private static async Task Predict(string fileName)
{
using (Image <Rgba32> image = Image.Load(fileName))
{
var preprocessor = new Preprocessor(Rgba32.White, Rgba32.Black);
var i = preprocessor.Preprocess(image);
i.Save("result2-7.png", new PngEncoder());
var pixels = Preprocessor.ConvertImageToArray(i);
//Console.WriteLine(JsonConvert.SerializeObject(pixels));
for (int j = 0; j < 784; j++)
{
Console.Write(pixels[j].ToString("D3"));
if ((j + 1) % 28 == 0)
{
Console.WriteLine();
}
}
var recognizer = new MLStudioDigitRecognizer("API_URL", "API_KEY");
var prediction = await recognizer.PredictAsync(i);
Console.WriteLine($"\n\n\nThis is a(n) {prediction.Tag}! (I'm {prediction.Probability*100}% sure.)\n\n\n");
}
}
/// <summary>
/// Handle attachments uploaded by users. The bot receives an <see cref="Attachment"/> in an <see cref="Activity"/>.
/// The activity has a <see cref="IList{T}"/> of attachments.
/// </summary>
/// <remarks>
/// Not all channels allow users to upload files. Some channels have restrictions
/// on file type, size, and other attributes. Consult the documentation for the channel for
/// more information. For example Skype's limits are here
/// <see ref="https://support.skype.com/en/faq/FA34644/skype-file-sharing-file-types-size-and-time-limits"/>.
/// </remarks>
private async Task HandleIncomingAttachmentAsync(DialogContext dc, IMessageActivity activity)
{
foreach (var file in activity.Attachments)
{
if (file.ContentType != "image/png" && file.ContentType != "image/jpeg")
{
await dc.Context.SendActivityAsync("Sorry, I cannot process images other than png/jpeg.");
}
// Download the actual attachment
using (var client = new HttpClient())
{
var stream = await client.GetStreamAsync(file.ContentUrl);
var memoryStream = new MemoryStream();
await stream.CopyToAsync(memoryStream);
var byteArray = memoryStream.ToArray();
//var recognizer = new CustomVisionDigitRecognizer(
// _configuration["CustomVisionBaseUrl"],
// _configuration["CustomVisionProjectId"],
// _configuration["CustomVisionPublishedName"],
// _configuration["CustomVisionApiKey"]);
var recognizer = new MLStudioDigitRecognizer(
_configuration["MLStudioApiUrl"],
_configuration["MLStudioApiKey"]);
var prediction = await recognizer.PredictAsync(byteArray);
await SendPredictionAnswer(dc, prediction.Tag, prediction.Probability);
}
}
}
public async Task PredictWithMLStudioAsync_ReturnsPredictionAsync()
{
var fileStream = new FileStream("test2.jpg", FileMode.Open, FileAccess.Read);
var memoryStream = new MemoryStream();
await fileStream.CopyToAsync(memoryStream);
var byteArray = memoryStream.ToArray();
var recognizer = new MLStudioDigitRecognizer(
_mlStudioApiUrl,
_mlStudioApiKey);
var prediction = await recognizer.PredictAsync(byteArray);
Assert.Equal(5, prediction.Tag);
}