🪄 ImageSorcery MCP

import os from typing import Annotated, Any, Dict, List, Optional import cv2 import numpy as np from fastmcp import FastMCP from pydantic import Field # Import the central logger and config from imagesorcery_mcp.config import get_config from imagesorcery_mcp.logging_config import logger def register_tool(mcp: FastMCP): @mcp.tool() def blur( input_path: Annotated[str, Field(description="Full path to the input image (must be a full path)")], areas: Annotated[ List[Dict[str, Any]], Field( description=( "List of areas to blur. Each area should have: " "a rectangle ({'x1', 'y1', 'x2', 'y2'}) or a polygon ({'polygon': [[x,y],...]}). " "Optionally, include 'blur_strength' (int, odd number, default 15) for each area." ) ), ], invert_areas: Annotated[ bool, Field( description="If True, blurs everything EXCEPT the specified areas. Useful for background blurring." ), ] = False, output_path: Annotated[ Optional[str], Field( description=( "Full path to save the output image (must be a full path). " "If not provided, will use input filename " "with '_blurred' suffix." ) ), ] = None, ) -> str: """ Blur specified rectangular or polygonal areas of an image using OpenCV. This tool allows blurring multiple rectangular or polygonal areas of an image with customizable blur strength. Each area can be a rectangle defined by a bounding box [x1, y1, x2, y2] or a polygon defined by a list of points. The blur_strength parameter controls the intensity of the blur effect. Higher values result in stronger blur. It must be an odd number (default is 15). If `invert_areas` is True, the tool will blur everything EXCEPT the specified areas. Returns: Path to the image with blurred areas """ logger.info(f"Blur tool requested for image: {input_path} with {len(areas)} areas, invert_areas={invert_areas}") # Check if input file exists if not os.path.exists(input_path): logger.error(f"Input file not found: {input_path}") raise FileNotFoundError(f"Input file not found: {input_path}. Please provide a full path to the file.") # Generate output path if not provided if not output_path: file_name, file_ext = os.path.splitext(input_path) output_path = f"{file_name}_blurred{file_ext}" logger.info(f"Output path not provided, generated: {output_path}") # Read the image using OpenCV logger.info(f"Reading image: {input_path}") img = cv2.imread(input_path) if img is None: logger.error(f"Failed to read image: {input_path}") raise ValueError(f"Failed to read image: {input_path}") logger.info(f"Image read successfully. Shape: {img.shape}") # Create a mask for the areas to be blurred (or not blurred if invert_areas is True) mask = np.zeros(img.shape[:2], dtype=np.uint8) # Populate the mask based on areas for area in areas: if "polygon" in area: polygon_points = np.array(area["polygon"], dtype=np.int32) cv2.fillPoly(mask, [polygon_points], 255) elif "x1" in area and "y1" in area and "x2" in area and "y2" in area: x1, y1, x2, y2 = area["x1"], area["y1"], area["x2"], area["y2"] cv2.rectangle(mask, (x1, y1), (x2, y2), 255, -1) else: logger.warning("Skipping area due to missing 'polygon' or 'x1,y1,x2,y2' keys.") continue # If invert_areas is True, invert the mask if invert_areas: mask = cv2.bitwise_not(mask) logger.info("Inverting blur areas: blurring everything EXCEPT the specified regions.") else: logger.info("Applying blur to specified areas.") # Apply blur to the entire image (this will be used for the masked regions) # Use the blur_strength from the first area, or config default config = get_config() global_blur_strength = areas[0].get("blur_strength", config.blur.strength) if areas else config.blur.strength if global_blur_strength % 2 == 0: global_blur_strength += 1 logger.warning(f"Adjusted global blur_strength to odd number: {global_blur_strength}") full_blurred_img = cv2.GaussianBlur(img, (global_blur_strength, global_blur_strength), 0) # Combine the original image and the fully blurred image using the mask # Where mask is 255 (white), use the blurred image. Where mask is 0 (black), use the original image. result_img = np.where(mask[:, :, None] == 255, full_blurred_img, img) # Create directory for output if it doesn't exist output_dir = os.path.dirname(output_path) if output_dir and not os.path.exists(output_dir): logger.info(f"Output directory does not exist, creating: {output_dir}") os.makedirs(output_dir) logger.info(f"Output directory created: {output_dir}") # Save the image with blurred areas logger.info(f"Saving blurred image to: {output_path}") cv2.imwrite(output_path, result_img) logger.info(f"Blurred image saved successfully to: {output_path}") return output_path