public static async Task <HttpResponseMessage> Run(
[HttpTrigger(AuthorizationLevel.Anonymous, "get", Route = "DetectsCheck/{imageName}")] HttpRequestMessage req,
string imageName,
[Table("detects", " ", "{imageName}", Connection = "AzureWebJobsStorage")] DetectEntity detect,
TraceWriter log)
{
if (detect == null)
{
return(req.CreateResponse(HttpStatusCode.OK, DetectEntity.DetectState.NotProcessed));
}
return(req.CreateResponse(HttpStatusCode.OK, detect.Faces));
}
public static void Run([BlobTrigger("photos/{name}", Connection = "AzureWebJobsStorage")] Stream photo,
string name,
[DocumentDB("SignalData", "Faces", ConnectionStringSetting = "CosmosDbConnection")] out dynamic document,
[Table("detects", Connection = "AzureWebJobsStorage")] out DetectEntity detectCheck,
TraceWriter log)
{
log.Info($"Processing:{name} \n Size: {photo.Length} Bytes");
//DEBUG
//document = null;
//return;
var result = new DetectionResult()
{
DateTime = DateTime.Now,
Source = DetectionResult.SOURCE_PRODUCTION,
Image = Utils.EncodeStreamToBase64(photo),
Tags = new List <Tag>()
};
// Send image to FaceAPI
MemoryStream detectPhotoStream = new MemoryStream();
photo.CopyTo(detectPhotoStream);
detectPhotoStream.Seek(0, SeekOrigin.Begin);
if (detectPhotoStream.Length == 0)
{
log.Error("Image size 0.");
document = null;
detectCheck = new DetectEntity(name, 0);
return;
}
Face firstFace = GetFirstFaceAsync(detectPhotoStream, log).Result;
if (firstFace == null)
{
document = null;
detectCheck = new DetectEntity(name, 0);
return;
}
detectCheck = new DetectEntity(name, 1);
result.Tags.Add(new Tag("Age", firstFace.FaceAttributes.Age));
result.Tags.Add(new Tag("Gender", firstFace.FaceAttributes.Gender));
result.Tags.Add(new Tag("Smile", firstFace.FaceAttributes.Smile, firstFace.FaceAttributes.Smile));
int glasses = firstFace.FaceAttributes.Glasses > 0 ? 1 : 0;
result.Tags.Add(new Tag("Glasses", glasses, glasses));
Tuple <string, double> facialHair = GetTopFacialHair(firstFace.FaceAttributes.FacialHair);
result.Tags.Add(new Tag("FacialHair", facialHair.Item1, facialHair.Item2));
result.FaceRectangle = firstFace.FaceRectangle;
if (Environment.GetEnvironmentVariable("UseTagRecognition", EnvironmentVariableTarget.Process).ToLower() == bool.TrueString.ToLower())
{
// Send image to Custom Vision
var predictionClient = new CustomVisionClient(
Environment.GetEnvironmentVariable("PredictionKey"),
Environment.GetEnvironmentVariable("PredictionEndpoint"));
PredictionResult predRes = predictionClient.PredictAsync(photo).Result;
if (predRes == null)
{
log.Info("Prediction result empty.");
}
else
{
// Put results into single JSON
// - results coming from API are ordered by Probabilty, taking first 4
var firstResults = predRes.Predictions.Take(4);
foreach (var pr in firstResults)
{
string category = CategoryMapping.Where(c => c.Value.Contains(pr.Tag)).FirstOrDefault().Key;
result.Tags.Add(new Tag(category, pr.Tag, pr.Probability));
}
}
}
// Send to front-end API
using (var hc = new HttpClient())
{
var res = hc.PostAsync(Environment.GetEnvironmentVariable("SaveApiEndpoint"),
new StringContent(JsonConvert.SerializeObject(result), System.Text.Encoding.UTF8, "application/json")).Result;
if (res.IsSuccessStatusCode)
{
log.Info("Data sent to API.");
}
else
{
log.Error("Unable to send data to API. (" + res.Content.ReadAsStringAsync().Result + ")");
}
}
// Save to DocumentDB
result.Image = null; // neukládáme obrázek
document = result;
log.Info(JsonConvert.SerializeObject(result.Tags, Formatting.Indented));
}
