apply_smooth
Reduce image noise and soften details by applying a smoothing filter to images. This tool processes image files or base64 data to create cleaner visual outputs.
Instructions
应用平滑滤镜
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| image_source | Yes | 图片源，可以是文件路径或base64编码的图片数据 |
Implementation Reference
- tools/filters.py:489-537 (handler)Core implementation of the apply_smooth tool handler. Loads the image from base64 data, applies PIL's ImageFilter.SMOOTH filter, generates output info using ImageProcessor, and returns JSON result.async def apply_smooth(image_data: str) -> list[TextContent]: """ 应用平滑滤镜 Args: image_data: 图片数据（base64编码） Returns: 应用滤镜后的图片数据 """ try: # 验证参数 if not image_data: raise ValidationError("图片数据不能为空") # 加载图片 image = processor.load_image(image_data) # 应用平滑滤镜 smooth_image = image.filter(ImageFilter.SMOOTH) # 输出处理后的图片 output_info = processor.output_image(smooth_image, "smooth") result = { "success": True, "message": "平滑滤镜应用成功", "data": { **output_info, "filter_type": "smooth", "size": image.size } } return [TextContent(type="text", text=json.dumps(result, ensure_ascii=False))] except ValidationError as e: error_result = { "success": False, "error": f"参数验证失败: {str(e)}" } return [TextContent(type="text", text=json.dumps(error_result, ensure_ascii=False))] except Exception as e: error_result = { "success": False, "error": f"平滑滤镜应用失败: {str(e)}" } return [TextContent(type="text", text=json.dumps(error_result, ensure_ascii=False))]
- main.py:327-338 (registration)MCP tool registration for apply_smooth using @mcp.tool() decorator. Wraps the filters.apply_smooth handler with safe_run_async and error handling, defining input schema via Annotated Field.def apply_smooth( image_source: Annotated[str, Field(description="图片源，可以是文件路径或base64编码的图片数据")] ) -> str: """应用平滑滤镜""" try: result = safe_run_async(filters_apply_smooth(image_source)) return result[0].text except Exception as e: return json.dumps({ "success": False, "error": f"应用平滑效果失败: {str(e)}" }, ensure_ascii=False, indent=2)
- tools/filters.py:121-134 (schema)Tool schema definition for apply_smooth in get_filter_tools(), specifying inputSchema requiring 'image_data' string.Tool( name="apply_smooth", description="应用平滑滤镜", inputSchema={ "type": "object", "properties": { "image_data": { "type": "string", "description": "图片数据（base64编码）" } }, "required": ["image_data"] } ),
- main.py:40-51 (registration)Import of the apply_smooth handler from tools.filters as filters_apply_smooth for use in main.py tool registration.from tools.filters import ( apply_blur as filters_apply_blur, apply_gaussian_blur as filters_apply_gaussian_blur, apply_sharpen as filters_apply_sharpen, apply_edge_enhance as filters_apply_edge_enhance, apply_emboss as filters_apply_emboss, apply_find_edges as filters_apply_find_edges, apply_smooth as filters_apply_smooth, apply_contour as filters_apply_contour, apply_sepia as filters_apply_sepia, apply_invert as filters_apply_invert )