Updated the Readme.md file

README.md

@@ -1,53 +1,73 @@
-# 🖼️ Image Sticker Generator API
-Welcome to the Image Sticker Generator API! This service is designed to transform images into "stickers" by isolating the main object with advanced semantic segmentation. The stickers are crafted with smooth, feathered edges to ensure a clean and professional appearance.
+# 🖼️ AI Sticker Generator API
 
+## Welcome to the **AI Sticker Generator API**! This API is designed to transform images into high-quality "stickers" by isolating the primary object using advanced **semantic segmentation** techniques. The stickers produced have smooth, feathered edges to ensure a polished and professional look.
 
-## Examples 
+## Examples
 
-![Example1](output/sticker_check3.png)
-![Example2](output/sticker_check.png)
-![Example3](output/sticker_check5.png)
+### Before and After Transformation
 
+- **Before:** ![Before](output/check3.png)  
+  **After:** ![After](output/sticker_check3.png)
 
-## 📋 Features
-### 🔍 Semantic Segmentation: Automatically detects and highlights the main object in an image, ensuring accurate cutouts and clear subject isolation.
-### 🌟 Feathered Edges: Applies a soft Gaussian blur to mask edges, creating a natural transition to transparency.
-### ⚡ Built with FastAPI: Ensures high performance, scalability, and rapid response times for production use.
-### 📂 Versatile Image Support: Accepts both PNG and JPEG image formats.
+- **Before:** ![Before](output/check.png)  
+  **After:** ![After](output/sticker_check.png)
 
-### 🚀 Quick Start Guide
-Clone the repository and navigate to the project directory.
-Install Dependencies with Python 3.8+.
-Start the API Server using the provided configuration.
-Once running, the API will be accessible locally, ready for image uploads and sticker creation.
+- **Before:** ![Before](output/check5.png)  
+  **After:** ![After](output/sticker_check5.png)
+
+## 📋 Key Features
+
+### 🔍 Semantic Segmentation
+Automatically identifies and isolates the main subject in an image, providing precise cutouts for clear and visually appealing stickers.
+
+### 🌟 Feathered Edges
+Applies a Gaussian blur to the mask edges, creating a soft and natural transition to transparency for a more polished finish.
+
+### ⚡ Built with FastAPI
+Utilizes FastAPI for high performance, scalability, and fast response times suitable for production environments.
+
+### 📂 Versatile Image Support
+Supports **PNG** and **JPEG** formats, ensuring compatibility with widely used image types.
+
+## 🚀 Quick Start Guide
+
+1. **Clone the repository** and navigate to the project directory.
+2. **Install dependencies** (requires Python 3.8+).
+3. **Start the API server** using the provided configuration file.
+4. Once the server is running, the API is accessible locally, ready to accept image uploads for sticker generation.
 
 ## 🛠️ API Endpoints
-POST /create_sticker/
-Description: Upload an image to generate a sticker with a transparent background.
-Supported File Types: Accepts PNG and JPEG formats.
-Response: Returns a PNG image of the sticker with a transparent background. In case of an unsupported file format, an error message will be returned.
+
+### `POST /create_sticker/`
+- **Description**: Upload an image to generate a sticker with a transparent background.
+- **Supported File Types**: PNG and JPEG formats.
+- **Response**: Returns a PNG image of the sticker with a transparent background. In case of an unsupported file format, an error message will be returned.
+
 ## 🧩 How It Works
-Model & Preprocessing: Uploaded images are preprocessed and passed through a pre-trained model for semantic segmentation.
-Mask Generation: A binary mask isolates the main object in the image.
-Edge Feathering: A Gaussian blur is applied to the mask edges to create a soft transition.
-Sticker Creation: The mask is used to add transparency, producing an image that can be directly used as a sticker.
+
+1. **Model & Preprocessing**: Uploaded images are preprocessed and passed through a pre-trained model for semantic segmentation.
+2. **Mask Generation**: A binary mask isolates the main object in the image.
+3. **Edge Feathering**: A Gaussian blur is applied to mask edges, creating a smooth transition.
+4. **Sticker Creation**: The mask adds transparency, producing an image that can be directly used as a sticker.
+
 ## 📂 Directory Structure
-The main application file manages the API and endpoints, while generated stickers are saved in a designated output directory. This ensures easy access and organization for generated images.
+
+Generated stickers are saved in a designated output directory, ensuring easy access and organization of created stickers.
 
 ## ⚙️ Configuration
-Before running the application, confirm that the output directory exists. This is essential for storing all generated stickers for easy retrieval and management.
+
+Before running the application, confirm that the output directory exists. This directory is essential for storing generated stickers for easy retrieval and management.
 
 ## 📜 License
-Licensed under the MIT License, making it easy for anyone to adapt and build upon the work.
+
+Licensed under the MIT License, allowing easy adaptation and building upon this work.
 
 ## 🙋‍♂️ Contributing
+
 Contributions are welcome! To contribute, create a new issue or pull request for bug fixes, enhancements, or new features. All contributions should adhere to the project's coding standards and guidelines.
 
 ## Built with ❤️ by [SAMIULLAH]
 
 ## 📞 Support
-For support or inquiries, please contact nicesami156@gmail.com.
 
----
-license: mit
----
+For support or inquiries, please contact nicesami156@gmail.com.