{ "cells": [ { "cell_type": "markdown", "id": "c1869066", "metadata": {}, "source": [ "# 百度地图开放平台-全景静态图API\n", "https://lbsyun.baidu.com/index.php?title=viewstatic" ] }, { "cell_type": "markdown", "id": "d5e35063", "metadata": {}, "source": [ "# 读取秘钥csv文件中的key" ] }, { "cell_type": "code", "execution_count": 1, "id": "83ceaf37", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[['key1', '4vdK0K1Z8LPmLNBv9fFBGRuzogdnP9hL'],\n", " ['key2', 'y2yXxM6FC9XUHI4KzkTCsvxHGRKZKWVO'],\n", " ['key3', '0fIaWysuTwB0yA6pbWYSFiwbuP7kezFK'],\n", " ['key4', '9sy8B4q5hjlkLGSRheGr8ES0qAwClp6v'],\n", " ['key5', 'IDy1NotnsXRMQhaTCIifN9my9RRTaCno'],\n", " ['key6', '8QohpT5YEgrkySGmXM2y40HVP31z7P6C'],\n", " ['key7', '3G1GoHZN9SI9vLo86YYplfXo92WgkYL2'],\n", " ['key8', 'KGYkoFyYbumiY5iofIeZ2Sz3Qwl0dqUm'],\n", " ['key9', 'RtxQQsqajjOo5bAC9b0SCzY2PHC8j8FF'],\n", " ['key10', '01esYaSVS73IynskVMBqY2FKWLDiyrHp'],\n", " ['key11', 'HgiutFdoWkKznSS7MhKxGbG7GpZR5H0s'],\n", " ['key12', 'dvm7peKfL3spkYRaLzLzqGVSY9j2hXuS'],\n", " ['key13', '6AK9XOQmFRWAjQHdjfzdNBTxtIjjAjdm'],\n", " ['key14', '1TLhvzPEHH51SfK84bzOxIRSxHUe6u4Y'],\n", " ['key15', 'EbBFkg00kvMYoboGOrMRaQ3vUKaoFoY4'],\n", " ['key16', 'AhL85b4Kz08YagalTIs7KNbNGZz1waVL'],\n", " ['key17', 'Y9lBAwZY2eDXh3oWYWlutaAfkGiTEVCl'],\n", " ['key18', '43URb7W1281q2yYTXEnrlVDU31hhCGAU'],\n", " ['key19', '9EaLULgSd7p6xhw86EHakqMn2sDehbs2'],\n", " ['key20', 'No3Nc4zPfeeACQ1OE2poSM9Lp8XFalZ6']]" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import csv\n", "\n", "# 储存着key的文件\n", "key_path = r'F:\\DataPai_Case\\StreetView/key.csv'\n", "\n", "# 创建一个list 记录所有的key\n", "key_list = []\n", "\n", "with open(key_path,mode='r',encoding='utf-8') as f:\n", " lines = csv.reader(f)\n", " for line in lines:\n", " key_list.append(line)\n", "key_list" ] }, { "cell_type": "markdown", "id": "85f52ba4", "metadata": {}, "source": [ "# 读取csv文件中的序号和坐标" ] }, { "cell_type": "code", "execution_count": 2, 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'121.5339519', '31.36507141'],\n", " ['953', '121.5364154', '31.36384299'],\n", " ['954', '121.5408597', '31.3691476'],\n", " ['955', '121.5428709', '31.36845945'],\n", " ['956', '121.5414174', '31.36666616'],\n", " ['957', '121.5428709', '31.36845945'],\n", " ['958', '121.5414174', '31.36666616'],\n", " ['959', '121.5426317', '31.36636144'],\n", " ['960', '121.5402873', '31.36535889'],\n", " ['961', '121.5426317', '31.36636144'],\n", " ['962', '121.5402873', '31.36535889'],\n", " ['963', '121.5364154', '31.36384299'],\n", " ['964', '121.5393197', '31.36680328'],\n", " ['965', '121.5374214', '31.36553054'],\n", " ['966', '121.5393197', '31.36680328'],\n", " ['967', '121.5402873', '31.36535889'],\n", " ['968', '121.5398365', '31.36719304'],\n", " ['969', '121.5393197', '31.36680328'],\n", " ['970', '121.5398365', '31.36719304'],\n", " ['971', '121.5383767', '31.3676082'],\n", " ['972', '121.5398365', '31.36719304'],\n", " ['973', '121.5408597', '31.3691476'],\n", " ['974', '121.5398365', '31.36719304'],\n", " ['975', '121.5414174', '31.36666616'],\n", " ['976', '121.5474216', '31.36481634'],\n", " ['977', '121.5475747', '31.36445924'],\n", " ['978', '121.546261', '31.36506841'],\n", " ['979', '121.5426317', '31.36636144'],\n", " ['980', '121.5466283', '31.36495479'],\n", " ['981', '121.5474216', '31.36481634'],\n", " ['982', '121.5466283', '31.36495479'],\n", " ['983', '121.546261', '31.36506841'],\n", " ['984', '121.5472738', '31.36563683'],\n", " ['985', '121.5474216', '31.36481634'],\n", " ['986', '121.5472738', '31.36563683'],\n", " ['987', '121.5466283', '31.36495479'],\n", " ['988', '121.5472738', '31.36563683'],\n", " ['989', '121.5475303', '31.36595968'],\n", " ['990', '121.5474216', '31.36481634'],\n", " ['991', '121.5475303', '31.36595968'],\n", " ['992', '121.546261', '31.36506841'],\n", " ['993', '121.5397173', '31.36150043'],\n", " ['994', '121.5524728', '31.36813225'],\n", " ['995', '121.552983', '31.36792819'],\n", " ['996', '121.5525748', '31.36823428'],\n", " ['997', '121.5524728', '31.36813225'],\n", " ['998', '121.5525748', '31.36823428'],\n", " ['999', '121.553085', '31.36803022'],\n", " ...]" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# 储存着坐标的文件\n", "csv_path = r'F:\\DataPai_Case\\StreetView/Shanghai.csv'\n", "\n", "# 创建一个list 记录所有的key\n", "data_list = []\n", "\n", "with open(csv_path,mode='r',encoding='utf-8') as f:\n", " lines = csv.reader(f)\n", " for line in lines:\n", " data_list.append(line)\n", "data_list = data_list[1:]\n", "data_list" ] }, { "cell_type": "markdown", "id": "6cf4fd28", "metadata": {}, "source": [ "# 坐标转换wgs84到bd09\n", "https://lbsyun.baidu.com/index.php?title=webapi/guide/changeposition" ] }, { "cell_type": "code", "execution_count": 3, "id": "abecf9fc", "metadata": {}, "outputs": [], "source": [ "import requests\n", "import json\n", "\n", "def wgs2bd09mc(lon, lat):\n", " url = 'https://api.map.baidu.com/geoconv/v1/?coords={},{}&from=1&to=5&ak=Vd88SC0LpGjiGNQywXsyVxZPOTcyear9'.format(lon, lat)\n", "\n", " response = requests.get(url)\n", " response = response.content\n", " response = response.decode()\n", " temp = json.loads(response)\n", "\n", " if temp['status'] == 0:\n", " bd09_lon = temp['result'][0]['x']\n", " bd09_lat = temp['result'][0]['y']\n", " \n", " return bd09_lon,bd09_lat" ] }, { "cell_type": "markdown", "id": "7be409dc", "metadata": {}, "source": [ "# 检测已经下载的图片名字" ] }, { "cell_type": "code", "execution_count": 4, "id": "361f7c66", "metadata": {}, "outputs": [], "source": [ "import glob\n", "\n", "filenames_exist = glob.glob1(r'F:\\DataPai_Case\\StreetView\\Shanghai','*.jpg')\n", "filenames_exist = [i.split('.jpg')[0] for i in filenames_exist]" ] }, { "cell_type": "code", "execution_count": 5, "id": "6d413e9c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['0_0', '0_1', '0_2', '0_3', '10_0', '10_1', '10_2', '10_3', '11_0', '11_1', '11_2', '11_3', '12_0', '12_1', '12_2', '12_3', '13_0', '13_1', '13_2', '13_3', '14_0', '14_1', '14_2', '14_3', '15_0', '15_1', '15_2', '15_3', '16_0', '16_1', '16_2', '16_3', '17_0', '17_1', '17_2', '17_3', '18_0', '18_1', '18_2', '18_3', '19_0', '19_1', '19_2', '19_3', '1_0', '1_1', '1_2', '1_3', '20_0', '20_1', '20_2', '20_3', '21_0', '21_1', '21_2', '21_3', '22_0', '22_1', '22_3', '23_0', '23_1', '23_2', '23_3', '24_0', '24_1', '24_2', '24_3', '25_1', '25_2', '26_0', '26_1', '26_2', '26_3', '27_0', '27_1', '27_2', '27_3', '28_0', '28_1', '28_2', '28_3', '29_0', '29_1', '29_2', '2_0', '2_1', '2_2', '2_3', '30_1', '30_2', '30_3', '31_0', '31_1', '31_2', '31_3', '32_0', '32_1', '32_2', '32_3', '33_0', '33_1', '33_3', '34_0', '34_1', '34_2', '34_3', '35_0', '35_1', '35_2', '35_3', '36_0', '36_1', '36_2', '36_3', '37_0', '37_1', '37_2', '37_3', '38_0', '38_1', '38_2', '38_3', '39_0', '39_1', '39_2', '39_3', '3_0', '3_1', '3_2', '3_3', '40_0', '40_1', '40_2', '40_3', '41_0', '41_1', '41_2', '4_0', '4_1', '4_2', '4_3', '5_0', '5_1', '5_2', '5_3', '6_0', '6_1', '6_2', '6_3', '7_0', '7_1', '7_2', '7_3', '8_0', '8_1', '8_2', '8_3', '9_0', '9_1', '9_2', '9_3']\n" ] } ], "source": [ "print(filenames_exist)" ] }, { "cell_type": "markdown", "id": "6306ad99", "metadata": {}, "source": [ "# 使用lon,lat,key下载街景" ] }, { "cell_type": "code", "execution_count": 6, "id": "12659472", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "街景图片0_0已经下载\n", "街景图片0_1已经下载\n", "街景图片0_2已经下载\n", "街景图片0_3已经下载\n", "街景图片1_0已经下载\n", "街景图片1_1已经下载\n", "街景图片1_2已经下载\n", "街景图片1_3已经下载\n", "街景图片2_0已经下载\n", "街景图片2_1已经下载\n", "街景图片2_2已经下载\n", "街景图片2_3已经下载\n", "街景图片3_0已经下载\n", "街景图片3_1已经下载\n", "街景图片3_2已经下载\n", "街景图片3_3已经下载\n", "街景图片4_0已经下载\n", "街景图片4_1已经下载\n", "街景图片4_2已经下载\n", "街景图片4_3已经下载\n", "街景图片5_0已经下载\n", "街景图片5_1已经下载\n", "街景图片5_2已经下载\n", "街景图片5_3已经下载\n", "街景图片6_0已经下载\n", "街景图片6_1已经下载\n", "街景图片6_2已经下载\n", "街景图片6_3已经下载\n", "街景图片7_0已经下载\n", "街景图片7_1已经下载\n", "街景图片7_2已经下载\n", "街景图片7_3已经下载\n", "街景图片8_0已经下载\n", "街景图片8_1已经下载\n", "街景图片8_2已经下载\n", "街景图片8_3已经下载\n", "街景图片9_0已经下载\n", "街景图片9_1已经下载\n", "街景图片9_2已经下载\n", "街景图片9_3已经下载\n", "街景图片10_0已经下载\n", "街景图片10_1已经下载\n", "街景图片10_2已经下载\n", "街景图片10_3已经下载\n", "街景图片11_0已经下载\n", "街景图片11_1已经下载\n", "街景图片11_2已经下载\n", "街景图片11_3已经下载\n", "街景图片12_0已经下载\n", "街景图片12_1已经下载\n", "街景图片12_2已经下载\n", "街景图片12_3已经下载\n", "街景图片13_0已经下载\n", "街景图片13_1已经下载\n", "街景图片13_2已经下载\n", "街景图片13_3已经下载\n", "街景图片14_0已经下载\n", "街景图片14_1已经下载\n", "街景图片14_2已经下载\n", "街景图片14_3已经下载\n", "街景图片15_0已经下载\n", "街景图片15_1已经下载\n", "街景图片15_2已经下载\n", "街景图片15_3已经下载\n", "街景图片16_0已经下载\n", "街景图片16_1已经下载\n", "街景图片16_2已经下载\n", "街景图片16_3已经下载\n", "街景图片17_0已经下载\n", "街景图片17_1已经下载\n", "街景图片17_2已经下载\n", "街景图片17_3已经下载\n", "街景图片18_0已经下载\n", "街景图片18_1已经下载\n", "街景图片18_2已经下载\n", "街景图片18_3已经下载\n", "街景图片19_0已经下载\n", "街景图片19_1已经下载\n", "街景图片19_2已经下载\n", "街景图片19_3已经下载\n", "街景图片20_0已经下载\n", "街景图片20_1已经下载\n", "街景图片20_2已经下载\n", "街景图片20_3已经下载\n", "街景图片21_0已经下载\n", "街景图片21_1已经下载\n", "街景图片21_2已经下载\n", "街景图片21_3已经下载\n", "街景图片22_0已经下载\n", "街景图片22_1已经下载\n", "成功下载图片22_2\n", "街景图片22_3已经下载\n", "街景图片23_0已经下载\n", "街景图片23_1已经下载\n", "街景图片23_2已经下载\n", "街景图片23_3已经下载\n", "街景图片24_0已经下载\n", "街景图片24_1已经下载\n", "街景图片24_2已经下载\n", "街景图片24_3已经下载\n", "成功下载图片25_0\n", "街景图片25_1已经下载\n", "街景图片25_2已经下载\n", "成功下载图片25_3\n", "街景图片26_0已经下载\n", "街景图片26_1已经下载\n", "街景图片26_2已经下载\n", "街景图片26_3已经下载\n", "街景图片27_0已经下载\n", "街景图片27_1已经下载\n", "街景图片27_2已经下载\n", "街景图片27_3已经下载\n", "街景图片28_0已经下载\n", "街景图片28_1已经下载\n", "街景图片28_2已经下载\n", "街景图片28_3已经下载\n", "街景图片29_0已经下载\n", "街景图片29_1已经下载\n", "街景图片29_2已经下载\n", "成功下载图片29_3\n", "成功下载图片30_0\n", "街景图片30_1已经下载\n", "街景图片30_2已经下载\n", "街景图片30_3已经下载\n", "街景图片31_0已经下载\n", "街景图片31_1已经下载\n", "街景图片31_2已经下载\n", "街景图片31_3已经下载\n", "街景图片32_0已经下载\n", "街景图片32_1已经下载\n", "街景图片32_2已经下载\n", "街景图片32_3已经下载\n", "街景图片33_0已经下载\n", "街景图片33_1已经下载\n", "成功下载图片33_2\n", "街景图片33_3已经下载\n", "街景图片34_0已经下载\n", "街景图片34_1已经下载\n", "街景图片34_2已经下载\n", "街景图片34_3已经下载\n", "街景图片35_0已经下载\n", "街景图片35_1已经下载\n", "街景图片35_2已经下载\n", "街景图片35_3已经下载\n", "街景图片36_0已经下载\n", "街景图片36_1已经下载\n", "街景图片36_2已经下载\n", "街景图片36_3已经下载\n", "街景图片37_0已经下载\n", "街景图片37_1已经下载\n", "街景图片37_2已经下载\n", "街景图片37_3已经下载\n", "街景图片38_0已经下载\n", "街景图片38_1已经下载\n", "街景图片38_2已经下载\n", "街景图片38_3已经下载\n", "街景图片39_0已经下载\n", "街景图片39_1已经下载\n", "街景图片39_2已经下载\n", "街景图片39_3已经下载\n", "街景图片40_0已经下载\n", "街景图片40_1已经下载\n", "街景图片40_2已经下载\n", "街景图片40_3已经下载\n", "街景图片41_0已经下载\n", "街景图片41_1已经下载\n", "街景图片41_2已经下载\n", "成功下载图片41_3\n", "成功下载图片42_0\n", "今日key额度已经使用完，程序结束\n" ] } ], "source": [ "import requests\n", "import json\n", "import time\n", "\n", "key_count = 0\n", "key_num = 0\n", "\n", "# 循环拿到FID、lon、lat、key\n", "for data in data_list:\n", "\n", " FID, lon, lat = data[0], data[1], data[2]\n", " lon, lat = wgs2bd09mc(lon,lat)\n", " \n", " try:\n", " # 百度街景key计数切换功能\n", " if key_count > 99:\n", " key_num += 1\n", " key_count = 0\n", " key = key_list[key_num][1]\n", "\n", " for heading in range(0,4):\n", " \n", " if '{}_{}'.format(FID,heading)in filenames_exist:\n", " print('街景图片{}_{}已经下载'.format(FID,heading))\n", " continue\n", "\n", " url = 'https://api.map.baidu.com/panorama/v2?ak={}&pitch=20&width=600&height=400&location={},{}&fov=90&heading='.format(key,lon, lat)+str(heading*90)\n", " time.sleep(2) #休眠2秒钟\n", " response = requests.get(url)\n", " img = response.content\n", " \n", " if len(img)>100:\n", " with open(r'F:\\DataPai_Case\\StreetView\\Shanghai/{}_{}.jpg'.format(FID,heading),'wb') as f:\n", " f.write(img)\n", " print('成功下载图片{}_{}'.format(FID,heading))\n", " else:\n", " print('下载图片错误{}_{}'.format(FID,heading))\n", " \n", " key_count += 1\n", " except:\n", " print('今日key额度已经使用完，程序结束')\n", " break\n", " \n", " \n", " \n", " " ] }, { "cell_type": "code", "execution_count": null, "id": "ac9abb08", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "eca27fd8", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "f3cc3b3e", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "ff34deab", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "3bfb8310", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "2fa6e16f", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.9" } }, "nbformat": 4, "nbformat_minor": 5 }