python+OpenCV人臉識(shí)別考勤系統(tǒng)實(shí)現(xiàn)的詳細(xì)代碼
更新時(shí)間：2023年05月22日 08:55:12 作者：A等天晴
作為一個(gè)基于人臉識(shí)別算法的考勤系統(tǒng)的設(shè)計(jì)與實(shí)現(xiàn)教程，以下內(nèi)容將提供詳細(xì)的步驟和代碼示例。本教程將使用 Python 語(yǔ)言和 OpenCV 庫(kù)進(jìn)行實(shí)現(xiàn),需要的朋友可以參考下
一、環(huán)境配置
- 安裝 Python
請(qǐng)確保您已經(jīng)安裝了 Python 3.x?？梢栽赑ython 官網(wǎng)下載并安裝。
- 安裝所需庫(kù)
在命令提示符或終端中運(yùn)行以下命令來(lái)安裝所需的庫(kù)：
pip install opencv-python pip install opencv-contrib-python pip install numpy pip install face-recognition
二、創(chuàng)建數(shù)據(jù)集
- 創(chuàng)建文件夾結(jié)構(gòu)
在項(xiàng)目目錄下創(chuàng)建如下文件夾結(jié)構(gòu)：
attendance-system/
├── dataset/
│ ├── person1/
│ ├── person2/
│ └── ...
└── src/
將每個(gè)人的照片放入對(duì)應(yīng)的文件夾中，例如：
attendance-system/
├── dataset/
│ ├── person1/
│ │ ├── 01.jpg
│ │ ├── 02.jpg
│ │ └── ...
│ ├── person2/
│ │ ├── 01.jpg
│ │ ├── 02.jpg
│ │ └── ...
│ └── ...
└── src/
三、實(shí)現(xiàn)人臉識(shí)別算法
在 src 文件夾下創(chuàng)建一個(gè)名為 face_recognition.py 的文件，并添加以下代碼：
import os
import cv2
import face_recognition
import numpy as np
def load_images_from_folder(folder):
images = []
for filename in os.listdir(folder):
img = cv2.imread(os.path.join(folder, filename))
if img is not None:
images.append(img)
return images
def create_known_face_encodings(root_folder):
known_face_encodings = []
known_face_names = []
for person_name in os.listdir(root_folder):
person_folder = os.path.join(root_folder, person_name)
images = load_images_from_folder(person_folder)
for image in images:
face_encoding = face_recognition.face_encodings(image)[0]
known_face_encodings.append(face_encoding)
known_face_names.append(person_name)
return known_face_encodings, known_face_names
def recognize_faces_in_video(known_face_encodings, known_face_names):
video_capture = cv2.VideoCapture(0)
face_locations = []
face_encodings = []
face_names = []
process_this_frame = True
while True:
ret, frame = video_capture.read()
small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
rgb_small_frame = small_frame[:, :, ::-1]
if process_this_frame:
face_locations = face_recognition.face_locations(rgb_small_frame)
face_encodings = face_recognition.face_encodings(rgb_small_frame, face_locations)
face_names = []
for face_encoding in face_encodings:
matches = face_recognition.compare_faces(known_face_encodings, face_encoding)
name = "Unknown"
face_distances = face_recognition.face_distance(known_face_encodings, face_encoding)
best_match_index = np.argmin(face_distances)
if matches[best_match_index]:
name = known_face_names[best_match_index]
face_names.append(name)
process_this_frame = not process_this_frame
for (top, right, bottom, left), name in zip(face_locations, face_names):
top *= 4
right *= 4
bottom *= 4
left *= 4
cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
font = cv2.FONT_HERSHEY_DUPLEX
cv2.putText(frame, name, (left + 6, bottom - 6), font, 0.8, (255, 255, 255), 1)
cv2.imshow('Video', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
video_capture.release()
cv2.destroyAllWindows()
if __name__ == "__main__":
dataset_folder = "../dataset/"
known_face_encodings, known_face_names = create_known_face_encodings(dataset_folder)
recognize_faces_in_video(known_face_encodings, known_face_names)
四、實(shí)現(xiàn)考勤系統(tǒng)
在 src 文件夾下創(chuàng)建一個(gè)名為 attendance.py 的文件，并添加以下代碼：
import os
import datetime
import csv
from face_recognition import create_known_face_encodings, recognize_faces_in_video
def save_attendance(name):
attendance_file = "../attendance/attendance.csv"
now = datetime.datetime.now()
date_string = now.strftime("%Y-%m-%d")
time_string = now.strftime("%H:%M:%S")
if not os.path.exists(attendance_file):
with open(attendance_file, "w", newline="") as csvfile:
csv_writer = csv.writer(csvfile)
csv_writer.writerow(["Name", "Date", "Time"])
with open(attendance_file, "r+", newline="") as csvfile:
csv_reader = csv.reader(csvfile)
rows = [row for row in csv_reader]
for row in rows:
if row[0] == name and row[1] == date_string:
return
csv_writer = csv.writer(csvfile)
csv_writer.writerow([name, date_string, time_string])
def custom_recognize_faces_in_video(known_face_encodings, known_face_names):
video_capture = cv2.VideoCapture(0)
face_locations = []
face_encodings = []
face_names = []
process_this_frame = True
while True:
ret, frame = video_capture.read()
small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
rgb_small_frame = small_frame[:, :, ::-1]
if process_this_frame:
face_locations = face_recognition.face_locations(rgb_small_frame)
face_encodings = face_recognition.face_encodings(rgb_small_frame, face_locations)
face_names = []
for face_encoding in face_encodings:
matches = face_recognition.compare_faces(known_face_encodings, face_encoding)
name = "Unknown"
face_distances = face_recognition.face_distance(known_face_encodings, face_encoding)
best_match_index = np.argmin(face_distances)
if matches[best_match_index]:
name = known_face_names[best_match_index]
save_attendance(name)
face_names.append(name)
process_this_frame = not process_this_frame
for (top, right, bottom, left), name in zip(face_locations, face_names):
top *= 4
right *= 4
bottom *= 4
left *= 4
cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
font = cv2.FONT_HERSHEY_DUPLEX
cv2.putText(frame, name, (left + 6, bottom - 6), font, 0.8, (255, 255, 255), 1)
cv2.imshow('Video', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
video_capture.release()
cv2.destroyAllWindows()
if __name__ == "__main__":
dataset_folder = "../dataset/"
known_face_encodings, known_face_names = create_known_face_encodings(dataset_folder)
custom_recognize_faces_in_video(known_face_encodings, known_face_names)
五、運(yùn)行考勤系統(tǒng)
運(yùn)行 attendance.py 文件，系統(tǒng)將開(kāi)始識(shí)別并記錄考勤信息?？记谟涗泴⒈４嬖?nbsp;attendance.csv 文件中。
python src/attendance.py
現(xiàn)在，您的基于人臉識(shí)別的考勤系統(tǒng)已經(jīng)實(shí)現(xiàn)。請(qǐng)注意，這是一個(gè)基本示例，您可能需要根據(jù)實(shí)際需求對(duì)其進(jìn)行優(yōu)化和擴(kuò)展。例如，您可以考慮添加更多的人臉識(shí)別算法、考勤規(guī)則等。
到此這篇關(guān)于python+OpenCV人臉識(shí)別考勤系統(tǒng)實(shí)現(xiàn)的詳細(xì)代碼的文章就介紹到這了,更多相關(guān)python OpenCV人臉識(shí)別考勤系統(tǒng)內(nèi)容請(qǐng)搜索腳本之家以前的文章或繼續(xù)瀏覽下面的相關(guān)文章希望大家以后多多支持腳本之家！
相關(guān)文章
這篇文章主要為大家介紹了python進(jìn)程和線程，具有一定的參考價(jià)值，感興趣的小伙伴們可以參考一下，希望能夠給你帶來(lái)幫助2022-01-01
工作中經(jīng)常要處理各種各樣的數(shù)據(jù)，遇到項(xiàng)目趕進(jìn)度的時(shí)候自己寫(xiě)函數(shù)容易浪費(fèi)時(shí)間。Python 中有很多內(nèi)置函數(shù)幫你提高工作效率。2020-09-09
python抓取豆瓣圖片并自動(dòng)保存示例學(xué)習(xí)
python抓取豆瓣圖片并自動(dòng)保存示例學(xué)習(xí)，示例使用了beautifulsoup庫(kù)分析HTML代碼，beautifulsoup是一個(gè)HTML/XML解析器，可以用來(lái)做網(wǎng)頁(yè)爬蟲(chóng)2014-01-01
這篇文章主要介紹了python讀寫(xiě)二進(jìn)制文件的方法,實(shí)例分析了Python讀寫(xiě)二進(jìn)制文件的相關(guān)技巧,需要的朋友可以參考下2015-05-05
python中的__init__ 、__new__、__call__小結(jié)
這篇文章主要介紹了python中的__init__ 、__new__、__call__小結(jié),需要的朋友可以參考下
2014-04-04 
這篇文章主要為大家詳細(xì)介紹了基于Pytorch實(shí)現(xiàn)邏輯回歸，文中示例代碼介紹的非常詳細(xì)，具有一定的參考價(jià)值，感興趣的小伙伴們可以參考一下
2022-07-07 
Python內(nèi)建類型str源碼學(xué)習(xí)
這篇文章主要為大家介紹了Python內(nèi)建類型str的源碼學(xué)習(xí)，有需要的朋友可以借鑒參考下，希望能夠有所幫助，祝大家多多進(jìn)步，早日升職加薪
2022-05-05 
Python使用cx_Freeze庫(kù)生成msi格式安裝文件的方法
這篇文章主要介紹了Python使用cx_Freeze庫(kù)生成msi格式安裝文件的方法,結(jié)合實(shí)例形式分析了Python基于cx_Freeze庫(kù)生成msi格式安裝文件操作技巧與相關(guān)問(wèn)題解決方法,需要的朋友可以參考下
2018-07-07 
詳解如何使用SQLAlchemy連接數(shù)據(jù)庫(kù)
這篇文章主要為大家詳細(xì)介紹了如何使用 SQLAlchemy 連接數(shù)據(jù)庫(kù)、建立模型、操作表、以及查詢操作表數(shù)據(jù)等內(nèi)容,感興趣的小伙伴可以跟隨小編一起學(xué)習(xí)一下
2023-11-11