import cv2 import time from datetime import datetime import numpy as np import ch340 import atexit import utils from utils import State, History,login_to_platform,send_data_to_platform from scipy.signal import find_peaks import tkinter as tk class MAT: def __init__(self, videoSourceIndex=0, bounce_time=2, end_bounce_time=5,k=30): # 初始化logging utils.setup_logging() self.system_logger = utils.get_system_logger() self.control_logger = utils.get_control_logger() self.endpoint_logger = utils.get_endpoint_logger() self.volume_logger = utils.get_volume_logger() self.system_logger.info('正在初始化MAT系统...') self.videoSourceIndex = videoSourceIndex self.cap = cv2.VideoCapture(videoSourceIndex, cv2.CAP_DSHOW) self.ch340 = ch340.CH340() self.total_volume = 0 self.k = k self.state = State(bounce_time, end_bounce_time) atexit.register(self.ch340.stop) self.history = History(max(bounce_time, end_bounce_time)) self.first_about = 0 self.colored_volume = None self.colored_time = None self.colored_im = None def ch340_pull(self): self.control_logger.info("开始抽取12ml") self.ch340.max_speed() self.ch340.pull(vol=12) self.control_logger.info('完成抽取') def ch340_init(self): # self.ch340.push(speed=1,t=1) self.ch340.pull(speed=1.2,vol=1.8) self.control_logger.info('电极位置已初始化') def ch340_push(self, speed=0.1): self.ch340.push_async(speed=speed, t=1) def process_left(self, now: float, value_only=False): if self.state.mode == State.Mode.CRAZY: value_only = True if self.state.mode == State.Mode.ABOUT: return self.total_volume st = self.ch340.start if not value_only: self.ch340.stop() if not abs(self.ch340._get_time()-1) < 1e-3: self.control_logger.warning(f"CH340 timing issue detected: {self.ch340._get_time()}") return self.total_volume r = now - st ret = self.total_volume - (1-r) * self.speeds[self.state.mode.value] if value_only: return ret else: self.total_volume = ret def _pred(self): """预测当前图像状态，返回'transport'、'middle'、'about'或'colored'""" suc, im = self.cap.read() if not suc: self.control_logger.error("无法从摄像头捕获帧") return None # 录制当前帧到视频文件 if hasattr(self, 'capFile') and self.capFile.isOpened(): self.capFile.write(im) ret, rate = self.predictor(im) if ret is None: return None now = time.time() val = self.process_left(now, value_only=True) # 确保val不为None if val is None: self.control_logger.warning("体积计算返回None，跳过本次记录") return ret # 更新滑动窗口历史记录 - 维护最近end_bounce_time内的状态 self.history.add_record(now, ret, rate, val, im) if self.history.is_empty(): self.control_logger.error("未预期的没有可用的历史记录") return ret if self.state.mode == State.Mode.CRAZY: self._display_status(im, ret, rate, val) return ret # === 状态进入逻辑 === if now - self._start_time<10: self._display_status(im, ret, rate, val) return ret if not self.edited and self.history.base is not None and rate>self.history.base * 2: self.edited = True self.speeds[0] /= 2 # 1. middle: predictor返回middle立即进入slow状态 if ret == "middle": if self.state.is_fast_mode(): self.process_left(now) self.state.enter_middle_state(now) self.control_logger.info(f"检测到middle，立即进入slow模式，当前体积: {val:.2f} ml") # 2. about: 返回about，且处于middle则进入about状态 elif ret == "about": if self.state.is_slow_mode(): self.process_left(now) self.state.enter_about_state(now) self.control_logger.info(f"检测到about，进入about模式，当前体积: {val:.2f} ml") # 3. end：返回colored，置end_check标记开始检查 # elif ret == "colored": # if not self.state.in_end_check: # self.state.enter_end_check(now) # if self.colored_volume is None: # self.colored_volume = val # self.colored_time = now # self.colored_im = im.copy() # self.endpoint_logger.info(f"检测到colored，开始end检查，记录体积: {val:.2f} ml") # === 状态检查逻辑 === # middle检查: 进入middle的bounce_time后，在最近bounce_time内middle比例<70%返回fast状态 if self.state.should_check_middle_exit(now) and not self.history.last_end: # 计算最近bounce_time内的middle比例 recent_records = self.history.get_recent_records(self.state.bounce_time, now) if recent_records: trans_ratio = self.history.get_state_ratio("transport", recent_records) if trans_ratio > 0.4: self.process_left(now) self.state.exit_middle_check() # about状态随middle一起退出 # self.state.exit_about_with_middle() self.control_logger.info(f"middle比例{trans_ratio:.2%}<60%，退出middle检查，返回fast模式") if self.state.mode == State.Mode.ABOUT and self.state.about_check: h = self.history.get_recent_records(self.about_time/3,now) ratio = self.history.get_state_ratio("transport", h) self.history.about_history.append(ratio == 1) while len(self.history.about_history) > 5: self.history.about_history.pop(0) if len(self.history.about_history) == 5 and self.history.last_end < 2: rate = sum(self.history.about_history) / len(self.history.about_history) if rate > 0.8: self.state.exit_about() self.control_logger.info(f"about比例{ratio:.2%}<80%，退出about检查，返回middle模式") ret = self.end_check() if ret == "colored": return ret if not self.history.last_end: self.history.last_end = max(self.history.last_end,ret) self.state.about_check = False # 显示状态信息 self._display_status(im, ret, rate, val) return ret def end_check(self,dep=0): if not self.running: return "colored" if dep == 1: suc,im = self.cap.read() hsv = cv2.cvtColor(im, cv2.COLOR_BGR2HSV) # 降低饱和度通道 (S通道是索引1) hsv[:, :, 1] = hsv[:, :, 1] * 0.8 # 转换回BGR颜色空间 result = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR) name = f"colored_{datetime.now().strftime('%Y%m%d_%H%M%S')}.jpg" cv2.imwrite(name,result) self.colored_im = name if dep > 3: # self.endpoint_logger.info(f"colored比例{.2%}>=70%，确认滴定终点") self.colored_volume = self.total_volume self.endpoint_logger.info(f"最终体积: {self.colored_volume:.2f} ml") self.running = False self.ch340.stop() # if self.colored_im is not None: # cv2.imwrite(f"colored_{datetime.now().strftime('%Y%m%d_%H%M%S')}.jpg", self.colored_im) return "colored" suc,im = self.cap.read() hsv = cv2.cvtColor(im, cv2.COLOR_BGR2HSV) s = hsv[:, :, 0] s = s[s > 0] hist = cv2.calcHist([s], [0], None, [256], [0, 256]) hist = hist.flatten() # 转换为一维数组 # 峰值检测 - 找到直方图中的峰值 peaks, properties = find_peaks(hist, height=np.max(hist) * 0.2, # 峰值高度至少是最大值的10% distance=10, # 峰值之间的最小距离 prominence=np.max(hist) * 0.01) # 峰值的突出度 if np.any(peaks>130): if dep == 0: self.process_left(time.time()) self.history.end_history.append(True) self.control_logger.info(f"检测到colored状态，end_check at {dep}") bgn = time.time() while time.time()-bgn < 2: suc,im = self.cap.read() if hasattr(self, 'capFile') and self.capFile.isOpened(): self.capFile.write(im) cv2.putText(im, "ENDCHK", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 0), 2) cv2.imshow("Frame", im) return self.end_check(dep+1) # time.sleep(2) else: self.colored_im = None return dep def _display_status(self, im, detection_result, rate, volume): """显示状态信息到图像上""" mode_color = { State.Mode.FAST: (255, 255, 255), State.Mode.SLOW: (10, 215, 255), State.Mode.ABOUT: (228,116,167), State.Mode.CRAZY: (0, 255, 0), # State.Mode.END: (0, 0, 255) } status_text = f"Stat: {detection_result}, rate: {round(rate,2)}, Vol: {volume:.2f} ml" status_text += self.state.get_status_text() cv2.putText(im, status_text, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, mode_color[self.state.mode], 2) cv2.imshow("Frame", im) cv2.waitKey(1) def predictor(self,im): hsv = cv2.cvtColor(im,cv2.COLOR_BGR2HSV) s = hsv[:,:,1] mask = s>self.k cv2.imshow('mask',im*mask[:,:,np.newaxis]) tot = mask.shape[0]*mask.shape[1] val = np.sum(mask) rate = val/tot if self.history.base is not None: base = self.history.base thr = (min(0.05,base*5), min(0.2,base*13), 0.5) # thr = (base*5, base*13, 0.5) if rate < thr[0]: return "transport",rate elif rate mid_time: should_push = True elif self.state.is_about_mode() and time.time() - self.ch340.start > about_time: if not self.state.about_first_flag: self.state.about_check = True else: self.state.about_first_flag = False should_push = True if should_push: speed = self.speeds[self.state.mode.value] self.volume_logger.info(f"当前体积: {self.total_volume:.2f} ml, 加入速度: {speed:.2f} ml/次") self.ch340_push(speed) self.total_volume += speed self.volume_list.append(round(self.total_volume,2)) try: self.color_list.append(self.state.mode.name) except Exception as e: self.control_logger.error(f"报表失败: {e}") # if (self.state.is_about_mode() and time.time() - self.ch340.start > end_time) or not self.state.is_about_mode(): if self._pred() is None: self.control_logger.error("预测失败，跳过当前帧") continue # try: # self.control_logger.info("推送安全体积") # self.ch340_push(0.15) # except Exception as e: # self.control_logger.error(f"推送失败: {e}") # 释放视频录制器 if hasattr(self, 'capFile') and self.capFile.isOpened(): self.capFile.release() self.system_logger.info(f"视频录制完成: {vid_name}") # 实验结束，记录结果 experiment_results = { "总体积 ": f"{self.total_volume:.2f} ml", "终点体积": f"{self.colored_volume:.2f} ml", "理论体积": f"{self.colored_volume:.2f} ml", "实验时长": f"{time.time() - self.start_time:.2f} 秒", "滴定速率": f"{self.total_volume / (time.time() - self.start_time):.2f} mL/s", } upload_data = { "start_time":self.format_date_time(self.start_time), "end_time":self.format_date_time(time.time()), "volume_record": f'{self.volume_list}', 'voltage_record': f'{[]}', 'color_record': f'{self.color_list}', 'final_volume': f'{self.colored_volume}', } self.system_logger.info("实验结果:") for key, value in experiment_results.items(): self.system_logger.info(f" {key}: {value}") return upload_data, self.colored_im if __name__ == "__main__": token = login_to_platform("13504022184","password") # 创建MAT类的实例并运行 mat = MAT( videoSourceIndex = 1, bounce_time=2, end_bounce_time=0.01, k = 32 ) mat.state.mode = State.Mode.FAST final_data, finish_picture = mat.run( slow_speed = 0.05, quick_speed = 1.0, about_time=3, # cap_dir=None ) with open("log.json","w") as f: import json json.dump(final_data, f, indent=4) send_data_to_platform(token, final_data, finish_picture)