public async Task <ModerationResponse> AnalyzeImage(byte[] imageBytes)
{
var channel = new Grpc.Core.Channel(ImageAnnotatorClient.DefaultEndpoint.Host, Credentials.ToChannelCredentials());
try
{
var client = ImageAnnotatorClient.Create(channel);
var image = Image.FromBytes(imageBytes);
var response = await client.DetectSafeSearchAsync(image);
var moderationResponse = new ModerationResponse();
moderationResponse.ModerationScores = new[] {
new ModerationScore()
{
Category = $"Adult", Score = ConvertLikelyhood(response.Adult)
},
new ModerationScore()
{
Category = $"Medical", Score = ConvertLikelyhood(response.Medical)
},
new ModerationScore()
{
Category = $"Spoof", Score = ConvertLikelyhood(response.Spoof)
},
new ModerationScore()
{
Category = $"Violent", Score = ConvertLikelyhood(response.Violence)
}
};
moderationResponse.Pass = !moderationResponse.ModerationScores.Any(s => s.Score > .40F);
return(moderationResponse);
}
catch (Exception ex)
{
return(new ModerationResponse()
{
Pass = false,
ModerationScores = new[] { new ModerationScore()
{
Category = $"ServerError:{ex.Message}", Score = 100
} }
});
}
finally
{
await channel.ShutdownAsync();
}
}
public async Task <ModerationResponse> AnalyzeImage(MemoryStream imageStream)
{
using (var client = new AmazonRekognitionClient(Endpoint))
{
var request = new DetectModerationLabelsRequest()
{
Image = new Image()
{
Bytes = imageStream
},
MinConfidence = 0 //do this so that scores are always returned?
};
var awsResponse = await client.DetectModerationLabelsAsync(request);
var response = new ModerationResponse();
if (awsResponse.HttpStatusCode != System.Net.HttpStatusCode.OK)
{
response.Pass = false;
response.ModerationScores = new[] { new ModerationScore()
{
Category = $"ServerError:{awsResponse.HttpStatusCode}", Score = 100
} };
}
else
{
if (awsResponse.ModerationLabels.Any(s => s.Confidence >= 50))
{
response.Pass = false;
}
else
{
response.Pass = true;
}
response.ModerationScores = awsResponse.ModerationLabels
.Select(m => new ModerationScore()
{
Category = $"{m.ParentName}:{m.Name}",
Score = m.Confidence
});
}
return(response);
}
}
public async Task <ModerationResponse> AnalyzeImage(byte[] imageBytes, string imageName)
{
var client = new RestClient(String.Format(API_URL_FORMAT, AzureRegion));
client.AddDefaultHeader(API_KEY_HEADER, ApiKey);
var request = new RestRequest(API_ENDPOINT, Method.POST);
request.AddParameter(DetermineMimeType(imageName), imageBytes, ParameterType.RequestBody);
var apiResponse = await client.ExecuteTaskAsync <AzureModerationResponse>(request);
var response = new ModerationResponse();
if (apiResponse.ResponseStatus != ResponseStatus.Completed || !apiResponse.IsSuccessful)
{
response.Pass = false;
response.ModerationScores = new[] { new ModerationScore()
{
Category = $"ServerError:{apiResponse.StatusDescription}", Score = 100
} };
}
else
{
response.Pass = !(apiResponse.Data.IsImageAdultClassified || apiResponse.Data.IsImageRacyClassified);
var list = new List <ModerationScore>();
list.Add(new ModerationScore {
Category = "Adult", Score = apiResponse.Data.AdultClassificationScore
});
list.Add(new ModerationScore {
Category = "Racy", Score = apiResponse.Data.RacyClassificationScore
});
response.ModerationScores = list;
}
return(response);
}
