285 lines
8.5 KiB
Python
285 lines
8.5 KiB
Python
#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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"""
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API客户端调用示例
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演示如何使用三个核心接口
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"""
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import requests
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import json
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import os
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from typing import List, Dict, Optional
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# API基础地址
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API_BASE = "http://localhost:8000"
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class FaceAPIClient:
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"""人脸特征API客户端"""
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def __init__(self, base_url: str = "http://localhost:8000"):
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self.base_url = base_url.rstrip('/')
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def extract_feature(self, image_path: str) -> Optional[List[float]]:
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"""
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接口1: 提取人脸特征
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Args:
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image_path: 图像文件路径
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Returns:
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特征向量列表,失败返回None
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"""
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url = f"{self.base_url}/api/extract_feature"
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try:
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with open(image_path, "rb") as f:
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files = {"image": f}
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response = requests.post(url, files=files)
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response.raise_for_status()
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result = response.json()
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if result["success"]:
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print(f"✓ 特征提取成功")
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print(f" - 特征维度: {result['feature_dim']}")
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print(f" - 质量检查: {'通过' if result['quality_passed'] else '未通过'}")
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print(f" - 处理时间: {result['processing_time']:.3f}秒")
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return result["feature"]
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else:
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print(f"✗ 特征提取失败: {result['message']}")
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return None
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except FileNotFoundError:
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print(f"✗ 文件不存在: {image_path}")
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return None
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except Exception as e:
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print(f"✗ 请求失败: {e}")
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return None
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def compare_features(self, feature1: List[float], feature2: List[float]) -> Optional[Dict]:
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"""
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接口2: 对比两个特征向量
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Args:
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feature1: 特征向量1
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feature2: 特征向量2
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Returns:
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对比结果字典,失败返回None
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"""
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url = f"{self.base_url}/api/compare_features"
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try:
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data = {
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"feature1": feature1,
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"feature2": feature2
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}
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response = requests.post(url, json=data)
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response.raise_for_status()
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result = response.json()
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if result["success"]:
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print(f"✓ 特征对比成功")
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print(f" - 相似度: {result['similarity']:.4f}")
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print(f" - 判断结果: {'同一人' if result['is_same_person'] else '不是同一人'}")
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print(f" - 阈值: {result['threshold']}")
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return result
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else:
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print(f"✗ 特征对比失败: {result['message']}")
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return None
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except Exception as e:
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print(f"✗ 请求失败: {e}")
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return None
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def compare_image_feature(self, image_path: str, feature: List[float]) -> Optional[Dict]:
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"""
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接口3: 对比图像和特征向量
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Args:
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image_path: 图像文件路径
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feature: 目标特征向量
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Returns:
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对比结果字典,失败返回None
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"""
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url = f"{self.base_url}/api/compare_image_feature"
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try:
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with open(image_path, "rb") as f:
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files = {"image": f}
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data = {"feature": json.dumps(feature)}
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response = requests.post(url, files=files, data=data)
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response.raise_for_status()
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result = response.json()
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if result["success"]:
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print(f"✓ 图像特征对比成功")
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print(f" - 相似度: {result['similarity']:.4f}")
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print(f" - 判断结果: {'同一人' if result['is_same_person'] else '不是同一人'}")
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print(f" - 处理时间: {result['processing_time']:.3f}秒")
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return result
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else:
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print(f"✗ 图像特征对比失败: {result['message']}")
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return None
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except FileNotFoundError:
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print(f"✗ 文件不存在: {image_path}")
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return None
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except Exception as e:
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print(f"✗ 请求失败: {e}")
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return None
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def health_check(self) -> bool:
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"""健康检查"""
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url = f"{self.base_url}/health"
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try:
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response = requests.get(url)
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result = response.json()
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if result["status"] == "healthy":
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print(f"✓ API服务运行正常")
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return True
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else:
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print(f"✗ API服务异常: {result}")
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return False
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except Exception as e:
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print(f"✗ 无法连接到API服务: {e}")
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return False
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# ==================== 示例场景 ====================
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def example1_extract_and_compare():
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"""示例1: 提取特征并对比"""
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print("\n" + "="*60)
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print("示例1: 提取两张图像的特征并对比")
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print("="*60)
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client = FaceAPIClient()
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# 检查服务状态
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if not client.health_check():
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return
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# 图像路径（请替换为实际路径）
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image1 = "person1.jpg"
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image2 = "person1_verify.jpg"
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print(f"\n步骤1: 提取第一张图像特征")
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feature1 = client.extract_feature(image1)
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if not feature1:
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return
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print(f"\n步骤2: 提取第二张图像特征")
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feature2 = client.extract_feature(image2)
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if not feature2:
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return
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print(f"\n步骤3: 对比两个特征")
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result = client.compare_features(feature1, feature2)
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def example2_image_feature_compare():
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"""示例2: 使用组合接口对比图像和特征"""
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print("\n" + "="*60)
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print("示例2: 使用组合接口对比图像和特征")
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print("="*60)
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client = FaceAPIClient()
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# 先提取一个已知用户的特征
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known_user_image = "person1.jpg"
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test_image = "person1_verify.jpg"
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print(f"\n步骤1: 提取已知用户的特征")
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known_feature = client.extract_feature(known_user_image)
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if not known_feature:
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return
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print(f"\n步骤2: 使用组合接口验证新图像")
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result = client.compare_image_feature(test_image, known_feature)
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def example3_face_recognition_system():
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"""示例3: 简单的人脸识别系统"""
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print("\n" + "="*60)
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print("示例3: 简单的人脸识别系统")
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print("="*60)
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client = FaceAPIClient()
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# 模拟用户数据库
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user_database = {}
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# 注册用户
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users_to_register = [
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("张三", "person1.jpg"),
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# ("李四", "person2.jpg"),
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# ("王五", "person3.jpg"),
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]
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print("\n[注册阶段]")
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for user_name, image_path in users_to_register:
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if not os.path.exists(image_path):
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print(f"⚠ 跳过 {user_name}: 文件不存在 {image_path}")
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continue
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print(f"\n注册用户: {user_name}")
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feature = client.extract_feature(image_path)
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if feature:
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user_database[user_name] = feature
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print(f"✓ {user_name} 注册成功")
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else:
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print(f"✗ {user_name} 注册失败")
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print(f"\n当前数据库中有 {len(user_database)} 个用户")
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# 识别测试
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test_images = [
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"test_person1.jpg",
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]
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print("\n[识别阶段]")
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for test_image in test_images:
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if not os.path.exists(test_image):
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print(f"⚠ 跳过: 文件不存在 {test_image}")
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continue
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print(f"\n识别图像: {test_image}")
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# 提取待识别图像的特征
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test_feature = client.extract_feature(test_image)
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if not test_feature:
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continue
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# 与数据库中所有用户对比
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best_match = None
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best_similarity = 0.0
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for user_name, user_feature in user_database.items():
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result = client.compare_features(test_feature, user_feature)
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if result and result['similarity'] > best_similarity:
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best_similarity = result['similarity']
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best_match = user_name
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# 输出结果
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if best_similarity >= 0.7:
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print(f"✓ 识别结果: {best_match} (相似度: {best_similarity:.4f})")
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else:
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print(f"✗ 未识别到已注册用户 (最高相似度: {best_similarity:.4f})")
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def main():
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"""主函数"""
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print("人脸特征API客户端示例")
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print("请确保API服务正在运行: python app.py")
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# 运行示例
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# example1_extract_and_compare()
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# example2_image_feature_compare()
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example3_face_recognition_system()
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if __name__ == "__main__":
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main()
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