/// <summary>
/// Call the CPU-based model for our image
/// </summary>
/// <param name="jsonContent">
/// The JSON representing the image, to be sent to the model.
/// </param>
/// <returns>
/// If the call is successful, returns a ModelResponse object
/// representing the result of the call. Otherwise returns null.
/// </returns>
private CpuModelResponse InvokeCpuModel(string jsonContent)
{
const string url = "http://grocerymodel:5001/score";
try
{
using (var client = new HttpClient())
{
var content = new StringContent(jsonContent);
content.Headers.ContentType = new MediaTypeHeaderValue("application/json");
DateTime then = DateTime.Now;
var response = client.PostAsync(url, content).Result;
string text = response.Content.ReadAsStringAsync().Result;
// TODO: timing recognitionDuration = DateTime.Now - then;
Console.WriteLine($"POST return status code {response.StatusCode}");
Console.WriteLine(text);
if (response.IsSuccessStatusCode)
{
CpuModelResponse modelResponse = JsonConvert.DeserializeObject <CpuModelResponse>(text);
return(modelResponse);
}
}
}
catch (Exception ex)
{
Console.WriteLine("Failure uploading to model.");
Console.WriteLine(ex);
}
return(null);
}
public List <ImageFeature> Process(Google.Protobuf.ByteString image)
{
string imageJson = MakeImageJson(image);
if (imageJson != null)
{
CpuModelResponse response = InvokeCpuModel(imageJson);
if (response != null)
{
List <ImageFeature> result = new List <ImageFeature>();
for (int i = 0; i < response.classes.Length; i++)
{
ImageFeature feature = new ImageFeature(response.classes[i],
response.scores[i], response.bboxes[i]);
result.Add(feature);
}
return(result);
}
}
return(null);
}
