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4 Best AI-Based Text-To-Image Generation Models

In this article, we will explore some of the best and most powerful AI-based text-to-image generation models available today.
Mohammed Wasim Akram
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Last Updated: December 19, 2022
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Text-to-image generation is a field of artificial intelligence that involves creating realistic images based on written descriptions. In recent years, significant progress has been made in the development of AI-based text-to-image generation models, which can be used for a variety of applications.

In this article, we will explore some of the best and most powerful AI-based text-to-image generation models available today.

Midjourney

Midjourney is an artificial intelligence program that creates images from textual descriptions. It is accessible through a Discord bot or through a web interface and can be used for rapid prototyping of artistic concepts or for brainstorming ideas in the advertising industry.

  • Founder Company: Midjourney is an independent research lab.
  • Main Researchers & Developers: The Midjourney team is led by David Holz, who co-founded Leap Motion, and includes researchers and developers Daniel, Max, Jack, Thomas, Red, Sam, Nadir, and Sebastian.
  • License Type: Proprietary
  • API Availability: It is currently not clear if Midjourney offers an API for developers to access its image generation capabilities.
  • Best Use Cases: Midjourney is primarily used by artists for rapid prototyping of artistic concepts to show to clients before starting work themselves. It is also used in the advertising industry to create original content and brainstorm ideas quickly.

DALL-E 2

DALL-E 2 is an improved version of the DALL-E model, developed by OpenAI. It is based on transformer-based architecture and is capable of generating high-quality and diverse images from text descriptions.

  • Founder Company: OpenAI
  • Main Researchers & Developers: Ian Goodfellow, Alec Radford, and the team at OpenAI
  • License Type: Proprietary
  • API Availability: Not available for public use
  • Best Use Cases: DALL-E 2 is best used for generating novel and diverse images based on a given text description. It has been used to create a wide variety of images, including animals, objects, and even fictional characters.

Stable Diffusion

Stable Diffusion is a deep learning, text-to-image model released in 2022. It is primarily used to generate detailed images based on text descriptions, but it can also be applied to other tasks such as inpainting, outpainting, and generating image-to-image translations guided by a text prompt.

  • Founder Company: Stability AI, CompVis LMU, Runway, with support from EleutherAI and LAION
  • Main Researchers & Developers: CompVis group at LMU Munich
  • License Type: Open Source
  • API Availability: Stable Diffusion's code and model weights have been released publicly and can run on most consumer hardware equipped with a modest GPU with at least 8 GB VRAM.
  • Best Use Cases: Stable Diffusion is best used for generating detailed and diverse images based on a given text description. It can be used to generate images of objects, animals, and even fictional characters, as well as modify existing images based on text descriptions.

Imagen

Imagen is a computer program that can create pictures from written descriptions. It uses large transformer language models, which are trained on a lot of text and understand the language very well, to turn written descriptions into pictures. Imagen's pictures are very realistic, and they achieved a high score on a test that measures how good a computer program is at creating pictures. Imagen was also preferred by people who compared it to other programs that create pictures from written descriptions.

  • Founder Company: Google Research and the Brain Team
  • Main Researchers & Developers: Google Research and the Brain Team
  • License Type: Proprietary
  • API Availability: It is not clear if Imagen can be used through an API.
  • Best Use Cases: Imagen may be useful for creating pictures for use in movies or video games, or for research purposes. It may have potential applications in areas such as creative content generation, data visualization, and education.

Conclusion

AI-based text-to-image generation models have made significant progress in recent years, allowing for the creation of high-quality and realistic images based on written descriptions.

The models mentioned in this article, including DALL-E, DALL-E 2, Midjourney, and Stable Diffusion, are some of the best and most powerful models available today and can be used for a variety of applications.

These models demonstrate the potential for AI to generate realistic and diverse images based on written descriptions, and it is likely that we will see even more progress in this field in the future.

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