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mark-szabo/DigitRecognizerBot.cs

Last active November 21, 2019 17:18
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Digit Recognizer Bot Workshop
Raw
DigitRecognizerBot.cs
if (turnContext.Activity.Attachments != null && turnContext.Activity.Attachments.Any())
{
// We know the user is sending an attachment as there is at least one item
// in the Attachments list.
await HandleIncomingAttachmentAsync(turnContext, turnContext.Activity);
return;
}
if (turnContext.Activity.Text?.Trim()?.ToLowerInvariant() == "hi")
{
await turnContext.SendActivitiesAsync(
new IActivity[]
{
new Activity(type: ActivityTypes.Message, text: "Hi! 🙋‍"),
new Activity(type: ActivityTypes.Message, text: "Send me a picture of a handwritten digit and I'll tell you what the number is!"),
new Activity(type: ActivityTypes.Message, text: "Yeah, I'm that smart! 😎"),
},
cancellationToken);
}
Raw
Helpers.cs
/// <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(ITurnContext turnContext, IMessageActivity activity)
{
foreach (var file in activity.Attachments)
{
if (file.ContentType != "image/png" && file.ContentType != "image/jpeg")
{
await turnContext.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 MLStudioDigitRecognizer(
_configuration["MLStudioApiUrl"],
_configuration["MLStudioApiKey"]);
var prediction = await recognizer.PredictAsync(byteArray);
await SendPredictionAnswer(turnContext, prediction.Tag, prediction.Probability);
}
}
}
private static async Task SendPredictionAnswer(ITurnContext turnContext, int digit, double probability)
{
var digitWithArticle = string.Empty;
switch (digit)
{
case 0:
digitWithArticle = "a zero";
break;
case 1:
case 2:
case 3:
case 4:
case 5:
case 6:
case 7:
case 9:
digitWithArticle = $"a {digit}";
break;
case 8:
digitWithArticle = $"an {digit}";
break;
default:
break;
}
if (probability < 0.5)
{
await turnContext.SendActivityAsync($"I'm not 100% sure, but I think this is {digitWithArticle}.");
return;
}
var random = new Random();
switch (random.Next(0, 4))
{
case 0:
await turnContext.SendActivityAsync($"I know! I know! It's {digitWithArticle}!");
break;
case 1:
await turnContext.SendActivityAsync($"OK, this should be {digitWithArticle}!");
break;
case 2:
await turnContext.SendActivityAsync($"This is {digitWithArticle}!");
break;
case 3:
await turnContext.SendActivityAsync($"Easy-peasy! This is {digitWithArticle}.");
break;
}
}
Raw
MLStudioDigitRecognizer.cs
using System;
using System.Linq;
using System.Net.Http;
using System.Net.Http.Headers;
using System.Threading.Tasks;
using ImagePreprocessingService;
using Newtonsoft.Json;
using SixLabors.ImageSharp;
using SixLabors.ImageSharp.PixelFormats;
namespace DigitRecognizerService
{
public class MLStudioDigitRecognizer : IDigitRecognizer
{
private readonly HttpClient _httpClient = new HttpClient();
private readonly string _apiUrl;
private readonly string _apiKey;
/// <summary>
/// Recognize digits using Azure ML Studio.
/// </summary>
/// <param name="apiUrl">API url for the web service.</param>
/// <param name="apiKey">API key for the web service.</param>
public MLStudioDigitRecognizer(string apiUrl, string apiKey)
{
_apiUrl = apiUrl;
_apiKey = apiKey;
}
public async Task<Prediction> PredictAsync(byte[] image) => await PredictAsync(Image.Load(image));
public async Task<Prediction> PredictAsync(Image<Rgba32> image)
{
var preprocessor = new Preprocessor(Rgba32.White, Rgba32.Black);
image = preprocessor.Preprocess(image);
var inputs = PrepareMLStudioInput(image);
var requestContent = new StringContent(inputs);
requestContent.Headers.ContentType = new MediaTypeHeaderValue("application/json");
_httpClient.DefaultRequestHeaders.Authorization = new AuthenticationHeaderValue("Bearer", _apiKey);
var response = await _httpClient.PostAsync(_apiUrl, requestContent);
var responseContent = response.Content is HttpContent c ? await c.ReadAsStringAsync() : null;
var prediction = JsonConvert.DeserializeObject<MLStudioResponseObject>(responseContent);
var tag = prediction.results.output1.value.Values[0].ToList().Last();
return new Prediction
{
Tag = Convert.ToInt32(tag),
Probability = 1
};
}
private static string PrepareMLStudioInput(Image<Rgba32> image)
{
var pixels = new string[785];
pixels[0] = "0";
int i = 1;
for (int j = 0; j < image.Height; j++)
{
for (int k = 0; k < image.Width; k++)
{
pixels[i] = (255 - ((image[k, j].R + image[k, j].G + image[k, j].B) / 3)).ToString();
i++;
}
}
return "{\"Inputs\":{\"input1\":{\"ColumnNames\":[\"label\",\"pixel0\",\"pixel1\",\"pixel2\",\"pixel3\",\"pixel4\",\"pixel5\",\"pixel6\",\"pixel7\",\"pixel8\",\"pixel9\",\"pixel10\",\"pixel11\",\"pixel12\",\"pixel13\",\"pixel14\",\"pixel15\",\"pixel16\",\"pixel17\",\"pixel18\",\"pixel19\",\"pixel20\",\"pixel21\",\"pixel22\",\"pixel23\",\"pixel24\",\"pixel25\",\"pixel26\",\"pixel27\",\"pixel28\",\"pixel29\",\"pixel30\",\"pixel31\",\"pixel32\",\"pixel33\",\"pixel34\",\"pixel35\",\"pixel36\",\"pixel37\",\"pixel38\",\"pixel39\",\"pixel40\",\"pixel41\",\"pixel42\",\"pixel43\",\"pixel44\",\"pixel45\",\"pixel46\",\"pixel47\",\"pixel48\",\"pixel49\",\"pixel50\",\"pixel51\",\"pixel52\",\"pixel53\",\"pixel54\",\"pixel55\",\"pixel56\",\"pixel57\",\"pixel58\",\"pixel59\",\"pixel60\",\"pixel61\",\"pixel62\",\"pixel63\",\"pixel64\",\"pixel65\",\"pixel66\",\"pixel67\",\"pixel68\",\"pixel69\",\"pixel70\",\"pixel71\",\"pixel72\",\"pixel73\",\"pixel74\",\"pixel75\",\"pixel76\",\"pixel77\",\"pixel78\",\"pixel79\",\"pixel80\",\"pixel81\",\"pixel82\",\"pixel83\",\"pixel84\",\"pixel85\",\"pixel86\",\"pixel87\",\"pixel88\",\"pixel89\",\"pixel90\",\"pixel91\",\"pixel92\",\"pixel93\",\"pixel94\",\"pixel95\",\"pixel96\",\"pixel97\",\"pixel98\",\"pixel99\",\"pixel100\",\"pixel101\",\"pixel102\",\"pixel103\",\"pixel104\",\"pixel105\",\"pixel106\",\"pixel107\",\"pixel108\",\"pixel109\",\"pixel110\",\"pixel111\",\"pixel112\",\"pixel113\",\"pixel114\",\"pixel115\",\"pixel116\",\"pixel117\",\"pixel118\",\"pixel119\",\"pixel120\",\"pixel121\",\"pixel122\",\"pixel123\",\"pixel124\",\"pixel125\",\"pixel126\",\"pixel127\",\"pixel128\",\"pixel129\",\"pixel130\",\"pixel131\",\"pixel132\",\"pixel133\",\"pixel134\",\"pixel135\",\"pixel136\",\"pixel137\",\"pixel138\",\"pixel139\",\"pixel140\",\"pixel141\",\"pixel142\",\"pixel143\",\"pixel144\",\"pixel145\",\"pixel146\",\"pixel147\",\"pixel148\",\"pixel149\",\"pixel150\",\"pixel151\",\"pixel152\",\"pixel153\",\"pixel154\",\"pixel155\",\"pixel156\",\"pixel157\",\"pixel158\",\"pixel159\",\"pixel160\",\"pixel161\",\"pixel162\",\"pixel163\",\"pixel164\",\"pixel165\",\"pixel166\",\"pixel167\",\"pixel168\",\"pixel169\",\"pixel170\",\"pixel171\",\"pixel172\",\"pixel173\",\"pixel174\",\"pixel175\",\"pixel176\",\"pixel177\",\"pixel178\",\"pixel179\",\"pixel180\",\"pixel181\",\"pixel182\",\"pixel183\",\"pixel184\",\"pixel185\",\"pixel186\",\"pixel187\",\"pixel188\",\"pixel189\",\"pixel190\",\"pixel191\",\"pixel192\",\"pixel193\",\"pixel194\",\"pixel195\",\"pixel196\",\"pixel197\",\"pixel198\",\"pixel199\",\"pixel200\",\"pixel201\",\"pixel202\",\"pixel203\",\"pixel204\",\"pixel205\",\"pixel206\",\"pixel207\",\"pixel208\",\"pixel209\",\"pixel210\",\"pixel211\",\"pixel212\",\"pixel213\",\"pixel214\",\"pixel215\",\"pixel216\",\"pixel217\",\"pixel218\",\"pixel219\",\"pixel220\",\"pixel221\",\"pixel222\",\"pixel223\",\"pixel224\",\"pixel225\",\"pixel226\",\"pixel227\",\"pixel228\",\"pixel229\",\"pixel230\",\"pixel231\",\"pixel232\",\"pixel233\",\"pixel234\",\"pixel235\",\"pixel236\",\"pixel237\",\"pixel238\",\"pixel239\",\"pixel240\",\"pixel241\",\"pixel242\",\"pixel243\",\"pixel244\",\"pixel245\",\"pixel246\",\"pixel247\",\"pixel248\",\"pixel249\",\"pixel250\",\"pixel251\",\"pixel252\",\"pixel253\",\"pixel254\",\"pixel255\",\"pixel256\",\"pixel257\",\"pixel258\",\"pixel259\",\"pixel260\",\"pixel261\",\"pixel262\",\"pixel263\",\"pixel264\",\"pixel265\",\"pixel266\",\"pixel267\",\"pixel268\",\"pixel269\",\"pixel270\",\"pixel271\",\"pixel272\",\"pixel273\",\"pixel274\",\"pixel275\",\"pixel276\",\"pixel277\",\"pixel278\",\"pixel279\",\"pixel280\",\"pixel281\",\"pixel282\",\"pixel283\",\"pixel284\",\"pixel285\",\"pixel286\",\"pixel287\",\"pixel288\",\"pixel289\",\"pixel290\",\"pixel291\",\"pixel292\",\"pixel293\",\"pixel294\",\"pixel295\",\"pixel296\",\"pixel297\",\"pixel298\",\"pixel299\",\"pixel300\",\"pixel301\",\"pixel302\",\"pixel303\",\"pixel304\",\"pixel305\",\"pixel306\",\"pixel307\",\"pixel308\",\"pixel309\",\"pixel310\",\"pixel311\",\"pixel312\",\"pixel313\",\"pixel314\",\"pixel315\",\"pixel316\",\"pixel317\",\"pixel318\",\"pixel319\",\"pixel320\",\"pixel321\",\"pixel322\",\"pixel323\",\"pixel324\",\"pixel325\",\"pixel326\",\"pixel327\",\"pixel328\",\"pixel329\",\"pixel330\",\"pixel331\",\"pixel332\",\"pixel333\",\"pixel334\",\"pixel335\",\"pixel336\",\"pixel337\",\"pixel338\",\"pixel339\",\"pixel340\",\"pixel341\",\"pixel342\",\"pixel343\",\"pixel344\",\"pixel345\",\"pixel346\",\"pixel347\",\"pixel348\",\"pixel349\",\"pixel350\",\"pixel351\",\"pixel352\",\"pixel353\",\"pixel354\",\"pixel355\",\"pixel356\",\"pixel357\",\"pixel358\",\"pixel359\",\"pixel360\",\"pixel361\",\"pixel362\",\"pixel363\",\"pixel364\",\"pixel365\",\"pixel366\",\"pixel367\",\"pixel368\",\"pixel369\",\"pixel370\",\"pixel371\",\"pixel372\",\"pixel373\",\"pixel374\",\"pixel375\",\"pixel376\",\"pixel377\",\"pixel378\",\"pixel379\",\"pixel380\",\"pixel381\",\"pixel382\",\"pixel383\",\"pixel384\",\"pixel385\",\"pixel386\",\"pixel387\",\"pixel388\",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+ JsonConvert.SerializeObject(pixels)
+ "]}},\"GlobalParameters\":{}}";
}
private class MLStudioResponseObject
{
public Results results { get; set; }
public class Results
{
public Output1 output1 { get; set; }
}
public class Output1
{
public string type { get; set; }
public Value value { get; set; }
}
public class Value
{
public string[] ColumnNames { get; set; }
public string[] ColumnTypes { get; set; }
public string[][] Values { get; set; }
}
}
}
public interface IDigitRecognizer
{
Task<Prediction> PredictAsync(byte[] image);
Task<Prediction> PredictAsync(Image<Rgba32> image);
}
public class Prediction
{
public int Tag { get; set; }
public double Probability { get; set; }
public override string ToString() => JsonConvert.SerializeObject(this);
}
}
Raw
Preprocessor.cs
using SixLabors.ImageSharp;
using SixLabors.ImageSharp.Formats.Jpeg;
using SixLabors.ImageSharp.PixelFormats;
using SixLabors.ImageSharp.Processing;
using SixLabors.Primitives;
using System;
using System.IO;
namespace ImagePreprocessingService
{
public class Preprocessor
{
private readonly Rgba32 _backgroundColor = Rgba32.White;
private readonly Rgba32 _foregroundColor = Rgba32.Black;
public Preprocessor() { }
public Preprocessor(Rgba32 backgroundColor, Rgba32 foregroundColor)
{
_backgroundColor = backgroundColor;
_foregroundColor = foregroundColor;
}
/// <summary>
/// Preprocess camera images for MNIST-based neural networks.
/// </summary>
/// <param name="image">Source image in a byte array.</param>
/// <returns>Preprocessed image in a byte array.</returns>
public byte[] Preprocess(byte[] input)
{
Image<Rgba32> image = Image.Load(input);
image = Preprocess(image);
var stream = new MemoryStream();
image.SaveAsPng(stream);
return stream.ToArray();
}
/// <summary>
/// Preprocess camera images for MNIST-based neural networks.
/// </summary>
/// <param name="image">Source image in a file format agnostic structure in memory as a series of Rgba32 pixels.</param>
/// <returns>Preprocessed image in a file format agnostic structure in memory as a series of Rgba32 pixels.</returns>
public Image<Rgba32> Preprocess(Image<Rgba32> image)
{
// Step 1: Apply a grayscale filter
image.Mutate(i => i.Grayscale());
// Step 2: Apply a white vignette on the corners to remove shadow marks
image.Mutate(i => i.Vignette(Rgba32.White));
// Step 3: Separate foreground and background with a threshold and set the correct colors
image.Mutate(i => i.BinaryThreshold(0.6f, _backgroundColor, _foregroundColor));
// Step 4: Crop to bounding box
var boundingBox = FindBoundingBox(image);
image.Mutate(i => i.Crop(boundingBox));
// Step 5: Make the image a square
var maxWidthHeight = Math.Max(image.Width, image.Height);
image.Mutate(i => i.Pad(maxWidthHeight, maxWidthHeight).BackgroundColor(_backgroundColor));
// Step 6: Downscale to 20x20
image.Mutate(i => i.Resize(20, 20));
// Step 7: Add 4 pixel margin
image.Mutate(i => i.Pad(28, 28).BackgroundColor(_backgroundColor));
return image;
}
private Rectangle FindBoundingBox(Image<Rgba32> image)
{
// ➡
var topLeftX = F(0, 0, x => x < image.Width, y => y < image.Height, true, 1);
// ⬇
var topLeftY = F(0, 0, y => y < image.Height, x => x < image.Width, false, 1);
// ⬅
var bottomRightX = F(image.Width - 1, image.Height - 1, x => x >= 0, y => y >= 0, true, -1);
// ⬆
var bottomRightY = F(image.Height - 1, image.Width - 1, y => y >= 0, x => x >= 0, false, -1);
return new Rectangle(topLeftX, topLeftY, bottomRightX - topLeftX, bottomRightY - topLeftY);
int F(int coordinateI, int coordinateJ, Func<int, bool> comparerI, Func<int, bool> comparerJ, bool horizontal, int increment)
{
var limit = 0;
for (int i = coordinateI; comparerI(i); i += increment)
{
bool foundForegroundPixel = false;
for (int j = coordinateJ; comparerJ(j); j += increment)
{
var pixel = horizontal ? image[i, j] : image[j, i];
if (pixel != _backgroundColor)
{
foundForegroundPixel = true;
break;
}
}
if (foundForegroundPixel) break;
limit = i;
}
return limit;
}
}
public static int[] ConvertImageToArray(Image<Rgba32> image)
{
var pixels = new int[28*28];
var i = 0;
for (int j = 0; j < image.Height; j++)
{
for (int k = 0; k < image.Width; k++)
{
pixels[i] = 255 - ((image[k, j].R + image[k, j].G + image[k, j].B) / 3);
i++;
}
}
return pixels;
}
public static double[,] ConvertImageToTwoDimensionalArray(Image<Rgba32> image)
{
var pixels = new double[28, 28];
for (int j = 0; j < image.Height; j++)
{
for (int k = 0; k < image.Width; k++)
{
pixels[j, k] = (255 - ((image[k, j].R + image[k, j].G + image[k, j].B) / 3)) / 255;
}
}
return pixels;
}
private static void PrintImageToConsole(Image<Rgba32> image)
{
var pixels = ConvertImageToArray(image);
for (int i = 0; i < 784; i++)
{
Console.Write(pixels[i].ToString("D3"));
if ((i + 1) % 28 == 0) Console.WriteLine();
}
}
}
}
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