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Hands-on tutorials for generating and editing images using Stable Diffusion with Hugging Face Diffusers — includes text-to-image, inpainting, and image-to-image pipelines.

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🧪 Stable Diffusion Lab

A hands-on, tutorial-driven project for experimenting with various Stable Diffusion pipelines using Hugging Face's diffusers library.

📚 Tutorials Included

Notebook Description
01_txt2img_tutorial.ipynb Generate images from text prompts
02_inpainting_tutorial.ipynb Modify masked image areas using prompts
03_img2img_tutorial.ipynb Transform images using guiding prompts

✨ Prompt Ideas

Text-to-Image Prompts

  • "A futuristic cityscape at sunset, highly detailed"
  • "A magical forest with glowing plants and floating lanterns"
  • "An astronaut playing guitar on the moon, digital art"
  • "A cat wearing a spacesuit in a spaceship cockpit"

Inpainting Use Cases

  • Remove objects from background and regenerate surroundings
  • Replace sky with dramatic sunset
  • Change outfits or accessories in portraits
  • Fill missing or damaged parts of an image creatively

Image-to-Image Prompts

  • "Turn this pencil sketch into a realistic portrait"
  • "Make this daytime photo look like night with neon lights"
  • "Convert this rough landscape into a digital oil painting"

🖥️ App Interfaces

App File Description
Gradio app/gradio_app.py Launches a Gradio web UI for text-to-image generation
Streamlit app/streamlit_app.py Launches a Streamlit app with prompt input and image output

To run locally:

# Gradio
python app/gradio_app.py

# Streamlit
streamlit run app/streamlit_app.py

🧰 Requirements

pip install -r requirements.txt

🧠 Author

By Zahra Anvari


📜 License

This project is licensed under the MIT License. You are free to use, modify, and distribute it with attribution.

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Hands-on tutorials for generating and editing images using Stable Diffusion with Hugging Face Diffusers — includes text-to-image, inpainting, and image-to-image pipelines.

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