Stable Diffusion is a type of neural network* model specifically designed for generating images. It works by taking a text description and gradually transforming a random pattern of pixels into a coherent image that matches the description, using its learned understanding of how words relate to visual elements.
This innovative approach allows Stable Diffusion to create a wide range of images, from realistic photographs to artistic renderings, all based on textual descriptions, with processes below:
1. Text-to-Image Conversion: Stable Diffusion takes a text prompt and generates an image that corresponds to the description. This is achieved through a process known as diffusion, which involves gradually refining random noise into a structured image.You can try generate Images with prompts: https://stablediffusionweb.com/#ai-image-generator
*Neural Network: A neural network is a computer system modeled after the human brain that learns from data by adjusting connections between layers of artificial neurons. It's used in AI to recognize patterns and make decisions, such as identifying objects in images or understanding human speech.
Source and Links:
- https://stablediffusion.gitbook.io/overview/stable-diffusion-overview/license
- https://en.wikipedia.org/wiki/Stable_Diffusion
- https://huggingface.co/runwayml/stable-diffusion-v1-5
YouTube video:
- https://www.youtube.com/watch?v=kqXpAKVQDNU (8min at 1.75speed) - How to install Python 3.10.6, Git, A1111 UI for Stable Diffusion and update (Git Pull), AI Model download, Style management.
- https://www.youtube.com/watch?v=nJlHJZo66UA
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