人脸识别系统代码--视频处理

1.导入库

OpenCV用于视频处理，Tkinter用于GUI，filedialog用于文件选择，face_recognition用于人脸识别，os用于文件操作，subprocess用于运行其他Python脚本。

import cv2
import tkinter as tk
from tkinter import filedialog
import face_recognition
import os
import subprocess
from PIL import Image, ImageTk

2.设置窗口

创建一个Tkinter窗口，设置标题和大小。

win = tk.Tk()
win.title('Welcome')
win.geometry('750x600')

3.设置背景

设置窗口背景为一张GIF图片，并调整图片大小以适应窗口。

image = Image.open("12.gif")
image = image.resize((750, 600))  # 调整背景图片大小
photo1 = ImageTk.PhotoImage(image)
canvas = tk.Label(win, image=photo1)
canvas.pack()

4.定义全局变量

save_video、canvas和face_dir，用于存储视频路径、Canvas实例和保存人脸图片的文件夹路径。

save_video = None
canvas = None
face_dir = None

5.定义函数xz_video

用于打开文件对话框，让用户选择一个视频文件，并调用sb_video函数进行视频人脸识别。

def xz_video():
    global save_video
    file_path = filedialog.askopenfilename(title="选择视频",
                                           filetypes=(("视频文件", "*.mp4;*.avi;*.mkv;*.mov"),
                                                      ("所有文件", "*.*")))
    if file_path:
        save_video = file_path
        sb_video()

6.定义函数sb_video

用于识别人脸并在Canvas上显示。

def sb_video():
    global save_video, canvas, face_dir
    if save_video:
        # 创建保存人脸的文件夹
        if not face_dir:
            face_dir = 'video_image'
            if not os.path.exists(face_dir):
                os.makedirs(face_dir)

        # 加载视频
        video_capture = cv2.VideoCapture(save_video)

        # 初始化Canvas
        canvas = tk.Canvas(win, width=640, height=480)
        canvas.place(x=80,y=180)

        try:
            # 初始化变量
            face_count = 0

            while True:
                # 抓取一帧视频
                ret, frame = video_capture.read()
                if not ret:
                    break

                # 转换颜色从BGR到RGB
                rgb_frame = frame[:, :, ::-1]

                # 查找图像中的人脸位置
                face_locations = face_recognition.face_locations(rgb_frame)

                # 在每个检测到的人脸周围画框
                for top, right, bottom, left in face_locations:
                    cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)

                    # 裁剪人脸并保存
                    face_image = frame[top:bottom, left:right]
                    face_path = os.path.join(face_dir, f'face_{face_count}.jpg')
                    cv2.imwrite(face_path, face_image)
                    face_count += 1

                # 转换OpenCV图像格式到PIL图像格式
                pil_image = Image.fromarray(frame[:, :, ::-1])
                photo = ImageTk.PhotoImage(image=pil_image)

                # 在Canvas上显示图像
                canvas.create_image(0, 0, anchor=tk.NW, image=photo)
                win.update_idletasks()
                win.update()

                if cv2.waitKey(1) & 0xFF == ord('q'):
                    break
        finally:
            # 释放视频
            video_capture.release()

7.定义函数open_face

用于打开指定的文件夹或文件。当用户点击“打开人脸图片文件夹”按钮时，如果face_dir变量不为None且指向的文件夹确实存在，这个函数将会被调用，尝试在文件资源管理器中打开该文件夹。

def open_face():
    if face_dir and os.path.exists(face_dir):
        os.startfile(face_dir)

8.定义函数close

def close():
    subprocess.Popen(["python", "动态处理.py"])
    win.destroy()

9.设置按钮

image = Image.open("F8.gif")  # 加载一张图片
photo2 = ImageTk.PhotoImage(image)
bt1 = tk.Button(win, image=photo2, width=198, height=32,command=xz_video)
bt1.place(x=30, y=30)

image = Image.open("F9.gif")  # 加载一张图片
photo3 = ImageTk.PhotoImage(image)
bt2 = tk.Button(win, image=photo3, width=198, height=32,command=open_face)
bt2.place(x=275, y=30)

image = Image.open("B.gif")  # 加载一张图片
photo4 = ImageTk.PhotoImage(image)
bt3 = tk.Button(win, image=photo4, width=198, height=32,command=close)
bt3.place(x=520, y=30)

10.退出窗口

win.mainloop()