public static void CreateImageFromUrls([QueueTrigger("create-image-from-urls")] CreateImageFromUrlsRequest imageCreateRequest, TraceWriter log)
{
log.Info($"C# Queue trigger function processed: {imageCreateRequest}");
// https://docs.microsoft.com/ja-jp/azure/cognitive-services/custom-vision-service/csharp-tutorial
var CV_ProjectId = Environment.GetEnvironmentVariable("CV_ProjectId");
var CV_TrainingKey = Environment.GetEnvironmentVariable("CV_TrainingKey");
//var CV_PredictionKey = Environment.GetEnvironmentVariable("CV_PredictionKey");
var trainingApi = new TrainingApi()
{
ApiKey = CV_TrainingKey
};
var projectId = Guid.Parse(CV_ProjectId);
//var project = new ProjectInfo(trainingApi.GetProject(Guid.Parse(CV_ProjectId)));
var requestTags = imageCreateRequest.Tags.ToList();
var existTags = trainingApi.GetTags(projectId);
var nonExistTagNames = requestTags.Except(existTags.Select(x => x.Name));
var tagIds = existTags.Where(x => requestTags.Contains(x.Name)).Select(x => x.Id).ToList();
nonExistTagNames.ToList().ForEach(tagName =>
{
// XXX 同時に同じタグ名を指定された複数のキューを処理すると、重複してタグ作成してしまう。
// 現状、重複エラー後のリトライで処理
var tag = trainingApi.CreateTag(projectId, tagName);
tagIds.Add(tag.Id);
});
var images = new List <ImageUrlCreateEntry>()
{
new ImageUrlCreateEntry()
{
Url = imageCreateRequest.Url
}
};
trainingApi.CreateImagesFromUrls(Guid.Parse(CV_ProjectId), new ImageUrlCreateBatch(images, tagIds));
}
public static HttpResponseMessage Run([HttpTrigger(AuthorizationLevel.Anonymous, "post", Route = nameof(TrainClassifier))]
HttpRequestMessage req, TraceWriter log)
{
using (var analytic = new AnalyticService(new RequestTelemetry
{
Name = nameof(TrainClassifier)
}))
{
try
{
var allTags = new List <string>();
var json = req.Content.ReadAsStringAsync().Result;
var j = JObject.Parse(json);
var gameId = (string)j["gameId"];
var imageUrls = j["imageUrls"].ToObject <List <string> >();
var tags = (JArray)j["tags"];
var game = CosmosDataService.Instance.GetItemAsync <Game>(gameId).Result;
var api = new TrainingApi(new TrainingApiCredentials(ConfigManager.Instance.CustomVisionTrainingKey));
ProjectModel project = null;
//Get the existing project for this game if there is one
if (!string.IsNullOrEmpty(game.CustomVisionProjectId))
{
try
{
project = api.GetProject(Guid.Parse(game.CustomVisionProjectId));
}
catch (Exception) { }
}
//Otherwise create a new project and associate it with the game
if (project == null)
{
project = api.CreateProject(game.Name, game.Id);
game.CustomVisionProjectId = project.Id.ToString();
CosmosDataService.Instance.UpdateItemAsync <Game>(game).Wait();
}
//Generate tag models for training
var tagModels = new List <ImageTagModel>();
foreach (string tag in tags)
{
var model = api.CreateTag(project.Id, tag.Trim());
tagModels.Add(model);
}
//Batch the image urls that were sent up from Azure Storage (blob)
var batch = new ImageUrlCreateBatch(tagModels.Select(m => m.Id).ToList(), imageUrls);
var summary = api.CreateImagesFromUrls(project.Id, batch);
if (!summary.IsBatchSuccessful)
{
return(req.CreateErrorResponse(HttpStatusCode.BadRequest, "Image batch was unsuccessful"));
}
//Traing the classifier and generate a new iteration, that we'll set as the default
var iteration = api.TrainProject(project.Id);
while (iteration.Status == "Training")
{
Thread.Sleep(1000);
iteration = api.GetIteration(project.Id, iteration.Id);
}
iteration.IsDefault = true;
api.UpdateIteration(project.Id, iteration.Id, iteration);
return(req.CreateResponse(HttpStatusCode.OK, true));
}
catch (Exception e)
{
analytic.TrackException(e);
return(req.CreateErrorResponse(HttpStatusCode.BadRequest, e));
}
}
}
/// <summary>
/// 上传图片
/// </summary>
/// <param name="projectId"></param>
/// <param name="createBatch"></param>
/// <returns></returns>
public Task UploadOnlineImage(Guid projectId, ImageUrlCreateBatch createBatch)
{
return(Task.Run(() => {
trainingApi.CreateImagesFromUrls(projectId, createBatch);
}));
}
async public static Task <HttpResponseMessage> Run([HttpTrigger(AuthorizationLevel.Anonymous, "post", Route = nameof(TrainClassifier))]
HttpRequestMessage req, TraceWriter log)
{
using (var analytic = new AnalyticService(new RequestTelemetry
{
Name = nameof(TrainClassifier)
}))
{
try
{
var allTags = new List <string>();
var json = req.Content.ReadAsStringAsync().Result;
var j = JObject.Parse(json);
var gameId = (string)j["gameId"];
var imageUrls = j["imageUrls"].ToObject <List <string> >();
var tags = (JArray)j["tags"];
var game = CosmosDataService.Instance.GetItemAsync <Game>(gameId).Result;
TrainingApi api = new TrainingApi {
ApiKey = ConfigManager.Instance.CustomVisionTrainingKey
};
Project project = null;
//Get the existing project for this game if there is one
if (!string.IsNullOrEmpty(game.CustomVisionProjectId))
{
try { project = api.GetProject(Guid.Parse(game.CustomVisionProjectId)); }
catch (Exception) { }
}
//Otherwise create a new project and associate it with the game
if (project == null)
{
project = api.CreateProject($"{game.Name}_{DateTime.Now.ToString()}_{Guid.NewGuid().ToString()}", game.Id);
game.CustomVisionProjectId = project.Id.ToString();
CosmosDataService.Instance.UpdateItemAsync <Game>(game).Wait();
}
var tagItems = tags.Select(t => api.CreateTag(project.Id, t.ToString().Trim()));
var entries = imageUrls.Select(u => new ImageUrlCreateEntry(u)).ToList();
//Batch the image urls that were sent up from Azure Storage (blob)
var batch = new ImageUrlCreateBatch(entries, tagItems.Select(t => t.Id).ToList());
var summary = api.CreateImagesFromUrls(project.Id, batch);
//if(!summary.IsBatchSuccessful)
// return req.CreateErrorResponse(HttpStatusCode.BadRequest, "Image batch was unsuccessful");
//Traing the classifier and generate a new iteration, that we'll set as the default
var iteration = api.TrainProject(project.Id);
while (iteration.Status == "Training")
{
Thread.Sleep(1000);
iteration = api.GetIteration(project.Id, iteration.Id);
}
iteration.IsDefault = true;
api.UpdateIteration(project.Id, iteration.Id, iteration);
var data = new Event("Training classifier");
data.Add("project", project.Name);
data.Add("iteration", iteration.Id);
await EventHubService.Instance.SendEvent(data);
return(req.CreateResponse(HttpStatusCode.OK, true));
}
catch (Exception e)
{
analytic.TrackException(e);
var baseException = e.GetBaseException();
var operationException = baseException as HttpOperationException;
var reason = baseException.Message;
if (operationException != null)
{
var jobj = JObject.Parse(operationException.Response.Content);
var code = jobj.GetValue("Code");
if (code != null && !string.IsNullOrWhiteSpace(code.ToString()))
{
reason = code.ToString();
}
}
return(req.CreateErrorResponse(HttpStatusCode.BadRequest, reason));
}
}
}
public static async Task <HttpResponseMessage> Run([HttpTrigger(AuthorizationLevel.Anonymous, "post", Route = null)] HttpRequestMessage req, TraceWriter log)
{
try
{
var allTags = new List <string>();
var json = req.Content.ReadAsStringAsync().Result;
var jobj = JObject.Parse(json);
var tags = (JArray)jobj["tags"];
var term = jobj["term"].ToString();
var projectId = jobj["projectId"].ToString();
var trainingKey = jobj["trainingKey"].ToString();
var offset = 0;
if (jobj["offset"] != null)
{
offset = (int)jobj["offset"];
}
var imageUrls = await SearchForImages(term, offset);
var api = new TrainingApi(new TrainingApiCredentials(trainingKey));
var project = api.GetProject(Guid.Parse(projectId));
var tagModels = new List <ImageTagModel>();
var existingTags = api.GetTags(project.Id);
foreach (string tag in tags)
{
ImageTagModel model = existingTags.Tags.SingleOrDefault(t => t.Name == tag);
if (model == null)
{
model = api.CreateTag(project.Id, tag.Trim());
}
tagModels.Add(model);
}
var batch = new ImageUrlCreateBatch(tagModels.Select(m => m.Id).ToList(), imageUrls);
var summary = api.CreateImagesFromUrls(project.Id, batch);
//if(!summary.IsBatchSuccessful)
// return req.CreateErrorResponse(HttpStatusCode.BadRequest, "Image batch was unsuccessful");
//Traing the classifier and generate a new iteration, that we'll set as the default
var iteration = api.TrainProject(project.Id);
while (iteration.Status == "Training")
{
Thread.Sleep(1000);
iteration = api.GetIteration(project.Id, iteration.Id);
}
iteration.IsDefault = true;
api.UpdateIteration(project.Id, iteration.Id, iteration);
return(req.CreateResponse(HttpStatusCode.OK, iteration.Id));
}
catch (Exception e)
{
var exception = e.GetBaseException();
return(req.CreateErrorResponse(HttpStatusCode.BadRequest, exception.Message));
}
async Task <List <string> > SearchForImages(string term, int offset)
{
var client = new HttpClient();
client.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", "c2adf0e5c057447ea9e0f50cc5202251");
var uri = $"https://api.cognitive.microsoft.com/bing/v7.0/images/search?count=50&q={term}&offset={offset}";
var json = await client.GetStringAsync(uri);
var jobj = JObject.Parse(json);
var arr = (JArray)jobj["value"];
var list = new List <string>();
foreach (var result in arr)
{
list.Add(result["contentUrl"].ToString());
}
return(list);
}
}