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ImageCallbackV5Demo.cs 4.49 KB
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longfan 提交于 2022-06-01 15:24 . C# demo补充
using Newtonsoft.Json.Linq;
using System;
using System.Collections.Generic;
using System.Net.Http;
namespace Com.Netease.Is.Antispam.Demo
{
class ImageCallbackV5Demo
{
public static void imageCallBack()
{
/** 产品密钥ID,产品标识 */
String secretId = "your_secret_id";
/** 产品私有密钥,服务端生成签名信息使用,请严格保管,避免泄露 */
String secretKey = "your_secret_key";
/** 业务ID,易盾根据产品业务特点分配 */
String businessId = "your_business_id";
/** 易盾反垃圾云服务图片离线检测结果获取接口地址 */
String apiUrl = "http://as.dun.163.com/v5/image/callback/results";
Dictionary<String, String> parameters = new Dictionary<String, String>();
long curr = (long)(DateTime.UtcNow - new DateTime(1970, 1, 1, 0, 0, 0, DateTimeKind.Utc)).TotalMilliseconds;
String time = curr.ToString();
// 1.设置公共参数
parameters.Add("secretId", secretId);
parameters.Add("businessId", businessId);
parameters.Add("version", "v5");
parameters.Add("timestamp", time);
parameters.Add("nonce", new Random().Next().ToString());
// 2.生成签名信息
String signature = Utils.genSignature(secretKey, parameters);
parameters.Add("signature", signature);
// 3.发送HTTP请求
HttpClient client = Utils.makeHttpClient();
String result = Utils.doPost(client, apiUrl, parameters, 10000);
if(result != null)
{
JObject ret = JObject.Parse(result);
int code = ret.GetValue("code").ToObject<Int32>();
String msg = ret.GetValue("msg").ToObject<String>();
if (code == 200)
{
JArray array = (JArray)ret.SelectToken("result");
if (array == null || !array.HasValues)
{
Console.WriteLine("暂时没有人工复审结果需要获取,请稍后重试!");
}else {
foreach (var item in array){
JObject tmp = (JObject)item;
JObject antispam = tmp.GetValue("antispam").ToObject<JObject>();
String name = antispam.GetValue("name").ToObject<String>();
String taskId = antispam.GetValue("taskId").ToObject<String>();
JArray labels = (JArray)antispam.SelectToken("labels");
int suggestion = antispam.GetValue("suggestion").ToObject<Int32>();
Console.WriteLine(String.Format("taskId={0},name={1},suggestion={2}", taskId, name, suggestion));
// 产品需根据自身需求,自行解析处理,本示例只是简单判断分类级别
foreach (var lable in labels)
{
JObject lableData = (JObject)lable;
int label = lableData.GetValue("label").ToObject<Int32>();
int level = lableData.GetValue("level").ToObject<Int32>();
double rate = lableData.GetValue("rate").ToObject<Double>();
Console.WriteLine(String.Format("label:{0}, level={1}, rate={2}", label, level, rate));
}
switch (suggestion)
{
case 0:
Console.WriteLine("#图片被动回调结果:最高等级为\"正常\"\n");
break;
case 2:
Console.WriteLine("#图片被动回调结果:最高等级为\"确定\"\n");
break;
default:
break;
}
}
}
}
else
{
Console.WriteLine(String.Format("ERROR: code={0}, msg={1}", code, msg));
}
}
else
{
Console.WriteLine("Request failed!");
}
}
}
}
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