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bbd0a6b201
Migrate workflow_templates/site into the frontend monorepo as apps/hub so the hub can use @comfyorg/design-system and shared packages. Changes to existing files: - pnpm-workspace.yaml: add @astrojs/sitemap, @astrojs/vercel, lucide-vue-next - eslint.config.ts: add hub ignores and i18n/import rule overrides - .oxlintrc.json: add hub scripts to ignore patterns - knip.config.ts: add hub workspace config apps/hub adaptations from source: - Replace local cn() with @comfyorg/tailwind-utils (19 files) - Integrate @comfyorg/design-system/css/base.css in global.css - Make TEMPLATES_DIR configurable via HUB_TEMPLATES_DIR env var - Add HUB_SKIP_SYNC flag for builds without template data - Remove Vite 8-incompatible rollupOptions.output.manualChunks - Fix stylelint violations (modern color notation, number precision) - Gitignore generated content (thumbnails, synced templates, AI cache)
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Inpainting
Inpainting selectively regenerates parts of an image using a mask while leaving the rest untouched. You paint a mask over the area you want to change, provide a text prompt describing the desired replacement, and the model fills in only the masked region. This is essential for fixing defects, replacing objects, or refining specific details in an otherwise finished image.
How It Works in ComfyUI
- Key nodes involved:
LoadImage,VAEEncodeForInpainting,CLIPTextEncode(positive + negative),KSampler,VAEDecode,SaveImage - Typical workflow pattern: Load image + mask → encode with inpainting-aware VAE node → encode text prompts → sample → decode → save
- The mask can be created using ComfyUI's built-in mask editor or loaded from an external image
Key Settings
- grow_mask_by: Expands the mask by a number of pixels, helping the regenerated area blend smoothly with the surrounding image. 6–8 pixels is typical. Too little causes visible seams; too much affects areas you wanted to keep.
- Denoise Strength: For inpainting, higher values (0.7–1.0) generally work best since you want the masked region to be fully regenerated. Lower values may produce inconsistent blending.
- Checkpoint: Dedicated inpainting models like
512-inpainting-emaproduce significantly better edge blending than standard checkpoints.
Tips
- Always expand your mask slightly beyond the target area. Tight masks create hard edges that look unnatural against the surrounding image.
- Describe what you want to appear in the masked region, not what you want to remove. For example, prompt "a clear blue sky" rather than "remove the bird."
- Use inpainting-specific checkpoints whenever possible. Standard models can inpaint but often struggle with seamless blending at mask boundaries.