Text to Image prompts

Text-to-image prompts, also known as text-based concepts into visual imagery, refer to a technique or process of generating visual images based on textual descriptions or prompts. It involves using artificial intelligence (AI) models capable of understanding and interpreting text and then generating corresponding images that represent the given textual input.

These models typically utilize deep learning architectures, such as generative adversarial networks (GANs) or variational autoencoders (VAEs), to generate the images. The process involves training the AI model on large datasets that contain pairs of text descriptions and corresponding images. The model learns to associate textual concepts with visual patterns and can then generate new images based on given text inputs.

For example, a text-to-image model trained on a dataset of animal descriptions could generate realistic images of animals based on textual prompts like "a brown horse standing in a meadow" or "a red bird perched on a branch." The model would generate images that attempt to visually represent the described concepts.

Text-to-image prompts have various applications, including computer vision, creative arts, and design. They can be used to generate realistic images for various purposes, such as creating visual content, prototyping, or assisting in the creative process. Additionally, they can be used as a tool for exploring and visualizing textual data or aiding in the generation of visual assets in areas like graphic design or game development.

It's worth noting that the capabilities of text-to-image models can vary depending on the specific architecture and training data used. While some models can generate reasonably realistic and detailed images, others may produce more abstract or stylized representations. The technology is continually evolving, and newer models may offer improved performance and quality in generating images from textual prompts.

Tips to create prompt item list

The prompt items, usually created using CHAT GPT3.5 with this prompt:

help me create a list from the list i give; the list is for/to/use for 
translating text-based concepts into visual imagery:
- remove any item that has similiar effect,
- write without description.
- suggest new item
- count removed item
- count new/added item
if you understand, reponse only in "OK"

or/then

list of [subject] that suit visual imagery concepts that correspond 
to the text-based concepts, combine the result with [sub-subject]

It's not perfect, but if you are lazzy, I create https://poe.com/prompimix-assistant

Learn it

• https://www.youtube.com/watch?v=9H0oOexrupY
• https://www.youtube.com/watch?v=UK8DZybg5Gs
• https://www.youtube.com/watch?v=UK8DZybg5Gs

Explore and Limitation

1. Let's put this in short explanation, if you use "toothbrush moustache" and you she male/female with chaplin/hitler look, then you know IT already know that information and draws.
2. While they refuse to make stereotype, they think in stereotype.