clean unused code

Former-commit-id: 3b6d3de61757e8833c8066935ccf468acd208eae

Auto_Ctrl/predictor_Syringe_Pump.py

@@ -1,16 +1,12 @@
 import torch
 from PIL import Image
 import torchvision.transforms as transforms
-from torch.autograd import Variable
-from torch import nn
-import matplotlib.pyplot as plt
 import cv2
 import time
 import os
 from model import resnet34
 import serial
 from datetime import datetime
-from scipy.optimize import curve_fit
 import numpy as np
 import joblib
 import json
@@ -27,9 +23,6 @@ class MAT:
         self.device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
         self.port = Find_COM.list_ch340_ports()[0]  # 串口名
         self.pump_ser = serial.Serial(self.port, 9600) # 初始化串口
-        # self.usb_port = Find_COM.list_USB_ports()  # 串口名
-        # if self.usb_port:
-        #     self.usb_ser = serial.Serial(self.usb_port, 115200) # 初始化串口
         self.classes = classes
         self.total_volume = 0 # 记录总体积
         self.now_volume = 0 # 记录当前注射泵内体积
@@ -99,75 +92,6 @@ class MAT:
         data = b"q6h6d"
         self.pump_ser.write(data)
 
-    def voltage(self): # 测量电位
-        self.usb_ser.write("VOL|\n".encode())
-        time.sleep(0.1)
-        while True:
-            response = self.usb_ser.readline().decode().strip()
-            if response:
-                try:
-                    return float(response)
-                except:
-                    return 0
-
-    @staticmethod
-    def poly_func(x, a, b, c, d):
-        return a * np.tanh(d * x + b) + c
-
-    def line_chart(self):
-        x = self.volume_list
-        y = self.voltage_list
-        z = self.color_list
-
-        fig, ax1 = plt.subplots()
-        plt.title("titration curve")
-        color = 'tab:red'
-        ax1.set_xlabel('value')
-        ax1.set_ylabel('voltage', color=color)
-        ax1.plot(x, y, color=color, antialiased=True)
-        ax1.tick_params(axis='y', labelcolor=color)
-
-        ax2 = ax1.twinx()
-        color = 'tab:blue'
-        ax2.set_ylabel('color', color=color)
-        ax2.plot(x, z, color=color)
-        ax2.tick_params(axis='y', labelcolor=color)
-        ax2.set_yticks([0, 1])
-        ax2.set_yticklabels(['yellow', 'orange'])
-        ax2.spines['right'].set_position(('outward', 60))
-
-        try:
-            popt, pcov = curve_fit(self.poly_func, x, y, p0=[max(y) * 3 / 4, -max(x), max(y), 1.5])
-            print("最优参数:", popt)
-            print(f'电位突跃点：{-popt[1] / popt[3]:.3f}')
-            x_d = np.arange(0, max(x), 0.05)
-            y_fit = self.poly_func(x_d, *popt)
-            dE_dV = np.gradient(y_fit)
-            d2E_dV2 = np.gradient(dE_dV)
-            y2 = d2E_dV2.tolist()
-
-            ax3 = ax1.twinx()
-            color = 'tab:green'
-            ax3.set_ylabel('2nd Derivative', color=color)
-            ax3.plot(x_d, y2, color=color)
-            ax3.tick_params(axis='y', labelcolor=color)
-            ax3.grid(True, linestyle='--', linewidth=0.5, color='gray', axis='both')
-
-            x_d, y_d = -popt[1] / popt[3], 0.0
-            ax3.plot(x_d, y_d, 'ro')
-            ax3.annotate(f'({x_d:.2f})', xy=(x_d, y_d), color='red', xytext=(x_d - 1, y_d + max(y2) / 10))
-
-        except Exception as e:
-            print(e)
-            pass
-
-        fig.tight_layout()
-        plt.savefig(f'Output/{self.formatted_time}.png')
-        plt.show()
-        plt.pause(1)
-        plt.close()
-
-    
     def preproc(self, im):
         try:
             hsv = cv2.cvtColor(im,cv2.COLOR_BGR2HSV)
@@ -264,6 +188,9 @@ class MAT:
 
     def save_img(self):
         suc,im = self.cap.read()
+        if not suc:
+            print("Failed to capture frame from camera.")
+            return
         cv2.imshow("new",im)
         name  = f"Imgs/{self.formatted_time}_{self.total_volume}.jpg"
         if not cv2.imwrite(name,im):
@@ -297,28 +224,11 @@ class MAT:
 
             self.total_volume = round(self.total_volume, 3)
 
-            # suc,im = self.cap.read()
-            # cv2.imshow('Color', im)
-            # cv2.waitKey(1)
-
-            # class_a, prob_b = self.my_predictor(im_file)
-            # class_a, prob_b = self.predictor(im_file)
             
             self.volume_list.append(self.total_volume)
             self.save_img()
             cv2.waitKey(1)
             
-            # 如果有电压测量设备，可以在这里读取电压
-            # self.voltage_list.append(self.voltage())
-
-            # if class_a == end_kind and prob_b > end_prob:  # 判断终点
-            #     print('----->>Visual Endpoint<<-----')
-            #     print(f"Total Volume: {self.total_volume} ml")
-            #     print(f"Image File: {im_file}")
-            #     self.color_list.append(1)
-            #     break
-            # else:
-            #     self.color_list.append(0)
             print(f"Current Total Volume: {self.total_volume} ml")
         self.save_img()
         print('----->>Visual Endpoint<<-----')