64 lines
2.1 KiB
Markdown
64 lines
2.1 KiB
Markdown
---
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name: image-edit
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description: Edit images using AI with text prompts and input images. Use this skill when the user wants to modify or transform an existing image with AI editing.
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---
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# Image Edit
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Edit images with AI by combining source images with text prompts via `python3 scripts/image_edit.py edit <prompt> <image_path> [options]`.
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## Commands
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| Command | Args | Description |
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|---------|------|-------------|
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| `edit` | `<prompt> <image_path> [--width W] [--height H] [--steps N] [--cfg-scale N]` | Edit image with prompt |
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## Options
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| Option | Default | Range | Description |
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|--------|---------|-------|-------------|
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| `--width` | 1024 | 128-2048 | Output image width in pixels |
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| `--height` | 1024 | 128-2048 | Output image height in pixels |
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| `--steps` | 40 | 5-100 | Number of inference steps |
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| `--seed` | null | 0-4294967295 | Random seed (null = random) |
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| `--cfg-scale` | 4 | 0-10 | True CFG scale for guidance |
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| `--negative-prompt` | "" | - | Negative prompt to avoid |
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## Examples
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```bash
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# Basic edit
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python3 scripts/image_edit.py edit "make it look like oil painting" photo.jpg
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# Style transfer
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python3 scripts/image_edit.py edit "convert to anime style" portrait.png
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# Object modification
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python3 scripts/image_edit.py edit "change the car color to red" street.jpg --steps 50
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# With negative prompt
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python3 scripts/image_edit.py edit "add a sunset background" landscape.png --negative-prompt "water, ocean"
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```
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## Workflow
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1. Provide a `prompt` describing the desired edit
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2. Provide an `image_path` to the source image (PNG, JPG, etc.)
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3. Script converts image to base64 and sends to API
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4. Saves edited image as `edited_[timestamp].jpg`
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5. Returns image path: `edited_1234567890.jpg [12345]`
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## Output Format
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- Success: `Image saved: filename.jpg [id]`
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- Error: `Error: message` (to stderr)
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- Images saved to current working directory as JPEG files
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## Notes
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- Requires `CHUTES_API_TOKEN` in environment
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- Supports up to 3 input images (currently uses first image)
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- Input file must be a valid image format (PNG, JPG, etc.)
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- Output is always JPEG format to save memory
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- Images are saved locally, not returned as base64 to save memory
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