Mastering Text-to-Image Prompts: A Complete Guide to AI Image Creation

Writing effective prompts is the key to controlling the content and quality of AI-generated images. A richer, more precise description produces higher-quality results that closely match your creative vision. This guide walks you through the prompt techniques that help you turn ideas into images with text-to-image models such as Wan Text-to-Image V1 and V2, from simple starting formulas to a detailed vocabulary of visual elements.

Text-to-image models rely on two prompt-related parameters. The prompt parameter is the positive prompt, supporting both Chinese and English, where you describe the image you want to generate. The negative_prompt parameter describes what you do not want to see in the image. Wan Text-to-Image V2 additionally supports prompt_extend, which enables LLM-based intelligent rewriting of your prompt. It defaults to true, and Alibaba Cloud recommends keeping this default setting for the best results.

The basic formula is designed for newcomers and for users who want AI to serve as a source of inspiration. Its structure is: Prompt = Subject + Scene + Style. The subject is the main focus of the image, which can be a person, animal, plant, object, or an imaginative element. The scene is the environment surrounding the subject, including indoor or outdoor settings, season, weather, and lighting. The style defines the artistic look, such as realistic or abstract, guiding the model toward a particular visual effect. A simple example is describing a 25-year-old woman with a round face, looking at the camera, wearing elegant traditional clothing, shot as commercial photography outdoors with cinematic lighting in a half-body close-up with refined makeup and sharp edges.

The advanced formula suits users with some experience in AI image generation and adds detail to improve texture, richness, and expressiveness. Its structure is: Prompt = Subject (description) + Scene (description) + Style (definition) + Shot language + Atmosphere words + Detail modifiers. Subject description specifies features and actions, for example 'a cute 10-year-old Chinese girl wearing red clothes.' Scene description adds environmental details through adjectives or phrases. Style definition explicitly names the artistic approach, such as watercolor or comic style. Shot language covers framing and camera perspective. Atmosphere words convey mood, such as dreamy, lonely, or majestic. Detail modifiers refine the image further, covering light source position, props, environmental elements, and resolution. An example prompt describes a wool-felt giant panda in a peaked cap and blue police vest running in an animal-kingdom street at night, with felt texture, Pixar style, backlighting, and 4K quality.

Shot size describes how much of the subject appears in the frame, determined by the distance between camera and subject. Common shot sizes include close-up, which emphasizes emotion and fine detail, as in a portrait with a high-definition camera and a sunset backdrop; close shot, which frames a half-body portrait with a traditional costume and cinematic light; medium shot, which balances subject and environment, as in a stylish young woman in a mid-wide-angle view under bright sunlight; and long shot, which showcases a wide landscape, such as two small figures on a snowy mountaintop watching the sunset with golden light on the snow.

Camera angle is the viewpoint from which the scene is captured. An eye-level angle shows the subject at natural height, as in grazing sheep in a meadow with golden morning light. A top-down angle looks straight down, useful for revealing patterns, such as an aerial view of a frozen lake with a small boat surrounded by swirling blue water. A low-angle shot looks up at the subject to create a sense of grandeur, like a towering coconut tree in a tropical scene with light filtering through the leaves. An aerial angle captures a broad overview from high above, such as a village under heavy snow with roads and lights visible.

Lens type shapes how the image looks and feels. Macro lenses capture tiny subjects with extreme sharpness, suitable for product photography such as cherries and sparkling water with professional color grading. Ultra-wide lenses capture expansive scenes, as with an island under blue skies with sunlight filtering through leaves. Telephoto lenses compress distance and blur backgrounds to isolate the subject, as with a cheetah in a forest with a sharp face against a soft background. Fisheye lenses produce a distinctive, distorted look that exaggerates the center of the frame, creating strong visual impact.

Specifying a style tells the model which artistic approach to follow. Popular options include 3D cartoon, which suits playful character designs like a tennis player in a cartoon-rendered style; wasteland style, for post-apocalyptic scenes like a Martian city; pointillism, for soft, dotted textures reminiscent of Monet; surrealism, for dreamlike imagery such as a glowing pink river in deep grey; watercolor, for light, airy, dreamy paintings; clay style, for handcrafted figures; realism, for photorealistic still life; porcelain, for finely detailed ceramic subjects; 3D rendering, for volumetric, C4D-like visuals; ink wash painting, for minimal, poetic compositions with blank space; meticulous gongbi, for refined traditional Chinese brushwork; Chinese ink style, which blends traditional aesthetics with modern elements; and origami, for paper-folded sculptural subjects.

Lighting sets the emotional tone of an image. Natural light, including sunlight, moonlight, and starlight, creates realistic and serene atmospheres, such as morning sun piercing through treetops in a misty forest. Backlight outlines the subject with glowing edges and can add a dreamy halo, as with a model wrapped in silk. Neon light produces vibrant reflections on wet surfaces, ideal for urban night scenes after rain. Ambient light creates a soft, warm glow, such as floating lanterns drifting across a riverside at night with light shimmering on the water.

The strongest prompts combine elements from several categories. Start with a clear subject and scene using the basic formula, then layer in shot size, camera angle, lens type, style, and lighting from the advanced formula. Keep descriptions specific and avoid contradictions. Use the negative prompt to exclude unwanted elements, such as people in a flower-shop scene. Experiment with prompt_extend to see how intelligent rewriting enhances your input, and iterate by adjusting one element at a time to understand its effect. With practice, the prompt dictionary becomes a toolkit for reliably producing images that match your creative intent.