import os
import time
from copy import deepcopy

import numpy as np
from PIL import Image, ImageDraw, ImageFont

from AcrossPlatform.get_platform import GLOBAL_DIR
from MCamera.mp_camera import *
from Speaker import speak_base
from Speaker.speak_base import beep
from Database.manager_database import NAME
from realtime_streaming import img_format_jpg


def base_detect_image(camera: Camera):
    _map = MediapipeAlgorithmPlugin()
    while True:
        _img = deepcopy(camera.get_frame())
        img = _map.find_pose_with_drawing(_img, True)
        yield b'--frame\r\nContent-Type: image/jpeg\r\n\r\n' + img_format_jpg(img) + b'\r\n'


class BaseExercise(threading.Thread):

    def __init__(self, info, statistic_time=120, camera: Camera = None):
        super().__init__(daemon=True)
        # 初始化窗体设置
        self.detector = MediapipeAlgorithmPlugin()
        # 摄像头对象
        if not camera:
            self.cap = Camera()
        else:
            self.cap = camera

        # 个数统计
        self.count = 0
        # 当前状态
        self.dir = 0
        # 统计时间
        self.statistic_time = statistic_time
        # 开始时间
        self.start_time = time.time()
        # 開始計算時間
        self.start_cal_time = time.time()
        # 强制结束标志
        self.kill_sign = False
        # 当前画面
        self.img = None
        # 记录是否开始
        self.is_start = False
        # 获得人员信息
        self.info = info
        # 设置摄像头长时间不关闭
        Camera.AUTO_CLOSE_TIMEOUT = float('inf')
        self.exercise_type = ""
        self.bright = -5
        self.speak_driver = speak_base.SpeakServer()

        self.corner = (0, 480, 0, 640)
        self.config = (True, 1, True, False, True, 0.5, 0.5)

    def start(self) -> None:
        super().start()
        self.start_cal_time = time.time()

    def get_info(self):
        return None

    def is_done(self):
        if time.time() - self.start_time > self.statistic_time or self.kill_sign:
            Camera.stop_record()
            return True
        else:
            return False

    def get_result(self):
        result = {}
        return result

    # 判断作训是否有效
    def is_valid(self):
        return True

    # 作训回传文字
    @staticmethod
    def valid_mes():
        return ""

    def tran_count(self):
        return self.count

    def speak_counting(self, counting_times, name):
        self.speak_driver.start()
        self.speak_driver.speed_control(200)
        self.speak_driver.volume_control(1)
        self.speak_driver.add_speak("考试人员{}".format(name))
        self.speak_driver.add_speak(f"考试项目{self.exercise_type}")
        self.speak_driver.add_speak(f"倒计时！")
        retail_counting = counting_times
        counting = 0
        start_time = time.time()
        while True:
            this_time = time.time()
            if this_time - start_time > counting:
                if retail_counting > 0:
                    self.speak_driver.add_speak(f"{retail_counting}！")
                    self.speak_driver.wait_4_speak()
                    counting += 1
                    retail_counting -= 1
                else:
                    break
        threading.Thread(target=beep, daemon=True).start()

    # 作訓計算數據流
    def analysis(self, frame):
        pass

    def thread_counting_streaming(self):
        self.cap.clear_cache()
        # start_time = time.time()
        # count = 0
        while not self.is_done():

            frame = self.cap.get_cache()
            if frame:
                # catch_time = frame[CATCH_TIME]
                self.analysis(frame=frame)

                # count += 1
                # if catch_time - start_time > 1:
                #     print(count, time.time() - catch_time, catch_time - start_time)
                #     start_time = catch_time
                #     count = 0

    # 作訓視頻流
    def display(self, img):
        return img

    def run(self) -> None:
        self.speak_counting(5, self.info[NAME])
        # 清除历史记录
        # 记录开始时间
        self.start_time = time.time()
        self.is_start = True
        # 不停更新计算和更新画面
        threading.Thread(target=self.thread_counting_streaming, daemon=True).start()
        while not self.is_done():
            _img = self.cap.get_frame()
            self.img = self.display(_img)
        self.is_start = False

    def skeleton_video(self):
        _img = deepcopy(self.cap.get_frame())
        self.img = self.detector.find_pose_with_drawing(_img, True)
        return self.img

    def pure_streaming_gen(self):
        if not self.kill_sign:
            if self.is_start and self.img is not None:
                return self.img
            else:
                return self.skeleton_video()

    def pure_video_gen(self):
        if not self.kill_sign:
            self.img = cv2.rectangle(
                self.skeleton_video(),
                (self.corner[2], self.corner[0]),
                (self.corner[3], self.corner[1]),
                (0, 255, 0), 2
            )
            return self.img


    def streaming_gen(self):
        while not self.kill_sign:
            if self.is_start and self.img is not None:
                yield (b'--frame\r\n'
                       b'Content-Type: image/jpeg\r\n\r\n' + img_format_jpg(self.img) + b'\r\n')
            else:
                yield (b'--frame\r\n'
                       b'Content-Type: image/jpeg\r\n\r\n' + img_format_jpg(self.skeleton_video()) + b'\r\n')

    def video_gen(self):
        while not self.kill_sign:
            self.img = cv2.rectangle(
                self.skeleton_video(),
                (self.corner[2], self.corner[0]),
                (self.corner[3], self.corner[1]),
                (0, 255, 0), 2
            )
            yield (
                    b'--frame\r\nContent-Type: image/jpeg\r\n\r\n'
                    + img_format_jpg(self.img)
                    + b'\r\n'
            )

    def waiting_for_start(self):
        while not self.is_start:
            time.sleep(0.001)

    def kill(self):
        self.kill_sign = True
        self.speak_driver.stop()
        while self.is_alive():
            time.sleep(0.1)

    @staticmethod
    def cv2_img_add_text(img, text, left, top, text_color=(0, 255, 0), text_size=30):
        if isinstance(img, np.ndarray):  # 判断是否OpenCV图片类型
            img = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
        # 创建一个可以在给定图像上绘图的对象
        draw = ImageDraw.Draw(img, None)
        # 字体的格式
        font_type_dir = os.path.join(GLOBAL_DIR, "Exercise3/simsun.ttc")
        fontstyle = ImageFont.truetype(font_type_dir, text_size, encoding="utf-8")
        # 绘制文本
        draw.text((left, top), text, text_color, font=fontstyle)
        # 转换回OpenCV格式
        return cv2.cvtColor(np.asarray(img), cv2.COLOR_RGB2BGR)