image_variation
Create variations of input images while preserving core content. Adjust parameters like similarity strength, dimensions, and prompts to customize output. Ideal for generating creative edits or adapting visuals.
Instructions
Generate a new variation of the input image while maintaining its content.
Args:
image_paths: List of file paths of the original images (1-5)
prompt: Text for generating a variation image (optional)
negative_prompt: Text specifying attributes to exclude from generation
similarity_strength: Similarity between the original image and the generated image (0.2-1.0)
height: Output image height (pixels)
width: Output image width (pixels)
cfg_scale: Prompt matching degree (1-20)
Returns:
Dict: Dictionary containing the file path of the variation imageInput Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| cfg_scale | No | ||
| height | No | ||
| image_paths | Yes | ||
| negative_prompt | No | ||
| prompt | No | ||
| similarity_strength | No | ||
| width | No |
Implementation Reference
- The main handler function for the 'image_variation' tool. It validates inputs, encodes images to base64, constructs a JSON payload for the Bedrock 'generate_image' call with taskType 'IMAGE_VARIATION', generates the image, saves it, and returns the path.
async def image_variation( image_paths: List[str], prompt: str = "", negative_prompt: str = "", similarity_strength: float = 0.7, height: int = 512, width: int = 512, cfg_scale: float = 8.0, output_path: str = None, ) -> Dict[str, Any]: """ Generate a new variation of the input image while maintaining its content. Args: image_paths: List of file paths of the original images (1-5) prompt: Text for generating a variation image (optional) negative_prompt: Text specifying attributes to exclude from generation similarity_strength: Similarity between the original image and the generated image (0.2-1.0) height: Output image height (pixels) width: Output image width (pixels) cfg_scale: Prompt matching degree (1-20) output_path: Absolute path to save the image Returns: Dict: Dictionary containing the file path of the variation image """ try: # Validate image paths if len(image_paths) < 1 or len(image_paths) > 5: raise ImageError("image_paths list must contain 1-5 images.") if similarity_strength < 0.2 or similarity_strength > 1.0: raise ImageError("similarity_strength must be between 0.2 and 1.0.") # Read image files and encode to base64 encoded_images = [] for img_path in image_paths: with open(img_path, "rb") as image_file: encoded_images.append(base64.b64encode(image_file.read()).decode('utf8')) body = json.dumps({ "taskType": "IMAGE_VARIATION", "imageVariationParams": { "text": prompt, "negativeText": negative_prompt, "images": encoded_images, "similarityStrength": similarity_strength, }, "imageGenerationConfig": { "numberOfImages": 1, "height": height, "width": width, "cfgScale": cfg_scale } }) # Generate image image_bytes = generate_image(body) # Save image image_info = save_image(image_bytes, output_path=output_path) # Generate result result = { "image_path": image_info["image_path"], "message": f"Image variation completed successfully. Saved location: {image_info['image_path']}" } return result except Exception as e: raise McpError(f"Error occurred while image variation: {str(e)}") - aws_nova_canvas_mcp/server.py:34-34 (registration)The registration of the image_variation tool with the MCP server (currently commented out). The tool is imported earlier at line 10.
# mcp.add_tool(image_variation) - aws_nova_canvas_mcp/server.py:10-10 (registration)Import of the image_variation handler function in the server file.
from .tools.image_variation import image_variation - Function signature providing the input schema via type hints and defaults, used by MCP for tool schema.
async def image_variation( image_paths: List[str], prompt: str = "", negative_prompt: str = "", similarity_strength: float = 0.7, height: int = 512, width: int = 512, cfg_scale: float = 8.0, output_path: str = None, ) -> Dict[str, Any]: