internal void Classify(ClassifyTaskModel[] tasks)
{
if (tasks == null || tasks.Length == 0)
{
this.log.LogWarning($"No images to process");
return;
}
var batches = tasks.Batch(MAX_BATCH_SIZE);
if (batches == null)
{
this.log.LogError($"Batch splitting error");
return;
}
foreach (var batch in batches)
{
// batch now has MAX_BATCH_SIZE items to work with
/* if (batch == null)
* {
* throw new ArgumentException($"Illegal arguments count in batch. min is 1 max is 8");
* }*/
dynamic taskResponse;
bool isErr = true;
do
{
BatchAnalyzeRequest analyzeRequest = new BatchAnalyzeRequest()
{
FolderId = config.folderId
};
foreach (ClassifyTaskModel t in batch)
{
analyzeRequest.AnalyzeSpecs.Add(makeAnalyzeSpec(t));
}
var call = visionClassifierClient.BatchAnalyzeAsync(
request: analyzeRequest,
headers: MakeMetadata(),
deadline: DateTime.UtcNow.AddMinutes(5)
).GetAwaiter().GetResult();
taskResponse = JObject.Parse(call.ToString());
isErr = isError(taskResponse);
if (isErr)
{
this.log.LogInformation($"Quota exceeded waiting 5 sec.");
Thread.Sleep(5 * 1000);
}
} while (isErr);
safeResults(batch, taskResponse);
}
}
public async Task <AnalyzeResult[]> RecognizeText(string folderId,
string iamToken,
Stream image,
string[] languages)
{
var channel = new Channel("vision.api.cloud.yandex.net", 443, new SslCredentials());
var client = new VisionService.VisionServiceClient(channel);
var request = new BatchAnalyzeRequest
{
FolderId = folderId,
AnalyzeSpecs =
{
new AnalyzeSpec
{
Content = await ByteString.FromStreamAsync(image),
Features =
{
new Feature
{
Type = Feature.Types.Type.TextDetection,
TextDetectionConfig = new FeatureTextDetectionConfig
{
LanguageCodes =
{
languages
}
}
}
}
}
}
};
var headers = new Metadata
{
{
"Authorization", "Bearer " + iamToken
}
};
var response = await client.BatchAnalyzeAsync(request, headers).ResponseAsync;
return(response.Results
.Select(ConvertAnalyzeResult)
.ToArray());
}
