Generating images with AI has moved from novelty to everyday workflow. Designers, marketers, and developers now use text-to-image models to prototype ideas, create placeholder art, and explore visual directions in minutes instead of days.
Why photorealism is hard
Photorealistic output requires models to get lighting, shadows, skin texture, reflections and perspective consistent at once. Small errors such as extra fingers, warped text, or mismatched light sources instantly break the illusion. Modern diffusion models handle this far better than earlier GANs because they iteratively denoise an image while conditioning on the prompt.
Writing better prompts
- Describe the subject first, then the setting, then the style.
- Name the camera and lens ("35mm, f/1.8, shallow depth of field") to nudge realistic optics.
- Specify lighting ("golden hour", "softbox studio light", "overcast").
- Use negative prompts to remove artifacts like blur, watermarks, or distorted hands.
- Iterate: change one variable at a time so you learn what each word does.
Practical workflow tips
- Start at low resolution to explore compositions quickly.
- Pick the best candidate and upscale it.
- Use inpainting to fix local problems instead of regenerating everything.
- Keep a prompt log so good results are reproducible.
Tools to try
There are many browser-based generators today. For Chinese-speaking users, a handy option is ai生图, which focuses on realistic photo-style results without any local GPU setup.
Ethics and licensing
Always check the usage terms of the tool you use, avoid generating misleading images of real people, and disclose AI-generated content where appropriate.
AI image generation is a skill: the more deliberately you prompt and iterate, the better your results become. Happy generating!
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