308 lines
12 KiB
Python
308 lines
12 KiB
Python
import cv2
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import time
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from datetime import datetime
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import numpy as np
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import ch340
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import atexit
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import utils
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from enum import Enum
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class Flags(Enum):
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ENDCHK = 0b01
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MIDCHK = 0b10
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@staticmethod
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def un(flag):
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return 0b11 ^ flag.value
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class MAT:
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def __init__(self, videoSourceIndex=0, bounce_time=1,end_bounce_time=5):
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# 初始化logging
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utils.setup_logging()
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self.system_logger = utils.get_system_logger()
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self.control_logger = utils.get_control_logger()
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self.endpoint_logger = utils.get_endpoint_logger()
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self.volume_logger = utils.get_volume_logger()
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self.system_logger.info('正在初始化MAT系统...')
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self.videoSourceIndex = videoSourceIndex
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self.cap = cv2.VideoCapture(videoSourceIndex, cv2.CAP_DSHOW)
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self.ch340 = ch340.CH340()
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self.bounce_time = bounce_time
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self.end_bounce_time = end_bounce_time
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self.total_volume = 0
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self.middle_time = 0
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self.flags = 0
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atexit.register(self.ch340.stop)
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self.history = [] # 滑动窗口历史记录
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self.colored_volume = None # 首次colored体积
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self.colored_time = None # 首次colored时间
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self.colored_im = None # 首次colored图像
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def ch340_pull(self):
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self.control_logger.info("开始抽取12ml")
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self.ch340.max_speed()
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self.ch340.pull(vol=12)
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self.control_logger.info('完成抽取')
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def ch340_init(self):
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self.ch340.push(speed=1,t=1)
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self.ch340.pull(speed=1.2,vol=1)
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self.control_logger.info('电极位置已初始化')
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def ch340_push(self, speed=0.1):
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self.ch340.push_async(speed=speed, t=1)
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def process_left(self,now:float, velue_only=False):
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st = self.ch340.start
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if not velue_only: self.ch340.stop()
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assert abs(self.ch340._get_time()-1) < 1e3 # run time should be 1s
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r = now-st
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ret = self.total_volume - (1-r)*self.speeds[self.typ] # 减去未完成的体积
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if velue_only:return ret
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else:self.total_volume = ret
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def _pred(self):
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"""预测当前图像状态，返回'transport'、'middle'或'colored'"""
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suc, im = self.cap.read()
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if not suc:
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self.control_logger.error("无法从摄像头捕获帧")
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return None
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# 录制当前帧到视频文件
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if hasattr(self, 'capFile') and self.capFile.isOpened():
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self.capFile.write(im)
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ret,rate = self.predictor(im)
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if ret is None:
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return None
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now = time.time()
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val = self.process_left(now,velue_only=True)
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# 记录历史状态，保留bounce_time时间内的记录
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self.history.append((now, ret, val, im))
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while self.history and self.history[0][0] < now - self.end_bounce_time:
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self.history.pop(0)
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if not self.history:
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self.control_logger.error("未预期的没有可用的历史记录")
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return ret
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# 处理检测结果
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if ret == "middle":
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# 检测到middle立即切换到慢速模式
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if self.typ == 0:
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self.process_left(now)
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self.typ = 1
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self.middle_time = now
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self.flags |= Flags.MIDCHK.value
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self.control_logger.info(f"检测到middle，切换到慢速模式，当前体积: {val:.2f} ml")
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elif ret == "colored":
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# 检测到colored时记录当前体积
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if self.colored_volume is None:
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self.colored_volume = val
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self.colored_time = now
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self.colored_im = self.history[-1][3] # 保存当前图像
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self.flags |= Flags.ENDCHK.value
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self.endpoint_logger.info(f"检测到colored，记录体积: {self.colored_volume:.2f} ml")
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# 检查是否要停止
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if self.colored_time is not None and now - self.colored_time > self.end_bounce_time:
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colored_count = sum(1 for _, state, _,_ in self.history if state == "colored")
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if colored_count / len(self.history) > 0.9:
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self.endpoint_logger.info(f"确认终点，最终体积: {self.colored_volume:.2f} ml")
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self.running = False
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self.ch340.stop()
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cv2.imwrite(f"colored_{datetime.now().strftime('%Y%m%d_%H%M%S')}.jpg", self.colored_im)
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return "colored"
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else:
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self.flags &= Flags.un(Flags.ENDCHK)
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self.endpoint_logger.warning(f"colored比例小于90%，当前体积: {val:.2f} ml, 比例: {colored_count / len(self.history):.2%}")
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self.colored_volume = val
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self.colored_time = now
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else: # ret == "transport"
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pass
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# 在慢速模式下检查是否要切回快速模式
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if self.typ == 1 and now - self.middle_time > self.bounce_time and not self.flags & Flags.ENDCHK.value:
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non_middle_count = sum(1 for _, state, _,_ in self.history if state == "transport")
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if non_middle_count / len(self.history) > 0.8:
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self.typ = 0
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self.process_left(now)
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# TODO: 滑动到第一个middle状态
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self.middle_time = 0
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self.control_logger.info(f"非middle比例超过80%，切回快速模式，当前体积: {val:.2f} ml")
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self.flags &= Flags.un(Flags.MIDCHK)
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# 如果已记录colored但在bounce_time内colored比例小于90%，重置
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if self.colored_volume is not None and self.colored_time is not None and now - self.colored_time > self.end_bounce_time:
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colored_count = sum(1 for _, state, _,_ in self.history if state == "colored")
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if colored_count / len(self.history) < 0.9:
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self.endpoint_logger.warning(f"colored比例小于90%，重置colored记录")
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self.colored_volume = None
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flag = False
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for t, state,vol,_ in self.history:
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if state == "colored":
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if not flag:
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flag = True
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continue
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self.endpoint_logger.debug(f"滑动窗口到: {vol:.2f} ml at {t}")
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self.colored_volume = vol
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self.colored_time = t
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break
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if self.colored_volume is None:
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self.flags &= Flags.un(Flags.ENDCHK)
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self.typ = 0
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else:
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self.endpoint_logger.warning("异常情况，colored超过90%但最后状态是transport")
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self.endpoint_logger.info(f"疑似滴定终点: {self.colored_volume:.2f} ml")
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t = f"Stat: {ret}, rate: {round(rate,2)}, Vol: {val:.2f} ml"
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if self.middle_time > 0 and (now - self.middle_time)<self.bounce_time:
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self.flags |= Flags.MIDCHK.value
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t += f", MIDCHK"
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if self.colored_time is not None and (now - self.colored_time) < self.end_bounce_time:
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self.flags |= Flags.ENDCHK.value
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t += f", ENDCHK"
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cv2.putText(im,
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t,
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(10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (10,215, 255) if self.typ else (255,255,255), 2)
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cv2.imshow("Frame", im)
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cv2.waitKey(1)
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return ret
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def predictor(self,im):
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hsv = cv2.cvtColor(im,cv2.COLOR_BGR2HSV)
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s = hsv[:,:,1]
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mask = s>30
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cv2.imshow('mask',im*mask[:,:,np.newaxis])
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tot = mask.shape[0]*mask.shape[1]
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val = np.sum(mask)
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rate = val/tot
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if rate < 0.02:
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return "transport",rate
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elif rate <0.2:
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return "middle",rate
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elif rate < 0.4:
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return "about",rate
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else:
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return "colored",rate
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def __del__(self):
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self.cap.release()
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if hasattr(self, 'capFile') and self.capFile.isOpened():
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self.capFile.release()
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cv2.destroyAllWindows()
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def run(self,quick_speed = 0.2,slow_speed = 0.05,end_speed = 0.02,mid_time = 0.5,end_time=1, cap_dir="Videos"):
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self.running = True
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self.typ = 0
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self.start_time = time.time()
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self.speeds = (quick_speed, slow_speed,end_speed)
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if cap_dir is not None:
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vid_name = f"{cap_dir}/{datetime.now().strftime('%Y%m%d_%H%M%S')}.mp4"
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else:
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vid_name = "Disabled"
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# 记录实验开始
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experiment_params = {
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"视频源索引 ": self.videoSourceIndex,
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"防抖时间 ": self.bounce_time,
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"快速模式速度": f"{quick_speed} ml/次",
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"慢速模式速度": f"{slow_speed} ml/次",
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"录制视频 ": vid_name
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}
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self.system_logger.info("实验参数:")
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for key, value in experiment_params.items():
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self.system_logger.info(f" {key}: {value}")
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speed = self.speeds[self.typ]
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# 获取摄像头的帧率和分辨率
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fps = int(self.cap.get(cv2.CAP_PROP_FPS)) or 30
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width = int(self.cap.get(cv2.CAP_PROP_FRAME_WIDTH))
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height = int(self.cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
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# 初始化视频录制器
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if vid_name != "Disabled":
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fourcc = cv2.VideoWriter_fourcc(*'avc1')
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self.capFile = cv2.VideoWriter(vid_name, fourcc, fps, (width, height))
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if not self.capFile.isOpened():
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self.system_logger.error(f"无法打开视频录制器: {vid_name}")
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del self.capFile
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else:
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self.system_logger.info(f"视频录制已初始化")
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self.ch340_init()
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cnt=0
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while self.running:
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match (self.flags):
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case 0:
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self.typ = 0
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case Flags.MIDCHK.value:
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self.typ = 1
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case Flags.ENDCHK.value:
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self.typ = 2
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if self.flags&Flags.ENDCHK.value and self.typ != 2:
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# self.system_logger.warning("Colored状态但未进入慢速")
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self.typ = 2
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# if self.flags == Flags.MIDCHK.value and self.typ != 1:
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# self.system_logger.warning("Middle状态但未进入慢速")
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# self.typ = 1
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if not self.ch340.running:
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if 12*cnt - self.total_volume<0.5:
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self.ch340_pull() # 抽取12ml
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cnt+=1
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time.sleep(0.01)
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flag = False
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flag |= self.typ == 0
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flag |= self.typ == 1 and time.time()-self.ch340.start > mid_time
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flag |= self.typ == 2 and time.time()-self.ch340.start > end_time
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if flag:
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self.volume_logger.info(f"当前体积: {self.total_volume:.2f} ml, 加入速度: {speed:.2f} ml/次")
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speed = self.speeds[self.typ]
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self.ch340_push(speed)
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self.total_volume += speed
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if self._pred() is None:
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self.control_logger.error("预测失败，跳过当前帧")
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continue
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# 释放视频录制器
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if hasattr(self, 'capFile') and self.capFile.isOpened():
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self.capFile.release()
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self.system_logger.info(f"视频录制完成: {vid_name}")
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# 实验结束，记录结果
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experiment_results = {
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"总体积 ": f"{self.total_volume:.2f} ml",
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"终点体积": f"{self.colored_volume:.2f} ml",
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"理论体积": f"{self.colored_volume:.2f} ml",
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"实验时长": f"{time.time() - self.start_time:.2f} 秒"
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}
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self.system_logger.info("实验结果:")
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for key, value in experiment_results.items():
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self.system_logger.info(f" {key}: {value}")
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if __name__ == "__main__":
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# 创建MAT类的实例并运行
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mat = MAT(
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videoSourceIndex = 1,
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bounce_time=3,
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end_bounce_time=20
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)
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mat.run(
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slow_speed = 0.05,
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quick_speed = 0.15,
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end_time= 2
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# cap_dir=None
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)
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