diff --git a/OnnxStack.Core/Extensions/OrtValueExtensions.cs b/OnnxStack.Core/Extensions/OrtValueExtensions.cs
index 95c4fc9..138efc5 100644
--- a/OnnxStack.Core/Extensions/OrtValueExtensions.cs
+++ b/OnnxStack.Core/Extensions/OrtValueExtensions.cs
@@ -84,6 +84,18 @@ public static OrtValue ToOrtValue(this DenseTensor<bool> tensor, OnnxNamedMetada
         }
 
 
+        /// <summary>
+        /// Converts DenseTensor<bool> to OrtValue.
+        /// </summary>
+        /// <param name="tensor">The tensor.</param>
+        /// <param name="metadata">The metadata.</param>
+        /// <returns></returns>
+        public static OrtValue ToOrtValue(this DenseTensor<byte> tensor, OnnxNamedMetadata metadata)
+        {
+            return OrtValue.CreateTensorValueFromMemory(OrtMemoryInfo.DefaultInstance, tensor.Buffer, tensor.Dimensions.ToLong());
+        }
+
+
         /// <summary>
         /// Creates and allocates the output tensors buffer.
         /// </summary>
diff --git a/OnnxStack.Core/Image/Extensions.cs b/OnnxStack.Core/Image/Extensions.cs
index ef8fa61..0afcac7 100644
--- a/OnnxStack.Core/Image/Extensions.cs
+++ b/OnnxStack.Core/Image/Extensions.cs
@@ -88,13 +88,13 @@ private static DenseTensor<float> SplitImageTile(DenseTensor<float> source, int
             var splitTensor = new DenseTensor<float>(new[] { 1, channels, height, width });
             Parallel.For(0, channels, (c) =>
             {
-                Parallel.For(0, height, (i) =>
+                for (int i = 0; i < height; i++)
                 {
-                    Parallel.For(0, width, (j) =>
+                    for (int j = 0; j < width; j++)
                     {
                         splitTensor[0, c, i, j] = source[0, c, startRow + i, startCol + j];
-                    });
-                });
+                    }
+                }
             });
             return splitTensor;
         }
@@ -135,9 +135,9 @@ private static void JoinImageTile(DenseTensor<float> destination, DenseTensor<fl
             int channels = tile.Dimensions[1];
             Parallel.For(0, channels, (c) =>
             {
-                Parallel.For(0, height, (i) =>
+                for (int i = 0; i < height; i++)
                 {
-                    Parallel.For(0, width, (j) =>
+                    for (int j = 0; j < width; j++)
                     {
                         var value = tile[0, c, i, j];
                         var existing = destination[0, c, startRow + i, startCol + j];
@@ -147,8 +147,8 @@ private static void JoinImageTile(DenseTensor<float> destination, DenseTensor<fl
                             value = (existing + value) / 2f;
                         }
                         destination[0, c, startRow + i, startCol + j] = value;
-                    });
-                });
+                    }
+                }
             });
         }
     }
diff --git a/OnnxStack.Core/Model/OnnxInferenceParameters.cs b/OnnxStack.Core/Model/OnnxInferenceParameters.cs
index fbdb738..e065899 100644
--- a/OnnxStack.Core/Model/OnnxInferenceParameters.cs
+++ b/OnnxStack.Core/Model/OnnxInferenceParameters.cs
@@ -112,6 +112,17 @@ public void AddInputTensor(DenseTensor<bool> value)
         }
 
 
+        /// <summary>
+        /// Adds the input tensor.
+        /// </summary>
+        /// <param name="value">The value.</param>
+        public void AddInputTensor(DenseTensor<byte> value)
+        {
+            var metaData = GetNextInputMetadata();
+            _inputs.Add(metaData, value.ToOrtValue(metaData));
+        }
+
+
         /// <summary>
         /// Adds an output parameter with known output size.
         /// </summary>