StableDiffuison README

Author: saddam213

OnnxStack.StableDiffusion/README.md

@@ -2,229 +2,6 @@
 
 `OnnxStack.StableDiffusion` is a library that provides higher-level Stable Diffusion services for use in .NET applications. It offers extensive support for features such as dependency injection, .NET configuration implementations, ASP.NET Core integration, and IHostedService support.
 
-## Getting Started
-
-OnnxStack.StableDiffusion can be found via the nuget package manager, download and install it.
-```
-PM> Install-Package OnnxStack.StableDiffusion
-```
-
-### Microsoft.ML.OnnxRuntime
-Depending on the devices you have and the platform you are running on, you will want to install the Microsoft.ML.OnnxRuntime package that best suits your needs.
-
-### CPU-GPU via Microsoft Drirect ML
-```
-PM> Install-Package Microsoft.ML.OnnxRuntime.DirectML
-```
-
-### GPU support for both NVIDIA and AMD?
-```
-PM> Install-Package Microsoft.ML.OnnxRuntime.Gpu
-```
-
-
-
-### .NET Core Registration
-
-You can easily integrate `OnnxStack.StableDiffusion` into your application services layer. This registration process sets up the necessary services and loads the `appsettings.json` configuration.
-
-Example: Registering OnnxStack.StableDiffusion
-```csharp
-builder.Services.AddOnnxStackStableDiffusion();
-```
-
-
-
-
-## .NET Console Application Example
-
-Required Nuget Packages for example
-```nuget
-Microsoft.Extensions.Hosting
-Microsoft.Extensions.Logging
-```
-
-```csharp
-using Microsoft.Extensions.DependencyInjection;
-using Microsoft.Extensions.Hosting;
-using OnnxStack.StableDiffusion.Common;
-using OnnxStack.StableDiffusion.Config;
-
-internal class Program
-{
-   static async Task Main(string[] _)
-   {
-      var builder = Host.CreateApplicationBuilder();
-      builder.Logging.ClearProviders();
-      builder.Services.AddLogging((loggingBuilder) => loggingBuilder.SetMinimumLevel(LogLevel.Error));
-
-      // Add OnnxStack Stable Diffusion
-      builder.Services.AddOnnxStackStableDiffusion();
-
-      // Add AppService
-      builder.Services.AddHostedService<AppService>();
-
-      // Start
-      await builder.Build().RunAsync();
-   }
-}
-
-internal class AppService : IHostedService
-{
-   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;
-   }
-}
-```
-
-
-## 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"
-         }
-      ]
-   }
-}
-```
 
 ###  **Prompt**
 
@@ -314,19 +91,14 @@ https://user-images.githubusercontent.com/4353684/285547207-3a7ea067-fcbf-47f0-9
 ## ONNX Model Download
 You will need an ONNX compatible model to use, Hugging Face is a great place to download the Stable Diffusion models
 
-Download the [ONNX Stable Diffusion models from Hugging Face](https://huggingface.co/models?sort=downloads&search=Stable+Diffusion).
-
-- [Stable Diffusion Models v1.4](https://huggingface.co/CompVis/stable-diffusion-v1-4/tree/onnx)
-- [Stable Diffusion Models v1.5](https://huggingface.co/runwayml/stable-diffusion-v1-5/tree/onnx)
-
-
-Once you have selected a model version repo, click `Files and Versions`, then select the `ONNX` branch. If there isn't an ONNX model branch available, use the `main` branch and convert it to ONNX. See the [ONNX conversion tutorial for PyTorch](https://learn.microsoft.com/windows/ai/windows-ml/tutorials/pytorch-convert-model) for more information.
-
-Clone the model repo:
-```text
-git lfs install
-git clone https://huggingface.co/runwayml/stable-diffusion-v1-5 -b onnx
-```
+- [OpenJourney V4](https://huggingface.co/TheyCallMeHex/OpenJourney-V4-ONNX)
+- [DreamLike PhotoReal 2.0](https://huggingface.co/TheyCallMeHex/DreamLike-PhotoReal-2.0-ONNX)
+- [CyberPunk Anime Diffusion](https://huggingface.co/TheyCallMeHex/Cyberpunk-Anime-Diffusion-ONNX)
+- [InkPunk Diffusion](https://huggingface.co/TheyCallMeHex/Inkpunk-Diffusion-ONNX)
+- [Mo-Di Diffusion](https://huggingface.co/TheyCallMeHex/Mo-Di-Diffusion-ONNX)
+- [epiCRealism](https://huggingface.co/TheyCallMeHex/epiCRealism-ONNX)
+- [Comic Diffusion](https://huggingface.co/TheyCallMeHex/Comic-Diffusion-ONNX)
+- [Redshift Diffusion](https://huggingface.co/TheyCallMeHex/Redshift-Diffusion-ONNX)
 
 
 ## Resources