Stable Diffusion is a latent diffusion model, a kind of deep generative artificial neural network. It is primarily used to generate detailed images conditioned on text descriptions, though it can also be applied to generating image-to-image translations guided by a text prompt.


<aside> ⏰ The Time Capsule Exhibition


<aside> 💻 Debugging AI Artifacts


The Time Capsule Exhibition

<aside> 👉 Objective Create a series of 15 images depicting the evolution of human civilization across different historical eras using Stable Diffusion. The images will be combined into a timeline exhibition showing key milestones in human progress.


This involves utilizing Stable Diffusion prompt engineering to create a 15-image timeline depicting key milestones in human evolution and civilization progress. The images will showcase a consistent style and aesthetic while avoiding AI distortions.

<aside> 🛠 Process Overview


  1. Identified the 15 key eras/milestones in human evolution and civilization to depict
  2. For each era, I have engineered a detailed text prompt to describe the key visual aspects, human activities, architecture, attire, etc
  3. Standardized prompt structure and stylistic keywords to maintain consistency
  4. Use the example image to determine optimal Stable Diffusion parameters to match style (steps, sampler, CFG scale, etc)
  5. Generate images iteratively, refining prompts based on results
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