public async Task <PredictImageResult> PredictImageAsync(IFormFile formFile)
{
var filePath = Path.GetTempFileName();
if (formFile != null && formFile.Length > 0)
{
var stream = new FileStream(filePath, FileMode.Create);
await formFile.CopyToAsync(stream);
stream.Close();
using (var memoryStream = new MemoryStream(System.IO.File.ReadAllBytes(filePath)))
{
PredictImageResult predictImageResult = await new ClassificationService().PredictImage(memoryStream);
//do some processing
return(predictImageResult);
}
}
else
{
throw new Exception("formFile not found or empty file");
}
//foreach (var formFile in files)
//{
// if (formFile.Length > 0)
// {
// using (var stream = new FileStream(filePath, FileMode.Create))
// {
// await formFile.CopyToAsync(stream);
// }
// }
//}
////var formFile = files.FirstOrDefault();
}
public async Task <PredictImageResult> PredictImage(Stream testImage)
{
string trainingKey = "6308b3b62b344e3f8e4170c4728deed2";
string predictionKey = "afdffbaa498445c1830aa18ee9216e0b";
// Create a prediction endpoint, passing in obtained prediction key
PredictionEndpoint endpoint = new PredictionEndpoint()
{
ApiKey = predictionKey
};
TrainingApi trainingApi = new TrainingApi()
{
ApiKey = trainingKey
};
var projects = await trainingApi.GetProjectsAsync();
var project = projects.First(f => f.Name == "WA-SE-AI");
try
{
var result = await endpoint.PredictImageAsync(project.Id, testImage);
var tags = await trainingApi.GetTagsAsync(project.Id);
// Loop over each prediction and write out the results
foreach (var c in result.Predictions)
{
Console.WriteLine($"\t{c.TagName}: {c.Probability:P1}");
}
var topPrediction = result.Predictions.OrderByDescending(m => m.Probability).First();
PredictImageResult predictImageResult = new PredictImageResult
{
PredictionModel = topPrediction,
Tag = tags.FirstOrDefault(f => f.Id == topPrediction.TagId)
};
return(predictImageResult);
}
catch (Exception e)
{
throw new Exception("PredictImage failed");
}
}
