public ClassificationResult GetResult(string inputImageLocation, string pictureName)
{
ImageAnnotatorClient client = ImageAnnotatorClient.Create();
Image image = Image.FromFile(inputImageLocation);
IReadOnlyList <EntityAnnotation> results;
var startTime = DateTime.Now;
try
{
results = client.DetectLabels(image, null, Constants.maxLabelsReturned);
}
catch (Exception e)
{
throw new Exception("Error during detect label call Google.", e);
}
var endTime = DateTime.Now;
var labels = new List <string>();
var scores = new List <float>();
foreach (var label in results)
{
if (!string.IsNullOrEmpty(label.Description) && label.Score != 0)
{
labels.Add(label.Description);
scores.Add(label.Score * 100);
}
else
{
throw new Exception("Exception during Google processing of image " + inputImageLocation);
}
}
var classificationResult = new ClassificationResult()
{
APIName = "Google"
};
classificationResult.ProcessingTimeMilliseconds = endTime.Subtract(startTime).TotalMilliseconds;
classificationResult.InputLabel = pictureName;
classificationResult.ReturnedLabel1 = labels[0];
classificationResult.ReturnedConfidence1 = scores[0];
classificationResult.ReturnedLabel2 = labels[1];
classificationResult.ReturnedConfidence2 = scores[1];
classificationResult.ReturnedLabel3 = labels[2];
classificationResult.ReturnedConfidence3 = scores[2];
classificationResult.FilePath = inputImageLocation;
return(classificationResult);
}
public ClassificationResult GetResult(string inputImageLocation, string pictureName)
{
Amazon.Rekognition.Model.Image image = new Amazon.Rekognition.Model.Image();
// Load image
try
{
using (FileStream fs = new FileStream(inputImageLocation, FileMode.Open, FileAccess.Read))
{
byte[] data = null;
data = new byte[fs.Length];
fs.Read(data, 0, (int)fs.Length);
image.Bytes = new MemoryStream(data);
}
}
catch (Exception e)
{
throw new Exception("Error during loading image file AWS.", e);
}
// Create client
AmazonRekognitionClient rekognitionClient = new AmazonRekognitionClient();
// Create detectLabelsRequest
DetectLabelsRequest detectlabelsRequest = new DetectLabelsRequest()
{
Image = image,
MaxLabels = Constants.maxLabelsReturned,
};
ClassificationResult classificationResult = new ClassificationResult()
{
APIName = "AWS"
};
try
{
var startTime = DateTime.Now;
var detectLabelsResponse = rekognitionClient.DetectLabelsAsync(detectlabelsRequest);
detectLabelsResponse.Wait();
var endTime = DateTime.Now;
var labels = new List <string>();
var scores = new List <float>();
foreach (var label in detectLabelsResponse.Result.Labels)
{
if (!string.IsNullOrEmpty(label.Name) && label.Confidence != 0)
{
labels.Add(label.Name);
scores.Add(label.Confidence);
}
else
{
throw new Exception("Exception during AWS processing of image " + inputImageLocation);
}
}
classificationResult.ProcessingTimeMilliseconds = endTime.Subtract(startTime).TotalMilliseconds;
classificationResult.InputLabel = pictureName;
classificationResult.ReturnedLabel1 = labels[0];
classificationResult.ReturnedConfidence1 = scores[0];
classificationResult.ReturnedLabel2 = labels[1];
classificationResult.ReturnedConfidence2 = scores[1];
classificationResult.ReturnedLabel3 = labels[2];
classificationResult.ReturnedConfidence3 = scores[2];
classificationResult.FilePath = inputImageLocation;
}
catch (Exception e)
{
throw e;
}
return(classificationResult);
}
public ClassificationResult GetResult(string inputImageLocation, string pictureName)
{
#region SETUP
string apiKey = "***";
string apiSecret = "***";
string basicAuthValue = System.Convert.ToBase64String(System.Text.Encoding.UTF8.GetBytes(String.Format("{0}:{1}", apiKey, apiSecret)));
#endregion SETUP
#region UPLOAD
var uploadClient = new RestClient("https://api.imagga.com/v2/uploads");
uploadClient.Timeout = -1;
var uploadRequest = new RestRequest(Method.POST);
uploadRequest.AddHeader("Authorization", String.Format("Basic {0}", basicAuthValue));
uploadRequest.AddFile("image", inputImageLocation);
var startTime = DateTime.Now;
IRestResponse uploadResponse = uploadClient.Execute(uploadRequest);
ImaggaUploadResponse immagaUploadResponse = JsonConvert.DeserializeObject <ImaggaUploadResponse>(uploadResponse.Content);
var uploadid = string.Empty;
if (immagaUploadResponse.status.type == "success")
{
uploadid = immagaUploadResponse.result.upload_id;
}
else
{
throw new Exception("error during immaggaUpload");
}
#endregion UPLOAD
#region LABEL
var labelClient = new RestClient("https://api.imagga.com/v2/tags");
labelClient.Timeout = -1;
var labelRequest = new RestRequest(Method.GET);
labelRequest.AddParameter("image_upload_id", uploadid);
labelRequest.AddParameter("limit", Constants.maxLabelsReturned);
labelRequest.AddHeader("Authorization", String.Format("Basic {0}", basicAuthValue));
IRestResponse labelResponse = labelClient.Execute(labelRequest);
var endTime = DateTime.Now;
ImaggaLabelResponse imaggaLabelResponse = JsonConvert.DeserializeObject <ImaggaLabelResponse>(labelResponse.Content);
var labels = new List <string>();
var scores = new List <float>();
if (imaggaLabelResponse.status.type == "success")
{
foreach (var label in imaggaLabelResponse.result.tags)
{
if (!string.IsNullOrEmpty(label.tag.en) && label.confidence != 0)
{
labels.Add(label.tag.en);
scores.Add(label.confidence);
}
else
{
throw new Exception("Exception during imagga processing of image " + inputImageLocation);
}
}
}
else
{
throw new Exception("Exception during imagga processing of image, no success returned: " + inputImageLocation);
}
#endregion LABEL
var classificationResult = new ClassificationResult()
{
APIName = "imagga"
};
classificationResult.ProcessingTimeMilliseconds = endTime.Subtract(startTime).TotalMilliseconds;
classificationResult.InputLabel = pictureName;
classificationResult.ReturnedLabel1 = labels[0];
classificationResult.ReturnedConfidence1 = scores[0];
classificationResult.ReturnedLabel2 = labels[1];
classificationResult.ReturnedConfidence2 = scores[1];
classificationResult.ReturnedLabel3 = labels[2];
classificationResult.ReturnedConfidence3 = scores[2];
classificationResult.FilePath = inputImageLocation;
return(classificationResult);
}
static void Main(string[] args)
{
Console.WriteLine("Get images from folder " + Constants.startPath);
/*
* Get all items from each subdirectory and send to computer vision API's
*/
Console.WriteLine("Start image classification.");
List <ClassificationResult> classResultsAll = new List <ClassificationResult>();
List <string> filePathsList = Directory.GetFiles(Constants.startPath).ToList();
Console.WriteLine(filePathsList.Count + " images found.");
foreach (string file in filePathsList)
{
var filename = Path.GetFileName(file);
long sizeBytes = new FileInfo(file).Length;
if (true)
{
try
{
IClassification googleLabeler = new GoogleClassification();
ClassificationResult classResultGoogle = googleLabeler.GetResult(file, filename);
classResultGoogle.FileSizeBytes = sizeBytes;
classResultsAll.Add(classResultGoogle);
}
catch (Exception e)
{
Console.WriteLine("Error during Google classification of image " + file);
throw e;
}
}
if (true)
{
try
{
IClassification awsLabeler = new AWSClassification();
ClassificationResult classResultAWS = awsLabeler.GetResult(file, filename);
classResultAWS.FileSizeBytes = sizeBytes;
classResultsAll.Add(classResultAWS);
}
catch (Exception e)
{
Console.WriteLine("Error during AWS classification of image " + file);
throw e;
}
}
try
{
IClassification imaggalabeler = new ImaggaClassification();
ClassificationResult classResultimaga = imaggalabeler.GetResult(file, filename);
classResultimaga.FileSizeBytes = sizeBytes;
classResultsAll.Add(classResultimaga);
}
catch (Exception e)
{
Console.WriteLine("Error during imagga classification of image " + file);
throw e;
}
}
Console.WriteLine("Successfully classified images.");
Console.WriteLine("Start write to CSV.");
try
{
// Write to CSV
using (var writer = new StreamWriter(Constants.outputFolder + @"\result" + Guid.NewGuid().ToString() + ".csv"))
using (var csv = new CsvWriter(writer, CultureInfo.InvariantCulture))
{
csv.WriteRecords(classResultsAll);
}
}
catch (Exception e)
{
Console.WriteLine("Error during write to CSV.");
throw e;
}
Console.WriteLine("End write to CSV.");
Console.WriteLine("Program executed successfully.");
Console.ReadLine();
}