ZeropisionError:
_infos["GPSAltitude"] = 0
_infos["GPSAltitude"] = "距%s%.2f米" % ("地面" if int(
_infos["GPSAltitudeRef"]) == 1 else "海平面", _infos["GPSAltitude"])
del _infos["GPSAltitudeRef"]
# 获取可用时间
_timeitem = list(set(_TimeList) & set(_tagkeys))
if _timeitem:
_infos["Dates"] = str(_tags[_timeitem[0]])
return _infos地址转换
一个简单的爬虫，调用高德地图api进行坐标转换，考虑到原本是跨域，这里添加基础的反防爬代码。这里有个小细节，海外的一律都取不到（包括台湾），可以通过更换googlemap的api来实现全球查询。
def address(gps):
global KEY
try:
# 随机UA
_ulist = [
"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/535.1 (KHTML, like Gecko) Chrome/14.0.835.163 Safari/535.1",
"Mozilla/5.0 (Windows NT 6.1; WOW64; rv:6.0) Gecko/20100101 Firefox/6.0",
"Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 5.1; Trident/4.0; InfoPath.2; .NET4.0C; .NET4.0E; .NET CLR 2.0.50727; 360SE)",
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_7_0) AppleWebKit/535.11 (KHTML, like Gecko) Chrome/17.0.963.56 Safari/535.11",
"Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_6_8; en-us) AppleWebKit/534.50 (KHTML, like Gecko) Version/5.1 Safari/534.50",
"Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; Win64; x64; Trident/5.0; .NET CLR 2.0.50727; SLCC2; .NET CLR 3.5.30729; .NET CLR 3.0.30729; Media Center PC 6.0; InfoPath.3; .NET4.0C; Tablet PC 2.0; .NET4.0E)",
"Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; WOW64; Trident/5.0)",
"Mozilla/5.0 (X11; U; Linux i686; rv:1.7.3) Gecko/20040913 Firefox/0.10",
"Opera/9.80 (Macintosh; Intel Mac OS X 10.6.8; U; ja) Presto/2.10.289 Version/12.00",
"Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/45.0.2454.93 Safari/537.36"
]
# 伪造header
_header = {
"User-Agent": random.choice(_ulist),
"Accept": "text/javascript, application/javascript, application/ecmascript, application/x-ecmascript, */*; q=0.01",
"Accept-Encoding": "gzip, deflate, sdch",
"Accept-Language": "zh-CN,zh;q=0.8",
"Referer": "http://www.gpsspg.com",
}
_res = requests.get(
"http://restapi.amap.com/v3/geocode/regeo?key={2}&s=rsv3&location={1},{0}&platform=JS&logversion=2.0&sdkversion=1.3&appname=http%3A%2F%2Fwww.gpsspg.com%2Fiframe%2Fmaps%2Famap_161128.htm%3Fmapi%3D3&csid=945C5A2C-E67F-4362-B881-9608D9BC9913".format(gps[0], gps[1], KEY), headers=_header, timeout=(5, 5))
_json = _res.json()
# 判断是否取得数据
if _json and _json["status"] == "1" and _json["info"] == "OK":
# 返回对应地址
return _json.get("regeocode").get("formatted_address")
except Exception as e:
pass实例
运行该代码 然后输入保存文件夹名和扫描位置即可
这边可以看到8019张中有396张存在有效的地理位置，打码的地方就不解释了，各位老司机~后期打算加入图像识别，和相似度识别。
下面给大家分享小编收集整理的python专题知识：
python基本语法
python多线程学习教程
python排序算法大全
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