A beginner’s guide to image generation with DALL-E 3
How to use DALL-E 3, plus a gallery of 77 different art styles to use when generating images
I’ve been experimenting with AI image generation tools Midjourney and DALL-E over the last few months in my capacity as assistant director of products and events at the Center for Cooperative Media at Montclair State University.
Several people asked me to give them tips and advice on how to use these and other AI-related tools after DALL-E 3 was released, so I decided to put together this guide as a one-stop resource for beginners who are interested in doing some image generation experiments of their own.
For me, the creation of this guide and my use of tools like DALL-E 3 for image generation stems from a practical necessity rather than any desire to overshadow the irreplaceable contributions of artists. The world of art, with its vast traditions, techniques, and emotions, is a realm that machines can mimic but never truly replicate. The genuine touch of an artist, the personal experiences that influence their work, and the years of honed skill and emotion they pour into each piece are unparalleled.
My goal in creating this guide is to empower individuals and publishers who may be operating with limited resources. For small teams or independent creators, sometimes all that’s needed is a fitting visual accompaniment to elevate their written content or event page.
In such scenarios, tools that generate images act as a bridge, offering a quick solution to a common challenge. Think of it as having a customizable stock image generator at your fingertips, allowing you to craft that ideal featured image for a blog post or event within minutes.
It’s crucial to understand that while these tools offer convenience, they aren’t a replacement for the artistry and expertise that professionals bring to the table. Nobody should be under the illusion of receiving accolades or recognition for merely generating an image via these platforms.
I view these generated images as a canvas for further enhancement. When paired with advanced editing tools like Adobe Photoshop, Adobe Illustrator, Canva, and others, the possibilities are endless. For example, while DALL-E 3 is much better at generating specifics and even accurate text (occasionally), it doesn’t always get it right.
In the example below, I took the image that DALL-E 3 generated, brought it into Adobe Photoshop, and replaced the garbled generated text with actual words and phrases.
Ultimately, this guide should be seen as a stepping stone — a starting point to help you get beyond the blank canvas — aiming to introduce and inspire curious creatives to new tools that can broaden their horizons in the world of graphics and illustrations.
More about this style gallery
Each art style in this guide is accompanied by a description, providing insights into its essence and characteristics, and a series of useful keywords to augment your initial prompts. To aid users in creating visuals using DALL-E 3, specific prompts and keywords have been crafted for each style.
When using this guide, it’s essential to approach it with an experimental mindset. DALL-E 3’s strength lies in its ability to interpret prompts in novel ways, so don’t hesitate to be creative with your inputs. Whether you’re looking to produce a traditional piece reminiscent of the Renaissance or dive into the pixelated realms of Digital Art, I hope this guide will be your compass, pointing you in the right direction on your creative journey.
These prompts should serve as a starting point, and I encourage users to tweak them, add their personal touch, or even combine styles to produce unique and bespoke illustrations. I plan to continue adding examples, styles, and techniques to the guide as I come across them.
A few tips + tricks to get the most out of DALL-E 3
- Use descriptive prompts: Be as detailed and descriptive as possible in your prompts. The more information you provide, the clearer the image DALL-E 3 can produce.
- Experiment with keywords: Try different combinations of keywords to see how slight variations can significantly change the output.
- Use specific numbers: If you want a certain number of objects in the image, specify that number in the prompt.
- Set the scene: Providing context or a setting can help DALL-E 3 understand the environment you want the main subject to be in.
- Try different styles: If you’re not satisfied with the initial result, consider specifying an art style or medium to guide the image generation.
- Take an iterative approach: Don’t hesitate to refine your prompts based on previous outputs. Iterative adjustments can lead to the perfect image.
- Limit ambiguity: While DALL-E 3 is great at interpreting prompts, overly ambiguous instructions might lead to unexpected results.
- Incorporate feedback: If you’re working on a project with others, gather feedback and incorporate it into revised prompts for better outcomes.
- Check recent updates: DALL-E 3, like many AI models, undergoes periodic updates and improvements. Stay updated with its capabilities.
- Use visual references: If possible, include references or examples in your prompts to give DALL-E 3 a clearer idea of what you’re aiming for.
- Explore chaos + randomness: Sometimes, allowing a bit of randomness can lead to surprising and delightful results. Don’t be afraid to let DALL-E 3 surprise you.
- Mind the resolution: Remember that DALL-E 3 has specific resolution capabilities. Ensure your prompts align with the resolution you desire.
- Stay updated with the OpenAI community: Join online forums or communities where users share their experiences, successes, and challenges with DALL-E 3. Learning from others can provide valuable insights.
It’s obvious that the fusion of art and technology offers a vast landscape of possibilities. With tools like DALL-E 3, we have an opportunity to explore and create in ways that were once beyond reach.
I hope this guide has provided a solid starting point of tips and information to help you navigate the world of DALL-E 3 more effectively. But remember, the real journey begins when you start experimenting on your own.
About the Center for Cooperative Media: The Center is a primarily grant-funded program of the School of Communication and Media at Montclair State University. Its mission is to grow and strengthen local journalism, and in doing so serve New Jersey residents. The Center is supported with operational and project funding from Montclair State University, the Geraldine R. Dodge Foundation, Democracy Fund, NJ Civic Information Consortium, Rita Allen Foundation, Inasmuch Foundation and the Independence Public Media Foundation. For more information, visit centerforcooperativemedia.org.