MCP Camera Tool

#!/usr/bin/env python3 """ 图像分析服务 提供基本的图像分析功能 """ import cv2 import numpy as np from typing import Dict, Any, Optional import base64 import logging logger = logging.getLogger(__name__) class ImageAnalyzer: """图像分析服务类""" def __init__(self): pass def analyze_brightness(self, image: np.ndarray) -> float: """分析图像亮度""" # 转换为灰度图 gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # 计算平均亮度 brightness = np.mean(gray) return float(brightness) def analyze_color_distribution(self, image: np.ndarray) -> Dict[str, float]: """分析图像颜色分布""" # 分离颜色通道 b, g, r = cv2.split(image) # 计算各通道平均值 color_dist = { "red_mean": float(np.mean(r)), "green_mean": float(np.mean(g)), "blue_mean": float(np.mean(b)) } return color_dist def detect_edges(self, image: np.ndarray) -> int: """检测图像边缘数量""" # 转换为灰度图 gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # 应用Canny边缘检测 edges = cv2.Canny(gray, 50, 150) # 计算边缘像素数量 edge_count = np.sum(edges > 0) return int(edge_count) def analyze_image_from_base64(self, image_base64: str) -> Optional[Dict[str, Any]]: """从Base64编码的图像数据进行分析""" try: # 解码Base64图像 image_data = base64.b64decode(image_base64) # 转换为numpy数组 nparr = np.frombuffer(image_data, np.uint8) # 解码图像 image = cv2.imdecode(nparr, cv2.IMREAD_COLOR) if image is None: logger.error("无法解码图像数据") return None # 执行各种分析 analysis_result = { "dimensions": { "width": image.shape[1], "height": image.shape[0], "channels": image.shape[2] if len(image.shape) > 2 else 1 }, "brightness": self.analyze_brightness(image), "color_distribution": self.analyze_color_distribution(image), "edge_count": self.detect_edges(image) } return analysis_result except Exception as e: logger.error(f"图像分析过程中发生错误: {e}") return None def get_basic_analysis(self, image_base64: str) -> str: """获取图像的基本分析结果（文本格式）""" analysis = self.analyze_image_from_base64(image_base64) if analysis is None: return "图像分析失败" # 格式化分析结果 result = f"""图像分析结果: 尺寸: {analysis['dimensions']['width']}x{analysis['dimensions']['height']} 亮度: {analysis['brightness']:.2f} 颜色分布: - 红色平均值: {analysis['color_distribution']['red_mean']:.2f} - 绿色平均值: {analysis['color_distribution']['green_mean']:.2f} - 蓝色平均值: {analysis['color_distribution']['blue_mean']:.2f} 边缘数量: {analysis['edge_count']}""" return result