gitproject/doc/文档1/自主开发代码/库.py

import cv2
import time
import os
from datetime import datetime, timedelta
import logging
import yaml
from PIL import Image, ImageFont, ImageDraw
import numpy as np  # 添加导入

# 初始化日志记录
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')


def create_training_directory(path_name):
    if not os.path.exists(path_name):
        os.makedirs(path_name)


def is_within_time_range(start_time_str, end_time_str):
    """判断当前时间是否在指定的时间范围内"""
    now = datetime.now().time()
    start_time = datetime.strptime(start_time_str, "%H:%M").time()  # 24小时制
    end_time = datetime.strptime(end_time_str, "%H:%M").time()
    return start_time <= now <= end_time


def calculate_required_time(start_time_str, end_time_str, percentage):
    """计算所需的最少时间（分钟）"""
    start_time = datetime.strptime(start_time_str, "%H:%M")
    end_time = datetime.strptime(end_time_str, "%H:%M")
    total_time = (end_time - start_time).total_seconds() / 60  # 总时长（分钟）
    return total_time * (percentage / 100)


def load_config(config_path='config.yaml'):
    base_dir = os.path.dirname(os.path.abspath(__file__))  # 获取脚本所在目录
    config_full_path = os.path.join(base_dir, config_path)  # 构建配置文件的绝对路径
    with open(config_full_path, 'r', encoding='utf-8') as file:
        return yaml.safe_load(file)


def put_chinese_text(frame, text, position, font_path, font_size, color, font_cache={}):
    """
    使用 PIL 绘制中文文本并转换回 OpenCV 图像
    """
    # 检查字体文件是否存在
    if not os.path.exists(font_path):
        logging.error(f"字体文件未找到: {font_path}")
        return frame

    # 使用缓存的字体对象
    if font_path in font_cache:
        font = font_cache[font_path]
    else:
        try:
            font = ImageFont.truetype(font_path, font_size)
            font_cache[font_path] = font
        except Exception as e:
            logging.error(f"加载字体失败: {e}")
            return frame

    # 将 OpenCV 的 BGR 图像转换为 RGB
    img_pil = Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
    draw = ImageDraw.Draw(img_pil)
    # 绘制文本
    draw.text(position, text, font=font, fill=color)
    # 将 PIL 图像转换回 OpenCV 的 BGR 图像
    frame = cv2.cvtColor(np.array(img_pil), cv2.COLOR_RGB2BGR)
    return frame


def capture_faces_with_timer(window_name, camera_id, path_name, max_num, required_time, start_time_str, end_time_str, font_path):
    cv2.namedWindow(window_name)
    try:
        cap = cv2.VideoCapture(camera_id)  # 直接初始化 VideoCapture
        face_cascade = cv2.CascadeClassifier(
            config['face_cascade_path'])  # 使用配置文件中的路径

        color = (0, 255, 0)
        face_count = 0
        countdown_started = False
        remaining_time = required_time * 60  # 转换为秒
        pause_time = None  # 初始化暂停时间

        create_training_directory(path_name)

        while cap.isOpened() and face_count < max_num:
            ret, frame = cap.read()
            if not ret:
                break

            gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
            faces = face_cascade.detectMultiScale(gray_frame, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))

            # 检查当前时间是否在指定的时间范围内
            if is_within_time_range(start_time_str, end_time_str):
                if len(faces) > 0:
                    if not countdown_started:
                        countdown_started = True
                        if pause_time is not None:
                            # 调整 start_time 以考虑暂停的时长
                            start_time += time.time() - pause_time
                        else:
                            start_time = time.time()

                    remaining_time = required_time * 60 - int(time.time() - start_time)

                    for (x, y, w, h) in faces:
                        face_image = frame[y:y + h, x:x + w]
                        image_name = os.path.join(path_name, f'face_{face_count}.jpg')
                        cv2.imwrite(image_name, face_image)

                        face_count += 1
                        cv2.rectangle(frame, (x, y), (x + w, y + h), color, 2)

                    # 显示剩余学习时长
                    text = f'剩余学习时长: {remaining_time // 60}m {remaining_time % 60}s'
                    frame = put_chinese_text(
                        frame,
                        text,
                        (10, 30),
                        font_path,
                        30,  # 字体大小
                        (0, 0, 255)  # 颜色
                    )

                    if remaining_time <= 0:
                        break
                else:
                    # 如果计时器已经暂停，继续显示剩余时间
                    text = f'剩余学习时长: {remaining_time // 60}m {remaining_time % 60}s'
                    frame = put_chinese_text(
                        frame,
                        text,
                        (10, 30),
                        font_path,
                        30,  # 字体大小
                        (0, 0, 255)  # 颜色
                    )
            else:
                if countdown_started:
                    logging.info('未检测到人脸，暂停计时。')
                    countdown_started = False
                    pause_time = time.time()  # 记录暂停时间
                # 显示外部时间范围提示
                frame = put_chinese_text(
                    frame,
                    '不在指定的时间范围内',
                    (10, 30),
                    font_path,
                    30,  # 字体大小
                    (0, 0, 255)  # 颜色
                )

            cv2.imshow(window_name, frame)

            if cv2.waitKey(10) & 0xFF == ord('q'):
                break

    except Exception as e:
        logging.error(f"发生错误: {e}")
    finally:
        cap.release()  # 确保摄像头资源被释放
        cv2.destroyAllWindows()
        logging.info('人脸捕捉完成。')


def get_time_input(prompt):
    while True:
        time_str = input(prompt)
        try:
            datetime.strptime(time_str, "%H:%M")
            return time_str
        except ValueError:
            print("时间格式错误，请输入如 17:00 这样的24小时制时间。")


if __name__ == '__main__':
    config = load_config()
    start_time_str = get_time_input("Enter the start time (e.g., 17:00 for 5pm): ")
    end_time_str = get_time_input("Enter the end time (e.g., 18:00 for 6pm): ")
    while True:
        try:
            percentage = int(input("Enter the minimum percentage of the time to monitor (0-100): "))
            if 0 <= percentage <= 100:
                break
            else:
                print("请输入 0 到 100 之间的整数。")
        except ValueError:
            print("请输入有效的整数。")

    required_time = calculate_required_time(start_time_str, end_time_str, percentage)

    # 指定中文字体的路径
    font_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'fonts', 'SimHei.ttf')  # 确保路径正确

    logging.info(f'Starting face capture, will monitor for at least {required_time} minutes...')
    capture_faces_with_timer('FaceCapture', config['camera_id'], config['path_name'], 1000, required_time, start_time_str,
                             end_time_str, font_path)