#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
简单示例：人脸特征提取
"""

import cv2
import sys
import os

# 添加父目录到路径
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

from face_feature_extractor import FaceFeatureExtractor
import numpy as np


def main():
    """主函数"""

    # 示例1: 基础使用
    print("=" * 60)
    print("示例1: 基础人脸特征提取")
    print("=" * 60)

    # 读取图像
    image_path = r"E:\FaceFeatureExtractorAPI\muti.png"  # 请替换为实际图像路径

    if not os.path.exists(image_path):
        print(f"错误: 图像文件不存在: {image_path}")
        print("请提供有效的图像路径")
        return

    image = cv2.imread(image_path)
    if image is None:
        print(f"错误: 无法读取图像: {image_path}")
        return

    # 创建特征提取器
    extractor = FaceFeatureExtractor()

    # 提取特征
    feature = extractor.extract_single_feature(image)

    if feature is not None:
        print(f"✓ 特征提取成功")
        print(f"  特征维度: {feature.shape}")
        print(f"  特征范数: {np.linalg.norm(feature):.6f}")
        print(f"  特征类型: {feature.dtype}")
    else:
        print("✗ 特征提取失败（质量检查未通过或未检测到人脸）")

    # 示例2: 详细信息提取
    print("\n" + "=" * 60)
    print("示例2: 获取详细信息")
    print("=" * 60)

    result = extractor.extract_features(image, return_all_faces=True, quality_filter=False)

    print(f"处理时间: {result.processing_time:.3f}秒")
    print(f"检测到 {len(result.faces)} 个人脸")

    for i, face in enumerate(result.faces):
        print(f"\n人脸 {i+1}:")
        print(f"  位置: ({face.bbox[0]:.1f}, {face.bbox[1]:.1f}, {face.bbox[2]:.1f}, {face.bbox[3]:.1f})")
        print(f"  置信度: {face.confidence:.3f}")

        print("  质量评估:")
        for name, score in face.quality_scores.items():
            if name != 'overall':
                status = "✓" if score['passed'] else "✗"
                print(f"    {status} {score['description']}")

        overall_status = "✓ 合格" if face.quality_scores['overall']['passed'] else "✗ 不合格"
        print(f"  整体评估: {overall_status}")

    # 示例3: 统计信息
    print("\n" + "=" * 60)
    print("示例3: 统计信息")
    print("=" * 60)

    stats = extractor.get_statistics()
    print(f"总处理次数: {stats['total_extractions']}")
    print(f"成功次数: {stats['successful_extractions']}")
    print(f"质量过滤次数: {stats['quality_filtered']}")
    print(f"成功率: {stats['success_rate']:.2%}")
    print(f"平均处理时间: {stats['average_processing_time']:.3f}秒")


if __name__ == "__main__":
    main()