FunCaptchaClassification: Funcaptcha 图像识别

此对象不会返回 RESPONSE, 只返回图像识别结果

如果是截图，请仔细检查您上传的图片是否完整，如果不完整会影响识别效果

识别流程

获取验证码图片，并转成base64（需要您自己处理，底部有一个canvas转base64参考方法）
获取验证码问题，直接取网页上的问题即可，不需要翻译
使用本接口提交识别任务（发送到 /createTask 创建识别任务，见本文档处理）
获得返回的识别结果（创建任务时返回的内容就是结果，见下方返回示例，如"objects": [4]）
根据返回的结果，自己点击网页上相应的位置（结果从0开始计算）

创建任务

通过 createTask方法创建识别任务

请求节点：国际节点 https://api.yescaptcha.com 国内节点 https://cn.yescaptcha.com
请求地址： https://api.yescaptcha.com/createTask
请求格式：POST application/json

对象结构

属性	类型	必须	说明

属性

类型

必须

说明

type

string

是

FunCaptchaClassification 3点数

image

string

是

Base64 编码的图片，可以是截图（只传六宫格图片部份，其他内容不要传，上面标题之类的东西不要传，只传图片！）

question

String

是

问题名称，请传全称，如：Pick the lion

服务器会根据问题自动判断不同的图片类型，所以请确保问题正确。

直接取网页上显示的问题，不要自己翻译

请求示例

{
    "clientKey": "cc9c18d3e263515c2c072b36a7125eecc078618f", // 填你的密钥
    "task": {
        "type": "FunCaptchaClassification",
        "image": "data:image/jpeg;base64,/9j/2wCEAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9PjsBCgsLDg0OHBAQHDsoIig7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7Ozs7O//AABEIAMgBLAMBIgACEQEDEQH/xAGiAAABBQEBAQEBAQAAAAAAAAAAAQIDBAUGBwgJCgsQAAIBAwMCBAMFBQQEAAABfQECAwAEEQUSITFBBhNRYQcicRQygZGhCCNCscEVUtHwJDNicoIJChYXGBkaJSYnKCkqNDU2Nzg5OkNERUZHSElKU1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6g4SFhoeIiYqSk5SVlpeYmZqio6Slpqeoqaqys7S1tre4ubrCw8TFxsfIycrS09TV1tfY2drh4uPk5ebn6Onq8fLz9PX29/j5+gEAAwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoLEQACAQIEBAMEBwUEBAABAncAAQIDEQQFITEGEkFRB2FxEyIygQgUQpGhscEJIzNS8BVictEKFiQ04SXxFxgZGiYnKCkqNTY3ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqCg4SFhoeIiYqSk5SVlpeYmZqio6Slpqeoqaqys7S1tre4ubrCw8TFxsfIycrS09TV1tfY2dri4+Tl5ufo6ery8/T19vf4+fr/2gAMAwEAAhEDEQA/AO28J+E/Ddz4O0Wefw9pcssunwPJI9lGzOxjUkkkcknvWt/whnhX/oWtI/8AAGL/AOJrE0XxXp+leBNFVJEubpNOtl8hXwc+WucnBxin6B4+Op62ulXtg0LzZ8iWI7kJAyVbPIOO/T6U+V2uTzK9jY/4Qzwr/wBC1pH/AIAxf/E0f8IZ4V/6FrSP/AGL/wCJrargLnxpqdr8Q/7GuPKisxOkYXbyyuMAk9c5IPFIo6X/AIQzwr/0LWkf+AMX/wATR/whnhX/AKFrSP8AwBi/+JraooAxf+EM8K/9C1pH/gDF/wDE0jeDvCiKWbw3o6gckmxiwP8Ax2tuuC1ax8XatfXUAikFmz4CPKixEA8erehppXJk7dDfg8K+DrpPMt9A0SZAcbo7OFhn8BUn/CGeFf8AoWtI/wDAGL/4ms/wp4WvdDvZbu6uoT5sezyYQxGcg5JOM9PTvXRX19a6baPdXkywwp1Zj+QHqfah2Q43a1M3/hDPCv8A0LWkf+AMX/xNH/CGeFf+ha0j/wAAYv8A4mr+majBq2nxXttu8uUHAcYYYOMEVbpbjOPtvCfhtvGOpQHw9pZiTT7R1jNlHtVjJcAkDHBIVcn2HpWt/wAIZ4V/6FrSP/AGL/4mi1/5HjVP+wbZ/wDoy6raoAxf+EM8K/8AQtaR/wCAMX/xNH/CGeFf+ha0j/wBi/8Aia2qKAMX/hDPCv8A0LWkf+AMX/xNH/CGeFf+ha0j/wAAYv8A4morvxx4bs2KyapG7A4KxKX/AJCse5+KOmrkWlhdzn1YKg/U0Abv/CGeFf8AoWtI/wDAGL/4mj/hDPCv/QtaR/4Axf8AxNcbcfErV5si1sLW3B7u7SEflitnwP4h1XWr+/i1GVJEiRGTbGECE549aAE8YeFPD9p4T1C6s/D+kwzQR+bvWyiBCqQW52/3Qa82m03RURymn2rNjI/cjk/lXp/xIhEmgW0rn93FeIZFPRlYMmD+LCvPvPtY/ugf8BWgD0zTvDng7U7GK8tfDukPFIOD9gjHPQjlfWrP/CGeFf8AoWtI/wDAGL/4msDwX4lsYbWPTZjMJprgiP5MqMgY57c5/Ou5oA4/xZ4T8N23g7Wp4PD2lxSxafO8ciWUasjCNiCCBwQe9a3/AAhnhX/oWtI/8AYv/iaPGf8AyI+vf9g24/8ARbVtUAYv/CGeFf8AoWtI/wDAGL/4mj/hDPCv/QtaR/4Axf8AxNbVFAGL/wAIZ4V/6FrSP/AGL/4mj/hDPCv/AELWkf8AgDF/8TW1RQBz1x4a8FWjxpc6JoULykiNZLSFS5Hpkc1Mvg7wo6hl8N6OynoRYxEH/wAdrhPiJcm/8ZRWaKXFnbBQuP45Dk/+OhfzrHtpdR0mT91c3Nmx+6I5SFIA9AcH8a3jS5op31fQhyau7Oy6nb+NtB8MaP4Sv7uLw7pMc2zy4mFlECGY4BB29ec/hWT4T0bwpY6Xs1TSbC4lJABksVkbhRk5K8ZOfyqOLVNQ1fTUTVJ1uolkDxBkUHIGMnHXvQz4+tcVSpyScT18LgfawU5vRnVWui+BrxgsOhaNvPRHsI1J/ArzV3/hDPCv/QtaR/4Axf8AxNcKXNdXo/ibbpVybxt8lqoK5OC4JwBn1zgfiKUK3NowxOXumuaGpf8A+EN8K/8AQtaR/wCAMX/xNeIfGvTNP0rxjaQadY21lE2no5jt4ljUt5kgzhQOcAc+1epWckhvLW9uXlmu7y4UxpGxG1cjJP8As7a82+PX/I8Wf/YNT/0ZLWsZcyucNamqcuW9z0Dwz4C0m/8ADGjXk894fNsIHaJZQqZMak9BnH411mmeGtH0dg9jYxxSAYEhyze/JqHwZ/yI+g/9g23/APRa1tVd2zBJLYjnnitreSeZwkUSlnY9AByTXg/jHV117xLJqdrEUjTasRXKv8vRjz1/wFdl8UPFPlL/AGFCJE3ENO5UgOOCFX1Gev0rzP7T/djY+5OK7cPGnFc02Y1HJu0Tv/DfxVntYvJ14PdovAnhjxIvsy8A/Xg/WvStL1ew1qyW8066S4hbup5U+hHUH2NfN9xJK2xgFVtwGVHIH1rvPhZrtnYajNZ3KztcXRRIpABs6nOef9316msqsab1p3Li5faPYaTNLXn3xMhme80qazvWguYSzgLk4AIwa5JSjBc0noapNuyOu1vXrPQrYSXDF5n/ANVAn35D/QepPAry7xDq9zrUjz3kyeZHloYEb5YgOeB3OOp/lTbx5tQkmmu53lnnGHlPB/D0A9KoJZ2tim+R40XoWKhc/jXj1cWq10m0uitudMafLqej/Dq5EmjT22eYZtw+jDP8wa66vNPhpd+VqktqTxLB/wCPIf8AAmvS69PDy5qSMqqtNmLa/wDI8ap/2DbP/wBGXVeb6z8UPEKXtxaw/ZrMxSMmFi3sCDjBzkfpXZa9q0Ojatr93LO8JOk2iROiliHL3QX9a8Tka5u53mdWlkkYszuSxYnqTXbTinqzjqyaskz2n4feLE1vS/Ivr9JNQErYRiA7LgHOB+P5V1txeWtqha5uYoVHUyOFH61862F1qugXS6nbERSR/dJjBHQjofYmtu60knyrqa6E32iNZPMc85PUEk9Qc1M42ZcJ8yNK80ayXULgWNzHNbCQhHRtwI+o9OlU7i2NvMI44g/Gdxp9pcGysGCqH2S7OuMA028nmaVSJCisgOF9e9KEW2OckkWbGHcG86MZ7ccUye7v9M1Bm067mtfOiAcQ4G7BPqPeq9nIGnKeaWZhj72TyCP8KkjjkiaHeGXdlMk9yM/0onHleoQlzJWKt3JdzBZbx7m6wwx9omaTac5yAeKQkxyI2cIByOEyQfw7U+RGk0+ZHLBtucnk8Ef/AF6gypijcDkN8u1cA7h7/Sk1Z2KTurlmxmNreCQEO0Mgkzk/wsGAr3EEEAg5B6GvClwboqcLvUFyW65H/wBavZ9Cuftmg2FxkZe3QtjscDP65qRlTxn/AMiPr3/YNuP/AEW1bVYvjP8A5EfXv+wbcf8Aotq2qACiiigAoorL8S6j/ZPhrUb8feht3Kf72ML+pFAHkVxqlxN4kvtZtCpme9doN33Sq/IoP1A/Wugv5bbV9ES8NqYHmVmaJhgZX+IexPfoa5C3T7NbIoJJhiJz7gf4103iZX0+xa1s0KqsKRRd9qkYyf1JrXFx5VBR32OjLXzTnzP3bNsj0y4jl0m1aMrjylyAehxzUnnxsCUcMAcHB6Vz9je21u0Nv5ixGLERRmAJ7Z98/wBa1xBHBFIsQIyCeTXmTspSv3Pp6MJezpuLTTSv93QkkukW5+z5Jc9OKbdTXNvbzPbkOAmXjHVwGUkD1wAx/AU8hGYSFVLY4PpVfSp5f7eSW9VrW0s5FlMm7JmwchVA9e/60la6sOakoSbfpZfd+J1Hg3WY57hQSsuyE+VJgZMeeVz7cGvPfj1/yO9n/wBg1P8A0ZLXa6ctvZyX2tLbrZWsxcWsBYKGd/4R7E8f8CrhPjeksfivTEnfzJV0mIO/95t8mT+ddVK/KfP5go+2ulZvdefU9s8Gf8iPoP8A2Dbf/wBFrW1WL4M/5EfQf+wbb/8Aota2q1PPPJvi7eNJqtpaPGscdvCZBL1Lbjgj6DbXAMsaQGY7nAXOOma9Q+LunrJb2F4RkZaF/wAeR/Jq80iZHjCq+8L8v5dq9TDwg4J2X/BOWo2mxCpW3LxxqHKblGM9s1PpNybS7gnVstG4bpjB+9j86htpFkj3IhVQxUfhUcEreczuQH3fdAx93v8ArXQrO2u+hC0Z9JwSrPbxzIcrIgYfQjNch8Q7Zjb211Hww3R57ZIyP5GtfwZeC98LWT5JaNfLbPX5Tgfpil8XW32nw9OQMtERIOPQ8/oTXzuLp3pzj/Wh6FN2kmeSLHNLpMkd1IUk2nc8mAB36jtUUtzbfZI4XWfaArLJDCzqPTkCqN1Ncza61jM5e2hU3DpxggfdH59jXU2GiSHTLLUL9tSaC5smvJbu0nRIrXCllTZg7sjjPOTXn0sNKa5r2vZ6dDtXs1Hmnfqv8yHwlqEUPiW1uIpleJpwN69CHG0/qTXs1eJweEvEEIttZiNvPJNEsk8EY8qQnqD/AHSw9eM16/pOqW+sael3bNkH5XQjDRuPvKwPIIPat8HUhJSjGV7M566V00cv4ntftl54jQYymkWcgJGcbZbls479K8pDSPwHvZR/0zQRLXtyRLP4w1iFxlZNKtFOfQyXQrxS8tHhuZY5oJG2OVLXM+0Eg+lerSfQ8+stmVbiJPLcNFFGxHV597/gK6e13ah4Q0+QbmeEmM5HAwd2P/HzXNBolBVJbRM9oYzIfz5re8Lyeb4dv7ZWCyQSB155AOR0/Ffyq56K5NLV27k0X7r7Ssse4bBJtzjOP/1VS1i4tksYLm4UKgYoFDeoyKs2bsbmIyEt5iMh3d+9YF3Mt34gnaSPbFp8AMcec8nq317VkrqRvZSSXcksdXgtpEea2liVQN0hhbn8hW4reYhuYn82EyB0kDbgVz2P0JqS10J9StYk0uZ57tlV3IC+RGDzhjjOcdhzW1ZfCm3Uu11q14iyMWaC2YRxhj1IGP8ACpdRyZfslDRMxmleSaW3KqqkFeBycisuElrYhVG4DhOT0Pv7V3Mnwzs0bzLLWtTgl45kdZQcdMhh/UVyniHw9r3hq1lleCPULdiQLmJyiRA8ZdT90e4yPpSbXQST6lYko0TFjsXII4XnOf5V6v4Gn87w1GmRmGWRCB2+bI/RhXiy3GpRxI8lnDMiksDAxDYPsRz+lepfDDUY73TrtYpA6lklAxyCV2nPvlKGM3/Gf/Ij69/2Dbj/ANFtW1WL4z/5EfXv+wbcf+i2rapAFFIzKilmIVQMkk4AFc3q/j/w5pCsGvluplGfJtf3jdcdRwOvcigDpa4n4pXnl6Ba2APN7dKGH+wnzn9QtYWqfFTUroGPR9PS1X5f3twd7e/A4Hbua5a71HUtYvxeapeyXMkakIp4SPOM7QMAdK0pR5ppE1Pdg2KoBVsjIZguPXv/AFFb9prFstpFp+vb7XyE2wX7sCrjsrehA4561iQu8DRSx8PERIv1zkfyFbsU+i6/CBI8el3cjlXsbkh0Leqn0NVjW3bS6N8u5FJ3lyy6dvn1IZtI0pzFfrc6dMob93MDkg/TBxTHfIIzU76BomixvfXuoWsMSk5MPJJ7ge/0FNEia1fwwadD5duwCxHYQ23qWYHv1/SvLqJvU+owlSPwu3d2VkvwX5DIG3Rx4ySwAA96lN5DaPGG0lrtw+HDS4APrtx9PWotPQ3sM7WtrdQ/Z2yFmZS0iEnDrgDHTp1HFTyeIdRheIXOkQapCq4eYMBMTn0xg/hTUbPUVSvGrDmp3a8tGMuRquq3At5ZYr52wEhhh2xQHIJOT1xgckD2rz74lRWlt4igtLa5Fw9vaLHcMCSFl3uSB6YBHSvXtJ/tbXZHs0FrpERAl8y3kEkpX+7t4wcnk84rzb41WEWm+K9PtoiWC6ahZ2+87GWXLH1JrohHXmZ4eJr+57GKst33bPb/AAZ/yI+g/wDYNt//AEWtT+I9Rm0nw/e39v5fnQxFkEn3Sf6/SoPBn/Ij6D/2Dbf/ANFrWd47hLWdvMy+ZGhbKHkE4yOPwNannnBR+L73xR4UvdP1cSSXizJJayCHbu5+ZTgAcDPPvXNNp81ihDoVXdkg/wAJb/8AVW8mtzS29nPDaARzSmOQEk7APpVW8W9lF2t4vOWERC4BVfmH171vSryhZW0uRKmpamJGyee8aIQVG5j25pkkhN0FOFVFyCf4s8Y/z6UlzcQWn76TIJHUdwK6Ky8D6pq1hDerc6dKh+b7LvJB9mdcj8MV1YvG0cJG9WVtdP6/UxpUnUeht+D/ABjNouhTRLZLPEreYsrXARFGADnrxxVi38can4oaS1/tHStItnDKVlAM8injIVyMD3P5VzY0KaTxDbWh8LjzLRPtE8SzRqJVzhQGHBGcnBxnFdncazYvF5WtaBfQJ3NxZCaP803Cvn8XjK0v3lKm5KXVa/8ADnfKlTg+RT2MHV/CUPh6Ia3Dqk9zczzRxMkqoUmBOMcAYwMnj0qJp9YtvDtxo1p5Nzp9wuFgmYo8SkglFboVPIwemetM1NfD9zqtomgRwBVDSTmAlQGOAoZexxuPIzWh7Dp2rGjVn7NS29dD18Hho1aLVTVX0/r+thlt4h0myiNlb6hLoFzuEghv/wB5FjkbQSSAv0I6VqeA/E0OreMLqKAKsktqTdiLJiZ42AWRSR0YMRzz8o64FcDd2dnqWpXd7dSfMJDBbqTgNtH/AMUTXovwqgsYE1HyLdI55SkjOOrDBGPoMfrWeEw9KnW5ot38/wDPd/M8/EKzklsmdRa/8jxqn/YNs/8A0ZdV5P44tIrDxffrts0MknmgyAux3ANnH1NesWv/ACPGqf8AYNs//Rl1XDfFW2aHWLS7VpVE0O393CGJKn17cEV7tN+8ebVV4nDLLI/CS3DD0ggCD8zWp4Qdo9ZvbQq4a4t2IVhuJwNwyfqB+dZTRSMMvDcuPWecRr+VS6JcJY+J7CYeQEMgV1jkyMZ5BNbSV0zng7SRsyTt52DGiCKYdOvXH9aorpj674/TT7GMwhIf9Nl7FDyOPXn9a09Ujt7We6icnzQGJx0475/Crvw7vxp3hC88Q37maS8umCL/ABEjgID6Z/LFc7sdkb9z0HTNMtdKso7WzhWGKMYVVGP8mrlec3PiDxJdyeaupJYjORFFCrAD3Lcmtrwj4kv7+9n0nV/KkuY4xLDcRLtEqZwcr2YH060uWW7Ro1Y6ykZVdSjqGVhgqRkEehqO5uYLO3e4uJViiQZZmPArCXx74d+0CGS8eHJwJJYWWMn/AHsYH41FxJNnM+INCstFuHt1tUEE+JbOUL80ZBG+IkckYORn1x2pfhPIbfXdQhJ2x3G5lHqw2H+rVv8AxBiWXwfPdoy5tWSZHwGGMgHH1UmvP7W6u9OKmwvfs0iE/vEwzc8N68mqXYG7rU9e8Z/8iPr3/YNuP/RbVtVyeo3U178KdSnuH3zHSbgSOf4mEbAn8cZroNWvV03SLy+Y4FvA8n5Amgk8X8a6/d63rN5DJcyNZQzPFFCGwm0HGcDrnGcnPWsqKHZF8qbgg+Yk9Kghiadmyw+VdzE9/wD9dWjvCAkEIx9epHtVJdS79Azz0I9CRwakiBYEDqxwP5VGzseHBBUYwRjFTwDaQf7ilvx//XXVh1ZuXY5670S7ljI3bu27P4D/APVTJIkeEh41c4xyM8n/APUadjC49gv+P8qU9R+J/p/jW9uhzlvTfCtrJbJqSNZQ27Zc3MswY8cE49frVye6t3spLDQpDKJ0Al1ASbMcnIXHI+7gj3rKTTLAQG4ktVJZstjIB57gcEd6tRQ2Lr+5meMnrtwRn6c15qw9pXk7nr1MwnOn7OKUV2X9aiS2l2ZLeURAXNswa3nDbtjA5BPIyOOc1tWY1y+SQNoMWpyRtue6hlWDK8HbtJ5br+lULWGVHyLlZI+mAOf516R4Vtvs+hxMfvTsZD9DwP0Ap1IpnPSqzp6xdjF8OafqMmtw3w06TT9Pjjbb9ofMsxYYA2fw49/avMvj1/yPFn/2DU/9GS19AV8//Hr/AJHiz/7Bqf8AoyWoSS2HUqSqO8mezeDP+RH0H/sG2/8A6LWpPE1v9o0Of1jxIPwPP6ZqPwZ/yI+g/wDYNt//AEWta08SzwSQt92RSp+hGKZB4nLqF4BqENpaIktswMYxneO5xSXAv5LqOeXP2Ty1JXAAVjw3v3NXbya9g1lLQRL5TowMu05DiqH2bWLyytxNIyypIwmTO3ep6dODSKObvreHy3juVysbY46gg1US3u9IY3emX09q64J8tih/HHB69xWvqUavcuWXKzIHI+o5/UVWidZIgyksp4BI6163s4V4LnS1RxuTpydjT8PeNtW07V57nVbU34mjXzpUT97tRTtAxx39B1rYuPi87BI7fSBaPK20TXU2UT3IAGfzrldIuPLv4bgAIrSdB27Gr3je5QQSQXUUbR+Tvt2PD+ZkDg59OoriqUlRjGNPY2habbktToLKB3Z72a4+1XFwd7zcfMce3A44AHSo9U1WLT4ti4lun4igU/Mx/oPeuIuNAutM8NpqX2qSFuN8WSvJPGMHntWxpNtp1lo0bXFwi3NzFmV3bLgnt615NaDinN6nuxzBKChThy/oXksYrXTrc3U4V4GMjS9ixOT+prp/hzdi31/7ODlZkeMH1x8w/QVxq3tiumiwJknG3bmJCPfPOKt2th4iuzu0nS7+JsqUnUMhU4xkEcfrXPQp1VO+u/orPrqcEpxad+qPYLX/AJHjVP8AsG2f/oy6rC+KVmZtAt7hVctDNjCPsOGHPPpkCq3w4sdc0/WNXh8QSSyXRtbVk82XzGCGS4wM5Pfd3rpfGNmL7wlqMJRXxF5gDdPlIbn8q9iLs0cc1eLR4QViRslLND6ySGVqZNJ80Mgk3BHH3YdigVMsg6RzD6W1rn9Wpl2kr2zllujgZBmkAH/fIrqOE7DXbc3rm5BA8+33YI27iy5P6k1W8OJJJ8LNOuIomkWwu5TcIi5IBLfNjvjI/DNAzfeF9MmXDvGDGfmz90n8uGFWPAmqr4c8SXOjXbeXaam/nWrNwFlPVPbPb6VzPY7lvsDG0ntEuBeYKNuGACjj6/jV/S7uHQifEeoQXH2dx9mgEceWbPJbHpx+NdoNA0cXP2kaXaCbOd4hGc1Drmi3GrRiOHUTbRlCjxNAssbg8g7W7gjrUOUmbXTOZ17XrXxBZafLZmb7K8kgIliKEuuOCD9T+vpWOVMqPHNCfLOV2uvDD+tdxN4bF9oH9mX06b1bfDLaxCIQMOhUc9OevXJrF/4RTXm2W0l3ayQofll3MCB67Mdf+BVUZ8qBWMp7hl+Fep6fK7FYpxaQE8nazrtH4Zx+Fc2eSep/Kt7xc8Nq1r4etCWism8+5kPG+Uj5R+AJP5Vz/B7j+dTe+pDO/sbgTfCXXkAAMVldDj3iJ/mTWp8Tb77J4PliBw11KkQ47Z3H9FNctolwD4D8VW/H/IMmYZPPEb9vxFVfiP4qsNeubey06YyrZPIJsoR8+QoxnqOGoBbnJQQny/PJGN20DuasHzUcKyksvKr9736VFDbuuwKQzSqGAHaniSUFn+bPRm64z71pbyHfzF3GR8k5LHJNW4h8rH+8QPy5/wAKqRD5s+gq6nyxr6hc/if/AK2K7KKtT9WclZ3nbsOz0/Fv6f0pf4j7cflQMB+egOPwH+TT7Zd8qA+uT/Orv1M/IvMJIkjWNN+OCo6mmSXFq7f6VaBG9WXafz/+vTykskxeCZFIGCGOOfbFOMt/FxJB5g/2SG/wNcjt1N0T6fbxSkLaFmMzBFyxbBJwP516zBEsEEcKDCxqFUewGK4Dwrai51m3/d7ViBlZcDjHT9SK9DrGT1NVsFfP/wAev+R4s/8AsGp/6Mlr6Ar5/wDj1/yPFn/2DU/9GS1Iz2bwZ/yI+g/9g23/APRa1tVi+DP+RH0H/sG2/wD6LWs7x7ZeJNU0+HT9AUIkzf6RMJtjKB0HUceuKAOY8bR31lrD/YVB3Th5Btz8rcnr7k1hXFjqE66hFJclIpSGgYtgJ3x7VsaZ8LvEiRFJ9djtVc7mEeZGz064H862bf4SaUSG1HUr69bjguFHv1yf1osO55rqjwxGNfOjd4yUYI27jgg/qaz4MkiK2glkyeFUdzXu1l4B8L2IHl6RDIR3mzJ+jEity3tLa1XZbW8UK9MRoFH6V0QxEoRUUZSpqTuzwO08H+Jr+RXtdFnjyDzIuwf+PYroJ/hV4h12ZJtTmsrZlQICCSQvXGBkH869iorOdWdT4mVGKjseKa78GtdS1SPTtSS9gjXi3JMWDz0BJB/MV3Hh/wCG2i2OmW39p2MVxfBB5zb22bvYZxXZ0VmUVLTStO08AWdhbW+OnlRKv8hVuiigDFtf+R41T/sG2f8A6Muq15olnheJwCsilSD3BGKyLX/keNU/7Btn/wCjLqtqgD53vLa4gupoJFu38tyhLyCJTg47VTKwrnP2NG93MrfpXQ+O7KKy8YX4ZLUeY/mgyszMdwBPyjpyTXPi6RBhbkj2gtwv6muxaq5wSVnY6Hw1M0vhS7gQ4e2l3LhfUHPP4LUYtotRBt7xTKk0fc4IYHgg9jzXPWepahp128lkHeGT/WRM2PMHv+IBrRiu/EmoyRmy0+NSCSnlRNIen61zzerR109UmdZ4f8bajpFmsWrRPqNlHhVuYyDPGOgDr/H9RzXXWnjTw3eRh01e3j9VnPlMD6YbFeaQeDPG+pKVZLiJHGSNqwj9cGtG1+DerXHN9dwqCM4eVnIP0Ax+tZvyNU+53l14w8N2cZkm1uyAH92UMfyFcbrnxWs7hXtdH89FIw10Ist/wBT/ADP5VpWXwX0yEZuL4scdIoQuD9ST/Kt61+Gnhq2+/bzT9P8AWSkD/wAdxU8r6sfMuiPJbe5W5gWeWQh2JyZW3Oeep781YhRrg4t457g5xiKInmvarbwzodp/qdJtFPqYgx/WtJUVBhFCj0AxVEniF5pXia00DUZoNOu7aAWswuGkwm6MxsGBB6jHPfkV2mofC+1uW3RXHzdMtlT+Yzn8q6Pxn/yI+vf9g24/9FtW1QB5Jc/DbVbQZtmLgdMYPX6c/pWJdeH9Xs1MclsduckdM/gcGvdqayq6lWUMp6gjIp3Hdnz95MsGRPFJGSf4lIq2pVjuB44IH06D9K9puND0y5z5lnHk9So2/wAqxbv4f6PcHMYaI/QH+WD+tdMa9kk1sYSpXbdzzDBEZ9+Pz61ash8zvjO0Y/z+VdXd/Da4QFrS7DexP+I/rWbJ4W1rTgwNp5qgk7lB/pmqdaLWhKpyTMlBZzkt5skbk5OxuPy5qaGCZXBhvFdQeQy84/CrMljEQEmt1ZlAzuXmmRWUMMoePeuOxckfrWXMacp2vgm2xHdXRHUiNfw5P8x+VdVWL4Rkt5fDdtLbuHV9xYj+9uOR+HT8K2qwNAr5/wDj1/yPFn/2DU/9GS19AV8//Hr/AJHiz/7Bqf8AoyWgD1DwnbeJG8HaKYNW0tIjp8BjR9MkZlXy1wCROMnHfA+grSnTxJbRGWfXtFijXq76ZIoH4m4qTwZ/yI+g/wDYNt//AEWtZnxPcL4Guwf4pIx/4+D/AEoAnsr3WNSdksvE2g3DKMsI9MkJA9f+Pirn2XxV/wBBnSP/AAVS/wDyRXnPwXRRrF8QACLRR+ZFevkgDJOAKAMb7L4q/wCgzpH/AIKpf/kij7L4q/6DOkf+CqX/AOSKkbxToSMVOqW+QcHDZH51JF4h0af/AFep2p+soH86SaYFf7L4q/6DOkf+CqX/AOSKPsvir/oM6R/4Kpf/AJIqa98TaJp9lNeT6nbeVCu5tkoY/gAck1l+HPiFoHia4Nra3DQ3QBIhnAUsPUHODTAvfZfFX/QZ0j/wVS//ACRR9l8Vf9BnSP8AwVS//JFbIIIyCCPaloAxfsvir/oM6R/4Kpf/AJIo+y+Kv+gzpH/gql/+SK2qKAOPtrbxJ/wmOpAatpYlGn2hZzpkm0r5lxgAefwQd2Tk5yOBjnWNt4pAyda0gD/sFS//ACRUa3EVr4w1eeeQRxR6XZszN0A8y6rm/EnjWLUrSXT7GCURORuncgbh6AdfTrQBz3iDQbK/124vL7xdbPcSMN4h0mVkXAxgHzT6etbGkfDmGa3S6tdU0m8jJOHfT5vyIFwP1Fc1V7w54nk0DxOguHuDp88WJgqF1UjO04HOfp60uZsfKkdvaeE9QscfZpfDsZU5Df2I5YfibjNaC2fihF2rq+jqB2Gkyj/24q5pWt6drUTSWFysuw4ZcFWX6g81fpiMX7L4q/6DOkf+CqX/AOSKPsvir/oM6R/4Kpf/AJIraqtf30Gm2M15cttihUsfU+w9z0FAGY0PiZGVX1zRlLnCg6XIMn2/0infZfFX/QZ0j/wVS/8AyRXmGt+IL3XNSF3I7Q+Wf3CRt/qfofX1Nej+EvE8WvWfkyfJewKPNX+8Om4ex/SpUkynGxY+y+Kv+gzpH/gql/8AkisHVvEut6ZeGzTVdMup0x5gi0qTEefUm56+3Xmuu1OSSHSruWEEyJA7JtODkKcV5HYNv0+3k3bzJGrsxOSzEZJPuTmuPG4mVCK5VqzWjTU3qb+ra5q+qeEdZjl1bTUb+z7gvB/Zkis6iNiQreeRnGexx6Gut+y+Kv8AoM6R/wCCqX/5Iry3WnaPQdRZSQfsso491IP869sp4LESrwbluhVqag9DF+y+Kv8AoM6R/wCCqX/5Io+y+Kv+gzpH/gql/wDkitqiu0xMX7L4q/6DOkf+CqX/AOSKPsvir/oM6R/4Kpf/AJIraooAxfsvir/oM6R/4Kpf/kiue1HxRrWn+KLPw8dW0uW6uSu4rpMoEW77uf8ASOc4ru68l8WjyfjPpT/3zaH85GWgDvJdN8RzjE2p6JIPR9HkP87is248HapOP+QjpER9Y9MlH6faMV2FFAHNaZoXiLSbT7LbazpXl7i3zaVJnJP/AF8Vb+y+Kv8AoM6R/wCCqX/5IraooAxfsvir/oM6R/4Kpf8A5IrxD41x6hH4xtBqNzbXEv8AZ6EPb27QqF8yTjDO/Oc85/Cvomvn/wCPX/I8Wf8A2DU/9GS0AezeDP8AkR9B/wCwbb/+i1rz7xZqmq66LjT5ruNLYS8IsQ7HjnrXbeH9UtNJ+HuhXN5Jsj/s62AwMknyl4Arzqe7hmuJJBIo3sTycdaaJk2ZmmXuoeB3kvbC5SRpwI2V4wRgV7TpWoPqPhe21GdVV57RZXC9ASuTivDvEkyfYYyGDfP/AA81614f1SwvfAQisrlZXtNOCyqAQUPl98j2P5UpaIcdTgiik8qp+opDFEesaflUGp3kdjZSzySBMAhPUt2A96wtJl1Lxdcvp5eSG3xl5oY8BD2DE9QfQV87Rw0qq5lokexOoovl6lXxpexBLaytChZmLOIyOvQD8zXT6n4bNh4KsLe0iX7ZbSxyGTbk7m4cn25/IVa0v4e6ZabJL2SS8lUhgCdqKfYD+tbFpbzeJ7y5U6k1jp8MphQRFRLcuPvEE5woPHA5Oa9WnFRioRexzvS8p9TmdHuprldPeCSS3mluEjdY5DgMJApFezajrOnaQ8C390lv9oYrGX6cDnJ6AdOT615rN4JvvDl5BqWmTy6la21ytzLaOAJjhwzbCMBicdDV/wAYa1Za9b6ZdWMgmtpInYEjBB3AEEHoQRgitqS9nF3d9THl9rUS2PR0kSQbkdWHqpzTq8StJ77TJDJpl/PaMxyVVsqx6ZKng11mmfEe4hUprVl5gAG2W0HLH3Un8cg/hWimmFTDVIdLjPG/n/27f+X/AKr7HZeZ/wB/LrH61yVemaVd2Wt+JdSuICs9rcaXZj5l4I826BBB9waguvh5pkz7oLm5tx3UFWH6jNU0YJnndFd+PhxY99SvPwEf/wATS/8ACuNP76jffh5f/wARSsF0ch4UlvYPGtiLFFYShkuBnGY8ZJ/DAP1xXr9cpf2dr4E8L6hqOmQ+bcoi/vLhtxY5CjJ9Oc4GKyPCepap4ssrd9YuJT54mMccAMcZVCqkyFeckscL6c1WyJ3Z6FXO+O4xJ4TuQc43IeDg/eFaF1eR6LZQQRxy3MrfLDCp+ZsdTk9APU9OPasLxBe3194MvpL7TxZOsyqqiYSBl3LyCPy/Cplsyo/Ejy5REbs2ypOxAyW8zgfrn0/Ou0+G0Ea+IbtsEstqNpZiSMtz1+grkFgZLxrhGGGGCCOR06fkK7L4b4/4SG8Hf7IP/Qqyha6Oionys9Jrh9Q8BTwzSyaNPF5LlmW1nyBGxIOFYZ+X73BHFdxRV1KUKseWaujnjJxd0cBqnhP+zvCGv3V+8c0yadceUqA7U/dNzz1P8q7+sXxn/wAiPr3/AGDbj/0W1bVFOnCnHlgrIJScndhRRRWhIUUV5lrnxD1i11m9tbSO3jit5miXchYnacZJz3oAzLnxHq91dTzf2jdRh5XIRJ2VUG4gKAMcDFZ07Pd3sd7cySTXMYASaSRmdQDkYJORgkms9b6aNSBHC2WLEspJySSe/vSHUp/+edv/AN+z/jU3fYovrrWrSIvmaneN67rhz/WvYfDlxJd+HdPuJXLySQKWZupOOteEG9lACrHAo9oh/XNTW3jbxJBaRQQapJFFGu1URVAA/KhXEz6Doqjotw93odjcyMXeW3jdmPclRk1eqhBXz/8AHr/keLP/ALBqf+jJa+gK+f8A49f8jxZ/9g1P/RktAHoMjY+G/hkZ62Vv/wCiRWJgHqM/WtqX/knXhj/rxg/9ErWLQBFMiLBIwjQkISPlHpXI+ELjxNex6jDossdsj4F0rvtByDgdCfWuvuTi1lP+w38q4fTINa025fxBYSGOz84wTSld6KeoDj+6c9aTvbQqNr6mnfeC/EmqXVrHfSQiJWw8kcuQg7nBAOa7/TtNtNJsY7OyiEcSD8WPqT3NZ1jcan4nuJYtLuEsrW1AWe62By8hGSEzxgAjk+tU7KbxCLYX8eoWt1aXFwYrOK8QRSXAGRkMvQnBIGDxXFNqMVeyR3RcYvTU6UnAJ9BXNeFdK8O32m6fa6jpgkvtSgluRcsOXYSEMFbOVYDB4qa48WwW0ISSxuFv/MWNrFsCTnup6MPcU7wfeaxdeGray0vSRG1s8sIvrt12R/Oc4UEsSM9OBWVSE5Q9z8xVJJ2NrQ9XubDRbiC4hvdTksL6SzR4kDySKMFSckdAQCfUVyvi5xput2N55Mlpb6zG7NbS4DRTrjJwCQNwxnHeuotrGKPGg6Zr13YalZbppWaNT9qL4LSFWGHGc9OlZnjTT4vEeu2+ku2fsdjI7yAfcdyoQ/XKk117R1M6baknE5C1vp3inLsD5cQYHHerNldyXEUpkAGzjI78ZrP+z3WlteWOoIEufKUqy8rKucblP1PTtVnTB/oM5/vOf5AU2lZtHVSlPmim+9z03wJCsF5Ii9DpFm34ma6P9a6TV9VGl2yssLTzyHbFEvGT6k9gO5rE8JxLDqrovQaJp5H4vcmtbW7dnSOdRny8qfYHH+FOvOVOk5RV2jzoJSnqYL6trzP5095HAp4WG3iUjJ9WbJP4YrN0/wAVeKbK/uIrmGDVLdpMRMWEUgHTHC4PNakkayIUbp7dqhtrRbcu7NuJJOcYwK+dWPxClzXPR9jScbNFXV/Geox6feWt/wCHknYIGjMTGSKQ7h8rDG4d/XpUPw28XPq82oi+nt0m2xm3tIVCADDZCA9TnrzTrxvNhZG6zAg89FIwf04rz/WPD95pepG+0eAQWkEIcbZSxDDrjPP4e1ehg8yjVfLV0fRmNbCOK5obHtcFnqV5ciXUZYtgKMiQxlChB3EZJJOSAD0GB71ieMbqbV510jTY5bhYHP2wq2yKM4BG5u5A5wPUVN4c8U3Os+GbdrUxvqUQVLpZ1YbPlJDEDn5sAj6mqXiq3uIbC1a4fEkufNWLKRu3Utt9yx654Ar1JP3TjiveOJ3af9oS33ESyLuVct0rX8PRi28U6Y0BaMvNtchj8y7TwfaseWe0GsRQtC5uCvDqOAPQ81t6IM+J9K56T/0NYR+JG0neLPWKKKK6zmMXxn/yI+vf9g24/wDRbVtVi+M/+RH17/sG3H/otq2qAEZgqlmIAAySegqi2uaQn39Vsl+twg/rXP8AxML/APCLqFYhWuFVwDgMu1uD6ivJ4rKJuEtoz9Iwf6V0U6PPHmvYzlU5Xax7sfEWhgZOs2H/AIEp/jXjeuPBceJNRkglSaGS8cq8bBlYHB4I+tUY9OlMkipbAFpPlzHjqq+3HeumsfCSTRo00zIQc/uwAOua58RKnQjzSkbUozqbIx9R0hbK2WYTF9zAbduMUabo8N/bmR5XQg4wuK7C98JvqVi0a3vkeWQwLxbug9MiqFnoN7o9q/nGOdd2cxZ4HuDWEcXQlZ8243TntY4/TrSO71FbaQkKSwyOvFUtTsorG4EUW7bz9457mtbTEeDxCkcilGDtww7HOKpeIRi9H1b/ANCrqSXKzN3Ukj3Dwi2/whpLHvaR/wDoIrYrG8HkHwfpOP8An0jH6Vs1Awr5/wDj1/yPFn/2DU/9GS19AV8//Hr/AJHiz/7Bqf8AoyWgDSsb67bSdM866d0SxgSONz8qDy16D8Ksi6k/uqaw2W3m8PactzMYk+zQ4YeoQVUWwtD/AKnVwPqcUyVc6aWdpYXjKAb1IyD0rDUavpHhbU9LivA9tdq7yrsHJx279qjWwuh/qdWVv+B//XrUijf7PDFO3mNt2uf73BzUVJcsJS7IqKvJLzOg+EUSSeA2TP355VbHUdqksIUTSU8K67p11vsRmCeGNikyRnKOrr0bAHHXNYnw01JdA1nUPDE5OJz59lvOPMOPu59SAPyNdhbJ4gtYNHimleS4ub1pdQIwyxRlWbywewB2gfSuapCNaK180dKutzPm8Py+Mbn+0NRtpdOt4UIsUPyz7zjMrY+70wF+uateB9H1PQ01W01DY6Pd+dDKgx5m5QG47dB+ZrX0uHUYb7VReO0kEl0JLRmfOEKLlQOwDA/nVDV/FkFrM1hpcf8AaGod40b5IveR+i/TrVQgoR5Y7BqzQ1a7trFRP5UMt8I3FsjEK7nGSoJ+gzXDz3x0HSbi/nliudTu38yXDcO/QKP9kDgfSsu71u5tdVvJpkXUL9U2tdl9qQ552IvYD8z3rGga1jiaQHexOJH2kEljz+HNDOmlT7u25a1DUptZikvrhFjMX7qNEOQASpJz+AosTs0dnPGWY/8Aj1RIbV4zboybGOdgJGTT4zE9qbdGUxEEbM54/nQ5aWsb06SupKSelvmeveH3t/8AhJLyO2njmjh0iwjLRuGAIe57iuV+J/jDNlb2eh6xEVkZxcm2kBcYxgZHQdfyrnNCElv4f8V+TI6Dy7JcqcEqZJVI47Vy0slhBJsdAG7gKTXfSgpLnb0PDrN05OHU9F8IeLU1mIWN6ypqEa9egnA7j39RXTuCyMoOCQRXi5+xpAtzjanVXGQQc9R3rvdB8YxSLHaas6xSHCpcHhX9N3offoa8TMMrcL1aGq6rt6eR14fF83u1NGaskE7z7fKbKqB04/OrMNgqDfcEYHO2r1Q3Ecj7SmGA/hJxzXzvKlqj1faN6bGfpazab4ysruG5SOC9zbTxSHHmcEofdhjH0471qePLmBltrYTIZ0Jdow3zBT0OPTisPUdLe9EQumeMpKsqtG+GUqcjB7Vw2pXc6aleXV9OxujMyTSKT8xDEYGO3HFe7l1Zzouk91+RxYmmlNTWxrS6dv1NL0SYKrgrj/PrWppl1BZ+INNnupkhiWf5ndsAZGBzXJieQjPnSYxn75qNZ0vIgS7SIGyN5JGR9a9FKV1foYO1nbqfRSsrqHRgysMgg5BFOritD8RaZ4X+HGl3mpTFEMeyNF5eRtx4Ud6zx8ZdH2gmwuRxnGRkV0nMdX4z/wCRH17/ALBtx/6LatquY1zV7PW/hvrV9Yyh4n0y4yO6nymyCOxrp6AOW+IqbvCUrf3JUP64/rXmGm362jMHXIYdR1FeofETP/CH3GP+ekf/AKEK8+8OaCl8n9oXvFqpOxP+emOpPt/Ouj29Ojh3Oo9LmXs5TqqMR+nXiX19KY1fah3biOCdo6Guxitfttk0SFlEkZUMuMj3FYjyJNMGhi8uJU2oAAAB9K66ygQ2sDK/CqMYrxsR/tCUpK3kery+xhynP2XirTY4zpwjuVCN5KzMoKtg7T0Oe3cVo2y3Kx3H250bMjbAoxtTsD+tTJYaVeXTzrp8InVsiUoOW9eOtR640i2SB2Id5MHHdfT6VjisNGaUYaPzMaSmpWmcRqqhNa02UDq5Rj+ZH8jWB4lGL3/gT/zFbOrz58QWMQ6I2T/L/GsfxQMXn/bR/wClevSVqdjHEP8Ae/12LNv4r8R2Nnb29nrMkMCRLsjESHaPTJFLJ418VlGJ12fgdkQfyFZBP+jwH/piP610EGg2U9okriTLpkgNgdK9JRpRpxlKJ5rlUlNpM0fAXi3XrrxTaWd5qct1b3O4Ok2Dj5SQQe3Irn/j1/yPFn/2DU/9GS1J4FYReNNM9ptv5gio/j1/yPFn/wBg1P8A0ZLXPioxjNcq6G9CTlHUjE1tH4c043UJljMEQwOx2CqnmaFJ1jmT6H/69XLaW5i0DT2toBMfIjDKRnjaKia/l/5b6Op/4B/9auY0RD9m0V+VupU+v/6q3YFRIrdI23Iq/K3qMdaw2vdNIPnaUV9cDFbsW3EOwYXZ8o9BgVjiH+5n6M1pL95H1Mjxbaq9hHeIxjuLdwY5FOCO/X8K6Xwp4j8UapoyTW2q2lzsPlyC7tzvRh/tKRu+tVLi3huoTFPGHQ9jVDwq1x4X+3WM1vLcQzOHgliXOT0wfSvNwldKm4N6o9CpTXPzNaHQ63NqUemy3eua1NJbxjLW1kogD+2fvH86xQbfU0tjZ2hstPh3MsattaRumTg9OvXrSXOmPexql5f3c4U7grONoOc9Mdqs2tutpbJAhJVOhPXrmprYuLhaD1HGk+bVaGRdhIDOIoxtQnCgcGqgntvsrOLfbGXAYevvVu7aTfM0Qy+84HrzVczz+QJGtud2Cg54rqpfAr+R2u6St27f19wy2axaYGFWDgEj0/nT7RbYyGSFm3FeVPYGkiuA7Ni1KMqk5I6+3SltJLeQuYYthGN3GM1q+pnTs+XXq+ljf0qNh4V8Ruf+WlvZsPoLmcf0rjb2e3jn2y2vmHH3ulehadbsvg7VVYctpVpJ+Bu7pv5VwF3LdJIBDArpjqRmvUofwj53Eu9Zse0sQ04SmBjGR/q+pAzipLoBrfnkFlyCc96YJJ/sO8Qr52OUxgdf8KdcHNqOMcrkDtyK6OnyOfr8zV0LxbqOjSCKUte2WMeU7/PHj+4T29jx9K9A0vxBpmsR7rS5UuPvRP8AK6/Uf1rx9Rtv1kYZTYw/HB/qRRbjZPcMwIYgGNh1ByOQe3Ga8PFZdSrvmWj/AK6Hp08RKGj1R7Pcvvf5QWCg9B1JrzPxLp7Q6lfWe/LpOxJbuc5P866/4UXdxfaxeRXk8lysMIePzjv2HdjIJrlvHaO/iHVlQEn7SxwPrXNhcFLDNuTu2bVKyqJJLYpAkoAePlC/kMVFaRtb23ksQQGJyD16D+lOUgxKAMfIB+OOar2AZLMo4IcOSc+mB/XNd3fUy7CTR6nNJGl9I84tVMUCHG2Nck8fnSeRP/zzar+oiZnlEDBX3VABdGzK7sT+pxXqRgkkkjzZTbbY6DV9S0fS9ThhyILu0lhmQ/dIZCufqM19DajqEOmWT3U+dq8BR1YnoBXznf7v7HuA/wB7yTn3OK958XW7zaWkqBmEEodwP7vIJ/CubELl1R04f3nZmBqGp33inwjqrSW8MEAnjityrEsTvXJJ9sgfnU0NvHFbpbRx/ukUIq+wGKpeHrg6fa3mlGMvDcTG4icLwhJBZT+WQfc+1akcyq+zaeTt3e9fO5nWb5YLpr9//DHp0qfI5OxRj0mNjtSV1C8FGHI/GtSNPLiEaltoGMZqMH/TGx2UA/WllJ86JQSByTj0ry51qk7KUjV6lfU7/wDsTSLzUIY0LwxM4Rs7WIHAP41zun+I7jxFEJbtoEmjJHkRZwo7Hnk59ad45unHhYxbstdTqgB/u53H9BXM+Hba2u5p1uII5QFBXcuSPp6V7eW03Kld9/0OapU9nUvuTa1GsHia2YSFmkwSp/h5/wDr1R8WDF0D/wBNG/kKjuY0t/ELRoCFScAAknA49am8XcT5/wCmn/sor14K0WjkqS5p8xmKc28H/XP/ANmNS/brpIwi3MgVRgDd0qvGc2sH+4f/AEI11OnRae2nwPKsG8oMliM16ako0Ytq553K5VZJOxkeDXP/AAlekMTkm5jyfqRUnx6/5Hiz/wCwan/oyWmeF8DxnpoGMC+TGOn36f8AHr/keLP/ALBqf+jJa5sZ8Sfkb4fZljSP+QLY/wDXtH/6CKuZrpPD3gNb3wro91Hf+WZrGB2Vos4JRT61Yk+Ht8GPlXluw9W3Kf5GuW5rZnJEA9QD9RQP9cv+6f6V0T+B9aQEiOJ8dlkHP51l32iajpbJJe2xhV8qpLKcn8DXPin+4l6GtBP2sSrXK6jPKmp3Hlyuo3nhWIrqhXH6gd2oTn/poa8vLleo/Q9DFv3F6mv4fnnne482Z5AoXAY5x1raFYfhofJct6so/Q1uVhjLe3lby/I0w/8ACVzAuQ8gfym2vvJB/GoW+2CJCGV5QTuzjBFTg8ZqnPeSwXDKmwrxwy57V6lJNpRR1VnCnDnlfa2hKkl4yyeZGqkL8u3ufzqSGaSRHaSHyiO3rxUNvfPPMIzFGMgklc/41YlbbC5PZTVSTTs0FCUZxUot2V9zu7aIx+GtSRxgjw5Yn/yJcmvMLqK7eQG3m2LjkdK9cu4mj07WYiMMnhuxBHuGua8fv4beSRTLP5TY4B7161H+G/8Ahj5ir8aZOqXP2PYZP3+D85p0+fsvzfeG3PucjNQxxw/2eYxMDFz+8BqSUAWQAIYBVwR3HHNbrb5dzF7/AD7FZWJv44icRspJ/InP6CiB2ee4Vzwigr9cgfyJ/KgNvu4oNo+fOCexwT/SiJhLNKu0AxIGz68gf1rkOw9C+Drf8VFfj/p1/wDZ1/xrn/HkjweI9WdDhhcNz+Nb3wd/5GS//wCvU/8AoS1keM1H/CXampAIM5zmueruaQMYH92pzklAT9cVBZTPPaF5Gy28j8MD/Gr0en3LRh44SVIyMVWCqFJUAZ9KxutTWz0JtTQSNMpk8v5vvGq/lf6CYjOOn+szU2p+STKJyQm7qKrBbYafjcTB2P4/4166tp6Hl66+ot6CNIuFJziFhn14r6W61803YH9kThTlfs7bT7Y4r6Xrnr9PQ2o9TnNX0bTtNtrjVolkh8lGeREdihXqfkzjP0/rWPbaxpmovEbW+t5MZYgOAc9Oh5710/iYZ8Lar/15y/8AoBrwOxvTY3PnCJJOMFWHauKeVwxac07NHR9blSaTV0exR8XMnfdhgR0ximyk+bMw/gj2j+deWnxVPBcAwQmIlc/JKyjr6CrEXjnWo9zxyREE4ZZU3Z49eDXl1clr01dNOx0QxlOTNnxvMhurG0aQKsVrNMATwzEBVH15P5Vg+G7y3tbmZriVYwyDBbvzSa54ruddsobWe1t4RE+/ejEk8Hjnp1rDLr/eH5134SEqVJRkrNXM6slKTaNPUbiJ9eknjcNEZFbcPTil8TahaXsh+zTCTDgnH0rK3D1FV5FfzXYKSOOcV1JtGTSLsJ/0SH6N/wChGpBDK2CsTkHkELUVtmSCKNeX3MNp46niuk0rWrK106KGaRg65BAU+terTqNUVy6s8+cL1XzaGR4YYweI9MLAqUuo8g9vmFXPj1/yPFn/ANg1P/RktUbCZX8SW80Z+VrxWB9t4q98ev8AkeLP/sGp/wCjJa58ZvF+Rvh9mj1Dwn4s8N23g7RYJ/EOlxSxafAkkb3sasjCNQQQTwQe1a3/AAmfhX/oZdI/8Dov/iq+TaK4jpPrL/hM/Cv/AEMukf8AgdF/8VVW/wDEHgnU41jvNf0eVV5XN/GMfk1fK9FJpNWY02tUfScqfDtx8niDTIj6rqcZ/mxrBvPCvw8uJjJF4ztItxyQb+BufzrwqipjThB3irDlOUlZs9ytNA8Kaekq2/jrSHDtuAkuIgemOof+lE1no6xsY/FugO2OB/aCD+teG0VjUwlKpLmktTSNecVZM9/sdH8AJp0KXvijTnuQuZHj1KIDPoOeg6VTu/Cvw/uJ2kj8a2cWf4TfQNj9a8MordRS2JlVnJWk7o9lXwj4YglaSHx/oz8YVXnjH6h/6VHLoGknav8AwmPh90ZgH26ggIXPJGfavHqKHBN3ZdPEVKceWL0Po2/8QeHbvVNdhi8QaUEuNItoYna9jCM4e5yAc4yNy59Mj1ryme0tJiDLd6eSOhF9D/8AFVxFFbQqOCtY5J01J3O2WKzSEwi8svL5+X7ZGf8A2amytbi2Ma3tocKAB9qj6D8a4uitPrD7Ij2K7nWYh8xZBd2oZc4IuY/8aAIEdnF3agsMNi5j5H51ydFZc5tY9q+Fl3pGlXV7qOo69plqJF8mOKS8iDNyCWxu4HGKw/GGoafP4pv54NRs5opZNyPFco4Ix6g15jRWclzFRdj1O21fS0s4lbUrQEIMjz14/Wud+32e3H2qHp/z0FcdRWfs1cv2jO5u72wlmkDXds6k/wDPVSD+tQi508R+X9ptthGNvmLj+dcZRXcsQ0tjkdFPqdhdXdmbC4jS6gJMLgASrknB96+gv+Ez8K/9DLpH/gdF/wDFV8m0VlUqc7uaQhyI+pda8V+GbrQr+3j8R6Qzy20iKovouSVIA+9Xgct7biN9tzFnBxiQVy1FXSrukmktyalJTsdVbT20s0Ye5twued0qjH5mtUHTR0utP/G4j/xrgKKmpUdSxUI8p6PFDZyfcvdKH+9fQL/NqmW0gJx/aWjr7nU7b/4uvMqKxsaXPV00y2YZPiDQU9m1OH+jU7+x7SRSreJ/DygjGTqcf+NeTUUWC56pH4S05WRj418NDaQcfb17VaHhTRHkZpPHegKCSflu0b/2YV5DRWtOrOnflZnOnGfxHs+n+E/C1nfW9xJ4/wBHkSKRXZFmiUtg5xnzDj8q5v416np+q+MbSfTr62vYl09EMlvKsihvMkOMqTzgjj3rzyiidSU/iYRhGOx//9k=",
        // 仅支持英文要求大小写准确，其他语言请自行转换为英文
        // 服务器会根据问题自动判断不同的图片类型，所以请确保问题正确。
        "question": "Pick the bread"  
    }
}

响应示例

{
    "errorId": 0,
    "errorCode": "",
    "status": "ready",
    "solution": {
        "objects": [4], // 目标所处的位置，第5张图片（从0开始）
        "labels": [
            "parrot",
            "panda",
            "octopus",
            "owl",
            "bread",
            "dog"
        ]
    },
    "taskId": "04a3fa76-11a0-11ed-a58c-0ef20f419382"
}

图片格式与问题说明：

请直接获取网页上显示的问题全文+图片提交，全部可以识别
如果遇到新的类型，请联系客服增加支持。
如果遇到竖的6宫格，直接获取原图上传，服务端可以自动识别。

类型	英文问题	中文问题	说明

英文问题	中文问题	说明
`Pick the bread`	选出面包	目前有52种不同的分类，请直接传完整问题
`Pick one square that shows two identical objects`	选出两个相同的图形	还有一种3个黑白扭曲变形图标，请看下面。
`Pick one square that shows two identical objects`	选出两个相同的图形	问题与上面的相同，区别是黑暗版本的尺寸为450300，请确保图片尺寸正确*
`Pick the penguin`	选出企鹅
`Pick the shadow with a different object silhouette`	选择具有不同对象轮廓的阴影
`Pick the dice pair with the same icon facing up`	选择相同图标的骰子对
`Pick the dice pair whose top sides add up to 14`	选择顶边加起来为 14 的骰子对	准确率98.8%，更新于2023/04/20
`Pick the matching cards`	选择匹配的卡片
`Pick the animal looking at the shape that matches the shape it's standing on`	选择动物看向的形状与它站立的形状相匹配的
`Pick one square that shows three of the same object.`	选出三个相同图形的方块
`Pick the mouse that can reach all the cheese in the maze`	选出能够拿到迷宫里所有奶酪的老鼠
`Pick the mouse that can't reach the cheese`	选出不能够拿到迷宫里所有奶酪的老鼠	准确率98.19%，更新于2023/06/20
`Pick the image where the darts add up to 10`	选择飞镖加起来为 10 的图像
`Pick the image that is the correct way up`	选择正确向上的图像
`Pick the dice pair whose top sides add up to 5`	选择顶边加起来为 5 的骰子对	（5/6/7/8/9都有）
`Pick the wrong shadow`	选择错误的阴影	准确率99.94%，更新于2023/07/04
`Select the animal with the wrong head`	选择头部错误的动物	准确率99.94%，更新于2023/06/14
`Pick the shadow that mathes the icons at the top of the image`	选择与图像顶部的图标匹配的阴影	准确率98.80%，更新于2023/06/23
`Pick the spiral galaxy`	选择螺旋星系
`Pick the image where all animals are walking in the same direction as the arrow`	选出所有动物都沿着箭头方向行走的图像
`Select the image with the icon order Chair then Fence`	选择先椅子再围栏的图片
`Select the image where the total fingers add up to 4`	选择总共有4根手指的图片	准确率100.00%，更新于2023/04/03
`Select the image where the total fingers add up to 3`	选择总共有3根手指的图片	准确率100.00%，更新于2023/04/03
`Pick any square`	选择任何正方形
`Select an image of three circles in any direction on a straight line`	选取任意方向上三个圆圈在一条直线上的图片	准确率100.00%，更新于2023/04/03
`Pick the image with 3 crosses in a row in any direction`	选择任何方向连续 3 个叉的图像	准确率100.00%，更新于2023/04/03
`Pick the image where the number matches the amount of animals`	选择数字与动物数量相匹配的图像
`Pick the distorted object`	选择扭曲的物体	准确率67.00%，更新于2023/06/09
`Pick the object that is not distorted`	选择没有扭曲的物体	准确率54.00%，更新于2023/06/09
`Select the animal with the wrong head`	选择头和身体匹配错误的动物	准确率100.00%，更新于2023/06/14
`Pick the image with only one rope`	选择只有一根绳子的图片	准确率98.20%，更新于2023/06/28
`Pick the image where the darts add up to 8`	选择飞镖总数为 8 的图片	准确率100.00%，更新于2023/06/28
`Pick the image of the brick cube and the striped heart`	选择砖块立方体和条纹心形的图像	准确率100.00%，更新于2023/06/28
`Pick the image of the brick cube and the striped sphere`	选择砖块立方体和条纹球体的图像	准确率100.00%，更新于2023/06/29
`Pick the image of the brick heart and the striped heart`	选择砖块心形和条纹心形的图像	准确率97.00%，更新于2023/06/28
`Pick the image of the brick sphere and the checkered heart`	选择砖块球体和方格心形的图像	准确率100.00%，更新于2023/06/29
`Pick the image of the checkered cone and the checkered sphere`	选择方格圆锥体和方格球体的图像	准确率99.50%，更新于2023/06/29
`Pick the image of the fuzzy cone and the brick sphere`	选择毛绒锥体和砖块球体图像	准确率100.00%，更新于2023/06/29
`Pick the image of the fuzzy cube and the checkered cube`	选择毛绒立方体和方格立方体的图像	准确率100.00%，更新于2023/06/29
`Pick the image of the fuzzy heart and the brick heart`	选择毛绒心形和砖块心形的图像	准确率100.00%，更新于2023/06/29
`Pick the image of the fuzzy heart and the striped heart`	选择毛绒心形和条纹心形的图像	准确率100.00%，更新于2023/06/29
`Pick the image of the fuzzy cube and the striped cube`	选择毛绒立方体和条纹立方体的图像	准确率100.00%，更新于2023/06/29
`Pick the image of the striped cone and the checkered cube`	选择条纹圆锥体和方格立方体的图像	准确率96.00%，更新于2023/06/29
`Pick the image of the brick cone and the striped cone`	选择砖块锥体和条纹锥体的图像	准确率100.00%，更新于2023/06/29
`Pick the image of the striped cube and the checkered cube`	选择条纹立方体和方格立方体的图像	准确率100.00%，更新于2023/06/29
`Pick the image of the fuzzy sphere and the striped cone`	选择毛绒球体和条纹锥体的图像	准确率100.00%，更新于2023/06/29
`Pick the image of the striped cube and the checkered sphere`	选择条纹立方体和方格球体的图像	准确率100.00%，更新于2023/06/29
`Pick the image of the striped cube and the checkered heart`	选择条纹立方体和方格心形的图像	准确率100.00%，更新于2023/06/29
`Pick the image of the brick cone and the checkered cube`	选择砖块锥体和方格立方体的图像	准确率100.00%，更新于2023/06/29
`Pick the image of the striped heart and the checkered cube`	选择条纹心形和方格立方体的图像	准确率100.00%，更新于2023/06/29
`Pick the image of the brick cone and the checkered sphere`	选择砖块锥体和方格球体的图像
`Pick the image of the fuzzy sphere and the striped cube`	选择毛绒球体和条纹立方体的图像	准确率100.00%，更新于2023/06/30
`Pick the image of 2 striped shapes`	选择2个条纹形状的图像	准确率100.00%，更新于2023/07/06
`Pick the image of 2 checkered shapes`	选择2个方格形状的图像	准确率100.00%，更新于2023/07/06
`Pick the image with the matching reflection`	选择动物和水中倒影相匹配的图像	准确率100.00%，更新于2023/07/06
`Pick the image of the person walking up the stairs`	选择爬上楼梯的人	准确率99.50%，更新于2023/07/07