OpenClaw Backup
94 lines
2.0 KiB
Markdown
94 lines
2.0 KiB
Markdown
# Inpainting
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Replace or remove parts of an image using AI.
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## How It Works
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1. Provide source image
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2. Create mask (white = area to change)
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3. Optionally describe replacement content
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4. AI fills masked area matching surrounding context
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## Tools
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### DALL-E 2 (OpenAI)
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```python
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from openai import OpenAI
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client = OpenAI()
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response = client.images.edit(
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model="dall-e-2",
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image=open("image.png", "rb"),
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mask=open("mask.png", "rb"),
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prompt="A sunny beach with palm trees",
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size="1024x1024"
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)
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```
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**Requirements:**
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- Image must be square PNG
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- Mask: transparent areas = edit zone
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- Max 4MB per file
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### Stable Diffusion Inpaint
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```python
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from diffusers import StableDiffusionInpaintPipeline
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import torch
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pipe = StableDiffusionInpaintPipeline.from_pretrained(
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"runwayml/stable-diffusion-inpainting",
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torch_dtype=torch.float16
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)
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pipe.to("cuda")
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result = pipe(
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prompt="A fluffy cat",
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image=init_image,
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mask_image=mask,
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num_inference_steps=30,
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guidance_scale=7.5
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).images[0]
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```
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**Key parameters:**
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- `strength` — How much to change (0.5-1.0)
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- `guidance_scale` — Prompt adherence (5-15)
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### IOPaint (Local, Free)
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```bash
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# Install
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pip install iopaint
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# Run web UI
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iopaint start --model lama --port 8080
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```
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**Models:**
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- `lama` — Fast, good for object removal
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- `ldm` — Better quality, slower
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- `sd` — Stable Diffusion backend
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## Best Practices
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- **Extend mask slightly** — cover edges of object to remove
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- **Describe surroundings** — "grassy field" helps context
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- **Multiple passes** — for large areas, edit in chunks
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- **Clean up edges** — blend modes in photo editor
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## Object Removal (No Prompt)
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For pure removal without replacement:
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- Use LaMa model (designed for removal)
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- Leave prompt empty or minimal
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- AI infers from surrounding context
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## Common Issues
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- **Visible seams** — feather mask edges
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- **Wrong content** — be more specific in prompt
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- **Repeating patterns** — edit in smaller sections
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- **Color mismatch** — adjust levels after inpainting
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