Updating readme.md

README.md

@@ -10,58 +10,77 @@ pinned: false
 short_description: Stable Diffusion using Text Inversion
 ---
 
-# Stable Diffusion using Text Inversion
+# Stable Diffusion with Text Inversion and Style Transfer
 
-A Gradio web application that generates images using Stable Diffusion with various text inversion concepts and loss functions.
+A Gradio-based web application that generates images using Stable Diffusion with various style concepts and loss functions.
 
 ## Features
 
-- Generate images using Stable Diffusion v1.4
-- Apply different artistic styles using text inversion concepts:
+- Text-to-image generation using Stable Diffusion v1.4
+- Multiple pre-trained style concepts:
   - Dreams
   - Midjourney Style
   - Moebius
   - Marc Allante
   - WLOP
-- Automatic application of multiple loss functions:
-  - No Loss (Base generation)
-  - Blue Channel Loss
-  - Elastic Transformation Loss
-  - Symmetry Loss
-  - Saturation Loss
-- User-friendly interface with preset prompts and custom prompt input
-- Side-by-side comparison of different loss function effects
+- Five different image variations using loss functions:
+  1. Original (No Loss)
+  2. Blue Channel Loss
+  3. Elastic Loss
+  4. Symmetry Loss
+  5. Saturation Loss
 
-## Usage
+## Requirements
 
-1. Select a preset prompt or enter your own custom prompt
-2. Choose a style concept from the dropdown menu
-3. Click "Submit" to generate images
-4. View the results showing different loss function effects side by side
+- Python 3.8+
+- PyTorch
+- Diffusers
+- Gradio
+- PIL
+- Torchvision
 
 ## Installation
 
-1. Clone this repository
+1. Clone the repository:
+```bash
+git clone <repository-url>
+cd stable-diffusion-using-text-inversion
+```
 2. Install the required dependencies:
 ```bash
 pip install -r requirements.txt
 ```
-3. Run the application:
+
+## Usage
+1. Run the application:
 ```bash
 python app.py
 ```
+2. Open your web browser and navigate to:
 
-## Requirements
-- Python 3.7+
-- PyTorch
-- Diffusers
-- Transformers
-- Gradio
-- Torchvision
-- PIL
+- Local URL: http://127.0.0.1:7860
+- Or use the public URL provided in the terminal
+3. Select or enter a prompt and choose a style concept
+4. Click submit and wait for the images to generate.py
+
+## Image Generation Process
+The application generates five variations of each image:
 
-## Model Details
-The application uses the CompVis/stable-diffusion-v1-4 model with text inversion concepts from the Hugging Face SD concepts library. The model runs with float16 precision and supports CUDA, MPS, and CPU devices.
+1. Original Image : Base generation without modifications
+2. Blue Channel Loss : Enhanced blue tones for atmospheric effects
+3. Elastic Loss : Added elastic deformation for artistic distortion
+4. Symmetry Loss : Enforced symmetrical features
+5. Saturation Loss : Modified color saturation for vibrant effects
+
+## Performance Notes
+- Image generation takes several minutes per set
+- Uses 384x384 resolution for optimal speed/quality balance
+- CUDA-enabled GPU recommended for faster generation
+- Supports CPU, CUDA, and MPS (Apple Silicon) backends
 
 ## License
-This project uses the CompVis/stable-diffusion-v1-4 model which is subject to the CreativeML Open RAIL-M license.
+MIT License
+
+## Acknowledgments
+- Stable Diffusion by CompVis
+- Textual Inversion concepts from Hugging Face's SD Concepts Library