Image Generation

📌 Description

An end-to-end computer vision project for text-to-image generation and image analysis. This repository features data exploration, model experimentation, and an interactive Streamlit dashboard. Users can generate creative images from text prompts, analyze visual content, and perform prompt engineering experiments using advanced Generative AI and deep learning pipelines.

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🛠️ Tech Stack

Category	Technologies Used
🌐 Programming Language	Python
🌱 Environment	Jupyter Notebook
🧩 Frameworks	PyTorch, Streamlit
⚛️ Libraries	NumPy, Matplotlib, Diffusers, pyngrok, Streamlit - Drawable Canvas, Transformers, Pillow, Accelerate, safetensors
🤖 Generative AI Models	Stable-Diffusion-v1-5, Stable-Diffusion-Inpainting
⚡ Tool	Google Colab
🚧 Tunneling Service	ngrok

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⚙️ Setup Instructions

1. Prerequisites

   • Python 3.11 or higher.
   • Git installed on your system.
   • An active ngrok account.

2. Ngrok Authtoken Setup

   • Visit the official ngrok website.
   • Sign up for a new account or log in to your existing account.
   • Once redirected to the ngrok dashboard, navigate to the Your Authtoken menu on the left sidebar.
   • Copy your unique authentication token to use during the configuration phase.

3. Clone the Repository

git clone https://github.com/Fikri-Rouzan/image-generation.git
cd image-generation

4. Configure Authentication Token

   Open the streamlit.ipynb file and insert your ngrok authtoken into the following code cell

   auth_token = "YOUR_AUTHENTICATION_KEY"
   
   ngrok.set_auth_token(auth_token)
   subprocess.Popen(["streamlit", "run", "app.py"])