adjust_gamma
Adjust image brightness and contrast by modifying gamma values to correct exposure or enhance visual details in digital images.
Instructions
调整图片伽马值
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 | |
| gamma | Yes | 伽马值，1.0为原始，>1.0变亮，<1.0变暗 |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Implementation Reference
- tools/color_adjust.py:506-579 (handler)Core handler function implementing the gamma adjustment logic. Validates inputs, loads image using ImageProcessor, applies gamma correction via lookup table and PIL's point() method for RGB/L/ other modes, processes output, and returns JSON result.
async def adjust_gamma(image_source: str, gamma: float) -> list[TextContent]: """ 调整图片伽马值 Args: image_source: 图片数据（base64编码）或文件路径 gamma: 伽马值（0.1-3.0） Returns: 调整后的图片数据 """ try: # 验证参数 if not image_source: raise ValidationError("图片数据不能为空") if not validate_numeric_range(gamma, 0.1, 3.0): raise ValidationError(f"伽马值必须在0.1-3.0范围内: {gamma}") # 加载图片 image = processor.load_image(image_source) # 创建伽马校正查找表 gamma_table = [int(((i / 255.0) ** (1.0 / gamma)) * 255) for i in range(256)] # 应用伽马校正 if image.mode == 'RGB': # 对RGB图片分别处理每个通道 r, g, b = image.split() r = r.point(gamma_table) g = g.point(gamma_table) b = b.point(gamma_table) gamma_image = Image.merge('RGB', (r, g, b)) elif image.mode == 'L': # 对灰度图直接处理 gamma_image = image.point(gamma_table) else: # 其他模式先转换为RGB rgb_image = image.convert('RGB') r, g, b = rgb_image.split() r = r.point(gamma_table) g = g.point(gamma_table) b = b.point(gamma_table) gamma_image = Image.merge('RGB', (r, g, b)) # 输出处理后的图片 output_info = processor.output_image(gamma_image, "gamma") result = { "success": True, "message": f"伽马调整成功: 伽马值 {gamma}", "data": { **output_info, "gamma_value": gamma, "original_mode": image.mode, "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"伽马调整失败: {str(e)}" } return [TextContent(type="text", text=json.dumps(error_result, ensure_ascii=False))] - main.py:458-472 (registration)Tool registration via @mcp.tool() decorator in FastMCP server. Defines input schema using Pydantic Annotated fields and provides a synchronous wrapper that calls the async handler from color_adjust module using safe_run_async.
@mcp.tool() def adjust_gamma( 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")], gamma: Annotated[float, Field(description="伽马值，1.0为原始，>1.0变亮，<1.0变暗", gt=0)] ) -> str: """调整图片伽马值""" try: result = safe_run_async(color_adjust_gamma(image_source, gamma)) return result[0].text except Exception as e: return json.dumps({ "success": False, "error": f"调整伽马值失败: {str(e)}" }, ensure_ascii=False, indent=2) - tools/color_adjust.py:119-138 (schema)Explicit Tool schema definition for adjust_gamma in get_color_adjust_tools(), matching the registered input parameters (though not directly used in MCP registration).
Tool( name="adjust_gamma", description="调整图片伽马值", inputSchema={ "type": "object", "properties": { "image_source": { "type": "string", "description": "图片数据（base64编码）或文件路径" }, "gamma": { "type": "number", "description": "伽马值（0.1-3.0，1.0为原始值）", "minimum": 0.1, "maximum": 3.0 } }, "required": ["image_source", "gamma"] } ),