add wrapper

Author: LittleLittleCloud

src/Microsoft.ML.AutoML/CodeGen/estimator-schema.json

@@ -72,7 +72,8 @@
               "Naive",
               "ForecastBySsa",
               "TextClassifcation",
-              "SentenceSimilarity"
+              "SentenceSimilarity",
+              "ObjectDetection"
             ]
           },
           "nugetDependencies": {
@@ -187,7 +188,15 @@
                     "confidenceLevel",
                     "variableHorizon",
                     "modelFactory",
-                    "sentence1ColumnName"
+                    "sentence1ColumnName",
+                    "boundingBoxColumnName",
+                    "imageColumnName",
+                    "maxEpoch",
+                    "iOUThreshold",
+                    "scoreThreshold",
+                    "steps",
+                    "initLearningRate",
+                    "weightDecay"
                   ]
                 },
                 "argumentType": {

src/Microsoft.ML.AutoML/CodeGen/object_detection_search_space.json

@@ -0,0 +1,46 @@
+{
+  "$schema": "./search-space-schema.json#",
+  "name": "object_detection_option",
+  "search_space": [
+    {
+      "name": "LabelColumnName",
+      "type": "string",
+      "default": "Label"
+    },
+    {
+      "name": "PredictedLabelColumnName",
+      "type": "string",
+      "default": "PredictedLabel"
+    },
+    {
+      "name": "BoundingBoxColumnName",
+      "type": "string",
+      "default": "BoundingBox"
+    },
+    {
+      "name": "ImageColumnName",
+      "type": "string",
+      "default": "Image"
+    },
+    {
+      "name": "ScoreColumnName",
+      "type": "string",
+      "default": "Score"
+    },
+    {
+      "name": "MaxEpoch",
+      "type": "integer",
+      "default": 10
+    },
+    {
+      "name": "InitLearningRate",
+      "type": "float",
+      "default": 1.0
+    },
+    {
+      "name": "WeightDecay",
+      "type": "float",
+      "default": 0.0
+    }
+  ]
+}

src/Microsoft.ML.AutoML/CodeGen/search-space-schema.json

@@ -145,7 +145,8 @@
         "matrix_factorization_option",
         "dnn_featurizer_image_option",
         "text_classification_option",
-        "sentence_similarity_option"
+        "sentence_similarity_option",
+        "object_detection_option"
       ]
     },
     "option_name": {
@@ -198,7 +199,16 @@
         "Epoch",
         "Architecture",
         "AddKeyValueAnnotationsAsText",
-        "Arch"
+        "Arch",
+        "PredictedLabelColumnName",
+        "BoundingBoxColumnName",
+        "ImageColumnName",
+        "IOUThreshold",
+        "ScoreThreshold",
+        "Steps",
+        "MaxEpoch",
+        "InitLearningRate",
+        "WeightDecay"
       ]
     },
     "option_type": {

src/Microsoft.ML.AutoML/CodeGen/trainer-estimators.json

@@ -525,6 +525,13 @@
       "usingStatements": [ "Microsoft.ML", "Microsoft.ML.Trainers", "Microsoft.ML.TorchSharp" ],
       "searchOption": "sentence_similarity_option"
     },
+    {
+      "functionName": "ObjectDetection",
+      "estimatorTypes": [ "MultiClassification" ],
+      "nugetDependencies": [ "Microsoft.ML", "Microsoft.ML.TorchSharp" ],
+      "usingStatements": [ "Microsoft.ML", "Microsoft.ML.Trainers", "Microsoft.ML.TorchSharp" ],
+      "searchOption": "object_detection_option"
+    },
     {
       "functionName": "ForecastBySsa",
       "estimatorTypes": [ "Forecasting" ],

src/Microsoft.ML.AutoML/SweepableEstimator/Estimators/ObjectDetection.cs

@@ -0,0 +1,32 @@
+// Licensed to the .NET Foundation under one or more agreements.
+// The .NET Foundation licenses this file to you under the MIT license.
+// See the LICENSE file in the project root for more information.
+
+using System;
+using System.Collections.Generic;
+using System.Text;
+using Microsoft.ML.TorchSharp;
+using Microsoft.ML.TorchSharp.AutoFormerV2;
+
+namespace Microsoft.ML.AutoML.CodeGen
+{
+    internal partial class ObjectDetectionMulti
+    {
+        public override IEstimator<ITransformer> BuildFromOption(MLContext context, ObjectDetectionOption param)
+        {
+            var option = new ObjectDetectionTrainer.Options
+            {
+                LabelColumnName = param.LabelColumnName,
+                PredictedLabelColumnName = param.PredictedLabelColumnName,
+                BoundingBoxColumnName = param.BoundingBoxColumnName,
+                ImageColumnName = param.ImageColumnName,
+                ScoreColumnName = param.ScoreColumnName,
+                MaxEpoch = param.MaxEpoch,
+                InitLearningRate = param.InitLearningRate,
+                WeightDecay = param.WeightDecay,
+            };
+
+            return context.MulticlassClassification.Trainers.ObjectDetection(option);
+        }
+    }
+}