fix read me file

README.md

@@ -1,58 +1,24 @@
-# CSE 555 Term Project (Computer Vision and Natural Language Processing)
-
-## Overview
-This project is a multi-featured application focused on food image classification, variation detection, recipe recommendation, and reporting. It leverages deep learning and NLP techniques to provide a comprehensive toolkit for food-related data analysis and user interaction.
-
-## Features
-- **Image Classification:** Classify food images using pre-trained models.
-- **Variation Detection:** Detect variations in food items.
-- **Recipe Recommendation:** Recommend recipes based on user input and image analysis.
-- **Report Generation:** Generate reports based on classification and recommendation results.
-
-## Project Structure
-```
-PatternRec_Project_Group5/
-├── assets/
-│   ├── css/                # Stylesheets
-│   ├── modelWeights/       # Pre-trained model weights (.pth)
-│   └── nlp/                # NLP data and models (to be downloaded from google drive once the app runs)
-├── config.py               # Configuration file
-├── Scripts/                # Configuration file
-│   ├── CV/                 # CV Training script
-│   ├── NLP/                # NLP Training script
-├── Home.py                 # Main entry point (possibly Streamlit or similar)
-├── model/                  # Model code (classifier, search recipe)
-├── pages/                  # App pages (image classification, variation detection, etc.)
-├── utils/                  # Utility functions (layout, etc.)
-├── sakenv/                 # Python virtual environment
-```
-
-## Setup Instructions
-1. **Clone the repository:**
-   ```bash
-   git clone <repo-url>
-   cd PatternRec_Project_Group5
-   ```
-2. **Create and activate the virtual environment: (Already included as sakenv/):**
-   ```bash
-   source sakenv/bin/activate
-   ```
-3. **Install dependencies:**
-   ```bash
-   pip install -r requirements.txt
-   ```
-4. **Run the application:**
-   - If using Streamlit:
-     ```bash
-     streamlit run Home.py
-     ```
-   - Or follow the instructions in `Home.py`.
-
-## Python Version
-- Python 3.12.2
-
-## Notes
-- Model weights are stored in the `assets/` directory.
-- NLP weights were quite large and are stored at [CSE 555 Project Group 5](https://drive.google.com/drive/folders/1m6cfy4NuxIKNDBtJqm150NNN0FSUS8Np)
-- Ensure you have the necessary permissions to access large files in `assets/modelWeights/` and `assets/nlp/`.
-- For best results, use the provided virtual environment and requirements file. 
+---
+title: Pattern
+emoji: 🚀
+colorFrom: red
+colorTo: red
+sdk: docker
+app_port: 8501
+tags:
+- streamlit
+pinned: false
+short_description: for pattern recg
+---
+
+# Welcome to Streamlit!
+
+
+Edit `/src/streamlit_app.py` to customize this app to your heart's desire. :heart:
+
+
+
+
+
+If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
+forums](https://discuss.streamlit.io).