class PowerLineSearchFuzzy(Resource):
def __init__(self):
self.dao = LinesDao()
self.userDao = UserDAO()
def post(self):
#if (request.data != ""):
# data = json.loads(request.data)
# token = data['token']
# user = self.userDao.verify_token(token, '')
# if (not user):
# return make_response(jsonify({'error': 'Unauthorized access'}), 401)
args = parser.parse_args()
linename = args.get('linename')
rs = self.dao.query_line_fuzzy(linename)
if rs == None:
return make_response(
jsonify({
'error': '根据线路名称查询线路信息失败',
'errorcode': 10000000
}), 401)
else:
return json.dumps(rs)
#else:
# return make_response(jsonify({'error': 'Unauthorized access'}), 401)
def get(self):
return self.post()
def ClassifyPhoto(self,towers,photoPath,date,basefolder):
#纬度一度的差异 直接计算差异比坐标转换之后再计算虽然在精度上下降了，但是效率上得到了很大的提高
# 综合考虑之后采用直接通过经度和纬度差异的方式进行计算
unitLat = 111000.0
photoCoordinate = self.GetPhotoCoordinate(photoPath)
if photoCoordinate==None:
return None
dis = []
for towerItem in towers:
unitLng = unitLat*math.cos(math.radians(photoCoordinate['lat']))
dLat = (towerItem['tower_lat']-photoCoordinate['lat'])*unitLat*(towerItem['tower_lat']-photoCoordinate['lat'])*unitLat
dLng = (towerItem['tower_lng']-photoCoordinate['lng'])*unitLng*(towerItem['tower_lng']-photoCoordinate['lng'])*unitLng
dis.append(math.sqrt(dLat+dLng))
index = dis.index(min(dis))
#将文件移动到对应的文件夹下
daoLine=LinesDao()
line=daoLine.query_line_fuzzy(towers[index]['tower_linename'])
filename=os.path.basename(photoPath)
#构建目标路径
basePath = '\\'+str(line[0]['lines_voltage'])+'\\'+str(line[0]['lines_id'])+'\\'+str(towers[index]['tower_id'])+'\\'+date+'\\未分类\\'+filename
distPath= basefolder+basePath
#移动文件夹
self.MoveFile(photoPath,distPath)
return (basePath,index,line[0]['lines_id'])