Update Basic and Batch example

Author: saddam213

OnnxStack.StableDiffusion/README_Example.md

@@ -17,7 +17,7 @@ Depending on the devices you have and the platform you are running on, you will
 PM> Install-Package Microsoft.ML.OnnxRuntime.DirectML
 ```
 
-### GPU support for both NVIDIA and AMD?
+### GPU support for NVIDIA
 ```
 PM> Install-Package Microsoft.ML.OnnxRuntime.Gpu
 ```
@@ -42,192 +42,58 @@ https://github.com/ffbinaries/ffbinaries-prebuilt/releases/download/v6.1/ffprobe
 ```
 
 
-## .NET Console Application Example
+# C# Stable Diffusion Examples
+Excample Model: https://huggingface.co/runwayml/stable-diffusion-v1-5 (onnx branch)
 
-Required Nuget Packages for example
-```nuget
-Microsoft.Extensions.Hosting
-Microsoft.Extensions.Logging
-```
 
+## Basic Stable Diffusion
+Run a simple Stable Diffusion process with a basic prompt
 ```csharp
-using Microsoft.Extensions.DependencyInjection;
-using Microsoft.Extensions.Hosting;
-using OnnxStack.StableDiffusion.Common;
-using OnnxStack.StableDiffusion.Config;
+// Create Pipeline
+var pipeline = StableDiffusionPipeline.CreatePipeline("D:\\Repositories\\stable-diffusion-v1-5");
 
-internal class Program
-{
-   static async Task Main(string[] _)
-   {
-      var builder = Host.CreateApplicationBuilder();
-      builder.Logging.ClearProviders();
-      builder.Services.AddLogging((loggingBuilder) => loggingBuilder.SetMinimumLevel(LogLevel.Error));
+// Set Prompt Options
+var promptOptions = new PromptOptions { Prompt = "Photo of a cute dog." };
 
-      // Add OnnxStack Stable Diffusion
-      builder.Services.AddOnnxStackStableDiffusion();
+// Run Pipleine
+var result = await pipeline.RunAsync(promptOptions);
 
-      // Add AppService
-      builder.Services.AddHostedService<AppService>();
+// Save image result
+var image = result.ToImage();
+await image.SaveAsPngAsync("D:\\Results\\Image.png");
 
-      // Start
-      await builder.Build().RunAsync();
-   }
-}
+// Unload Pipleine
+await pipeline.UnloadAsync();
+```
+
+## Stable Diffusion Batch Example
+Run Stable Diffusion process and return a batch of results
+```csharp
+// Create Pipeline
+var pipeline = StableDiffusionPipeline.CreatePipeline("D:\\Repositories\\stable-diffusion-v1-5");
+
+// Prompt
+var promptOptions = new PromptOptions{ Prompt = "Photo of a cat" };
 
-internal class AppService : IHostedService
+// Batch Of 5 Images with unique seeds
+var batchOptions = new BatchOptions
 {
-   private readonly string _outputDirectory;
-   private readonly IStableDiffusionService _stableDiffusionService;
-
-   public AppService(IStableDiffusionService stableDiffusionService)
-   {
-      _stableDiffusionService = stableDiffusionService;
-      _outputDirectory = Path.Combine(Directory.GetCurrentDirectory(), "Images");
-   }
-
-   public async Task StartAsync(CancellationToken cancellationToken)
-   {
-      Directory.CreateDirectory(_outputDirectory);
-
-      while (true)
-      {
-         System.Console.WriteLine("Please type a prompt and press ENTER");
-         var prompt = System.Console.ReadLine();
-
-         System.Console.WriteLine("Please type a negative prompt and press ENTER (optional)");
-         var negativePrompt = System.Console.ReadLine();
-
-
-         // Example only, full config depends on model
-         // appsettings.json is recommended for ease of use
-         var modelOptions = new ModelOptions
-         {
-            Name = "Stable  Diffusion 1.5",
-            ExecutionProvider = ExecutionProvider.DirectML,
-            ModelConfigurations = new List<OnnxModelSessionConfig>
-            {
-                  new OnnxModelSessionConfig
-                  {
-                     Type = OnnxModelType.Unet,
-                     OnnxModelPath = "model path"
-                  }
-            }
-         };
-
-         var promptOptions = new PromptOptions
-         {
-            Prompt = prompt,
-            NegativePrompt = negativePrompt,
-            DiffuserType = DiffuserType.TextToImage,
-
-            // Input for ImageToImage
-            // InputImage = new InputImage(File.ReadAllBytesAsync("image to image filename"))
-         };
-
-         var schedulerOptions = new SchedulerOptions
-         {
-            Seed = Random.Shared.Next(),
-            GuidanceScale = 7.5f,
-            InferenceSteps = 30,
-            Height = 512,
-            Width = 512,
-            SchedulerType = SchedulerType.LMS,
-         };
-
-
-         // Generate Image Example
-         var outputFilename = Path.Combine(_outputDirectory, $"{schedulerOptions.Seed}_{schedulerOptions.SchedulerType}.png");
-         var result = await _stableDiffusionService.GenerateAsImageAsync(modelOptions, promptOptions, schedulerOptions);
-         if (result is not null)
-         {
-            // Save image to disk
-            await result.SaveAsPngAsync(outputFilename);
-         }
-
-
-
-
-         // Generate Batch Example
-         var batchOptions = new BatchOptions
-         {
-            BatchType = BatchOptionType.Seed,
-            ValueTo = 20
-         };
-
-         await foreach (var batchResult in _stableDiffusionService.GenerateBatchAsImageAsync(modelOptions, promptOptions, schedulerOptions, batchOptions))
-         {
-            // Save image to disk
-            await batchResult.SaveAsPngAsync(outputFilename);
-         }
-
-
-      }
-   }
-
-   public Task StopAsync(CancellationToken cancellationToken)
-   {
-      return Task.CompletedTask;
-   }
+    ValueTo = 5,
+    BatchType = BatchOptionType.Seed
+};
+
+// Run Pipleine
+await foreach (var result in pipeline.RunBatchAsync(batchOptions, promptOptions))
+{
+    // Save Image result
+   var image = result.ImageResult.ToImage();
+   await image.SaveAsPngAsync($"D:\\Results\\Image_{result.SchedulerOptions.Seed}.png");
 }
+
+// Unload Pipleine
+await pipeline.UnloadAsync();
+
 ```
 
 
-## Configuration
-The `appsettings.json` is the easiest option for configuring model sets. Below is an example of `Stable Diffusion 1.5`.
-The example adds the necessary paths to each model file required for Stable Diffusion, as well as any model-specific configurations. 
-Each model can be assigned to its own device, which is handy if you have only a small GPU. This way, you can offload only what you need. There are limitations depending on the version of the `Microsoft.ML.OnnxRuntime` package you are using, but in most cases, you can split the load between CPU and GPU.
 
-```json
-{
-   "Logging": {
-      "LogLevel": {
-         "Default": "Information",
-         "Microsoft.AspNetCore": "Warning"
-      }
-   },
-
-   "OnnxStackConfig": {
-      "Name": "StableDiffusion 1.5",
-      "IsEnabled": true,
-      "PadTokenId": 49407,
-      "BlankTokenId": 49407,
-      "TokenizerLimit": 77,
-      "EmbeddingsLength": 768,
-      "ScaleFactor": 0.18215,
-      "PipelineType": "StableDiffusion",
-      "Diffusers": [
-         "TextToImage",
-         "ImageToImage",
-         "ImageInpaintLegacy"
-      ],
-      "DeviceId": 0,
-      "InterOpNumThreads": 0,
-      "IntraOpNumThreads": 0,
-      "ExecutionMode": "ORT_SEQUENTIAL",
-      "ExecutionProvider": "DirectML",
-      "ModelConfigurations": [
-         {
-            "Type": "Tokenizer",
-            "OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\cliptokenizer.onnx"
-         },
-         {
-            "Type": "Unet",
-            "OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\unet\\model.onnx"
-         },
-         {
-            "Type": "TextEncoder",
-            "OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\text_encoder\\model.onnx"
-         },
-         {
-            "Type": "VaeEncoder",
-            "OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\vae_encoder\\model.onnx"
-         },
-         {
-            "Type": "VaeDecoder",
-            "OnnxModelPath": "D:\\Repositories\\stable-diffusion-v1-5\\vae_decoder\\model.onnx"
-         }
-      ]
-   }
-}
-```