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generation-workflows

generation-workflows

Operate Dream Textures prompt, image editing, ControlNet, history, seamless texture, and AI upscaling workflows in Blender.

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Documentation de la Skill

GitHub

name: generation-workflows description: "Operate Dream Textures prompt, image editing, ControlNet, history, seamless texture, and AI upscaling workflows in Blender." disable-model-invocation: true metadata: disco-role: operating license: GPL 3.0

Generation Workflows

Use this sub-skill when a task is about generating, modifying, repairing, extending, recalling, or upscaling images with Dream Textures from Blender's Dream panel, Image Editor, Shader Editor, prompt history, or selected Image Texture nodes.

Route here

  • Generate a texture or image from a prompt with Generate, prompt presets, negative prompts, scheduler/steps/CFG/seed, iterations, or file-batch prompt lines.
  • Modify a source image with image-to-image strength/fit, generated depth, depth map, or depth-only conditioning.
  • Make a texture seamless, interpret seamless axes, or understand auto-detection from source images and history hashes.
  • Inpaint or repair an image using alpha masks, prompt masks, the Mark Inpaint Area brush, or seamless inpainting.
  • Outpaint an image using tile size, top-left origin coordinates, overlap, and bounds checks.
  • Add ControlNet models, control images, conditioning scales, and image processors/baked control images to a prompt.
  • Export, import, validate, or edit prompt-history JSON.
  • Upscale from the AI Upscaling panel using a selected Image Texture node or open Image Editor image, tile size, blend, prompt guidance, and seamless axes.

Reroute

  • Installing the add-on, dependency variants, Hugging Face/DreamStudio credentials, model download/import/linking, checkpoint config choices, and model cache failures: use ../setup-and-models/SKILL.md.
  • 3D texture projection, viewport depth/color inputs, render-pass/compositor workflows, and scene annotation maps: use ../scene-integration/SKILL.md.
  • Backend class internals, custom backend implementation, generator actor details, scheduler enum implementation, and Diffusers pipeline diagnosis: use ../backend-and-api/SKILL.md.
  • Full Stable Diffusion inference, model downloads, or Blender UI automation are outside this sub-skill's bundled scripts; use the scripts here only for safe planning and validation.

Start fast

  1. Open an Image Editor or Shader Editor, show the sidebar with N, select the Dream tab, choose Backend and Model, then configure the Prompt, Size, Source Image, ControlNet, and Advanced panels before pressing Generate.
  2. Match the selected model type to the task: prompt-to-image/image-to-image use a prompt-to-image model; depth modes use a depth model; inpaint/outpaint use an inpainting model; upscaling uses the Stable Diffusion x4 upscaler model; ControlNet also needs compatible ControlNet model entries.
  3. Use numeric seeds for repeatability. Random seed stores the actual result seed in history; text seeds are hashed by the running Blender/Python process and should be recalled from history rather than assumed stable across sessions.
  4. Keep generation dimensions in 64-pixel increments for the UI workflow, and reduce size, steps, batch/iterations, preview accuracy, or tile size when VRAM errors appear.
  5. For outpaint math, run the bundled planner before entering coordinates in Blender:
python scripts/plan_outpaint_origin.py --source-size 512x960 --tile-size 512x512 --overlap 64 --region bottom-right
  1. Before importing or editing prompt-history JSON, validate it without Blender:
python scripts/validate_prompt_history_json.py path/to/prompt-history.json

References

  • references/image-generation.md maps Dream panel fields to generation arguments, prompt-to-image, source-image modify/depth modes, negative prompts, size/seed/scheduler/seamless/iterations, and ControlNet.
  • references/editing-and-upscaling.md covers inpainting, seamless repair, outpainting origin/overlap math, and AI upscaling tile/blend behavior.
  • references/prompting-history-seamless.md covers prompt presets, file-batch prompts, history export/import JSON, validation, and seamless auto-detection behavior.
  • references/troubleshooting.md maps common Blender UI and parameter failures to recovery steps.

Bundled safe scripts

  • scripts/plan_outpaint_origin.py computes and validates Dream Textures outpaint origins from source size, tile size, overlap, region, and strategy. It never imports Blender or downloads models.
  • scripts/validate_prompt_history_json.py validates Dream Textures prompt-history JSON keys, types, enums, and selected cross-field constraints. It never imports Blender or downloads models.
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