How can I improve the accuracy of the my program to detect the required faces properly?

Question

The idea behind my program is to go through footage, detect and recognize a face that the user provides. However, my program recognizes other peoples faces as well. Any idea how I can make it better?

I have used haarcascade_frontalface_alt2.xml, and I have provided 10 images of the person to be found, lets say "criminal". However, the program wrongly identifies someone else's face as the criminal. Providing the code I have used :

def extract_faces(img):
    try:
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        face_points = face_detector.detectMultiScale(gray, 1.2, 5, minSize=(20, 20))
        return face_points
    except:
        return []


def identify_face(facearray):
    model = joblib.load('static/face_recognition_model.pkl')
    return model.predict(facearray)


def train_model():
    faces = []
    labels = []
    userlist = os.listdir('static/faces')
    for user in userlist:
        for imgname in os.listdir(f'static/faces/{user}'):
            img = cv2.imread(f'static/faces/{user}/{imgname}')
            resized_face = cv2.resize(img, (50, 50))
            faces.append(resized_face.ravel())
            labels.append(user)
    faces = np.array(faces)
    knn = KNeighborsClassifier(n_neighbors=5)
    knn.fit(faces, labels)
    joblib.dump(knn, 'static/face_recognition_model.pkl')

def process_video(video_path1, video_path2):
    names, times, l = extract_mp()

    if 'face_recognition_model.pkl' not in os.listdir('static'):
        return render_template('index.html', names=names,  times=times, l=l, totalregNames=totalregNames(), totalregNumber=totalregNumber(), datetoday2=datetoday2, mess='There is no trained model in the static folder. Please add a new face to continue.')

    cap1 = cv2.VideoCapture(video_path1)
    cap2 = cv2.VideoCapture(video_path2)
    while cap1.isOpened() and cap2.isOpened():
        ret1, frame1 = cap1.read()
        ret2, frame2 = cap2.read()
        if not ret1 or not ret2:
            break

        if len(extract_faces(frame1)) > 0:
            (x, y, w, h) = extract_faces(frame1)[0]
            cv2.rectangle(frame1, (x, y), (x+w, y+h), (86, 32, 251), 1)
            cv2.rectangle(frame1, (x, y), (x+w, y-40), (86, 32, 251), -1)
            face = cv2.resize(frame1[y:y+h, x:x+w], (50, 50))
            identified_person = identify_face(face.reshape(1, -1))[0]
            add_mp(identified_person)
            abc = "Human"
            cv2.putText(frame1, f'{abc}', (x+5, y-5),
                        cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2)