Update README

Author: saddam213

README.md

@@ -1,31 +1,7 @@
 # OnnxStack
 ONNX Runtime Projects for .NET Applications
 
-## Hardware Requirements
-You can choose between `Cpu` and `DirectML`(GPU) for inference, 
-Other `Microsoft.ML.OnnxRuntime.*` executors like `Cuda` may work but are untested
-
-`Cpu` > 12GB RAM
-
-`DirectML` > 10GB VRAM
-
-
-## 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
-```
+This repository harnesses the capabilities of both `ONNX Runtime` and `Microsoft ML`, offering a comprehensive solution that empowers developers to build, deploy, and execute machine learning models seamlessly in .NET environments, unlocking a world of possibilities for intelligent applications.
 
 
 # Projects
@@ -78,28 +54,67 @@ Image To Image Stable Diffusion is an advanced image processing and generation m
 | :--- | :--- | :--- |
 <img src="Assets/Samples/Img2Img_Start.bmp" width="256" alt="Image of browser inferencing on sample images."/> | <img src="Assets/Samples/Img2Img_End.png" width="256"  alt="Image of browser inferencing on sample images."/> |<img src="Assets/Samples/Img2Img_Animation.webp" width="256"  alt="Image of browser inferencing on sample images."/> |
 
+```
+   Prompt: Dog wearing storm trooper helmet, head shot
+```
 
 More information and Examples can be found in the `OnnxStack.StableDiffusion` project **[README](OnnxStack.StableDiffusion/README.md)**
 
 __________________________
 
 
 __________________________
-## `OnnxStack.ImageRecognition`
-Image recognition with ResNet50v2 with C# and ONNX Runtime
+## **[OnnxStack.ImageRecognition]()**
+**Image recognition with ResNet50v2 and ONNX Runtime**
 
-~WIP~
+Harness the accuracy of the ResNet50v2 deep learning model for image recognition, seamlessly integrated with ONNX for efficient deployment. This combination empowers your applications to classify images with precision, making it ideal for tasks like object detection, content filtering, and image tagging across various platforms and hardware accelerators. Achieve high-quality image recognition effortlessly with ResNet50v2 and ONNX integration.
+
+
+***work in progress***
 __________________________
 
 
 __________________________
-## `OnnxStack.ObjectDetection`
-Object detection with Faster RCNN Deep Learning with C# and ONNX Runtime
+## **[OnnxStack.ObjectDetection]()**
+**Object detection with Faster RCNN Deep Learning with C# and ONNX Runtime**
+
+Enable robust object detection in your applications using RCNN (Region-based Convolutional Neural Network) integrated with ONNX. This powerful combination allows you to accurately locate and classify objects within images. Whether for surveillance, autonomous vehicles, or content analysis, RCNN and ONNX integration offers efficient and precise object detection across various platforms and hardware, ensuring your solutions excel in recognizing and localizing objects in images.
 
-~WIP~
+***work in progress***
 __________________________
 
 
+# Getting Started
+
+
+## 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
+```
+
+
+## Hardware Requirements
+You can choose between `Cpu` and `DirectML`(GPU) for inference, 
+Other `Microsoft.ML.OnnxRuntime.*` executors like `Cuda` may work but are untested
+
+`Cpu` > 12GB RAM
+
+`DirectML` > 10GB VRAM
+
+
+
 ## Contribution
 
 We welcome contributions to OnnxStack! If you have any ideas, bug reports, or improvements, feel free to open an issue or submit a pull request.