public static async Task <string> AnalyzePhoto(TraceWriter log, PhotoToAnalyze photoToAnalyze, ImageAnalysisTableAdapter imageAnalysisTableAdapter)
{
using (HttpClient httpClient = new HttpClient())
{
Stopwatch stopwatch = Stopwatch.StartNew();
VisionApiResponse visionApiResponse = await GetGoogleVisionApi(log, photoToAnalyze, httpClient);
List <Face> msFaces = await GetMsFaces(log, photoToAnalyze, httpClient);
Analysis msAnalysis = await GetMsAnalysis(log, photoToAnalyze, httpClient);
if (visionApiResponse?.Responses.Count == 1 && msAnalysis != null)
{
ImageAnalysis canonicalImageAnalysis = new ImageAnalysis(visionApiResponse.Responses[0], msAnalysis, msFaces);
ImageAnalysisEntity imageAnalysisEntity = new ImageAnalysisEntity
{
// for canonical truncate decimal precision to 4 decimal places, for others keep original precision
CanonicalJson = JsonConvert.SerializeObject(canonicalImageAnalysis, JsonUtils.AnalysisSerializerSettings),
GoogleVisionApiJson = JsonConvert.SerializeObject(visionApiResponse.Responses[0], JsonUtils.JsonSerializerSettings),
MsCognitiveFaceDetectJson = JsonConvert.SerializeObject(msFaces, JsonUtils.JsonSerializerSettings),
MsAnalysisJson = JsonConvert.SerializeObject(msAnalysis, JsonUtils.JsonSerializerSettings)
};
if (imageAnalysisEntity.GoogleVisionApiJson.Length > 30000)
{
log.Warning($"Google vision API response JSON is {imageAnalysisEntity.GoogleVisionApiJson.Length} chars, removing TextAnnotations");
visionApiResponse.Responses[0].TextAnnotations = null;
imageAnalysisEntity.GoogleVisionApiJson = JsonConvert.SerializeObject(visionApiResponse.Responses[0], JsonUtils.JsonSerializerSettings);
}
if (imageAnalysisEntity.GoogleVisionApiJson.Length > 45000)
{
log.Warning($"GoogleVisionApiJson still is {imageAnalysisEntity.GoogleVisionApiJson.Length} chars after removing TextAnnotations");
}
if (imageAnalysisEntity.CanonicalJson.Length > 45000)
{
log.Warning($"CanonicalJson is {imageAnalysisEntity.CanonicalJson.Length} chars");
}
if (imageAnalysisEntity.MsCognitiveFaceDetectJson.Length > 45000)
{
log.Warning($"MsCognitiveFaceDetectJson is {imageAnalysisEntity.MsCognitiveFaceDetectJson.Length} chars");
}
if (imageAnalysisEntity.MsAnalysisJson.Length > 45000)
{
log.Warning($"MsAnalysisJson is {imageAnalysisEntity.MsAnalysisJson.Length} chars");
}
imageAnalysisTableAdapter.InsertImageAnalysis(imageAnalysisEntity, photoToAnalyze.Url);
imageAnalysisTableAdapter.InsertBlogImageAnalysis(SanityHelper.SanitizeSourceBlog(photoToAnalyze.Blog), photoToAnalyze.Url);
log.Info($"All analyses for {photoToAnalyze.Url} saved in {stopwatch.ElapsedMilliseconds}ms");
return(null);
}
log.Warning("Failed to get all responses");
return("Failed to get all responses");
}
}
public static HttpResponseMessage Run([HttpTrigger(AuthorizationLevel.Function, "get", "post", Route = "getfrequencies")]
HttpRequestMessage req, TraceWriter log)
{
Startup.Init();
ImageAnalysisTableAdapter imageAnalysisTableAdapter = new ImageAnalysisTableAdapter();
imageAnalysisTableAdapter.Init();
TokenAllocationTableAdapter tokenAllocationTableAdapter = new TokenAllocationTableAdapter();
tokenAllocationTableAdapter.Init();
List <ImageAnalysisEntity> analyses = imageAnalysisTableAdapter.GetAllCanonical();
Dictionary <string, int> digramFrequencies = new Dictionary <string, int>();
Dictionary <string, int> labelFrequencies = new Dictionary <string, int>();
int processedCount = 0;
foreach (ImageAnalysisEntity entity in analyses)
{
ImageAnalysis canonicalAnalysis = JsonConvert.DeserializeObject <ImageAnalysis>(entity.CanonicalJson);
UpdateCounts(StringTokenizer.GetDigrams(canonicalAnalysis.TokenizedText), digramFrequencies);
UpdateCounts(canonicalAnalysis.Labels.Keys.Distinct(), labelFrequencies);
processedCount++;
if (processedCount % 100 == 0)
{
log.Info($"Processed frequencies for {processedCount} image analyses");
}
}
log.Info($"Inserting {digramFrequencies.Count} digrams");
tokenAllocationTableAdapter.InsertFrequencies(TokenAllocationTableAdapter.PartitionDigram, digramFrequencies);
log.Info($"Inserting {labelFrequencies.Count} labels");
tokenAllocationTableAdapter.InsertFrequencies(TokenAllocationTableAdapter.PartitionLabel, labelFrequencies);
return(req.CreateResponse(HttpStatusCode.OK, $"Processed {analyses.Count} analyses"));
}
public static HttpResponseMessage Run([HttpTrigger(AuthorizationLevel.Function, "get", "post", Route = "redo-canonical")] HttpRequestMessage req, TraceWriter log)
{
Startup.Init();
ImageAnalysisTableAdapter imageAnalysisTableAdapter = new ImageAnalysisTableAdapter();
imageAnalysisTableAdapter.Init();
List <ImageAnalysisEntity> analyses = imageAnalysisTableAdapter.GetAll();
foreach (ImageAnalysisEntity entity in analyses)
{
Response visionResponse = JsonConvert.DeserializeObject <Response>(entity.GoogleVisionApiJson);
Analysis msAnalysis = JsonConvert.DeserializeObject <Analysis>(entity.MsAnalysisJson);
List <Face> msFaces = JsonConvert.DeserializeObject <List <Face> >(entity.MsCognitiveFaceDetectJson);
ImageAnalysis canonicalImageAnalysis = new ImageAnalysis(visionResponse, msAnalysis, msFaces);
entity.CanonicalJson = JsonConvert.SerializeObject(canonicalImageAnalysis, JsonUtils.AnalysisSerializerSettings);
imageAnalysisTableAdapter.UpdateImageAnalysis(entity);
}
return(req.CreateResponse(HttpStatusCode.OK, $"Updated {analyses.Count} analyses"));
}
public static async Task Run([HttpTrigger(AuthorizationLevel.Function, "get", "post", Route = "processimage")]
HttpRequestMessage req, TraceWriter log)
{
Startup.Init();
ImageAnalysisTableAdapter imageAnalysisTableAdapter = new ImageAnalysisTableAdapter();
imageAnalysisTableAdapter.Init();
const string imageUrl = "https://tumblrpics.blob.core.windows.net/orig-66/c48440825ac6eab1af6c4de39bbc59d6_ph8zkhbeVA1tf8706_1280.jpg";
using (HttpClient httpClient = new HttpClient())
{
Stopwatch stopwatch = Stopwatch.StartNew();
string apiKey = ConfigurationManager.AppSettings["GoogleApiKey"];
string url = "https://vision.googleapis.com/v1/images:annotate?key=" + apiKey;
VisionApiRequest request = VisionApiRequest.CreateFromImageUris(imageUrl);
string requestJson = JsonConvert.SerializeObject(request, JsonUtils.GoogleSerializerSettings);
StringContent stringContent = new StringContent(requestJson, Encoding.UTF8, "application/json");
HttpResponseMessage response = await httpClient.PostAsync(url, stringContent);
HttpContent responseContent = response.Content;
string googleVisionResponseString = await responseContent.ReadAsStringAsync();
VisionApiResponse visionApiResponse =
JsonConvert.DeserializeObject <VisionApiResponse>(googleVisionResponseString, JsonUtils.GoogleSerializerSettings);
string faceApiKey = ConfigurationManager.AppSettings["FaceApiKey"];
httpClient.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", faceApiKey);
stringContent = new StringContent($"{{\"url\":\"{imageUrl}\"}}", Encoding.UTF8, "application/json");
response = await httpClient.PostAsync(
"https://northeurope.api.cognitive.microsoft.com/face/v1.0/detect?returnFaceId=true&returnFaceLandmarks=false&returnFaceAttributes=" +
"age,gender,headPose,smile,facialHair,glasses,emotion,hair,makeup,occlusion,accessories,blur,exposure,noise",
stringContent);
responseContent = response.Content;
string msDetectResponseString = await responseContent.ReadAsStringAsync();
List <Face> msFaces = JsonConvert.DeserializeObject <List <Face> >(msDetectResponseString);
string visionApiKey = ConfigurationManager.AppSettings["ComputerVisionApiKey"];
httpClient.DefaultRequestHeaders.Remove("Ocp-Apim-Subscription-Key");
httpClient.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", visionApiKey);
stringContent = new StringContent($"{{\"url\":\"{imageUrl}\"}}", Encoding.UTF8, "application/json");
response = await httpClient.PostAsync(
"https://northeurope.api.cognitive.microsoft.com/vision/v2.0/analyze?visualFeatures=Description,ImageType,Adult,Categories,Tags,Objects,Color&language=en",
stringContent);
responseContent = response.Content;
string msAnalyzeResponseString = await responseContent.ReadAsStringAsync();
Analysis msAnalysis = JsonConvert.DeserializeObject <Analysis>(msAnalyzeResponseString);
if (visionApiResponse.Responses.Count == 1 && msFaces.Count > 0 && msAnalysis != null)
{
ImageAnalysis canonicalImageAnalysis = new ImageAnalysis(visionApiResponse.Responses[0], msAnalysis, msFaces);
}
}
}
