👗 Letsdress.AI – AI-Powered Fashion Personalization Tool

Letsdress.AI is a smart fashion personalization tool that uses generative AI to turn your clothing ideas into high-quality images. It combines the power of Stability AI's models with a clean, modern interface, allowing you to visualize unique outfits in real-time.

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📌 Overview

Letsdress.AI helps users visualize personalized fashion recommendations by offering:

• 🧠 Smart Recommendations based on user input and style prompts
• 🔁 Real-Time Trend Adaptation that reflects the latest fashion trends
• 💻 Modern UI/UX with interactive and responsive design

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📁 Project Structure

Letsdress.AI/
├── authtoken.py                  # App entry point and API auth logic
├── requirements.txt             # Python dependencies
├── *.png                        # Screenshot assets
│
├── database/
│   ├── image_data.py           # DB script for storing images and metadata
│   └── Image_data.db           # SQLite database
│
├── static/                     # Static frontend files
│   ├── css/
│   ├── js/
│   └── images/
│
├── templates/                  # HTML templates (Jinja2)
│   ├── feedback.html
│   ├── index.html
│   └── opening.html
│
├── .idea/                      # IDE (PyCharm) configs [optional, can ignore]
└── __pycache__/                # Python bytecode cache [auto-generated]

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🧠 Features

• 👤 User Personalization: Tailors results to user prompts
• 🛍️ Outfit Generation: Uses Stable Diffusion for realistic clothing previews
• 📈 Trend-Aware Filtering: Highlights trending styles
• 💅 Clean UI: Minimal, modern, and user-friendly
• 📊 Database Storage: Saves generated images with prompt tags

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🧰 Tech Stack

Frontend	Backend	Machine Learning	Database
HTML / CSS / JS	Flask	Stable Diffusion, Jinja2	SQLite3

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🔄 How It Works

1. User Prompt: Users input a desired clothing style
2. Image Generation: Prompt sent to the backend → Stable Diffusion generates visuals
3. Storage: Images saved in static/images/ and logged in SQLite DB
4. Display: Results rendered dynamically on the web UI
5. Database Logging: A reference to the image and its corresponding prompt is stored in the SQLite database.
6. Image Storage: The generated image is saved to the /static/images/ directory, overwriting one of the placeholder images to update the carousel.

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🛠️ Getting Started

1. Clone the Repo

git clone https://github.com/agrawal-2005/Letsdress.AI.git
cd Letsdress.AI

2. Set Up the Environment

python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate

3. Install Dependencies

pip install -r requirements.txt

4. Add API Credentials

Create a .env file in the root directory:

API_URL=https://router.huggingface.co/hf-inference/models/stabilityai/stable-diffusion-xl-base-1.0
API_TOKEN=your_huggingface_token_here
GMAIL=your_email_here
GMAIL_PASSWORD=your_gmail_app_password_here

5. Run the App

python authtoken.py

Visit: http://localhost:5000

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🧬 Machine Learning

• Powered by Stable Diffusion XL
• Prompt-based generation: "<style> outfit" patterns
• Images rendered and saved for future display + analytics
• Supports basic trend personalization via text prompts

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📸 UI Preview

Startup Page	Results Output

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🙋 Feedback

Found an issue or have an idea? Reach out via GitHub: @agrawal-2005

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📄 License

MIT License — See LICENSE for details.