fix commit

src/Microsoft.ML.CodeGenerator/CodeGenerator/CSharp/AzureCodeGenerator/AzureAttachModelCodeGenerator.cs

@@ -131,7 +131,7 @@ public AzureAttachModelCodeGenerator(Pipeline pipeline, ColumnInferenceResults c
                     Namespace = _nameSpaceValue,
                     ImportLabels = _settings.ClassificationLabel,
                 }.TransformText(),
-                Name = "LabelMapping.cs",
+                Name = "ObjectDetectionLabelMapping.cs",
             };
 
             ReshapeTransformerMap = new CSharpCodeFile()

src/Microsoft.ML.CodeGenerator/CodeGenerator/CSharp/TransformGeneratorFactory.cs

@@ -24,6 +24,9 @@ internal enum SpecialTransformer
         LabelMapping = 4,
         ObjectDetectionLabelMapping = 5, // Tevin: added for OD mappings
         ReshapeTransformer = 6,
+        ObjectDetectionResizeImage = 7,
+        ObjectDetectionExtractPixel = 8,
+        ApplyObjectDetectionModel = 9,
 
     }
     internal static class TransformGeneratorFactory
@@ -103,6 +106,15 @@ internal static ITransformGenerator GetInstance(PipelineNode node)
                     case SpecialTransformer.ObjectDetectionLabelMapping:
                         result = new CustomObjectDetectionLabelMapping(node);
                         break;
+                    case SpecialTransformer.ObjectDetectionExtractPixel:
+                        result = new ObjectDetectionPixelExtract(node);
+                        break;
+                    case SpecialTransformer.ObjectDetectionResizeImage:
+                        result = new ObjectDetectionImageResizing(node);
+                        break;
+                    case SpecialTransformer.ApplyObjectDetectionModel:
+                        result = new ApplyObjectDetectionOnnxModel(node);
+                        break;
                     case SpecialTransformer.ReshapeTransformer:
                         result = new CustomReshapeTransformer(node);
                         break;

src/Microsoft.ML.CodeGenerator/CodeGenerator/CSharp/TransformGenerators.cs

@@ -377,6 +377,17 @@ public override string GenerateTransformer()
         }
     }
 
+    internal class ObjectDetectionImageResizing : TransformGeneratorBase
+    {
+        public ObjectDetectionImageResizing(PipelineNode node) : base(node) { }
+        internal override string MethodName => "ResizeImages";
+
+        public override string GenerateTransformer()
+        {
+            return @"ResizeImages(outputColumnName: ""input"", imageWidth: 800, imageHeight: 600, inputColumnName: ""input"")";
+        }
+    }
+
     internal class PixelExtract : TransformGeneratorBase
     {
         public PixelExtract(PipelineNode node) : base(node) { }
@@ -388,7 +399,18 @@ public override string GenerateTransformer()
         }
     }
 
-    internal class CustomNormalizeMapping : TransformGeneratorBase
+    internal class ObjectDetectionPixelExtract : TransformGeneratorBase
+    {
+        public ObjectDetectionPixelExtract(PipelineNode node) : base(node) { }
+        internal override string MethodName => "ExtractPixels";
+
+        public override string GenerateTransformer()
+        {
+            return @"ExtractPixels(outputColumnName: ""input"", inputColumnName: ""input"")";
+        }
+    }
+
+internal class CustomNormalizeMapping : TransformGeneratorBase
     {
         public CustomNormalizeMapping(PipelineNode node) : base(node) { }
         internal override string MethodName => "NormalizeMapping";
@@ -422,7 +444,7 @@ public CustomObjectDetectionLabelMapping(PipelineNode node) : base(node) { }
 
         public override string GenerateTransformer()
         {
-            return @"CustomMapping<ObjectDetectionLabelMappingInput, ModelOutput>( // added this line not sure what to do.
+            return @"CustomMapping<ObjectDetectionLabelMappingInput, ObjectDetectionLabelMappingOutput>( // added this line not sure what to do.
                                           (input, output) => ObjectDetectionLabelMapping.Mapping(input, output),
                                           contractName: nameof(ObjectDetectionLabelMapping))";
         }
@@ -432,7 +454,7 @@ public override string GenerateTransformer()
     internal class CustomReshapeTransformer : TransformGeneratorBase
     {
         public CustomReshapeTransformer(PipelineNode node) : base(node) { }
-        internal override string MethodName => "ObjectDetectionLabelMapping";
+        internal override string MethodName => "ReshapeTransformer";
 
         public override string GenerateTransformer()
         {
@@ -442,6 +464,18 @@ public override string GenerateTransformer()
         }
     }
 
+    // Tevin: added to have correct ApplyOnnxModel
+    internal class ApplyObjectDetectionOnnxModel : TransformGeneratorBase
+    {
+        public ApplyObjectDetectionOnnxModel(PipelineNode node) : base(node) { }
+        internal override string MethodName => "ApplyOnnxModel";
+
+        public override string GenerateTransformer()
+        {
+            return @"ApplyOnnxModel(modelFile: modelFile, outputColumnNames: new[] { ""boxes"",""labels"", ""scores"" }, inputColumnNames: new[] { ""input"" })";
+        }
+    }
+
     internal class ApplyOnnxModel : TransformGeneratorBase
     {
         public ApplyOnnxModel(PipelineNode node) : base(node) { }

src/Microsoft.ML.CodeGenerator/Templates/Azure/Model/ObjectDetectionOnnxMapping.cs

@@ -62,18 +62,18 @@ public class ObjectDetectionLabelMapping : CustomMappingFactory<ObjectDetectionL
                     "oat Bottom;\r\n\r\n        public string Label;\r\n\r\n        public float Score;\r\n\r\n  " +
                     "      public override string ToString()\r\n        {\r\n            return $\"Top: {t" +
                     "his.Top}, Left: {this.Left}, Right: {this.Right}, Bottom: {this.Bottom}, Label: " +
-                    "{this.Label}, Score: {this.Score}\";\r\n        }\r\n    }\r\n\r\n\r\n    public class Mode" +
-                    "lOutput\r\n    {\r\n        [ColumnName(\"boxes\")]\r\n        public float[] Boxes;\r\n\r\n" +
-                    "        [ColumnName(\"PredictedLabels\")]\r\n        public string[] Labels;\r\n\r\n    " +
-                    "    [ColumnName(\"scores\")]\r\n        public float[] Scores;\r\n\r\n        private Bo" +
-                    "undingBox[] BoundingBoxes\r\n        {\r\n            get\r\n            {\r\n          " +
-                    "      var boundingBoxes = new List<BoundingBox>();\r\n                return bound" +
-                    "ingBoxes.ToArray();\r\n            }\r\n        }\r\n\r\n        public BoundingBox[] Ge" +
-                    "tBoundingBoxes()\r\n        {\r\n            return this.BoundingBoxes;\r\n        }\r\n" +
-                    "\r\n        public override string ToString()\r\n        {\r\n            var sb = new" +
-                    " StringBuilder();\r\n\r\n            foreach (var box in this.BoundingBoxes)\r\n      " +
-                    "      {\r\n                sb.AppendLine(box.ToString());\r\n            }\r\n\r\n      " +
-                    "      return sb.ToString();\r\n        }\r\n    }\r\n}\r\n");
+                    "{this.Label}, Score: {this.Score}\";\r\n        }\r\n    }\r\n\r\n\r\n    public class Obje" +
+                    "ctDetectionLabelMappingOutput\r\n    {\r\n        [ColumnName(\"boxes\")]\r\n        pub" +
+                    "lic float[] Boxes;\r\n\r\n        [ColumnName(\"PredictedLabels\")]\r\n        public st" +
+                    "ring[] Labels;\r\n\r\n        [ColumnName(\"scores\")]\r\n        public float[] Scores;" +
+                    "\r\n\r\n        private BoundingBox[] BoundingBoxes\r\n        {\r\n            get\r\n   " +
+                    "         {\r\n                var boundingBoxes = new List<BoundingBox>();\r\n      " +
+                    "          return boundingBoxes.ToArray();\r\n            }\r\n        }\r\n\r\n        p" +
+                    "ublic BoundingBox[] GetBoundingBoxes()\r\n        {\r\n            return this.Bound" +
+                    "ingBoxes;\r\n        }\r\n\r\n        public override string ToString()\r\n        {\r\n  " +
+                    "          var sb = new StringBuilder();\r\n\r\n            foreach (var box in this." +
+                    "BoundingBoxes)\r\n            {\r\n                sb.AppendLine(box.ToString());\r\n " +
+                    "           }\r\n\r\n            return sb.ToString();\r\n        }\r\n    }\r\n}\r\n");
             return this.GenerationEnvironment.ToString();
         }
 

src/Microsoft.ML.CodeGenerator/Templates/Azure/Model/ObjectDetectionOnnxMapping.tt

@@ -73,7 +73,7 @@ namespace <#= Namespace #>.Model
     }
 
 
-    public class ModelOutput
+    public class ObjectDetectionLabelMappingOutput
     {
         [ColumnName("boxes")]
         public float[] Boxes;

src/Microsoft.ML.CodeGenerator/Templates/Azure/Model/ReshapeTransformer.cs

@@ -39,7 +39,7 @@ public virtual string TransformText()
 namespace Microsoft.ML.ModelBuilder.AutoMLService.RemoteAutoML.ObjectDetectionTransformerHelpers
 {
     [CustomMappingFactoryAttribute(nameof(ReshapeTransformer))]
-    class ReshapeTransformer : CustomMappingFactory<Input, Output>
+    public class ReshapeTransformer : CustomMappingFactory<Input, Output>
     {
         // This is the custom mapping. We now separate it into a method, so that we can use it both in training and in loading.
         public static void Mapping(Input input, Output output)

src/Microsoft.ML.CodeGenerator/Templates/Azure/Model/ReshapeTransformer.tt

@@ -17,7 +17,7 @@ using Microsoft.ML.Transforms;
 namespace Microsoft.ML.ModelBuilder.AutoMLService.RemoteAutoML.ObjectDetectionTransformerHelpers
 {
     [CustomMappingFactoryAttribute(nameof(ReshapeTransformer))]
-    class ReshapeTransformer : CustomMappingFactory<Input, Output>
+    public class ReshapeTransformer : CustomMappingFactory<Input, Output>
     {
         // This is the custom mapping. We now separate it into a method, so that we can use it both in training and in loading.
         public static void Mapping(Input input, Output output)

src/Microsoft.ML.CodeGenerator/Templates/Console/ModelOutputClass.cs

@@ -46,9 +46,28 @@ public virtual string TransformText()
  }
 if("ObjectDetection".Equals(TaskType)){ 
             this.Write("        [ColumnName(\"boxes\")]\r\n        public float[] Boxes { get; set; }\r\n\r\n    " +
-                    "    [ColumnName(\"PredictedLabels)]\r\n        public string[] Labels { get; set; }" +
-                    "\r\n\r\n        [ColumnName(\"scores\")]\r\n        public float[] Scores { get; set; }\r" +
-                    "\n");
+                    "    [ColumnName(\"PredictedLabels\")]\r\n        public string[] Labels { get; set; " +
+                    "}\r\n\r\n        [ColumnName(\"scores\")]\r\n        public float[] Scores { get; set; }" +
+                    "\r\n\r\n        private BoundingBox[] BoundingBoxes\r\n        {\r\n            get\r\n   " +
+                    "         {\r\n                var boundingBoxes = new List<BoundingBox>();\r\n\r\n    " +
+                    "            boundingBoxes = Enumerable.Range(0, this.Labels.Length)\r\n           " +
+                    "               .Select((index) =>\r\n                          {\r\n                " +
+                    "              var boxes = this.Boxes;\r\n                              var scores " +
+                    "= this.Scores;\r\n                              var labels = this.Labels;\r\n\r\n     " +
+                    "                         return new BoundingBox()\r\n                             " +
+                    " {\r\n                                  Left = boxes[index * 4],\r\n                " +
+                    "                  Top = boxes[(index * 4) + 1],\r\n                               " +
+                    "   Right = boxes[(index * 4) + 2],\r\n                                  Bottom = b" +
+                    "oxes[(index * 4) + 3],\r\n                                  Score = scores[index]," +
+                    "\r\n                                  Label = labels[index].ToString(),\r\n         " +
+                    "                     };\r\n                          }).ToList();\r\n               " +
+                    " return boundingBoxes.ToArray();\r\n            }\r\n        }\r\n    }\r\n\r\n    public " +
+                    "class BoundingBox\r\n    {\r\n        public float Top;\r\n\r\n        public float Left" +
+                    ";\r\n\r\n        public float Right;\r\n\r\n        public float Bottom;\r\n\r\n        publ" +
+                    "ic string Label;\r\n\r\n        public float Score;\r\n\r\n        public override strin" +
+                    "g ToString()\r\n        {\r\n            return $\"Top: {this.Top}, Left: {this.Left}" +
+                    ", Right: {this.Right}, Bottom: {this.Bottom}, Label: {this.Label}, Score: {this." +
+                    "Score}\";\r\n        }\r\n");
 } else if("MulticlassClassification".Equals(TaskType)){ 
             this.Write("        public float[] Score { get; set; }\r\n");
 }else{ 

src/Microsoft.ML.CodeGenerator/Templates/Console/ModelOutputClass.tt

@@ -31,11 +31,58 @@ namespace  <#= Namespace #>.Model
         [ColumnName("boxes")]
         public float[] Boxes { get; set; }
 
-        [ColumnName("PredictedLabels)]
+        [ColumnName("PredictedLabels")]
         public string[] Labels { get; set; }
 
         [ColumnName("scores")]
         public float[] Scores { get; set; }
+
+        private BoundingBox[] BoundingBoxes
+        {
+            get
+            {
+                var boundingBoxes = new List<BoundingBox>();
+
+                boundingBoxes = Enumerable.Range(0, this.Labels.Length)
+                          .Select((index) =>
+                          {
+                              var boxes = this.Boxes;
+                              var scores = this.Scores;
+                              var labels = this.Labels;
+
+                              return new BoundingBox()
+                              {
+                                  Left = boxes[index * 4],
+                                  Top = boxes[(index * 4) + 1],
+                                  Right = boxes[(index * 4) + 2],
+                                  Bottom = boxes[(index * 4) + 3],
+                                  Score = scores[index],
+                                  Label = labels[index].ToString(),
+                              };
+                          }).ToList();
+                return boundingBoxes.ToArray();
+            }
+        }
+    }
+
+    public class BoundingBox
+    {
+        public float Top;
+
+        public float Left;
+
+        public float Right;
+
+        public float Bottom;
+
+        public string Label;
+
+        public float Score;
+
+        public override string ToString()
+        {
+            return $"Top: {this.Top}, Left: {this.Left}, Right: {this.Right}, Bottom: {this.Bottom}, Label: {this.Label}, Score: {this.Score}";
+        }
 <#} else if("MulticlassClassification".Equals(TaskType)){ #>
         public float[] Score { get; set; }
 <#}else{ #>

src/Microsoft.ML.CodeGenerator/Templates/Console/ModelProject.cs

@@ -53,7 +53,8 @@ public virtual string TransformText()
  if (IncludeOnnxModel){ 
             this.Write("    <PackageReference Include=\"Microsoft.ML.OnnxTransformer\" Version=\"");
             this.Write(this.ToStringHelper.ToStringWithCulture(StablePackageVersion));
-            this.Write("\" />\r\n");
+            this.Write("\" />\r\n    <PackageReference Include=\"Microsoft.ML.OnnxRuntime\" Version=\"1.2.0\" />" +
+                    "\r\n");
 }
  if (IncludeImageClassificationPackage){ 
             this.Write("    <PackageReference Include=\"Microsoft.ML.Vision\" Version=\"");

src/Microsoft.ML.CodeGenerator/Templates/Console/ModelProject.tt

@@ -24,6 +24,7 @@
 <#}#>
 <# if (IncludeOnnxModel){ #>
     <PackageReference Include="Microsoft.ML.OnnxTransformer" Version="<#= StablePackageVersion #>" />
+    <PackageReference Include="Microsoft.ML.OnnxRuntime" Version="1.2.0" />
 <#}#>
 <# if (IncludeImageClassificationPackage){ #>
     <PackageReference Include="Microsoft.ML.Vision" Version="<#= StablePackageVersion #>" />

src/Microsoft.ML.CodeGenerator/Templates/Console/PredictProject.cs

@@ -54,7 +54,8 @@ public virtual string TransformText()
  if (IncludeOnnxPackage){ 
             this.Write("    <PackageReference Include=\"Microsoft.ML.OnnxTransformer\" Version=\"");
             this.Write(this.ToStringHelper.ToStringWithCulture(StablePackageVersion));
-            this.Write("\" />\r\n");
+            this.Write("\" />\r\n    <PackageReference Include=\"Microsoft.ML.OnnxRuntime\" Version=\"1.2.0\" />" +
+                    "\r\n");
 }
  if (IncludeResNet18Package){ 
             this.Write("    <PackageReference Include=\"Microsoft.ML.DnnImageFeaturizer.ResNet18\" Version=" +

src/Microsoft.ML.CodeGenerator/Templates/Console/PredictProject.tt

@@ -26,6 +26,7 @@
 <#}#>
 <# if (IncludeOnnxPackage){ #>
     <PackageReference Include="Microsoft.ML.OnnxTransformer" Version="<#= StablePackageVersion #>" />
+    <PackageReference Include="Microsoft.ML.OnnxRuntime" Version="1.2.0" />
 <#}#>
 <# if (IncludeResNet18Package){ #>
     <PackageReference Include="Microsoft.ML.DnnImageFeaturizer.ResNet18" Version="0.15.1" />

test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.AzureObjectDetectionCodeGeneratorTest.CodeGenTest.ConsoleApp.csproj.approved.txt

@@ -7,6 +7,7 @@
   <ItemGroup>
     <PackageReference Include="Microsoft.ML" Version="stableversion" />
     <PackageReference Include="Microsoft.ML.OnnxTransformer" Version="stableversion" />
+    <PackageReference Include="Microsoft.ML.OnnxRuntime" Version="1.2.0" />
   </ItemGroup>
   <ItemGroup>
     <ProjectReference Include="..\CodeGenTest.Model\CodeGenTest.Model.csproj" />

test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.AzureObjectDetectionCodeGeneratorTest.CodeGenTest.Model.csproj.approved.txt

@@ -6,6 +6,7 @@
   <ItemGroup>
     <PackageReference Include="Microsoft.ML" Version="stableversion" />
     <PackageReference Include="Microsoft.ML.OnnxTransformer" Version="stableversion" />
+    <PackageReference Include="Microsoft.ML.OnnxRuntime" Version="1.2.0" />
   </ItemGroup>
 
   <ItemGroup>

test/Microsoft.ML.CodeGenerator.Tests/ApprovalTests/ConsoleCodeGeneratorTests.AzureObjectDetectionCodeGeneratorTest.ModelBuilder.cs.approved.txt

@@ -45,14 +45,14 @@ namespace CodeGenTest.ConsoleApp
             // Data process configuration with pipeline data transformations to:
             // 1. Score using provided onnx model
             // 2. Map scores to labels to make model output easier to understand and use
-            var pipeline = mlContext.Transforms.LoadImages("/path/to/onnxModel", null, "ImagePath")
-                                      .Append(mlContext.Transforms.ResizeImages("ImageSource_featurized", 224, 224, "ImageSource_featurized"))
-                                      .Append(mlContext.Transforms.ExtractPixels("ImageSource_featurized", "ImageSource_featurized"))
+            var pipeline = mlContext.Transforms.LoadImages("input", null, "ImagePath")
+                                      .Append(mlContext.Transforms.ResizeImages(outputColumnName: "input", imageWidth: 800, imageHeight: 600, inputColumnName: "input"))
+                                      .Append(mlContext.Transforms.ExtractPixels(outputColumnName: "input", inputColumnName: "input"))
                                       .Append(mlContext.Transforms.CustomMapping<Input, Output>(
                                           (input, output) => ReshapeTransformer.Mapping(input, output),
                                           contractName: nameof(ReshapeTransformer)))
-                                      .Append(mlContext.Transforms.ApplyOnnxModel(modelFile: ONNX_MODEL))
-                                      .Append(mlContext.Transforms.CustomMapping<ObjectDetectionLabelMappingInput, ModelOutput>( // added this line not sure what to do.
+                                      .Append(mlContext.Transforms.ApplyOnnxModel(modelFile: modelFile, outputColumnNames: new[] { "boxes", "labels", "scores" }, inputColumnNames: new[] { "input" }))
+                                      .Append(mlContext.Transforms.CustomMapping<ObjectDetectionLabelMappingInput, ObjectDetectionLabelMappingOutput>( // added this line not sure what to do.
                                           (input, output) => ObjectDetectionLabelMapping.Mapping(input, output),
                                           contractName: nameof(ObjectDetectionLabelMapping)));
             return pipeline;