解决Face_recognition中ValueError: list.remove(x): x not in list错误

错误原因 #

程序在持续运行的while循环中，每帧都会检测人脸并尝试移除students列表中的已识别学生。当某个学生被识别一次后，已从students列表中移除，但后续帧再次识别到该学生时，students.remove(name)会因目标名字不在列表中抛出错误。此外，程序启动时获取的now变量会导致所有考勤记录的时间都是程序启动时间，而非实际识别时间。

修复方案 #

1. 仅处理未考勤的学生 #

将判断条件从检查name in known_faces_names改为检查name in students，确保只有待考勤的学生才会被执行移除和写入操作：

if name in students:  # 替换原有的if name in known_faces_names:
    students.remove(name)
    print(students)
    time = datetime.now().strftime("%H-%M-%S")
    lnwriter.writerow([name, time])

2. 实时获取考勤时间 #

把时间获取逻辑移到循环内部，每次识别时获取当前时间，避免所有记录时间一致：

time = datetime.now().strftime("%H-%M-%S")

3. 可选：避免单帧重复识别 #

如果一帧中可能多次识别到同一个人，可使用集合临时存储当前帧识别到的名字，去重后再处理：

current_frame_names = set()
for face_encoding in face_encodings:
    # 原有识别逻辑...
    if matches[best_match_index]:
        name = known_faces_names[best_match_index]
        current_frame_names.add(name)
    face_names.append(name)

# 统一处理当前帧的已识别学生
for name in current_frame_names:
    if name in students:
        students.remove(name)
        print(students)
        time = datetime.now().strftime("%H-%M-%S")
        lnwriter.writerow([name, time])

修改后的完整代码 #

import face_recognition
import cv2
import numpy as np
import csv
import os
from datetime import datetime

video_capture = cv2.VideoCapture(0)

tata_image = face_recognition.load_image_file("./faces/index4.jpg")
tata_encoding = face_recognition.face_encodings(tata_image)[0]

einstein_image = face_recognition.load_image_file("./faces/index2.jpg")
einstein_encoding = face_recognition.face_encodings(einstein_image)[0]

tesla_image = face_recognition.load_image_file("./faces/index.jpg")
tesla_encoding = face_recognition.face_encodings(tesla_image)[0]

eefa_image = face_recognition.load_image_file("./faces/eefa.jpg")
eefa_encoding = face_recognition.face_encodings(eefa_image)[0]

teresa_image = face_recognition.load_image_file("./faces/index3.jpg")
teresa_encoding = face_recognition.face_encodings(teresa_image)[0]

known_face_encoding = [
    tesla_encoding,
    tata_encoding,
    teresa_encoding,
    eefa_encoding,
    einstein_encoding
]

known_faces_names = [
    "Nikola Tesla",
    "Ratan Tata",
    "Mother Teresa",
    "Eefa Khadeeja Abidi",
    "Albert Einstein"
]

students = known_faces_names.copy()

face_location = []
face_encodings = []
face_names = []
s=True

now = datetime.now()
date = now.strftime("%Y-%m-%d")

f = open(date+'.csv','w+',newline='')
lnwriter = csv.writer(f) 

while True:
    _,frame = video_capture.read()
    small_frame = cv2.resize(frame,(0,0),fx=0.25,fy=0.25)
    rgb_small_frame = small_frame[:,:,::-1]
    if s:
        face_locations = face_recognition.face_locations(rgb_small_frame)
        face_encodings = face_recognition.face_encodings(rgb_small_frame,face_locations)
        face_names = []
        current_frame_names = set()
        for face_encoding in face_encodings:
            matches = face_recognition.compare_faces(known_face_encoding,face_encoding)
            name = ""
            face_distance = face_recognition.face_distance(known_face_encoding,face_encoding)
            best_match_index = np.argmin(face_distance)
            if matches[best_match_index]:
                name = known_faces_names[best_match_index]
                current_frame_names.add(name)

            face_names.append(name)
        
        # 处理当前帧的考勤记录
        for name in current_frame_names:
            if name in students:
                students.remove(name)
                print(students)
                time = datetime.now().strftime("%H-%M-%S")
                lnwriter.writerow([name,time])
    cv2.imshow("attendance system",frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

video_capture.release()
cv2.destroyAllWindows()
f.close()

内容的提问来源于stack exchange，提问作者ZainCoder