Update image library

Author: saddam213

OnnxStack.StableDiffusion/Helpers/ImageHelpers.cs

@@ -117,16 +117,19 @@ public static DenseTensor<float> TensorFromImage(string filename, int width, int
             {
                 Resize(image, width, height);
                 var imageArray = new DenseTensor<float>(new[] { 1, 3, width, height });
-                for (int x = 0; x < width; x++)
+                image.ProcessPixelRows(img =>
                 {
-                    for (int y = 0; y < height; y++)
+                    for (int x = 0; x < width; x++)
                     {
-                        var pixelSpan = image.GetPixelRowSpan(y);
-                        imageArray[0, 0, y, x] = (pixelSpan[x].R / 255.0f) * 2.0f - 1.0f;
-                        imageArray[0, 1, y, x] = (pixelSpan[x].G / 255.0f) * 2.0f - 1.0f;
-                        imageArray[0, 2, y, x] = (pixelSpan[x].B / 255.0f) * 2.0f - 1.0f;
+                        for (int y = 0; y < height; y++)
+                        {
+                            var pixelSpan = img.GetRowSpan(y);
+                            imageArray[0, 0, y, x] = (pixelSpan[x].R / 255.0f) * 2.0f - 1.0f;
+                            imageArray[0, 1, y, x] = (pixelSpan[x].G / 255.0f) * 2.0f - 1.0f;
+                            imageArray[0, 2, y, x] = (pixelSpan[x].B / 255.0f) * 2.0f - 1.0f;
+                        }
                     }
-                }
+                });
                 return imageArray;
             }
         }

OnnxStack.StableDiffusion/OnnxStack.StableDiffusion.csproj

@@ -51,7 +51,7 @@
   <ItemGroup>
     <PackageReference Include="MathNet.Numerics" Version="5.0.0" />
     <PackageReference Include="NumSharp" Version="0.30.0" />
-    <PackageReference Include="SixLabors.ImageSharp" Version="1.0.3" />
+    <PackageReference Include="SixLabors.ImageSharp" Version="3.0.2" />
   </ItemGroup>
 
   <ItemGroup>

OnnxStack.StableDiffusion/Services/SchedulerService.cs

@@ -210,16 +210,19 @@ private static DenseTensor<float> ClipImageFeatureExtractor(SchedulerOptions opt
                 var input = new DenseTensor<float>(new[] { 1, 3, 224, 224 });
                 var mean = new[] { 0.485f, 0.456f, 0.406f };
                 var stddev = new[] { 0.229f, 0.224f, 0.225f };
-                for (int y = 0; y < image.Height; y++)
+                image.ProcessPixelRows(img =>
                 {
-                    var pixelSpan = image.GetPixelRowSpan(y);
-                    for (int x = 0; x < image.Width; x++)
+                    for (int y = 0; y < image.Height; y++)
                     {
-                        input[0, 0, y, x] = (pixelSpan[x].R / 255f - mean[0]) / stddev[0];
-                        input[0, 1, y, x] = (pixelSpan[x].G / 255f - mean[1]) / stddev[1];
-                        input[0, 2, y, x] = (pixelSpan[x].B / 255f - mean[2]) / stddev[2];
+                        var pixelSpan = img.GetRowSpan(y);
+                        for (int x = 0; x < image.Width; x++)
+                        {
+                            input[0, 0, y, x] = (pixelSpan[x].R / 255f - mean[0]) / stddev[0];
+                            input[0, 1, y, x] = (pixelSpan[x].G / 255f - mean[1]) / stddev[1];
+                            input[0, 2, y, x] = (pixelSpan[x].B / 255f - mean[2]) / stddev[2];
+                        }
                     }
-                }
+                });
                 return input;
             }
         }