> For the complete documentation index, see [llms.txt](https://docs.atlas.design/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.atlas.design/atlas-ai-studio-overview/node-index/image-nodes/image-generation-nodes.md). # Image Generation Nodes This section introduces the core nodes used for **Text → Image** generation and **Image → Text** extraction. ## When to use image generation nodes * **Concept exploration.** Use Text → Image (Fast) for rapid ideation, thumbnail generation, and quick variations during pre-production. Spending minimal credits to iterate on direction. * **Production-quality concept art.** Use Text → Image (High Quality) when the output will be referenced by downstream nodes (image-to-3D, video, retexturing) or shown to stakeholders. * **Reference description extraction.** Use Describe Image (image-to-text) to convert visual references into structured prompts. The output text feeds into other generation nodes for consistent style transfer. * **Procedural textures and patterns.** Use Procedural Image Builder for tileable textures, repeating patterns, and parametric variations across material libraries. * **Asset library generation.** Pair generation nodes with Create Image List from [Utility Nodes](/atlas-ai-studio-overview/node-index/utility-nodes.md) to produce families of variants in a single workflow run.
*** ### **Text → Image** (Fast) The **Text → Image (Fast)** node generates images quickly based on a text prompt.\ It uses a lightweight backend optimized for **speed** rather than fidelity. This node is ideal when you need: * rapid ideation * quick thumbnails * early explorations of a concept * instant variations The output is less detailed and less accurate compared to the **High Quality** version of the node, but significantly faster.
*** ### Text **→** Image (High Quality) Node The **Text → Image (High Quality)** node produces **high-fidelity, detailed images**.\ It uses **different backends**, allowing you to choose based on rendering styles and strengths. #### Key Features * best visual quality among text-only generation nodes * multiple backends → diverse interpretations * good for environments, props, characters, concept art * consistent structure and lighting compared to faster models #### Example: Fast v. High Quality Both nodes receive the same prompt. The Fast node generates a quick idea; the High Quality node generates a polished version suitable for downstream workflows such as: * Image → 3D * Text + Image → Image * Edit Image with Text * Marketing assets
*** ### Describe Image Node The **Describe Image** node converts an image into structured or descriptive text. The system prompt controls what type of information is extracted. These nodes can be powerful ways to craft custom, detailed prompts for image generation. #### You can request: * scene description * object list * spatial layout * material analysis * asset identification * style breakdown * inferred function or purpose
#### Example Use Cases * Describe the objects in a rendered scene * Extract the composition of a top-down plan * Identify modular parts of a building * Produce a clean text prompt for concept art * Provide metadata for Make3D or Auto Mesh Transform ### Describe Images Node The multi-image variant of Describe Image: converts multiple images into structured or descriptive text, with the same request types and system-prompt control described above. ### Procedural Image Builder Generates textures and materials using algorithmic patterns rather than AI synthesis. Creates geometric, noise-based, or mathematical designs suitable for tiling backgrounds, UI elements, and placeholder art.
* **Pattern types** — Voronoi, Perlin noise, grid, checkerboard, and other mathematically defined textures. * **Output resolution** — Configurable width and height for the generated image. * **Tileable option** — Ensures seamless wrapping for repeated textures across surfaces. * **Parameter inputs** — Scale, seed, color palette, and pattern-specific controls adjust the visual result. * **Deterministic** — Identical parameters always produce the same output; no randomness unless seed is changed. * **Backend selector** — Some backends offer extended pattern libraries or performance optimizations. **Useful for:** rapid prototyping of environmental textures, UI backgrounds, stylized materials for low-poly assets, and placeholder art during early production phases. * **Code-generated output** — Produces images through generated code that constructs patterns, gradients, and compositions. ## Common pitfalls * **Shipping Fast output as production assets.** The Text → Image (Fast) node produces visibly lower detail and accuracy than the Text → Image (High Quality) node. Using it for final assets yields results unsuitable for downstream work such as Image → 3D. * **Picking a High Quality backend without testing.** The Text → Image (High Quality) node exposes multiple selectable backends with distinct rendering styles. Choosing one that does not match the intended style direction wastes iterations; test a few with the same prompt early to lock one in. * **Re-rolling instead of editing.** Once a generation is close, re-running the whole prompt discards the parts that already worked. Refine specific aspects with [Image Edit Nodes](/atlas-ai-studio-overview/node-index/image-nodes/image-edit-nodes.md) for faster, more controlled iteration. * **Asking a text-to-image node for seamless textures.** Text-to-image nodes do not guarantee wrapping edges, so repeated results show visible seams. Use the Procedural Image Builder node with the Tileable option for repeating textures. ## Related nodes * [Image Edit Nodes](/atlas-ai-studio-overview/node-index/image-nodes/image-edit-nodes.md) — refine and modify images generated here without re-rolling the whole prompt. * [2D Post Processing Nodes](/atlas-ai-studio-overview/node-index/image-nodes/2d-post-processing-nodes.md) — camera framing, upscaling, background removal, and outpainting for finalizing generated images. * [Mesh Nodes](/atlas-ai-studio-overview/node-index/mesh-nodes.md) — image-to-3D nodes consume the output of image generation nodes; image quality at this stage affects 3D output. * [Utility Nodes](/atlas-ai-studio-overview/node-index/utility-nodes.md) — Create Image List for batching and Text Generation (LLM) for prompt refinement. * [Input Nodes](/atlas-ai-studio-overview/node-index/input-nodes.md) — Input Text supplies prompts, and Input Image supplies reference images. ## Frequently asked questions **Which backend should I use for the Text → Image (High Quality) node?** The Text → Image (High Quality) node supports multiple backends, each with different rendering strengths across photorealistic, illustrative, and stylized aesthetics. Run a few backends with the same prompt early in the project to compare. Lock in one backend per asset class and document the choice so the team uses it consistently. **How does the Describe Image node differ from a captioning tool?** The Describe Image node converts an image into structured or descriptive text, and its system prompt controls what is extracted: scene description, object list, spatial layout, material analysis, asset identification, style breakdown, or inferred function. The output is designed to feed back into prompt-driven image generation, not only to read as a human caption. **Can I generate the same image twice from the same prompt?** Yes. Fix the seed parameter to the same value and use the same backend to reproduce a result. Different seeds produce different variations. The Procedural Image Builder node is likewise deterministic: identical parameters always produce the same output unless the seed is changed. **How do I prevent style drift across a batch of assets?** Two patterns work. First, extract a description from a canonical reference with the Describe Image node, then feed that description into every batch prompt via Combine Text in [Utility Nodes](/atlas-ai-studio-overview/node-index/utility-nodes.md). Second, use Text + Image → Image in [Image Edit Nodes](/atlas-ai-studio-overview/node-index/image-nodes/image-edit-nodes.md) with a consistent style reference for every asset in the set. **When should I use the Procedural Image Builder node instead of a text-to-image node?** Use the Procedural Image Builder node when you need textures and materials built from algorithmic patterns such as Voronoi, Perlin noise, grids, and checkerboards, rather than AI synthesis. It suits tiling backgrounds, UI elements, and placeholder art, and its output width and height are configurable. **Are generated textures from the Procedural Image Builder node tileable?** The Tileable option ensures seamless wrapping. Enable it for textures intended for repeating UV maps, and leave it disabled for one-off images. Scale, seed, color palette, and pattern-specific controls adjust the visual result. **What can I use a generated image for downstream?** A polished image from the Text → Image (High Quality) node feeds downstream workflows including Image → 3D, Text + Image → Image, Edit Image with Text, and marketing assets. Descriptions produced by the Describe Image node can also supply metadata for Make3D or Auto Mesh Transform. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. 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