
- 最近更新时间
- 2020年03月05日
- 覆盖范围
- 全球209个国家和地区
- 运营公司
- 北京百度网讯科技有限公司
- 品牌愿景
- 科技让出行更简单
- 类 型
- 服务性软件
- 软件类型
- 出行类应用软件
- 推出时间
- 2005年
- 中文名
- 百度地图 [1]
- 外文名
- Baidu Maps
- 软件大小
- 94.8M
- 运营平台
- Web,PC,Android,iOS
- 最新版本
- 10.23.0.965
- 特色功能
- 智能语音,AR步导,智能驾车导航
-
Python实现百度地图、高德地图地理编码及高德地图经纬度坐标转百度地图经纬度坐标
2020-04-27 15:02:19pyecharts的基础还是echart,echart是百度地图开源的一个数据可视化 JS 库,从我个人使用的情况来看,目前pyecharts(博主pyecharts版本是0.5.11)有这两个问题: 地图精度不够。目前pyecharts...引言
近期博主在做地理数据可视化方面的研究,pyecharts提供了较好的工具,里面提供了很多图形,尤其是Map和Geo这两种图,一种是地图,一种是地理信息图。pyecharts的基础还是echart,echart是百度地图开源的一个数据可视化 JS 库,从我个人使用的情况来看,目前pyecharts(博主pyecharts版本是0.5.11)有这两个问题:
- 地图精度不够。目前pyecharts提供的地图层级有世界地图、各个国家的地图、中国各省地图、中国各地市图、区县图,到区县后,就不再细分,如果我想看某条道路的具体信息,就难以实现。
- 经纬度定位“不准确”。这不属于pyecharts是问题,应该属于百度地图在地理编码上的特点,当然,并不是说百度地图地理编码不准确,而是博主的目前在做的项目,地理位置都比较奇特,不管是BaiduMap还是AMap(高德地图)都很难定位到特别准确。由于pyecharts的底层地图是百度地图,所以看起来是pyecharts定位“不准确”。
要解决第一个问题,就是说想要更高层级的地图,这个就需要换可视化包了,也就是说,将pyecharts改成具有其他更高层级地图的可视化包。博主使用的是folium,这个包也很强大,pyecharts的强大之处在与echart的可视化功能,folium则体现在地图及地图的扩展应用上。folium目前支持OpenStreetMap、AMap等几种地图,但不支持百度地图。一度吐血,为啥我用的这两个包底层地图就不能通用下。但其实也好,为了用好这两个包,博主对百度、高德这两大地图大佬的开发文档进行了研究,现在将二者地理编码的方式记录下来。
开发环境:- Python3.7;
- pyecharts0.5.11;
- pycharm
百度地图地理编码
开发文档看这里,使用前需要去申请AK,同时最好申请开发者认证,能提升访问限制。开发文档其实写的很详细,无非是爬虫get和json解析那一套,我直接上代码。
import json import pandas as pd import numpy as np from urllib.request import urlopen, quote import requests def Scene2CoordinateBaiduMap(filename): data = pd.read_csv(filename) result = [] i = 1 j = 1 for k in data['地点']: address = quote(k) # 1 url = 'http://api.map.baidu.com/geocoder/v2/?address=' + address + '&output=json&ak=yourAK' # 2 req = urlopen(url) res = req.read().decode() temp = json.loads(res) try: # 3 result.append(temp['result']['location']) print('catch %d \n' % i) i = i + 1 except: result.append({'lat': 'null', 'lng': 'null'}) print('fail %d \n' % j) j = j + 1 print('成功定位%d个,成功率%.2f%%' % (i - 1, (i - 1) * 100 / (i + j - 2))) df = pd.DataFrame(result) df.to_csv('经纬度原始数据-百度地图.csv', index=False) if __name__ == '__main__': main()
先看导入的包,访问百度地图API返回的都是json格式的数据,要对数据进行解析,自然少不了json包,pandas和numpy常规包,基本上很难不用到,后面两个是网页数据获取的包。高德地图地理编码也是这几个包,后面不再重复写。
几点说明:
#1quote函数是为了得到GBK的url编码,国内的网站编码都是GBK编码的;
#2要把url里面的AK改成你自己申请的AK,而不是yourAK这个字符串;
#3为啥要用try来处理,因为不是所有的地理编码都能成功,如果不用try处理,容易报错,程序会中断。
这个函数写的很详细了,你提供一个CSV文件,其中一列命名为‘地点’,就能将你的所有填写的地点都能转换成经纬度,当然,也有不成功的,总体成功率在95%左右。总体来说,定位效果还是可以的,但是如果地点数据很多填写的不规范,地理编码虽然解析出经纬度,但很多都是有问题的,比如解析出来的点不在正确的地点,如下图。
这些点本来应该都出现在无锡市地图上,但还有不少点在无锡市外,也就是说,解析的不正确。问题出在哪里?博主又回过头去看文档,文档里说,请求的参数除了address外,还有city,也就是城市,这个参数不是必须要写的,如果是写了这个,会不会就正确了呢?于是,我找了一个落在无锡地图之外的点,将请求网址写成这样:http://api.map.baidu.com/geocoding/v3/?address=南湖大道双庆桥公交站前&city=无锡市&output=json&ak=您的ak&callback=showLocation
返回的数据如下:
showLocation&&showLocation({"status":0,"result":{"location":{"lng":120.31700801956372,"lat":31.532789952709309},"precise":0,"confidence":50,"comprehension":24,"level":"桥"}})
根据经纬度去百度地图拾取坐标系统中看看,巧了,点还对了。。。
博主懵逼了,上午的时候,明明是不对的,所以才想到要写一篇博客来解决这个问题,回过头来一想,因为我上午写的请求网址是这样的:http://api.map.baidu.com/geocoding/v3/?address=南湖大道双庆桥公交站前&city='无锡市'&output=json&ak=您的ak&callback=showLocation
无锡市我打了引号,其实是没必要打引号的。。。
所以,实际上,在请求网址里面加上城市名,就能保证经纬度转换的时候,所有点都落在你想要的城市里面。。。
持续吐血,这篇博客还要写吗,我上午已经按照我的解决思路,高德地图地理编码→高德地图转百度地图→pyecharts地点上图,这个套路,解析了3000+的地点。
都写了3000多字了,还是继续写完吧。。。高德地图地理编码
开发文档看这里
,技术细节与百度地图基本一致,请求格式上我换了一种写法,让读者可以更灵活的使用爬虫的技巧。
上代码def Scene2CoordinateAMap(filename): data = pd.read_csv(filename) sgdd = data['事故地点'].tolist() geo = [] key = 'yourKEY' base = 'https://restapi.amap.com/v3/geocode/geo' j = 1 k = 1 for i in range(len(sgdd)): parameters = {'address': sgdd[i], 'key': key, 'city':'无锡'} response = requests.get(base, parameters) answer = response.json() try: pos = answer['geocodes'][0]['location'] pos = pos.split(',') pos[0], pos[1] = pos[1], pos[0] geo.append(pos) print('catch %d \n'%j) j = j + 1 except: geo.append([ 'null','null']) print('fail %d \n'%k) k = k + 1 points = pd.DataFrame(geo) points.to_csv('经纬度填充-高德地图.csv', index=False, columns = ['lng', 'lat']) print('成功定位%d个,成功率%.2f%%' % (j - 1, (j - 1) * 100 / (j + k - 2)))
为啥我会写成‘无锡’,能理解了吧,我高德就是这么写的。。。
可以看出来,和百度地图请求方式有一点不同,我用的是requests.get去请求的,其实网上更多的推荐是用这种方式去请求,而不是用urlopen,不过我个人习惯用urlopen,两者都行吧。高德地图经纬度转百度地图经纬度
其实已经没啥必要写了,因为二者都差不多。
文档看这里,上代码def AMap2BaiduMap(filename): data = pd.read_csv(filename) base = 'http://api.map.baidu.com/geoconv/v1/?coords=' tail = '&from=3&to=5&ak=yourAK' transpos = [] j = 1 k = 1 for i in range(len(data)): url = base + str(data.iloc[i]['lng_Amap']) + ',' + str(data.iloc[i]['lat_Amap']) + tail req = urlopen(url) res = req.read().decode() temp = json.loads(res) try: pos = list(temp['result'][0].values()) # 字典转列表 transpos.append(pos) print('catch %d \n'%j) j = j + 1 except: transpos.append(['null','null']) print('fail %d \n'%k) k = k + 1 tran = pd.DataFrame(transpos) tran.to_csv('高德转百度.csv', index=False, columns = ['lng', 'lat']) print('成功转换%d个,成功率%.2f%%' % (j - 1, (j - 1) * 100 / (j + k - 2)))
注意下,链接里有这么句代码
from=3&to=5
官方文档解释如下:
源坐标类型:
1:GPS设备获取的角度坐标,WGS84坐标;
2:GPS获取的米制坐标、sogou地图所用坐标;
3:google地图、soso地图、aliyun地图、mapabc地图和amap地图所用坐标,国测局(GCJ02)坐标;
4:3中列表地图坐标对应的米制坐标;
5:百度地图采用的经纬度坐标;
6:百度地图采用的米制坐标;
7:mapbar地图坐标;
8:51地图坐标
目标坐标类型:
5:bd09ll(百度经纬度坐标);
6:bd09mc(百度米制经纬度坐标)我是高德经纬度转百度经纬度,自然是from=3to=5。
看看转换经纬度后的pyecharts-Geo图吧
全都在无锡市内了,大功告成,虽然没啥用了(╥╯^╰╥)完
-
百度地图接口爬取城市数据district_id
2020-12-16 16:48:07通过百度地图接口爬取百度地图城市数据,并存到mysql数据库里面: #!/usr/bin/python # coding=utf-8 import sys,time reload(sys) sys.setdefaultencoding("utf-8") import requests, traceback import json ...有问题可以联系本人QQ:1016401546,备注来意,否则不加
附件为通过百度地图接口爬取百度地图城市数据,并存到mysql数据库里面,信息表和脚本下载:
链接:https://pan.baidu.com/s/1w--dvalstFILrENbK4TasA
提取码:y71b
复制这段内容后打开百度网盘手机App,操作更方便哦--来自百度网盘超级会员V1的分享部分数据展示:
接口返回数据类型:
-
修复百度地图乱码
2019-04-17 09:58:46定位标注图标消失是因为原来的icon图片没有了,将 new BMap.Icon("http://app.baidu.com/map/images/us_mk_icon.png" /*修改为*/ ...中文乱码是因为生成的网页代码中,charset设置成gbk了,将 ......定位标注图标消失是因为原来的icon图片没有了,将
new BMap.Icon("http://app.baidu.com/map/images/us_mk_icon.png"
/*修改为*/new BMap.Icon("http://map.baidu.com/image/us_mk_icon.png"
中文乱码是因为生成的网页代码中,charset设置成gbk了,将
<meta http-equiv="Content-Type" content="text/html; charset=gb2312" />
/*修改为*/<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
-
vue使用百度地图----在线地图
2020-10-09 11:31:23Part1 在线地图 1、安装组件 npm install vue-baidu-map --save ... ak: '**********************' //此处为百度地图秘钥 }); 百度AK秘钥申请地址 3、HTML部分 <div id="baidu_map"> <baidu-ma1、安装组件
npm install vue-baidu-map --save
2、在main.js中引入组件
import BaiduMap from 'vue-baidu-map Vue.use(BaiduMap, { ak: '**********************' //此处为百度地图秘钥 });
3、HTML部分
<div id="baidu-map"> <baidu-map class="bm-view" :center="map.center" :zoom="map.zoom" @ready="ready" :map-click="false" @load="loadMap" @zoomend="syncCenterAndZoom"> <!--缩放--> <bm-navigation anchor="BMAP_ANCHOR_TOP_RIGHT"></bm-navigation> <!--定位--> <bm-geolocation anchor="BMAP_ANCHOR_BOTTOM_RIGHT" :showAddressBar="true" :autoLocation="true"></bm-geolocation> <!--点--> <bm-marker v-for="(item,index) in map.markList" :key="index" :position="item.position" animation="BMAP_ANIMATION_DROP" @click="markClick(index)" :dragging="true" :icon="item.icon" @dragend="markChange"> </bm-marker> <!--提示信息--> <bm-info-window :width="350" :height="220" :show="windowData.isShow" :position="windowData.position" :title="windowData.title" @open="infoWindowOpen" @close="infoWindowClose"> <div @click="windowClick(windowData)"> <el-row :gutter="23"> <el-col :span="10" style="text-align: center; margin-top: 30px"> <el-image :src="windowData.picUrl" style="width: 120px; height: 120px;" > </el-image> </el-col> <el-col :span="13" style="text-align:left; margin-top: 10px;"> <div :class="alarmClassName(windowData.powerSwitch)"> 总闸:<span :class="spanClass(windowData.powerSwitch)">{{windowData.powerSwitch}}</span> </div> <div :class="alarmClassName(windowData.power)"> 市电:<span :class="spanClass(windowData.power)">{{windowData.power}}</span> </div> <div :class="alarmClassName(windowData.net)"> 主网络:<span :class="spanClass(windowData.net)">{{windowData.net}}</span> </div> <div :class="alarmClassName(windowData.deviceState)"> 设备状态:<span :class="spanClass(windowData.deviceState)">{{windowData.deviceState}}</span> </div> </el-col> </el-row> </div> </bm-info-window> </baidu-map> </div>
4、JS数据及方法
<script> const level_99_url = 'data:image/gif;base64,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'; const defaupicUrl = 'data:image/png;base64,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'; export default { data(){ return{ map: { isShow: false, center: { lng: 116.2917, lat: 39.8427 }, zoom: 10, markList: [{ index:1, position: { lng: 116.2917, lat: 39.8427 }, faultLevel: 99, id: 1, name: '点位1', icon: { url: level_99_url, size: { width: 25, height: 25 } }, ip: '', picUrl: defaupicUrl, powerSwitch: '', power: '', net: '', deviceState: '', }], clickMarkIndex: '', }, windowData: { isShow: false, title: '', id: '', position: {}, powerSwitch: '', //总闸 power: '', //市电 net: '', //主网络 deviceState: '', //设备状态 picUrl: '', faultLevel:'', } } }, methods:{ //地图滚动 syncCenterAndZoom(e) { this.map.zoom = e.target.getZoom(); }, //初始化地图 ready({BMap, map}) { console.log(BMap, map); // 鼠标缩放 map.enableScrollWheelZoom(true); // 点击事件获取经纬度 map.addEventListener('click', function (e) { console.log(e.point.lng, e.point.lat) }); // 自定义样式 map.setMapStyle({ styleJson: [ { "featureType": "road", "elementType": "all", "stylers": { "lightness": 20 } }, { "featureType": "highway", "elementType": "geometry", "stylers": { "color": "#f49935" } }, { "featureType": "railway", "elementType": "all", "stylers": { "visibility": "off" } }, { "featureType": "local", "elementType": "labels", "stylers": { "visibility": "off" } }, { "featureType": "water", "elementType": "all", "stylers": { "color": "#d1e5ff" } }, { "featureType": "poi", "elementType": "labels", "stylers": { "visibility": "off" } } ] }); }, //标记点击事件 markClick(index) { this.map.clickMarkIndex = index; this.infoWindowOpen(); }, //信息窗体打开 infoWindowOpen() { this.windowData.isShow = true; var index = this.map.clickMarkIndex; this.windowData.id = this.map.markList[index].id; this.windowData.title = this.map.markList[index].name; this.windowData.position = this.map.markList[index].position; this.windowData.picUrl = this.map.markList[index].picUrl; this.windowData.faultLevel = this.map.markList[index].faultLevel; this.$nextTick(()=>{ if (this.windowData.faultLevel === 1) { //document.documentElement.style.setProperty('--box_background', 'rgba(8, 120, 18, 0.6)'); document.getElementsByClassName('BMap_pop')[0].childNodes[8].style.backgroundColor = 'transparent'; document.getElementsByClassName('BMap_pop')[0].childNodes[8].style.backgroundColor = 'rgba(253, 4, 95, 0.6)' } else if (this.windowData.faultLevel === 2) { //document.documentElement.style.setProperty('--box_background', 'rgba(255, 156, 1, 0.6)'); document.getElementsByClassName('BMap_pop')[0].childNodes[8].style.backgroundColor = 'transparent'; document.getElementsByClassName('BMap_pop')[0].childNodes[8].style.backgroundColor = 'rgba(255, 156, 1, 0.6)' } else if (this.windowData.faultLevel === 3) { //document.documentElement.style.setProperty('--box_background', 'rgba(226, 223, 30, 0.6)'); document.getElementsByClassName('BMap_pop')[0].childNodes[8].style.backgroundColor = 'transparent'; document.getElementsByClassName('BMap_pop')[0].childNodes[8].style.backgroundColor = 'rgba(226, 223, 30, 0.6)' } else if (this.windowData.faultLevel === 4) { //document.documentElement.style.setProperty('--box_background', 'rgba(8, 120, 18, 0.6)'); document.getElementsByClassName('BMap_pop')[0].childNodes[8].style.backgroundColor = 'transparent'; document.getElementsByClassName('BMap_pop')[0].childNodes[8].style.backgroundColor = 'rgba(0, 234, 220, 0.6)' } else{ //document.documentElement.style.setProperty('--box_background', 'rgba(8, 120, 18, 0.6)'); document.getElementsByClassName('BMap_pop')[0].childNodes[8].style.backgroundColor = 'transparent'; document.getElementsByClassName('BMap_pop')[0].childNodes[8].style.backgroundColor = 'rgba(8, 120, 18, 0.6)' } }) }, //信息窗体关闭 infoWindowClose() { this.windowData.isShow = false; this.windowData.faultLevel = '' }, //信息窗体点击事件 windowClick(id) { console.log(id) }, //信息窗体打开 bfClassName(faultLevel) { if (faultLevel === 1) { return 'bg_level_1' } else if (faultLevel === 2) { return 'bg_level_2' } else if (faultLevel === 3) { return 'bg_level_3' } else if (faultLevel === 4) { return 'bg_level_4' } else{ return 'bg_level_99' } }, //设置报警图标样式 alarmClassName(data) { if (data === '正常' || data === '-/-' || data[0] === '0') { return 'alarm_normal'; } else { return 'alarm_abnormal'; } }, //设置状态信息颜色 spanClass(data) { if (data === '正常' || data[0] === '0') { return 'span_normal'; } else if (data === '-/-') { return 'span_no_device'; } else { return 'span_abnormal'; } }, //标记点移动事件 markChange(params){ this.map.center.lat = params.point.lat; this.map.center.lng = params.point.lng; }, getMarkList(){ }, //加载数据(如果数据是异步加载) loadMap(){ this.getMarkList(); }, }, mounted() { } } </script>
**注:**上述代码,用到了this.$nextTick,这是在vue中如果要对dom进行操作,在此方法中可以保证dom节点已加载完成,vue中是以数据驱动的形式来渲染dom的,也就是说数据修改后,dom不会马上改变,它会排队等待修改。
5、CSS样式部分
<style > #baidu-map{ height: 100vh; } .bm-view { width: 100%; height: 100%; } /* 去除百度地图版权那行字 和 百度logo */ .bm-view .BMap_cpyCtrl { display: none !important; } .bm-view .anchorBL { display: none !important; } /*左上角*/ .BMap_pop div:nth-child(1) div { background-color: transparent !important; border-left: 0px !important; border-top: 0px !important; } /*右上角*/ .BMap_pop div:nth-child(3) div { display:none; } /*左下角*/ .BMap_pop div:nth-child(5) { display:none; } /*右下角*/ .BMap_pop div:nth-child(7) { display:none; } /*箭头部分*/ .BMap_pop div:nth-child(8) { display:none; } /*主体内容部分*/ .BMap_pop div:nth-child(9) { left: 0px !important; top: 0px !important ; font-size: 15px; color: #fff; line-height: 39px; width: 100% !important; height: 110% !important; background-color: var(--box_background); } /*顶中间*/ .BMap_pop .BMap_top{ display:none; } /*底中间*/ .BMap_pop .BMap_bottom{ display:none; } .BMap_pop .BMap_center { position: initial !important; border-left: 0px solid #ababab !important; border-right: 0px solid #ababab !important; background-color: transparent !important; } .BMap_bubble_title { color: #FFF; font-weight: bold; text-align: center; line-height: 35px; font-size: 18px; margin: 7px; } .alarm_normal{ color: #fff; line-height: 39px; font-size: 14px; } .alarm_normal:before{ content: ""; float: left; width: 20px; height: 20px; margin-right: 13px; margin-top: 8px; background-position: center center; background-image: url("../../../static/img/ElectronicMap/map.jk.one.png"); } .alarm_abnormal{ color: #fff; line-height: 39px; font-size: 14px; } .alarm_abnormal:before{ content: ""; float: left; width: 20px; height: 20px; margin-right: 13px; margin-top: 9px; background-position: center center; background-image: url("../../../static/img/ElectronicMap/map.jk.three.png"); } .span_normal{ color: #6ef22d; } .span_abnormal{ color: #fd0433; } .span_no_device{ color: rgb(74, 74, 74); font-weight: bolder; } .bg_level_1{ background: rgba(253, 4, 95, 0.7) } .bg_level_2{ background: rgba(255, 156, 1, 0.7) } .bg_level_3{ background: rgba(226, 223, 30, 0.7) } .bg_level_4{ background: rgba(0, 234, 220, 0.7) } .bg_level_99{ background: rgba(8, 120, 18, 0.7) } </style>
6、效果图
-
百度地图坐标系统解析
2019-06-22 14:55:52在地球上我们通过经纬度来描述某个位置,而经过投影之后的地图也有自己的坐标系统,本篇文章就来详细介绍在百度地图API中涉及的各种坐标体系。 在百度地图API中,你需要了解如下坐标系: 经纬度:通过经度... -
百度地图BaiduMap_AndroidSDK_v6.4.0中的路线规划功能为啥不可用???
2020-07-30 23:21:52百度地图BaiduMap_AndroidSDK_v6.4.0中的路线规划功能为啥不可用??? 百度地图例子BaiduMap_AndroidSDK_v6.4.0_Sample 中的路线规划都不可用?????[face]monkey:35.gif[/face] [img=... -
百度地图 创建应用
2019-09-25 23:55:281、你要使用百度地图的服务,就先要去百度地图开放平台创建一个应用,从而获取到一个大多数的Api服务都要用到的Key。连接地址:百度地图开放平台。 2、点击控制台。 3、点击创建应用 4、随便输一个应用名称,... -
常用的几种在线地图(天地图、百度地图、高德地图)坐标系之间的转换算法
2019-01-14 16:39:371、首先弄明白几种在线地图的坐标系; (1)天地图:CGCS2000,2000国家大地坐标系;我们其实很多时候直接用WGS84的坐标来代替CGCS2000坐标。因为CGCS2000的定义与WGS84实质一样。采用的参考椭球非常接近。扁率差异... -
百度地图自定义覆盖物工具栏,修改标识图标
2020-04-09 13:36:17drawingManager工具栏 drawingModes设置工具栏模式 直接上效果代码 <!DOCTYPE html> <html> <head> <meta http-equiv="Content-Type" content="text/html;...meta name="viewport" co... -
百度地图升级4:给点添加弹框
2020-05-25 17:29:10// 设置弹框的格式 var opts = { boxStyle: { width: "280px", height: "120px", }, enableAutoPan: true, }; //根据判断设置图标--排口 .. -
使用Python调用百度地图的API在地图上添加标记
2020-12-14 15:54:26地图的底图不支持百度地图,博主想用这个包的话,就不得不将数据点转到高德坐标系下,然后进行下一步工作,然而高德莫名其妙的封了我的账号,说我违规调取数据,简直莫须有; 间歇性的出现一些未知的问题,比如添加... -
百度地图POI数据获取
2019-01-17 00:57:06本文主要介绍百度地图POI数据获取:从百度地图得到POI数据,以json格式保存; POI数据获取的原理部分还可以参照零基础掌握百度地图兴趣点获取POI爬虫(python语言爬取)(基础篇)。 POI数据获取 百度地图POI数据... -
通过百度地图API获取用户所在地理位置信息
2020-10-18 21:42:38使用以下源码前,请先去百度地图开发平台申请密匙,前去申请:立即申请 2、源代码 此次定位代码是通过H5的方式实现的 <html> <head> <meta http-equiv="Content-Type" content="text/html; ... -
百度地图,地图轨迹
2020-06-06 21:20:20百度地图,记录行动轨迹: 效果图: 上代码: <!DOCTYPE html> <html> <head> <meta http-equiv="Content-Type" content="text/html; charset=utf-8" /> <meta name="viewport... -
使用百度地图绘制热力图
2018-01-30 10:01:51首先需要到百度地图开放平台注册开发者信息,并且获得AK应用访问标识码 因为要做本地调用,所以Referer白名单里面只写一个*就全允许了,拿到AK码之后写个HTML调用演示代码如下 这里是自己的... -
Python调用百度地图api获取起点终点路线规划距离和预估时长
2018-08-15 21:42:33现有起点和终点坐标值(经纬度lng、lat),目的是通过百度地图开发者平台的路线规划功能获取起点终点路线规划距离和预估时长,百度地图开发者平台路线规划使用说明网址为:... 工具:Python3 实现过程并不难,但是爬取... -
百度地图api 密钥获取
2019-03-14 17:05:291、进入百度地图api首页 http://lbsyun.baidu.com/ (首先要有个百度账号并登陆) 拉到页面最下方会看到申请密钥,点击 2、点击申请密钥后跳转到这个填写个人信息页面 3、填写完后 提交,等待邮件确认(别着急,我... -
Flutter百度地图
2020-07-29 23:26:11Flutter百度地图-重构项目 一、实现效果如下图 qq交流群:群号:730772561 1、地图中任意踩点进行杆塔和设备的新建,对与点和线进行关联 2、对于点和线进行各种操作。 3、自定义区域下载离线地图。 4…热烈线 5…... -
项目中加入百度地图(调用百度地图的接口)
2020-05-28 14:41:00这里用html调用百度地图做样例 先总结一下步骤, 首先需要注册账号,绑定之类的,然后申请一个AK密匙 然后在百度地图的De...
-
linux系统中的日志管理
-
Spring Boot API 的 Controller 如何获得发送的 JSON 数据
-
利用脚本,实现腾讯云DNSPod进行DDNS动态域名解析ipv6地址
-
基于CAN总线的数据可靠性传输
-
UE4游戏逆向与安全+FPS游戏逆向与安全
-
PHP框架最新性能压力测试比较
-
东南大学网络安全学院-软件学院夏令营
-
万象2004 非常好用
-
基于多传感器的三维目标位姿测量方法
-
一种具有在线自检功能的开出回路设计
-
原子光刻中原子通量的优化研究
-
PHP支付宝微信支付配置教程
-
易语言开发通达信DLL公式接口
-
Database Management Systems(数据库系统原理总结)- 第二章
-
Experimental methods for warm dense matter research
-
高精度位移测量系统的硬件在环仿真
-
数据类型转换、运算符、方法入门
-
【数据分析-随到随学】Spark理论及实战
-
软件测试基础
-
基于离散自适应滑模控制的DC-DC变换器的设计与仿真