Deep Daze: Generate images from text prompts

Understand the project

Practical overview

Use it for local, experimental prompt-to-image generation when you can work with a Python CLI and have a supported GPU.

People experimenting with text-guided image generation through a command-line workflow.
Python users with an Nvidia or AMD GPU who want configurable image-generation settings.
Users exploring image-guided optimization or story-style generation from longer text.

Generate an image from a short descriptive phrase.
Optimize generation using a PNG or JPG image input.
Create a sequence of images by optimizing successive text windows in story mode.

Before you choose

The project is distributed as a Python package and is licensed under MIT. Its README documents Nvidia or AMD GPU requirements.

GPU memory is a practical constraint: the README recommends 16 GB VRAM and describes 4 GB as a minimum only for very low settings.
Prompts are limited to fewer than 77 tokens unless story mode is used.
Story mode requires saving progress to visualize transitions.
The project provides CLI and notebook entry points; the README links two Google Colab notebooks.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Install the Python package and use the documented CLI example to generate an image from a short text prompt.

Python
An Nvidia or AMD GPU; the README recommends 16 GB VRAM and lists 4 GB as a minimum for very low settings.

Install the package with the command below.
Documented command
```
pip install deep-daze
```
Run imagine "a house in the forest".

The CLI starts image generation from the supplied text prompt.

Evidence and transparency

Source record details

Source availability: Active
Sources checked: 16 October 2026
Original website title: lucidrains/deep-daze · Official homepage title · retained in its source language