private void SendRequest(object state)
{
mServerResult = string.Empty;
try
{
#if TENCENT
ClientProfile clientProfile = new ClientProfile();
HttpProfile httpProfile = new HttpProfile();
httpProfile.Endpoint = ("iai.tencentcloudapi.com");
clientProfile.HttpProfile = httpProfile;
IaiClient client = new IaiClient(mCredential, "", clientProfile);
DetectFaceRequest req = DetectFaceRequest.FromJsonString <DetectFaceRequest>(state.ToString());
DetectFaceResponse resp = client.DetectFace(req).ConfigureAwait(false).GetAwaiter().GetResult();
mServerResult = AbstractModel.ToJsonString(resp);
mResult = JsonUtility.FromJson <DFServerResult>(mServerResult);
#endif
mIsDone = true;
}
catch (System.Exception ex)
{
mServerResult = ex.Message;
string[] sf = mServerResult.Split(' ');
DFServerResult rs = new DFServerResult();
rs.Error = new DFError();
rs.Error.Code = sf[0].Split(':')[1];
rs.Error.Message = sf[1].Split(':')[1];
mResult = rs;
mIsDone = true;
}
}
/// <summary>
/// Call Evaluate Image, to determine whether the image violates any policy
/// </summary>
/// <param name="imageContent">Image Content</param>
/// <returns>Evaluate result</returns>
public async Task <DetectFaceResult> DetectFaceAsync(ImageModeratableContent imageContent, bool cacheContent = false)
{
using (var client = new HttpClient())
{
client.BaseAddress = new Uri(this.options.HostUrl);
//string urlPath = $"{this.options.ImageServicePath}{string.Format("/Image/DetectFaces{0}", cacheContent ? "?cacheImage=true" : string.Empty)}";
//string urlPath = $"{this.options.ImageServicePathV2}{string.Format("/Faces{0}", cacheContent ? "?cacheImage=true" : string.Empty)}";
string urlPath = string.Format("{0}/Faces{1}", this.options.ImageServicePathV2,
cacheContent ? "?cacheImage=true" : string.Empty);
HttpRequestMessage message = new HttpRequestMessage(HttpMethod.Post, urlPath);
ServiceHelpers.Addkey(message, this.options.ImageServiceKey);
DetectFaceRequest request = new DetectFaceRequest(imageContent);
if (imageContent.BinaryContent == null)
{
message.Content = new StringContent(
JsonConvert.SerializeObject(request),
Encoding.UTF8,
"application/json");
}
else
{
message.Content = new StreamContent(imageContent.BinaryContent.Stream);
message.Content.Headers.ContentType = MediaTypeHeaderValue.Parse(imageContent.BinaryContent.ContentType);
}
return(await ServiceHelpers.SendRequest <DetectFaceResult>(client, message));
}
}
public async Task <DetectFaceResponse[]> DetectFace(DetectFaceRequest detectRequest, MemoryStream image)
{
var content = new ByteArrayContent(image.ToArray());
content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream");
HttpResponseMessage hrm = await _client.PostAsync("/detect?returnFaceAttributes=age,gender", content);
string result = await hrm.Content.ReadAsStringAsync();
var detectResponse = JsonConvert.DeserializeObject <DetectFaceResponse[]>(result);
return(detectResponse);
}
/// <summary>
/// 检测给定图片中的人脸（Face）的位置、相应的面部属性和人脸质量信息，位置包括 (x，y，w，h)，面部属性包括性别（gender）、年龄（age）、表情（expression）、魅力（beauty）、眼镜（glass）、发型（hair）、口罩（mask）和姿态 (pitch，roll，yaw)，人脸质量信息包括整体质量分（score）、模糊分（sharpness）、光照分（brightness）和五官遮挡分（completeness）。
///
///
/// 其中，人脸质量信息主要用于评价输入的人脸图片的质量。在使用人脸识别服务时，建议您对输入的人脸图片进行质量检测，提升后续业务处理的效果。该功能的应用场景包括：
///
/// 1） 人员库[创建人员](https://cloud.tencent.com/document/product/867/32793)/[增加人脸](https://cloud.tencent.com/document/product/867/32795)：保证人员人脸信息的质量，便于后续的业务处理。
///
/// 2） [人脸搜索](https://cloud.tencent.com/document/product/867/32798)：保证输入的图片质量，快速准确匹配到对应的人员。
///
/// 3） [人脸验证](https://cloud.tencent.com/document/product/867/32806)：保证人脸信息的质量，避免明明是本人却认证不通过的情况。
///
/// 4） [人脸融合](https://cloud.tencent.com/product/facefusion)：保证上传的人脸质量，人脸融合的效果更好。
///
/// </summary>
/// <param name="req">参考<see cref="DetectFaceRequest"/></param>
/// <returns>参考<see cref="DetectFaceResponse"/>实例</returns>
public async Task <DetectFaceResponse> DetectFace(DetectFaceRequest req)
{
JsonResponseModel <DetectFaceResponse> rsp = null;
try
{
var strResp = await this.InternalRequest(req, "DetectFace");
rsp = JsonConvert.DeserializeObject <JsonResponseModel <DetectFaceResponse> >(strResp);
}
catch (JsonSerializationException e)
{
throw new TencentCloudSDKException(e.Message);
}
return(rsp.Response);
}
public async Task <IDetectFaceResponse> Detect([FromBody] byte[] faceCapture)
{
var detectFaceRequest = new DetectFaceRequest(faceCapture);
return(await _cognitiveFaceService.Handle(detectFaceRequest));
}
