diff --git a/src/TensorFlowNET.Models/ObjectDetection/Utils/ConfigUtil.cs b/src/TensorFlowNET.Models/ObjectDetection/Utils/ConfigUtil.cs
index dbb64b0e..a8b3876e 100644
--- a/src/TensorFlowNET.Models/ObjectDetection/Utils/ConfigUtil.cs
+++ b/src/TensorFlowNET.Models/ObjectDetection/Utils/ConfigUtil.cs
@@ -15,5 +15,86 @@ namespace Tensorflow.Models.ObjectDetection.Utils
 
             return pipeline_config;
         }
+
+        public static ImageResizer get_image_resizer_config(DetectionModel model_config)
+        {
+            var meta_architecture = model_config.ModelCase;
+
+            if (meta_architecture == DetectionModel.ModelOneofCase.FasterRcnn)
+                return model_config.FasterRcnn.ImageResizer;
+            else if (meta_architecture == DetectionModel.ModelOneofCase.Ssd)
+                return model_config.Ssd.ImageResizer;
+            
+            throw new Exception($"Unknown model type: {meta_architecture}");
+        }
+
+        public static (int, int) get_spatial_image_size(ImageResizer image_resizer_config)
+        {
+            if (image_resizer_config.ImageResizerOneofCase == ImageResizer.ImageResizerOneofOneofCase.FixedShapeResizer)
+                return (image_resizer_config.FixedShapeResizer.Height, image_resizer_config.FixedShapeResizer.Width);
+            else if (image_resizer_config.ImageResizerOneofCase == ImageResizer.ImageResizerOneofOneofCase.KeepAspectRatioResizer)
+            {
+                if (image_resizer_config.KeepAspectRatioResizer.PadToMaxDimension)
+                    return (image_resizer_config.KeepAspectRatioResizer.MaxDimension, image_resizer_config.KeepAspectRatioResizer.MaxDimension);
+                else
+                    return (-1, -1);
+            }
+            else if (image_resizer_config.ImageResizerOneofCase == ImageResizer.ImageResizerOneofOneofCase.IdentityResizer
+                    || image_resizer_config.ImageResizerOneofCase == ImageResizer.ImageResizerOneofOneofCase.ConditionalShapeResizer)
+            {
+                return (-1, -1);
+            }
+            
+            throw new Exception("Unknown image resizer type.");
+        }
+
+        public static Dictionary<string, object> create_configs_from_pipeline_proto(TrainEvalPipelineConfig pipeline_config)
+        {
+            var configs = new Dictionary<string, object>(StringComparer.OrdinalIgnoreCase);
+
+            configs["model"] = pipeline_config.Model;
+            configs["train_config"] = pipeline_config.TrainConfig;
+            configs["train_input_config"] = pipeline_config.TrainInputReader;
+            configs["eval_config"] = pipeline_config.EvalConfig;
+            configs["eval_input_configs"] = pipeline_config.EvalInputReader;
+            
+            //# Keeps eval_input_config only for backwards compatibility. All clients should
+            //# read eval_input_configs instead.
+            if (pipeline_config.EvalInputReader != null && pipeline_config.EvalInputReader.Count > 0)
+                configs["eval_input_config"] = pipeline_config.EvalInputReader[0];
+
+            if (pipeline_config.GraphRewriter != null)
+                configs["graph_rewriter_config"] = pipeline_config.GraphRewriter;
+
+            return configs;
+        }
+
+        public static GraphRewriter get_graph_rewriter_config_from_file(string graph_rewriter_config_file)
+        {
+            throw new NotImplementedException();
+        }
+
+        public static int get_number_of_classes(DetectionModel model_config)
+        {
+            var meta_architecture = model_config.ModelCase;
+
+            if (meta_architecture == DetectionModel.ModelOneofCase.FasterRcnn)
+                return model_config.FasterRcnn.NumClasses;
+            
+            if (meta_architecture == DetectionModel.ModelOneofCase.Ssd)
+                return model_config.Ssd.NumClasses;
+
+            throw new Exception("Expected the model to be one of 'faster_rcnn' or 'ssd'.");
+        }
+
+        public static Protos.Optimizer.OptimizerOneofCase get_optimizer_type(TrainConfig train_config)
+        {
+            return train_config.Optimizer.OptimizerCase;
+        }
+
+        public static string get_learning_rate_type(Optimizer optimizer_config)
+        {
+            throw new NotImplementedException();
+        }
     }
 }