Find your landing page message
Connect a product’s value to a specific audience and write a clear first-screen message.
Edit images using AI on fal.ai. Style transfer, object removal, background changes, and more. Use when the user requests "Edit image", "Remove object", "Change background", "Apply style", or similar image editing tasks.
---
name: fal-image-edit
description: Edit images using AI on fal.ai. Style transfer, object removal, background changes, and more. Use when the user requests "Edit image", "Remove object", "Change background", "Apply style", or similar image editing tasks.
metadata:
author: fal-ai
version: "1.0.0"
---
# fal.ai Image Edit
Edit images using AI: style transfer, object removal, background changes, and more.
## How It Works
1. User provides image URL and editing instructions
2. Script selects appropriate model
3. Sends request to fal.ai API
4. Returns edited image URL
## Finding Models
To discover the best and latest image editing models, use the search API:
```bash
# Search for image editing models
bash /mnt/skills/user/fal-generate/scripts/search-models.sh --category "image-to-image"
# Search for specific editing capabilities
bash /mnt/skills/user/fal-generate/scripts/search-models.sh --query "image editing"
bash /mnt/skills/user/fal-generate/scripts/search-models.sh --query "inpainting"
bash /mnt/skills/user/fal-generate/scripts/search-models.sh --query "object removal"
bash /mnt/skills/user/fal-generate/scripts/search-models.sh --query "background removal"
```
Or use the `search_models` MCP tool with relevant keywords.
## Supported Operations
| Operation | Description |
|-----------|-------------|
| Style Transfer | Apply artistic style to image |
| Object Removal | Remove objects from image |
| Background Change | Change/replace background |
| Inpainting | Fill in masked areas |
| General Edit | Instruction-based edits |
## Usage
```bash
bash /mnt/skills/user/fal-image-edit/scripts/edit-image.sh [options]
```
**Arguments:**
- `--image-url` - URL of image to edit (required)
- `--prompt` - Description of desired edit (required)
- `--operation` - Edit operation: `style`, `remove`, `background`, `inpaint` (default: `style`)
- `--mask-url` - URL of mask image (required for inpainting/removal)
- `--strength` - Edit strength 0.0-1.0 (default: 0.75)
**Examples:**
```bash
# Style transfer
bash /mnt/skills/user/fal-image-edit/scripts/edit-image.sh \
--image-url "https://example.com/photo.jpg" \
--prompt "Convert to anime style" \
--operation style
# Remove object
bash /mnt/skills/user/fal-image-edit/scripts/edit-image.sh \
--image-url "https://example.com/photo.jpg" \
--prompt "Remove the person on the left" \
--operation remove
# Change background
bash /mnt/skills/user/fal-image-edit/scripts/edit-image.sh \
--image-url "https://example.com/portrait.jpg" \
--prompt "Place in a tropical beach setting" \
--operation background
# Inpainting with mask
bash /mnt/skills/user/fal-image-edit/scripts/edit-image.sh \
--image-url "https://example.com/photo.jpg" \
--mask-url "https://example.com/mask.png" \
--prompt "Fill with flowers" \
--operation inpaint
```
## MCP Tool Alternative
Use `search_models` MCP tool or `search-models.sh` to find the best current model for each operation (style transfer, object removal, background change, inpainting), then call `mcp__fal-ai__generate` with the discovered `modelId`.
## Output
```
Editing image...
Model: fal-ai/flux/dev/image-to-image
Operation: style transfer
Edit complete!
Image URL: https://v3.fal.media/files/abc123/edited.png
Dimensions: 1024x1024
```
JSON output:
```json
{
"images": [
{
"url": "https://v3.fal.media/files/abc123/edited.png",
"width": 1024,
"height": 1024
}
]
}
```
## Present Results to User
```
Here's your edited image:

• 1024×1024 | Operation: Style Transfer
```
## Model Selection Tips
- **General Editing**: Search for "image editing" models. Good for instruction-based changes.
- **Style Transfer**: Search for `image-to-image` category. Adjust strength: 0.3-0.5 for subtle, 0.7-0.9 for dramatic.
- **Object Removal**: Search for "eraser" or "object removal". Some work without masks.
- **Background Change**: Search for "background" or "kontext". Look for models that preserve subject identity.
- **Inpainting**: Search for "inpainting" or "fill". Requires binary mask (white = edit area).
## Mask Tips
For inpainting and some removal tasks:
- White pixels = areas to edit
- Black pixels = areas to preserve
- Use PNG format with transparency or solid colors
- Feathered edges create smoother transitions
## Troubleshooting
### Edit Too Subtle
```
The edit is barely visible.
Increase the strength parameter:
--strength 0.85
```
### Edit Too Dramatic
```
The edit changed too much of the image.
Decrease the strength parameter:
--strength 0.3
```
### Object Not Removed
```
The object wasn't fully removed.
Tips:
1. Be more specific in the prompt
2. Try using an explicit mask
3. Use the inpainting model for precise control
```
### Background Artifacts
```
The new background has artifacts around the subject.
Tips:
1. Use a cleaner source image
2. Try FLUX Kontext which handles edges better
3. Adjust the strength for smoother blending
```
---
name: fal-image-edit
description: Edit images using AI on fal.ai. Style transfer, object removal, background changes, and more. Use when the user requests "Edit image", "Remove object", "Change background", "Apply style", or similar image editing tasks.
metadata:
author: fal-ai
version: "1.0.0"
---
# fal.ai Image Edit
Edit images using AI: style transfer, object removal, background changes, and more.
## How It Works
1. User provides image URL and editing instructions
2. Script selects appropriate model
3. Sends request to fal.ai API
4. Returns edited image URL
## Finding Models
To discover the best and latest image editing models, use the search API:
```bash
# Search for image editing models
bash /mnt/skills/user/fal-generate/scripts/search-models.sh --category "image-to-image"
# Search for specific editing capabilities
bash /mnt/skills/user/fal-generate/scripts/search-models.sh --query "image editing"
bash /mnt/skills/user/fal-generate/scripts/search-models.sh --query "inpainting"
bash /mnt/skills/user/fal-generate/scripts/search-models.sh --query "object removal"
bash /mnt/skills/user/fal-generate/scripts/search-models.sh --query "background removal"
```
Or use the `search_models` MCP tool with relevant keywords.
## Supported Operations
| Operation | Description |
|-----------|-------------|
| Style Transfer | Apply artistic style to image |
| Object Removal | Remove objects from image |
| Background Change | Change/replace background |
| Inpainting | Fill in masked areas |
| General Edit | Instruction-based edits |
## Usage
```bash
bash /mnt/skills/user/fal-image-edit/scripts/edit-image.sh [options]
```
**Arguments:**
- `--image-url` - URL of image to edit (required)
- `--prompt` - Description of desired edit (required)
- `--operation` - Edit operation: `style`, `remove`, `background`, `inpaint` (default: `style`)
- `--mask-url` - URL of mask image (required for inpainting/removal)
- `--strength` - Edit strength 0.0-1.0 (default: 0.75)
**Examples:**
```bash
# Style transfer
bash /mnt/skills/user/fal-image-edit/scripts/edit-image.sh \
--image-url "https://example.com/photo.jpg" \
--prompt "Convert to anime style" \
--operation style
# Remove object
bash /mnt/skills/user/fal-image-edit/scripts/edit-image.sh \
--image-url "https://example.com/photo.jpg" \
--prompt "Remove the person on the left" \
--operation remove
# Change background
bash /mnt/skills/user/fal-image-edit/scripts/edit-image.sh \
--image-url "https://example.com/portrait.jpg" \
--prompt "Place in a tropical beach setting" \
--operation background
# Inpainting with mask
bash /mnt/skills/user/fal-image-edit/scripts/edit-image.sh \
--image-url "https://example.com/photo.jpg" \
--mask-url "https://example.com/mask.png" \
--prompt "Fill with flowers" \
--operation inpaint
```
## MCP Tool Alternative
Use `search_models` MCP tool or `search-models.sh` to find the best current model for each operation (style transfer, object removal, background change, inpainting), then call `mcp__fal-ai__generate` with the discovered `modelId`.
## Output
```
Editing image...
Model: fal-ai/flux/dev/image-to-image
Operation: style transfer
Edit complete!
Image URL: https://v3.fal.media/files/abc123/edited.png
Dimensions: 1024x1024
```
JSON output:
```json
{
"images": [
{
"url": "https://v3.fal.media/files/abc123/edited.png",
"width": 1024,
"height": 1024
}
]
}
```
## Present Results to User
```
Here's your edited image:

• 1024×1024 | Operation: Style Transfer
```
## Model Selection Tips
- **General Editing**: Search for "image editing" models. Good for instruction-based changes.
- **Style Transfer**: Search for `image-to-image` category. Adjust strength: 0.3-0.5 for subtle, 0.7-0.9 for dramatic.
- **Object Removal**: Search for "eraser" or "object removal". Some work without masks.
- **Background Change**: Search for "background" or "kontext". Look for models that preserve subject identity.
- **Inpainting**: Search for "inpainting" or "fill". Requires binary mask (white = edit area).
## Mask Tips
For inpainting and some removal tasks:
- White pixels = areas to edit
- Black pixels = areas to preserve
- Use PNG format with transparency or solid colors
- Feathered edges create smoother transitions
## Troubleshooting
### Edit Too Subtle
```
The edit is barely visible.
Increase the strength parameter:
--strength 0.85
```
### Edit Too Dramatic
```
The edit changed too much of the image.
Decrease the strength parameter:
--strength 0.3
```
### Object Not Removed
```
The object wasn't fully removed.
Tips:
1. Be more specific in the prompt
2. Try using an explicit mask
3. Use the inpainting model for precise control
```
### Background Artifacts
```
The new background has artifacts around the subject.
Tips:
1. Use a cleaner source image
2. Try FLUX Kontext which handles edges better
3. Adjust the strength for smoother blending
```
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Includes source scripts; review them before use. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.