🎨 Quantum Canvas V1 Ultimate — AI Image Generator

A powerful, browser-based AI Image Generation Studio built with Python & Flask.
Supports Text-to-Image, Image-to-Image, Background Removal, Upscaling, Denoising, and more — all running locally on CPU.

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🖼️ Project Preview

[ Text2Img ] [ Img2Img ] [ Upscale ] [ Remove BG ] [ Denoise ] [ Restore ]
      ↓
  Write Prompt → Pick AI Model → Adjust Steps → Generate → Download

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✨ Features

• 🤖 50+ AI Models — Speed, Realistic, Anime, Artistic, Sci-Fi & more
• 🖼️ Text to Image — Generate images from text prompts
• 🔄 Image to Image — Transform existing images with AI
• 🪄 Background Removal — One-click BG remover using rembg
• 📐 Super Resolution — Upscale images 2x, 4x, 8x
• 🔇 Denoising — Remove noise from photos
• 🕰️ Image Restoration — Restore old or damaged images
• ⚡ Speed Presets — Lightning Fast → Ultra Quality
• 🌗 Dark / Light Theme — Toggle with Ctrl+T
• 📜 Generation History — Persistent history with preview
• ⭐ Favorites — Star your favourite AI models
• 🔍 Model Search — Search 50+ models instantly
• ⌨️ Keyboard Shortcuts — Full keyboard control (press ? to see)
• 📱 Mobile Responsive — Works on phone & tablet too
• 🧠 CPU Optimized — No GPU required, runs on any machine

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🗂️ Project Structure

quantum-canvas/
│
├── app.py              ← Main application (Flask server + AI logic)
├── requirements.txt    ← Python dependencies
├── README.md           ← You are here
├── .gitignore          ← Git ignore rules
│
├── history.json        ← Auto-created: generation history
└── favorites.json      ← Auto-created: saved favourite models

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⚙️ Requirements

Tool	Version
Python	3.9 or higher
pip	Latest
RAM	Minimum 4GB (8GB recommended)
Storage	3–5 GB free (for AI model downloads)
GPU	❌ Not required — CPU works fine

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🚀 How to Run (Step by Step)

Step 1 — Clone the Repository

# Using Git
git clone https://github.com/vikrant-project/quantum-canvas-ai.git

cd canvas-ai

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Step 2 — Create a Virtual Environment (Recommended)

# Windows
python -m venv venv
venv\Scripts\activate

# Mac / Linux
python3 -m venv venv
source venv/bin/activate

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Step 3 — Install Dependencies

pip install -r requirements.txt

⏳ First time setup may take 5–10 minutes depending on your internet speed.
The app will also auto-install any missing packages when you first run it.

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Step 4 — Run the App

python app.py

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Step 5 — Open in Browser

http://localhost:1600

That's it! 🎉 The app will automatically download the default AI model (tiny-sd) on first launch.

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⌨️ Keyboard Shortcuts

Shortcut	Action
Ctrl + Enter	Generate image
Ctrl + D	Download image
Ctrl + N	New / Reset canvas
Ctrl + F	Search models
Ctrl + T	Toggle Dark/Light theme
1 – 6	Switch between modules
Alt + ↑ / ↓	Adjust steps by 5
Esc	Reset canvas
?	Show all shortcuts

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🧠 AI Models Included

Category	Examples
⚡ Speed	Tiny SD, SD Turbo, LCM SD
🎨 General	Stable Diffusion v1.5, v2.1, DreamShaper
📷 Realistic	Realistic Vision, Dreamlike Photoreal
🌸 Anime	Anything V5, Counterfeit
🖌️ Artistic	OpenJourney, Van Gogh Diffusion
🎭 Special	Ghibli Diffusion, Sci-Fi Diffusion, Modern Disney

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❓ Common Issues

Q: App is slow on first run?
A: It downloads the AI model on first use (~300MB–5GB). Wait for it to complete.

Q: ModuleNotFoundError?
A: Run pip install -r requirements.txt again inside your virtual environment.

Q: Port 1600 already in use?
A: Change the last line in app.py: app.run(port=5000) to any free port.

Q: Image generation is taking too long?
A: Use the ⚡ Lightning Fast preset or select the Tiny SD model.

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👨‍💻 About the Developer

Name: [soulcracks_owner

This project was built to demonstrate practical skills in:

• Python web development (Flask)
• AI/ML model integration (HuggingFace Diffusers)
• Computer Vision (OpenCV, rembg, scikit-image)
• Modern UI/UX design (Glassmorphism, Dark theme)
• REST API design

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📄 License

This project is open-source and free to use for educational purposes.

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⭐ If you liked this project, please give it a star on github!