How to Make AI Generated Images: A Practical Guide — LiliDi Blog
Demystify how to make AI generated images with a practical, step-by-step guide. Learn about prompts, models, and ethical considerations for better results.
By lilidi editorial
How to Make AI Generated Images: A Practical Guide The allure of artificially intelligent image generation has moved from science fiction to everyday reality. However, the path to creating compelling AI generated images isn't always as straightforward as the viral examples suggest. This isn't magic; it's technology, and like any tool, understanding its mechanics is key to harnessing its power effectively. This guide will cut through the hype and provide a practical, realistic approach to making AI generated images. We'll cover the fundamental concepts, delve into prompt engineering, discuss model selection, and touch on crucial ethical considerations. Understanding the Fundamentals: What Powers AI Image Generation? Before you dive in, it's helpful to grasp the core components at play. AI image generation platforms don't "understand" images in a human sense. Instead, they operate on
complex mathematical models trained on vast datasets of images and their corresponding text descriptions. The Role of Models At the heart of every AI image generator is a model. Think of this as the "brain." These models, often based on architectures like Generative Adversarial Networks (GANs) or diffusion models, learn patterns, styles, and relationships between text and visual elements during their training phase. When you provide a text prompt, the model uses its learned knowledge to synthesize a new image that aligns with your input. Training Data: The Foundation of Creativity (and Bias) The quality and diversity of the training data are paramount. If a model is primarily trained on images of a specific demographic or artistic style, it will naturally tend to produce results reflecting that bias. This is a critical point often overlooked and directly impacts the variety and fairness
of the images generated. Crafting Effective Prompts: Your Conversation with the AI The "prompt" is your instruction to the AI. It's how you articulate your desired image. Mastering prompt engineering is the single most important skill for anyone looking to make AI generated images successfully. Be Specific, Be Descriptive Ambiguous prompts lead to ambiguous results. Instead of "a dog," try: "A golden retriever puppy, panting happily, sitting on a sun drenched beach, with a turquoise ocean in the background, photographic style, bright, high detail." Key Elements of a Strong Prompt Subject: What is the main focus? (e.g., "a medieval knight") Action/Pose: What is the subject doing? (e.g., "fighting a dragon," "reading a book") Environment/Background: Where is the scene set? (e.g., "in a misty forest," "on a futuristic cityscape") Style/Medium: What artistic style should it emulate? (e.g.,
"oil painting," "digital art," "hyperrealistic photo," "watercolor") Lighting: How is the scene lit? (e.g., "dramatic chiaroscuro," "soft studio lighting," "golden hour sunset") Mood/Atmosphere: What feeling should the image evoke? (e.g., "eerie," "joyful," "serene") Technical Descriptors: Specific camera details or rendering qualities. (e.g., "8k, ultra detailed, cinematic, volumetric lighting, Canon EOS R5") Using Negative Prompts Many platforms allow "negative prompts," where you specify what you don't want to see. This is incredibly useful for refining results. For example, if your character keeps appearing with an extra limb, a negative prompt like "extra limbs, mutated, disfigured" can help. Choosing the Right AI Image Generator The landscape of AI image generators is vast and ever evolving. Each platform has its strengths, weaknesses, and unique aesthetic biases. Some are
excellent for photorealistic images, while others excel at stylized art. DALL E 3 (via ChatGPT Plus/Copilot): Known for its strong understanding of complex prompts and ability to generate coherent text within images. Excellent for creative concepts. Midjourney: Renowned for its artistic flair and consistent aesthetic, especially in fantasy, sci fi, and illustrative styles. Can be trickier for photorealism without specific prompting. Stable Diffusion (various interfaces like InvokeAI, Automatic1111, DreamStudio): Open source and highly customizable. Offers unparalleled control for those willing to dive into technical details. Great for specific art styles and in painting/out painting. lilidi.ai: An emerging platform focused on delivering honest, high quality image and video generation. lilidi.ai emphasizes transparency in its model training and aims to provide users with tools that offer
tangible creative control without overpromising capabilities. It's a good option if you value clear expectations and reliable results for professional and personal projects. Experimentation is key here. Many platforms offer free trials or limited free usage, allowing you to find one that best suits your needs and creative vision. Iteration and Refinement: The Art of Repetition Rarely will your first prompt yield a perfect image. Expect to iterate. Generate multiple variations, adjust your prompt, add or remove details, and experiment with different styles until you get closer to your desired outcome. This iterative process is fundamental to how to make AI generated images effectively. Ethical Considerations and Responsible Use As powerful as these tools are, it's crucial to approach them responsibly. Copyright and Ownership Attribution and copyright for AI generated images are still
evolving legal areas. Be mindful of incorporating copyrighted styles, characters, or specific artists' work without permission or proper attribution. While a simple prompt might generate an image inspired by a famous artist, directly copying their unique style for commercial gain could raise legal questions. Deepfakes and Misinformation The ability to create highly realistic imagery presents a risk for generating deepfakes or spreading misinformation. Always consider the potential impact of your creations and use these tools ethically and responsibly. Platforms like lilidi.ai are built with a commitment to responsible AI, but user discretion remains paramount. Bias Reinforcement As mentioned, training data bias can lead to AI generating images that perpetuate stereotypes. Be aware of this and actively try to diversify your prompts to challenge these biases, rather than reinforce them.
Beyond Basic Generation: Advanced Techniques Once you're comfortable with basic prompting, you can explore more advanced techniques: ControlNet: A powerful add on for Stable Diffusion that allows you to guide generations using existing images (e.g., pose estimation, depth maps, edge detection). Image to Image (Img2Img): Start with an existing image and use a prompt to transform it, maintaining some of the original's composition or style. Inpainting/Outpainting: Edit specific parts of an image or expand its borders, seamlessly integrating new AI generated elements. These techniques offer significantly more control and can elevate your AI image generation capabilities beyond simple text to image. Conclusion Learning how to make AI generated images is a continuous journey of experimentation, refinement, and ethical consideration. It's a potent creative tool that, when understood and wielded
responsibly, can unlock unprecedented possibilities for artists, designers, marketers, and enthusiasts alike. Start simple, iterate often, and always think critically about the outputs and their implications. FAQ Q: Is it hard to make AI generated images? A: The basic process is relatively easy to learn, especially with user friendly platforms. However, consistently generating high quality, specific images requires practice, an understanding of prompt engineering, and iterative refinement. It's a skill that improves with experience. Q: Can I use AI generated images commercially? A: Generally, yes, but with important caveats. The terms of service vary between different AI platforms regarding commercial use and ownership. Additionally, be mindful of potential copyright issues if your AI generated image closely resembles existing copyrighted work, or if the training data itself contained
copyrighted material. Always check the specific platform's guidelines (like those on lilidi.ai). Q: What Related on LiliDi How LiliDi compares to Midjourney