Python人脸识别实践：从零开始构建桌面应用

项目背景

人脸识别技术已广泛应用于安全、社交和智能系统。本文将详细介绍如何使用Python构建一个简单yet实用的人脸识别桌面应用。
D:\spiderdocs\facedetectandrecongnize.py

技术选型

• OpenCV：图像处理与人脸检测
• wxPython：跨平台桌面GUI
• Python：编程语言

核心功能

1. 添加已知人脸
2. 批量导入人脸库
3. 实时人脸识别
4. 可视化识别结果

全部代码

import cv2
import numpy as np
import os
import wx

class FaceRecognizer:
    def __init__(self):
        # 使用OpenCV的Haar级联分类器
        self.face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
        self.known_faces = {}

    def detect_faces(self, image):
        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        faces = self.face_cascade.detectMultiScale(gray, 1.1, 4)
        return faces

    def add_known_face(self, image, name):
        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        faces = self.detect_faces(image)
        if len(faces) > 0:
            (x, y, w, h) = faces[0]
            face_roi = gray[y:y+h, x:x+w]
            self.known_faces[name] = face_roi
            return True
        return False

    def recognize_face(self, image):
        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        faces = self.detect_faces(image)
        results = []
        for (x, y, w, h) in faces:
            face_roi = gray[y:y+h, x:x+w]
            name = "Unknown"
            for known_name, known_face in self.known_faces.items():
                # 简单的特征匹配
                if self.compare_faces(face_roi, known_face):
                    name = known_name
                    break
            results.append((name, (x, y, w, h)))
        return results

    def compare_faces(self, face1, face2, threshold=0.8):
        # 使用模板匹配方法比较人脸
        result = cv2.matchTemplate(face1, face2, cv2.TM_CCOEFF_NORMED)
        return result[0][0] > threshold

class FaceRecognitionApp(wx.Frame):
    def __init__(self):
        super().__init__(parent=None, title='人脸识别系统')
        
        self.face_recognizer = FaceRecognizer()
        
        panel = wx.Panel(self)
        main_sizer = wx.BoxSizer(wx.VERTICAL)
        
        btn_sizer = wx.BoxSizer(wx.HORIZONTAL)
        
        add_face_btn = wx.Button(panel, label='添加人脸')
        add_face_btn.Bind(wx.EVT_BUTTON, self.on_add_face)
        btn_sizer.Add(add_face_btn, 0, wx.ALL, 5)
        
        recognize_btn = wx.Button(panel, label='识别人脸')
        recognize_btn.Bind(wx.EVT_BUTTON, self.on_recognize)
        btn_sizer.Add(recognize_btn, 0, wx.ALL, 5)
        
        # 批量添加按钮
        batch_add_btn = wx.Button(panel, label='批量添加人脸')
        batch_add_btn.Bind(wx.EVT_BUTTON, self.on_batch_add)
        btn_sizer.Add(batch_add_btn, 0, wx.ALL, 5)
        
        name_label = wx.StaticText(panel, label='姓名:')
        self.name_input = wx.TextCtrl(panel)
        self.result_text = wx.StaticText(panel, label='')
        
        main_sizer.Add(btn_sizer, 0, wx.CENTER)
        main_sizer.Add(name_label, 0, wx.ALL|wx.CENTER, 5)
        main_sizer.Add(self.name_input, 0, wx.ALL|wx.CENTER, 5)
        main_sizer.Add(self.result_text, 0, wx.ALL|wx.CENTER, 5)
        
        panel.SetSizer(main_sizer)
        main_sizer.Fit(self)
        self.Center()
    
    def on_add_face(self, event):
        with wx.FileDialog(self, "选择图像", 
                           wildcard="图像文件 (*.jpg;*.png)|*.jpg;*.png", 
                           style=wx.FD_OPEN | wx.FD_FILE_MUST_EXIST) as fileDialog:
            
            if fileDialog.ShowModal() == wx.ID_CANCEL:
                return
            
            pathname = fileDialog.GetPath()
            name = self.name_input.GetValue().strip()
            
            if not name:
                wx.MessageBox('请输入姓名', '错误', wx.OK | wx.ICON_ERROR)
                return
            
            try:
                image = cv2.imread(pathname)
                
                if self.face_recognizer.add_known_face(image, name):
                    wx.MessageBox(f'{name} 的人脸已成功添加', '成功', wx.OK)
                else:
                    wx.MessageBox('未检测到人脸', '错误', wx.OK | wx.ICON_ERROR)
                
            except Exception as e:
                wx.MessageBox(f'处理图像时出错: {str(e)}', '错误', wx.OK | wx.ICON_ERROR)
    
    def on_batch_add(self, event):
        with wx.DirDialog(self, "选择包含人脸图像的文件夹") as dirDialog:
            if dirDialog.ShowModal() == wx.ID_CANCEL:
                return
            
            folder_path = dirDialog.GetPath()
            name = self.name_input.GetValue().strip()
            
            if not name:
                wx.MessageBox('请输入姓名', '错误', wx.OK | wx.ICON_ERROR)
                return
            
            added_count = 0
            total_count = 0
            
            for filename in os.listdir(folder_path):
                if filename.lower().endswith(('.png', '.jpg', '.jpeg')):
                    total_count += 1
                    filepath = os.path.join(folder_path, filename)
                    try:
                        image = cv2.imread(filepath)
                        if self.face_recognizer.add_known_face(image, name):
                            added_count += 1
                    except Exception:
                        pass
            
            wx.MessageBox(f'成功添加 {added_count}/{total_count} 张人脸', '批量添加结果', wx.OK)
    
    def on_recognize(self, event):
        with wx.FileDialog(self, "选择识别图像", 
                           wildcard="图像文件 (*.jpg;*.png)|*.jpg;*.png", 
                           style=wx.FD_OPEN | wx.FD_FILE_MUST_EXIST) as fileDialog:
            
            if fileDialog.ShowModal() == wx.ID_CANCEL:
                return
            
            pathname = fileDialog.GetPath()
            
            try:
                image = cv2.imread(pathname)
                image_copy = image.copy()
                
                results = self.face_recognizer.recognize_face(image)
                
                if results:
                    result_str = "识别结果:\n"
                    for name, (x, y, w, h) in results:
                        result_str += f"{name} "
                        # 在图像上绘制人脸框
                        cv2.rectangle(image_copy, (x, y), (x+w, y+h), (0, 255, 0), 2)
                    
                    self.result_text.SetLabel(result_str)
                    
                    # 显示带人脸框的图像
                    cv2.imshow('识别结果', image_copy)
                    cv2.waitKey(0)
                    cv2.destroyAllWindows()
                else:
                    self.result_text.SetLabel('未找到人脸')
                
            except Exception as e:
                wx.MessageBox(f'识别人脸时出错: {str(e)}', '错误', wx.OK | wx.ICON_ERROR)

def main():
    app = wx.App()
    frame = FaceRecognitionApp()
    frame.Show()
    app.MainLoop()

if __name__ == '__main__':
    main()

关键代码解析

人脸检测核心算法

def detect_faces(self, image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    faces = self.face_cascade.detectMultiScale(gray, 1.1, 4)
    return faces

特征匹配机制

def compare_faces(self, face1, face2, threshold=0.8):
    result = cv2.matchTemplate(face1, face2, cv2.TM_CCOEFF_NORMED)
    return result[0][0] > threshold

项目亮点

• 低依赖：仅依赖OpenCV和wxPython
• 易扩展：可轻松添加更多识别算法
• 跨平台：支持Windows、Linux和macOS

实际应用场景

• 安防系统
• 智能考勤
• 个人相册管理

运行结果