TensorFlow Featurizer sample updated InceptionV3 (dotnet#624)

Author: CESARDELATORRE

samples/csharp/getting-started/DeepLearning_TensorFlowEstimator/ImageClassification.Predict/ImageClassification.Predict.csproj

@@ -6,6 +6,12 @@
     <LangVersion>7.2</LangVersion>
   </PropertyGroup>
 
+  <ItemGroup>
+    <Compile Remove="assets\outputs\**" />
+    <EmbeddedResource Remove="assets\outputs\**" />
+    <None Remove="assets\outputs\**" />
+  </ItemGroup>
+
   <ItemGroup>
     <Compile Include="..\ImageClassification.Train\ImageData\ImagePrediction.cs" Link="ImageData\ImagePrediction.cs" />
     <Compile Include="..\ImageClassification.Train\Model\ConsoleHelpers.cs" Link="Model\ConsoleHelpers.cs" />
@@ -18,8 +24,4 @@
     <PackageReference Include="Microsoft.ML.TensorFlow" Version="$(MicrosoftMLVersion)" />
   </ItemGroup>
 
-  <ItemGroup>
-    <Folder Include="assets\outputs\" />
-  </ItemGroup>
-
 </Project>

samples/csharp/getting-started/DeepLearning_TensorFlowEstimator/ImageClassification.Predict/ImageData/ImageData.cs

@@ -0,0 +1,18 @@
+using Microsoft.ML.Data;
+using System;
+using System.Collections.Generic;
+using System.IO;
+using System.Linq;
+
+namespace ImageClassification.DataModels
+{
+    public class ImageData
+    {
+        [LoadColumn(0)]
+        public string ImagePath;
+
+        [LoadColumn(1)]
+        public string Label;
+    }
+
+}

samples/csharp/getting-started/DeepLearning_TensorFlowEstimator/ImageClassification.Predict/ImageData/ImageDataForScoring.cs

@@ -4,19 +4,19 @@
 using System.IO;
 using Microsoft.ML;
 using static ImageClassification.Model.ConsoleHelpers;
+using System.Collections.Generic;
+using Microsoft.ML.Data;
 
 namespace ImageClassification.Model
 {
     public class ModelScorer
     {
-        private readonly string dataLocation;
         private readonly string imagesFolder;
         private readonly string modelLocation;
         private readonly MLContext mlContext;
 
-        public ModelScorer(string dataLocation, string imagesFolder, string modelLocation)
+        public ModelScorer(string imagesFolder, string modelLocation)
         {
-            this.dataLocation = dataLocation;
             this.imagesFolder = imagesFolder;
             this.modelLocation = modelLocation;
             mlContext = new MLContext(seed: 1);
@@ -25,26 +25,84 @@ public ModelScorer(string dataLocation, string imagesFolder, string modelLocatio
         public void ClassifyImages()
         {
             ConsoleWriteHeader("Loading model");
+            Console.WriteLine("");
             Console.WriteLine($"Model loaded: {modelLocation}");
 
             // Load the model
             ITransformer loadedModel = mlContext.Model.Load(modelLocation,out var modelInputSchema);
 
-            // Make prediction function (input = ImageNetData, output = ImageNetPrediction)
-            var predictor = mlContext.Model.CreatePredictionEngine<ImageDataForScoring, ImagePrediction>(loadedModel);
-            // Read csv file into List<ImageNetData>
-            var imageListToPredict = ImageDataForScoring.ReadFromCsv(dataLocation, imagesFolder).ToList();
-
-            ConsoleWriteHeader("Making classifications");
-            // There is a bug (https://github.com/dotnet/machinelearning/issues/1138), 
-            // that always buffers the response from the predictor
-            // so we have to make a copy-by-value op everytime we get a response
-            // from the predictor
-            imageListToPredict
-                .Select(td => new { td, pred = predictor.Predict(td) })
-                .Select(pr => (pr.td.ImageFileName, pr.pred.PredictedLabelValue, pr.pred.Score))
-                .ToList()
-                .ForEach(pr => ConsoleWriteImagePrediction(pr.ImageFileName, pr.PredictedLabelValue, pr.Score.Max()));
+            // Make prediction engine (input = ImageDataForScoring, output = ImagePrediction)
+            var predictionEngine = mlContext.Model.CreatePredictionEngine<ImageData, ImagePrediction>(loadedModel);
+
+            IEnumerable<ImageData> imagesToPredict = LoadImagesFromDirectory(imagesFolder, true);
+
+            ConsoleWriteHeader("Predicting classifications...");
+
+            //Predict the first image in the folder
+            //
+            ImageData imageToPredict = new ImageData
+            {
+                ImagePath = imagesToPredict.First().ImagePath
+            };
+
+            var prediction = predictionEngine.Predict(imageToPredict);
+
+            Console.WriteLine("");
+            Console.WriteLine($"ImageFile : [{Path.GetFileName(imageToPredict.ImagePath)}], " +
+                              $"Scores : [{string.Join(",", prediction.Score)}], " +
+                              $"Predicted Label : {prediction.PredictedLabelValue}");
+                      
+            //////
+
+            //Predict all images in the folder
+            //
+            Console.WriteLine("");
+            Console.WriteLine("Predicting several images...");
+
+            foreach (ImageData currentImageToPredict in imagesToPredict)
+            {
+                var currentPrediction = predictionEngine.Predict(currentImageToPredict);
+                Console.WriteLine("");
+                Console.WriteLine($"ImageFile : [{Path.GetFileName(currentImageToPredict.ImagePath)}], " +
+                                  $"Scores : [{string.Join(",", currentPrediction.Score)}], " +
+                                  $"Predicted Label : {currentPrediction.PredictedLabelValue}");
+            }
+            //////
+
+        }
+
+        public static IEnumerable<ImageData> LoadImagesFromDirectory(string folder, bool useFolderNameasLabel = true)
+        {
+            var files = Directory.GetFiles(folder, "*",
+                searchOption: SearchOption.AllDirectories);
+
+            foreach (var file in files)
+            {
+                if ((Path.GetExtension(file) != ".jpg") && (Path.GetExtension(file) != ".png"))
+                    continue;
+
+                var label = Path.GetFileName(file);
+                if (useFolderNameasLabel)
+                    label = Directory.GetParent(file).Name;
+                else
+                {
+                    for (int index = 0; index < label.Length; index++)
+                    {
+                        if (!char.IsLetter(label[index]))
+                        {
+                            label = label.Substring(0, index);
+                            break;
+                        }
+                    }
+                }
+
+                yield return new ImageData()
+                {
+                    ImagePath = file,
+                    Label = label
+                };
+
+            }
         }
     }
 }

samples/csharp/getting-started/DeepLearning_TensorFlowEstimator/ImageClassification.Predict/Model/ModelScorer.cs

@@ -13,13 +13,13 @@ static void Main(string[] args)
             string assetsRelativePath = @"../../../assets";
             string assetsPath = GetAbsolutePath(assetsRelativePath);
 
-            var tagsTsv = Path.Combine(assetsPath, "inputs", "data", "images_list.tsv");
-            var imagesFolder = Path.Combine(assetsPath, "inputs", "data");
-            var imageClassifierZip = Path.Combine(assetsPath, "inputs", "imageClassifier.zip");
+            
+            var imagesFolder = Path.Combine(assetsPath, "inputs", "images-for-predictions");
+            var imageClassifierZip = Path.Combine(assetsPath, "inputs", "MLNETModel", "imageClassifier.zip");
 
             try
             {
-                var modelScorer = new ModelScorer(tagsTsv, imagesFolder, imageClassifierZip);
+                var modelScorer = new ModelScorer(imagesFolder, imageClassifierZip);
                 modelScorer.ClassifyImages();
             }
             catch (Exception ex)

samples/csharp/getting-started/DeepLearning_TensorFlowEstimator/ImageClassification.Predict/Program.cs

@@ -8,13 +8,16 @@
   </PropertyGroup>
 
   <ItemGroup>
+    <Compile Include="..\..\..\common\Compress.cs" Link="Common\Compress.cs" />
     <Compile Include="..\..\..\common\ConsoleHelper.cs" Link="Common\ConsoleHelper.cs" />
+    <Compile Include="..\..\..\common\Web.cs" Link="Common\Web.cs" />
   </ItemGroup>
 
   <ItemGroup>
     <PackageReference Include="Microsoft.ML" Version="$(MicrosoftMLVersion)" />
     <PackageReference Include="Microsoft.ML.ImageAnalytics" Version="$(MicrosoftMLVersion)" />
     <PackageReference Include="Microsoft.ML.TensorFlow" Version="$(MicrosoftMLVersion)" />
+    <PackageReference Include="SharpZipLib" Version="1.2.0" />
   </ItemGroup>
 
   <ItemGroup>

samples/csharp/getting-started/DeepLearning_TensorFlowEstimator/ImageClassification.Predict/assets/inputs/imageClassifier.zip renamed to samples/csharp/getting-started/DeepLearning_TensorFlowEstimator/ImageClassification.Predict/assets/inputs/MLNETModel/imageClassifier.zip

@@ -9,7 +9,7 @@ namespace ImageClassification.DataModels
     public class ImageData
     {
         [LoadColumn(0)]
-        public string ImageFileName;
+        public string ImagePath;
 
         [LoadColumn(1)]
         public string Label;

samples/csharp/getting-started/DeepLearning_TensorFlowEstimator/ImageClassification.Predict/assets/inputs/data/broccoli.png

@@ -0,0 +1,18 @@
+using Microsoft.ML.Data;
+using System;
+using System.Collections.Generic;
+using System.Text;
+
+namespace ImageClassification.DataModels
+{
+    public class ImagePredictionEx
+    {
+        public string ImagePath;
+        public string Label;
+        public string PredictedLabelValue;
+        public float[] Score;
+       
+        //[ColumnName("InceptionV3/Predictions/Reshape")]
+        //public float[] ImageFeatures;  //In Inception v1: "softmax2_pre_activation"
+    }
+}

samples/csharp/getting-started/DeepLearning_TensorFlowEstimator/ImageClassification.Predict/assets/inputs/data/images_list.tsv

@@ -44,7 +44,7 @@ public static void ConsoleWriteException(params string[] lines)
             }
         }
 
-        public static void ConsoleWriteImagePrediction(string ImagePath, string PredictedLabel, float Probability)
+        public static void ConsoleWriteImagePrediction(string ImagePath, string Label, string PredictedLabel, float Probability)
         {
             var defaultForeground = Console.ForegroundColor;
             var labelColor = ConsoleColor.Magenta;
@@ -54,6 +54,10 @@ public static void ConsoleWriteImagePrediction(string ImagePath, string Predicte
             Console.ForegroundColor = labelColor;
             Console.Write($"{Path.GetFileName(ImagePath)}");
             Console.ForegroundColor = defaultForeground;
+            Console.Write(" original labeled as ");
+            Console.ForegroundColor = labelColor;
+            Console.Write(Label);
+            Console.ForegroundColor = defaultForeground;
             Console.Write(" predicted as ");
             Console.ForegroundColor = labelColor;
             Console.Write(PredictedLabel);