Skip to content

Latest commit

 

History

History
72 lines (50 loc) · 2.62 KB

OTHER.md

File metadata and controls

72 lines (50 loc) · 2.62 KB
Raw
title
Others

:fontawesome-regular-share-from-square: Others

Google Colab

Open In Colab{ align="right" }

Open and follow instructions to use an isolated environment running Dream.

Output Example:

Colab Notebook

Seamless Tiling

The seamless tiling mode causes generated images to seamlessly tile with itself creating repetitive wallpaper-like patterns. To use it, activate the Seamless Tiling option in the Web GUI and then select whether to tile on the X (horizontal) and/or Y (vertical) axes. Tiling will then be active for the next set of generations.

A nice prompt to test seamless tiling with is:

pond garden with lotus by claude monet"

Weighted Prompts

You may weight different sections of the prompt to tell the sampler to attach different levels of priority to them, by adding :<percent> to the end of the section you wish to up- or downweight. For example consider this prompt:

tabby cat:0.25 white duck:0.75 hybrid

This will tell the sampler to invest 25% of its effort on the tabby cat aspect of the image and 75% on the white duck aspect (surprisingly, this example actually works). The prompt weights can use any combination of integers and floating point numbers, and they do not need to add up to 1.

Thresholding and Perlin Noise Initialization Options

Under the Noise section of the Web UI, you will find two options named Perlin Noise and Noise Threshold. Perlin noise is a type of structured noise used to simulate terrain and other natural textures. The slider controls the percentage of perlin noise that will be mixed into the image at the beginning of generation. Adding a little perlin noise to a generation will alter the image substantially.

The noise threshold limits the range of the latent values during sampling and helps combat the oversharpening seem with higher CFG scale values.

For better intuition into what these options do in practice:

here is a graphic demonstrating them both

In generating this graphic, perlin noise at initialization was programmatically varied going across on the diagram by values 0.0, 0.1, 0.2, 0.4, 0.5, 0.6, 0.8, 0.9, 1.0; and the threshold was varied going down from 0, 1, 2, 3, 4, 5, 10, 20, 100. The other options are fixed using the prompt "a portrait of a beautiful young lady" a CFG of 20, 100 steps, and a seed of 1950357039.