Major: API Refactor Part 2

OnnxStack.Console/Examples/ControlNetExample.cs

@@ -32,7 +32,7 @@ public ControlNetExample(StableDiffusionConfig configuration)
         public async Task RunAsync()
         {
             // Load Control Image
-            var controlImage = await InputImage.FromFileAsync("D:\\Repositories\\OnnxStack\\Assets\\Samples\\OpenPose.png");
+            var controlImage = await OnnxImage.FromFileAsync("D:\\Repositories\\OnnxStack\\Assets\\Samples\\OpenPose.png");
 
             // Create ControlNet
             var controlNet = ControlNetModel.Create("D:\\Repositories\\controlnet_onnx\\controlnet\\openpose.onnx");
@@ -54,11 +54,11 @@ public async Task RunAsync()
             var result = await pipeline.RunAsync(promptOptions, controlNet: controlNet, progressCallback: OutputHelpers.ProgressCallback);
 
             // Create Image from Tensor result
-            var image = result.ToImage();
+            var image = new OnnxImage(result);
 
             // Save Image File
             var outputFilename = Path.Combine(_outputDirectory, $"Output.png");
-            await image.SaveAsPngAsync(outputFilename);
+            await image.SaveAsync(outputFilename);
 
             //Unload
             await controlNet.UnloadAsync();

OnnxStack.Console/Examples/ControlNetFeatureExample.cs

@@ -32,7 +32,7 @@ public ControlNetFeatureExample(StableDiffusionConfig configuration)
         public async Task RunAsync()
         {
             // Load Control Image
-            var inputImage = await InputImage.FromFileAsync("D:\\Repositories\\OnnxStack\\Assets\\Samples\\Img2Img_Start.bmp");
+            var inputImage = await OnnxImage.FromFileAsync("D:\\Repositories\\OnnxStack\\Assets\\Samples\\Img2Img_Start.bmp");
 
             // Create Annotation pipeline
             var annotationPipeline = FeatureExtractorPipeline.CreatePipeline("D:\\Repositories\\controlnet_onnx\\annotators\\depth.onnx", true);
@@ -41,7 +41,7 @@ public async Task RunAsync()
             var controlImage = await annotationPipeline.RunAsync(inputImage);
 
             // Save Depth Image (Debug Only)
-            await controlImage.Image.SaveAsPngAsync(Path.Combine(_outputDirectory, $"Depth.png"));
+            await controlImage.SaveAsync(Path.Combine(_outputDirectory, $"Depth.png"));
 
             // Create ControlNet
             var controlNet = ControlNetModel.Create("D:\\Repositories\\controlnet_onnx\\controlnet\\depth.onnx");
@@ -61,11 +61,11 @@ public async Task RunAsync()
             var result = await pipeline.RunAsync(promptOptions, controlNet: controlNet, progressCallback: OutputHelpers.ProgressCallback);
 
             // Create Image from Tensor result
-            var image = result.ToImage();
+            var image = new OnnxImage(result);
 
             // Save Image File
             var outputFilename = Path.Combine(_outputDirectory, $"Output.png");
-            await image.SaveAsPngAsync(outputFilename);
+            await image.SaveAsync(outputFilename);
 
             //Unload
             await annotationPipeline.UnloadAsync();

OnnxStack.Console/Examples/FeatureExtractorExample.cs

@@ -1,4 +1,5 @@
 using OnnxStack.Core.Image;
+using OnnxStack.Core.Video;
 using OnnxStack.FeatureExtractor.Pipelines;
 using OnnxStack.StableDiffusion.Config;
 using SixLabors.ImageSharp;
@@ -30,7 +31,7 @@ public FeatureExtractorExample(StableDiffusionConfig configuration)
         public async Task RunAsync()
         {
             // Load Control Image
-            var inputImage = await InputImage.FromFileAsync("D:\\Repositories\\OnnxStack\\Assets\\Samples\\Img2Img_Start.bmp");
+            var inputImage = await OnnxImage.FromFileAsync("D:\\Repositories\\OnnxStack\\Assets\\Samples\\Img2Img_Start.bmp");
 
             var pipelines = new[]
             {
@@ -47,14 +48,13 @@ public async Task RunAsync()
                 var timestamp = Stopwatch.GetTimestamp();
                 OutputHelpers.WriteConsole($"Load pipeline`{pipeline.Name}`", ConsoleColor.Cyan);
 
-                // Run Pipeline
+                // Run Image Pipeline
                 var imageFeature = await pipeline.RunAsync(inputImage);
 
                 OutputHelpers.WriteConsole($"Generating image", ConsoleColor.Cyan);
 
                 // Save Image
-                await imageFeature.Image.SaveAsPngAsync(Path.Combine(_outputDirectory, $"{pipeline.Name}.png"));
-
+                await imageFeature.SaveAsync(Path.Combine(_outputDirectory, $"{pipeline.Name}.png"));
 
                 OutputHelpers.WriteConsole($"Unload pipeline", ConsoleColor.Cyan);
 

OnnxStack.Console/Examples/StableDebug.cs

@@ -69,11 +69,11 @@ public async Task RunAsync()
                         var result = await pipeline.RunAsync(promptOptions, schedulerOptions, progressCallback: OutputHelpers.ProgressCallback);
 
                         // Create Image from Tensor result
-                        var image = result.ToImage();
+                        var image = new OnnxImage(result);
 
                         // Save Image File
                         var outputFilename = Path.Combine(_outputDirectory, $"{modelSet.Name}_{schedulerOptions.SchedulerType}.png");
-                        await image.SaveAsPngAsync(outputFilename);
+                        await image.SaveAsync(outputFilename);
 
                         OutputHelpers.WriteConsole($"{schedulerOptions.SchedulerType} Image Created: {Path.GetFileName(outputFilename)}", ConsoleColor.Green);
                         OutputHelpers.WriteConsole($"Elapsed: {Stopwatch.GetElapsedTime(timestamp)}ms", ConsoleColor.Yellow);

OnnxStack.Console/Examples/StableDiffusionBatch.cs

@@ -61,11 +61,11 @@ public async Task RunAsync()
                 await foreach (var result in pipeline.RunBatchAsync(batchOptions, promptOptions, progressCallback: OutputHelpers.BatchProgressCallback))
                 {
                     // Create Image from Tensor result
-                    var image = result.ImageResult.ToImage();
+                    var image = new OnnxImage(result.Result);
 
                     // Save Image File
                     var outputFilename = Path.Combine(_outputDirectory, $"{modelSet.Name}_{result.SchedulerOptions.Seed}.png");
-                    await image.SaveAsPngAsync(outputFilename);
+                    await image.SaveAsync(outputFilename);
 
                     OutputHelpers.WriteConsole($"Image Created: {Path.GetFileName(outputFilename)}, Elapsed: {Stopwatch.GetElapsedTime(timestamp)}ms", ConsoleColor.Green);
                     timestamp = Stopwatch.GetTimestamp();

OnnxStack.Console/Examples/StableDiffusionExample.cs

@@ -67,14 +67,11 @@ public async Task RunAsync()
                         OutputHelpers.WriteConsole($"Generating '{schedulerType}' Image...", ConsoleColor.Green);
 
                         // Run pipeline
-                        var result = await pipeline.RunAsync(promptOptions, schedulerOptions, progressCallback: OutputHelpers.ProgressCallback);
-
-                        // Create Image from Tensor result
-                        var image = result.ToImage();
+                        var result = await pipeline.GenerateImageAsync(promptOptions, schedulerOptions, progressCallback: OutputHelpers.ProgressCallback);
 
                         // Save Image File
                         var outputFilename = Path.Combine(_outputDirectory, $"{modelSet.Name}_{schedulerOptions.SchedulerType}.png");
-                        await image.SaveAsPngAsync(outputFilename);
+                        await result.SaveAsync(outputFilename);
 
                         OutputHelpers.WriteConsole($"Image Created: {Path.GetFileName(outputFilename)}, Elapsed: {Stopwatch.GetElapsedTime(timestamp)}ms", ConsoleColor.Green);
                     }

OnnxStack.Console/Examples/StableDiffusionGenerator.cs

@@ -58,11 +58,11 @@ public async Task RunAsync()
                     var result = await pipeline.RunAsync(promptOptions, progressCallback: OutputHelpers.ProgressCallback);
 
                     // Create Image from Tensor result
-                    var image = result.ToImage();
+                    var image = new OnnxImage(result);
 
                     // Save Image File
                     var outputFilename = Path.Combine(_outputDirectory, $"{modelSet.Name}_{generationPrompt.Key}.png");
-                    await image.SaveAsPngAsync(outputFilename);
+                    await image.SaveAsync(outputFilename);
 
                     OutputHelpers.WriteConsole($"Image Created: {Path.GetFileName(outputFilename)}, Elapsed: {Stopwatch.GetElapsedTime(timestamp)}ms", ConsoleColor.Green);
                 }

OnnxStack.Console/Examples/UpscaleExample.cs

@@ -1,18 +1,14 @@
 using OnnxStack.Core.Image;
 using OnnxStack.FeatureExtractor.Pipelines;
-using OnnxStack.ImageUpscaler.Config;
-using SixLabors.ImageSharp;
 
 namespace OnnxStack.Console.Runner
 {
     public sealed class UpscaleExample : IExampleRunner
     {
         private readonly string _outputDirectory;
-        private readonly ImageUpscalerConfig _configuration;
 
-        public UpscaleExample(ImageUpscalerConfig configuration)
+        public UpscaleExample()
         {
-            _configuration = configuration;
             _outputDirectory = Path.Combine(Directory.GetCurrentDirectory(), "Examples", nameof(UpscaleExample));
             Directory.CreateDirectory(_outputDirectory);
         }
@@ -26,7 +22,7 @@ public UpscaleExample(ImageUpscalerConfig configuration)
         public async Task RunAsync()
         {
             // Load Input Image
-            var inputImage = await InputImage.FromFileAsync("D:\\Repositories\\OnnxStack\\Assets\\Samples\\Img2Img_Start.bmp");
+            var inputImage = await OnnxImage.FromFileAsync("D:\\Repositories\\OnnxStack\\Assets\\Samples\\Img2Img_Start.bmp");
 
             // Create Pipeline
             var pipeline = ImageUpscalePipeline.CreatePipeline("D:\\Repositories\\upscaler\\SwinIR\\003_realSR_BSRGAN_DFO_s64w8_SwinIR-M_x4_GAN.onnx", 4);
@@ -35,11 +31,11 @@ public async Task RunAsync()
             var result = await pipeline.RunAsync(inputImage);
 
             // Create Image from Tensor result
-            var image = result.ToImage(ImageNormalizeType.ZeroToOne);
+            var image = new OnnxImage(result, ImageNormalizeType.ZeroToOne);
 
             // Save Image File
             var outputFilename = Path.Combine(_outputDirectory, $"Upscaled.png");
-            await image.SaveAsPngAsync(outputFilename);
+            await image.SaveAsync(outputFilename);
 
             // Unload
             await pipeline.UnloadAsync();

OnnxStack.Console/Examples/VideoToVideoExample.cs

@@ -1,6 +1,4 @@
-using OnnxStack.Core.Services;
-using OnnxStack.Core.Video;
-using OnnxStack.StableDiffusion.Common;
+using OnnxStack.Core.Video;
 using OnnxStack.StableDiffusion.Config;
 using OnnxStack.StableDiffusion.Enums;
 using OnnxStack.StableDiffusion.Pipelines;
@@ -11,12 +9,10 @@ public sealed class VideoToVideoExample : IExampleRunner
     {
         private readonly string _outputDirectory;
         private readonly StableDiffusionConfig _configuration;
-        private readonly IVideoService _videoService;
 
-        public VideoToVideoExample(StableDiffusionConfig configuration, IVideoService videoService)
+        public VideoToVideoExample(StableDiffusionConfig configuration)
         {
             _configuration = configuration;
-            _videoService = videoService;
             _outputDirectory = Path.Combine(Directory.GetCurrentDirectory(), "Examples", nameof(VideoToVideoExample));
             Directory.CreateDirectory(_outputDirectory);
         }
@@ -30,8 +26,7 @@ public VideoToVideoExample(StableDiffusionConfig configuration, IVideoService vi
         public async Task RunAsync()
         {
             // Load Video
-            var targetFPS = 15;
-            var videoInput = await VideoInput.FromFileAsync("C:\\Users\\Deven\\Pictures\\gidsgphy.gif", targetFPS);
+            var videoInput = await OnnxVideo.FromFileAsync("C:\\Users\\Deven\\Pictures\\gidsgphy.gif");
 
             // Loop though the appsettings.json model sets
             foreach (var modelSet in _configuration.ModelSets)
@@ -53,11 +48,10 @@ public async Task RunAsync()
                 };
 
                 // Run pipeline
-                var result = await pipeline.RunAsync(promptOptions, progressCallback: OutputHelpers.FrameProgressCallback);
+                var result = await pipeline.GenerateVideoAsync(promptOptions, progressCallback: OutputHelpers.FrameProgressCallback);
 
                 // Save Video File
-                var outputFilename = Path.Combine(_outputDirectory, $"{modelSet.Name}.mp4");
-                await VideoInput.SaveFileAsync(result, outputFilename, targetFPS);
+                await result.SaveAsync(Path.Combine(_outputDirectory, $"Result.mp4"));
             }
         }
     }

OnnxStack.Console/Program.cs

@@ -19,7 +19,6 @@ static async Task Main(string[] _)
             // Add OnnxStack
             builder.Services.AddOnnxStack();
             builder.Services.AddOnnxStackConfig<StableDiffusionConfig>();
-            builder.Services.AddOnnxStackImageUpscaler();
 
             // Add AppService
             builder.Services.AddHostedService<AppService>();

OnnxStack.Core/Extensions/TensorExtension.cs

@@ -1,5 +1,6 @@
 using Microsoft.ML.OnnxRuntime.Tensors;
 using System;
+using System.Collections.Generic;
 
 namespace OnnxStack.Core
 {
@@ -54,6 +55,26 @@ public static void NormalizeMinMax(this DenseTensor<float> tensor)
         }
 
 
+        /// <summary>
+        /// Splits the tensor across the batch dimension.
+        /// </summary>
+        /// <param name="tensor">The tensor.</param>
+        /// <returns></returns>
+        public static IEnumerable<DenseTensor<float>> SplitBatch(this DenseTensor<float> tensor)
+        {
+            var count = tensor.Dimensions[0];
+            var dimensions = tensor.Dimensions.ToArray();
+            dimensions[0] = 1;
+
+            var newLength = (int)tensor.Length / count;
+            for (int i = 0; i < count; i++)
+            {
+                var start = i * newLength;
+                yield return new DenseTensor<float>(tensor.Buffer.Slice(start, newLength), dimensions);
+            }
+        }
+
+
         /// <summary>
         /// Concatenates the specified tensors along the specified axis.
         /// </summary>