AI image cleanup: ChatGPT, Leonardo, Stable Diffusion, and friends

End-to-end recipe for cleaning up AI-generated designs from ChatGPT, Leonardo, Stable Diffusion, and similar. Per-source tuning notes.

Different AI tools generate at different sizes, with different background styles, and produce different edge artifacts. The cleanup pipeline is mostly the same — what changes is the per-source tuning.

This article covers ChatGPT, Leonardo, Stable Diffusion, and other AI generators. For Midjourney specifically, see Midjourney cleanup — same pipeline, slightly different defaults.

The shared pipeline

Same shape across AI sources:

StepToolWhat it does
1Color Removal V2Removes the AI-generated background
2TrimCuts off the empty edges
3Speckle RemoverCleans up tiny stray AI pixels
4Transparency CleanerRemoves faint halos
5RepositionCenters on the target canvas

What changes per AI source: the Color Removal V2 settings and the source pixel sizes.

Per-source defaults

ChatGPT (DALL-E successor / GPT-Image)

  • Output size: 1024 × 1024 (default), 1024 × 1792 (portrait), 1792 × 1024 (landscape)
  • Backgrounds: typically clean and well-composed — usually easier for Color Removal V2 than Midjourney
  • Color Removal V2 settings:
    • Preset: Medium (standard; Base Threshold follows the preset)
    • ChatGPT subjects tend to have crisper edges than Midjourney, so little to no Halo Width is usually needed
  • Watch out: text inside ChatGPT-generated images usually doesn't survive cleanup. The Color Removal V2 step can eat into faint text strokes. If your design has text, generate the text separately (or add it via Watermark Text after the pipeline).

Leonardo

  • Output sizes: widely variable (512 × 512 to 1536 × 1536 typically, depending on model)
  • Backgrounds: vary by model — some Leonardo models produce clean backgrounds, others produce painterly textures
  • Color Removal V2 settings:
    • Preset: High (Leonardo backgrounds are often gradients; nudge Base Threshold up if needed)
    • Leonardo subjects often have softer edges than ChatGPT — run Transparency Cleaner or add a little Halo Width in Advanced
  • Watch out: Leonardo's built-in Alchemy upscaler produces much cleaner output than the base generator. Use Alchemy upscale in Leonardo before downloading if your Leonardo plan supports it — gives you a much better starting point for the ReadyPixl pipeline.

Stable Diffusion (local installs, hosted services like Replicate, ComfyUI)

  • Output sizes: wildly variable depending on your model and settings (768 × 768 typical for SD 1.5, 1024 × 1024 typical for SDXL)
  • Backgrounds: vary entirely by your prompt and model
  • Color Removal V2 settings: depend heavily on what you generated. Use the View mode in Color Removal V2 to test settings on one image before running the batch.
  • Watch out: Stable Diffusion outputs at low step counts or low CFG produce more artifacts. Quality of source matters most for SD batches. Good SDXL output cleans up beautifully; rushed SD output amplifies its own artifacts.

Other AI generators (Adobe Firefly, Recraft, Pika, etc.)

The pipeline shape is the same. Test Color Removal V2 settings on one output before running on a batch — every generator has slightly different background and edge characteristics.

Step-by-step (any AI source)

  1. Generate in your AI tool. Download the outputs to a folder.

  2. Open ReadyPixl. Drop the folder in.

  3. Add Color Removal V2 with the per-source settings above.

  4. Add Trim (defaults).

  5. Add Speckle Remover (defaults — Max Cluster Size 50).

  6. Add Transparency Cleaner. Set its slider to 30-40 to catch faint halos around the subject.

  7. Add Reposition for your target:

    • POD shirts: 4500 × 5400 @ 300 DPI
    • Etsy listing: 2000 × 2000 @ 72 DPI
    • Phone wallpaper: device-specific (1170 × 2532 for iPhone 13/14)
    • Social post: 2048 × 2048 @ 72 DPI

  8. Click Download All. Output ready.

  9. Save the pipeline as a preset per AI source. "ChatGPT → Merch," "Leonardo → Etsy," etc. Switching sources is one click.

Tips

  • Test on 1-2 images first. AI outputs vary a lot — what works for one batch might not work for the next.
  • Generate extras. AI quality is uneven. Generate 3-5 variants per concept, pipeline-run them all, pick the best at the end.
  • Save originals. Your ReadyPixl outputs are deliverables. Your raw AI generations are seeds.
  • Match cleanup pipeline to AI source. Don't run a Midjourney-tuned pipeline on ChatGPT output. The settings will be off.
  • Combine sources thoughtfully. A mixed batch of ChatGPT + Leonardo + Stable Diffusion outputs in one pipeline run will use the same Color Removal V2 settings for all of them — usually one source comes out worse than the others. Either separate by source or pick a middle-ground Color Removal V2 Preset.

Same upscale gap as Midjourney

AI sources tend to output at small sizes (512-1024 px). Print-on-demand sites want 4500 × 5400+. You can:

  • Use ReadyPixl AI Upscale before Reposition. It costs 10 credits per image because it calls an outside AI service.
  • Use the AI tool's built-in upscaler before downloading (Leonardo has Alchemy, Stable Diffusion has many upscaler nodes, and other generators have their own upscale options).
  • Accept that the design will be smaller relative to the target canvas. Reposition centers your subject — most POD sites accept this and print at the actual subject size, not the canvas size.

What AI cleanup can't fix

  • Bad anatomy / warped subjects — generate again in your AI tool with a better prompt
  • Misspelled / garbled text — generate without text, add text via Watermark Text after
  • Highly transparent subjects (glass, smoke, liquid) — these confuse Color Removal V2 regardless of source. Use AI Background Remover (Recraft model, 15 credits per use)
  • Very low-quality source generations — pipeline magnifies the source. Bad in = bad out.