cbc code added with GUI
This commit is contained in:
moonanjum26
256
src/ofm_code_cbc_v1/new_updated_ofm .py
Normal file
256
src/ofm_code_cbc_v1/new_updated_ofm .py
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@@ -0,0 +1,256 @@
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#import matlab.engine
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from PyQt5 import QtCore, QtGui, uic, QtWidgets
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import sys,os
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import numpy as np
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import cv2
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import serial,sys
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import threading, time, Queue
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from datetime import datetime
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name=raw_input("enter patient's name ")
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#age=raw_input("enter age ")
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today=datetime.now().date()
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today1=datetime.now().time()
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#t = datetime.time(datetime.now())
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path = "./%s-" %name + str(today)
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try:
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os.mkdir(path)
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except OSError:
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print ("Creation of the directory %s failed" % path)
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else:
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print ("Successfully created the directory %s " % path)
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running = False
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capture_thread = None
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#for i in range(3):
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form_class = uic.loadUiType("simple.ui")[0]
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q = Queue.Queue()
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ser = serial.Serial('COM3',57600)
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capture = cv2.VideoCapture(0)
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capture_duration = 60*1
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q_write = Queue.Queue()
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def grab(width, height):
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global running,q,capture
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#capture = cv2.VideoCapture(0)
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capture.set(cv2.CAP_PROP_FRAME_WIDTH, width)
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capture.set(cv2.CAP_PROP_FRAME_HEIGHT, height)
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capture.set(cv2.CAP_PROP_EXPOSURE, -13)
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#print (capture.get(cv2.CAP_PROP_EXPOSURE) )
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while(running):
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retval, img = capture.read()
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if q.qsize() < 7200:
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q.put(img)
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class OwnImageWidget(QtWidgets.QWidget):
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def __init__(self, parent=None):
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super(OwnImageWidget, self).__init__(parent)
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self.image = None
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def setImage(self, image):
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self.image = image
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sz = image.size()
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self.setMinimumSize(sz)
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self.update()
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def paintEvent(self, event):
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qp = QtGui.QPainter()
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qp.begin(self)
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if self.image:
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qp.drawImage(QtCore.QPoint(0, 0), self.image)
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qp.end()
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class MyWindowClass(QtWidgets.QMainWindow, form_class):
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location=''
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def __init__(self, parent=None):
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QtWidgets.QMainWindow.__init__(self, parent)
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self.setupUi(self)
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self.resize(730,730)
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self.currzpos=0
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#btn1 = QtWidgets.QPushButton('X+', self)
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#btn2 = QtWidgets.QPushButton('X-', self)
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#btn1.move(200, 500)
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#btn2.move(300, 500)
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self.startButton.clicked.connect(self.start_clicked)
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self.startButton4.clicked.connect(self.main)
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self.window_width = self.ImgWidget.frameSize().width()
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self.window_height = self.ImgWidget.frameSize().height()
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self.ImgWidget = OwnImageWidget(self.ImgWidget)
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self.startButton1.clicked.connect(self.xPos)
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self.startButton2.clicked.connect(self.xNeg)
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self.timer = QtCore.QTimer(self)
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self.timer.timeout.connect(self.update_frame)
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self.timer.start(.01)
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self.startButton3.clicked.connect(self.fCapture)
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self.startButton5.clicked.connect(self.home)
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self.startButton6.clicked.connect(self.start)
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self.startButton7.clicked.connect(self.xPoss)
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self.startButton8.clicked.connect(self.xNegg)
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def main(self):
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capture_thread2 = threading.Thread(target=self.autofocus, args = ())
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capture_thread2.start()
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#capture_thread2.join()
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#self.autofocus()
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def home(self):
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ser.write('Q')
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self.currzpos=0
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def start(self):
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self.Zpulserate = 57600
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#ser.write('S')
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auto_travel=-650000
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self.gotoZ(auto_travel)
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def gotoZ(self,zValue):
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zValue = int(zValue)
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if self.currzpos != zValue:
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zValue_str = str("%($)07d" % {"$":zValue})
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print zValue_str
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ser.write('M')
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ser.write(str(zValue_str))
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time.sleep(abs(self.currzpos-zValue)/self.Zpulserate)
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self.currzpos = int(zValue)
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def autofocus(self):
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global q
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Z_travel_for_crude = 16000; crude_step_count = 200;
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crude_pulse_count = Z_travel_for_crude / crude_step_count;
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crude_max_var=0; crude_loc_max_var=0;
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crude_start_loc = self.currzpos -(Z_travel_for_crude/2);
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self.gotoZ(crude_start_loc)
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crude_curr_loc = crude_start_loc;
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kernel = np.ones((5,5),np.float32)/25
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for i in range(int(crude_pulse_count)):
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img=q.get()
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crude_curr_var = np.var(cv2.filter2D(img,-1,kernel))
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#cv2.imwrite("image/image_crude_auto{0}.jpg".format(i),img)
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print(crude_curr_var,'||',self.currzpos)
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if crude_curr_var > crude_max_var:
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crude_max_var = crude_curr_var
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crude_loc_max_var = crude_curr_loc
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image=img
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crude_curr_loc = crude_curr_loc + crude_step_count
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self.gotoZ(crude_curr_loc)
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time.sleep(.075)
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#a="image/image_crude%d.jpg"%crude_loc_max_var
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#cv2.imwrite(a ,image)
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self.gotoZ(crude_loc_max_var)
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def xPos(self):
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self.currzpos=int(self.currzpos)
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ser.write('G')
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self.currzpos = self.currzpos + 1
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print self.currzpos
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def xNeg(self):
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self.currzpos=int(self.currzpos)
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ser.write('T')
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print self.currzpos
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def xPoss(self):
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self.currzpos=int(self.currzpos)
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ser.write('D')
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self.currzpos = self.currzpos + 1
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print self.currzpos
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def xNegg(self):
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self.currzpos=int(self.currzpos)
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ser.write('A')
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self.currzpos = self.currzpos - 1
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print self.currzpos
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def start_clicked(self):
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global running
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running = True
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capture_thread.start()
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def update_frame(self):
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global q
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if not q.empty():
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img = q.get()
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img_height, img_width, img_colors = img.shape
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scale_w = float(self.window_width) / float(img_width)
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scale_h = float(self.window_height) / float(img_height)
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scale = min([scale_w, scale_h])
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if scale == 0:
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scale = 1
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img = cv2.resize(img, None, fx=scale, fy=scale, interpolation = cv2.INTER_CUBIC)
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img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
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height, width, bpc = img.shape
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bpl = bpc * width
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image = QtGui.QImage(img.data, width, height, bpl, QtGui.QImage.Format_RGB888)
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self.ImgWidget.setImage(image)
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def fCapture(self):
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capture_thread3 = threading.Thread(target=self.fCapture_read, args = ())
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capture_thread3.start()
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def fCapture_read(self):
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global capture,capture_duration
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global q_write
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t_end = time.time() + capture_duration
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self.counter=0
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print "frame capture started"
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while(capture.isOpened()):
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ret, frame = capture.read()
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if time.time() < t_end:
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if (ret==True):
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self.counter=self.counter+1
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if q_write.qsize()<120*capture_duration:
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q_write.put(frame)
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else:
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print "frames captured"
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print self.counter
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self.fcapture_write()
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#cap.release()
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def fcapture_write(self):
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global q_write,capture
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i=0
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if not q_write.empty():
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for i in range (self.counter):
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img=q_write.get()
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i=i+1
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cv2.imwrite(str(path)+ "/image%d.bmp" %i,img)
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self.call_matlab()
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def call_matlab(self):
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print "calling matlab"
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print path
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import matlab.engine as m
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eng = m.start_matlab()
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eng.new_whole_blood_segment_odroid(path)
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#print "calling matlab"
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#mlab.new_whole_blood_segment_odroid(path)
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if __name__ == '__main__' :
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capture_thread = threading.Thread(target=grab, args = (640,480))
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app = QtWidgets.QApplication(sys.argv)
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w = MyWindowClass()
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w.setWindowTitle('OFM GUI')
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w.show()
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app.exec_()
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323
src/ofm_code_cbc_v1/new_whole_blood_segment_odroid.m
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323
src/ofm_code_cbc_v1/new_whole_blood_segment_odroid.m
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@@ -0,0 +1,323 @@
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%%
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%The code creates a feature table for the different types of cells and
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%is used to create a initial training dataset for the classifier
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%%
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function a=new_whole_blood_segment_odroid(path)
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%path='./mahwish-2018-10-21';
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%%
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disp(path);
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%mkdir('G:\Experiments\odroid\S\S1\gate1');
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%mkdir('G:\Experiments\odroid\S\S1\gate2');
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mkdir(path,'/gate3');
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%mkdir('I:\ofm\im\im\gate3');
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%mkdir('C:\Users\DOIAP\Desktop\OFM\images\set8-80\gate4');
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%mkdir('G:\Experiments\odroid\S\S1\P');
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%%
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% To create a circular mask to eliminate the spokes channels and perform
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% processing of cells in the central imaging region
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% Create a logical image of a circle with specified
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% diameter, center, and image size.
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% First create the image.
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imageSizeX = 640; %X pixel size of the image
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imageSizeY = 480; %Y pixel size of the image
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[columnsInImage rowsInImage] = meshgrid(1:imageSizeX, 1:imageSizeY);
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% Next create the circle in the image.
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centerX = 300; %center X pixel of the circle
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centerY = 240; %center y pixel of the circle
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radius = 220; %Radius of the circle
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circlePixels = (rowsInImage - centerY).^2 ...
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+ (columnsInImage - centerX).^2 <= radius.^2; % creates the circular mask
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%% Generate Background
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%a = rgb2gray(imread(strcat('E:\Experiments\odroid\step1\1 (',num2str(V),').jpg')));
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%imshow(a);
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%%% average ten frames to generate background.
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bg = 0; V=1;
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count = 100 ;% set number of frame to be averaged
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N = 0; % start frame number
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for i = N:N+count
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bg = bg +double(rgb2gray(imread(strcat(path,'/image',num2str(V+i),'.bmp'))));
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end
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bg = uint8(bg /count); % Final Background generated.
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%imshow(uint8(circlePixels).*bg);
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%%
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tic
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r =0;b=0;
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count = 0;
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maxglcm = 0;
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Cont =0;Corr=0;Homo=0;I_mean=0;I_std=0;I_cir=0;I_area =0;stain=0;Peri=0;Diameter=0;category=0;
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ccount = 0;
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C_Percentstained =0;StainMaxlength=0;StainMinlength=0;StainSolid=0; StainNumobj=0;Stainlength=0;
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Features_table = [];F=[];
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CellFeature_table = [];cell=[];
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% Feature_table = table('VariableNames',{'Area', 'ConvexArea', 'Eccentricity', 'EquivDiameter', 'EulerNumber', 'Extent', 'FilledArea', 'MajorAxisLength', 'MinorAxisLength', 'Orientation', 'Perimeter', 'Solidity'});
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for V =1:200
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disp(V);
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Shape_Features =[]; Texture_Features1 = [];
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% The if condition is used to refresh the background for every 2000 frames
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% This helps eliminate any debris/ struck cells in the ROI
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if mod(V,2000) == 0
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%if V <19999-30
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% bg1 = bg;
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bg =0;
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count = 100 ;% set number of frame to be averaged
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N = 1; % start frame number
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for i = N:N+count
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bg = bg +double(rgb2gray(imread(strcat(path,'/image',num2str(V+i),'.bmp'))));
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end
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bg = uint8(bg /count); % Final Background generated.
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% bg = (bg+bg1)/2.0
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end
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%imshow(bg)
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% The following section performs the segmentation based on histogram values
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CurrFrame = (rgb2gray((imread(strcat(path,'/image',num2str(V),'.bmp')))));
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Sub = double(CurrFrame.*uint8(circlePixels))-double(bg.*uint8(circlePixels));
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Submin = min(Sub(:));
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Submax = max(Sub(:));
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AdjBGSub = uint8( (Sub - Submin)/(Submax-Submin) * 255);
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%imshow(AdjBGSub);
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Ia = AdjBGSub;
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%imshow(Ia);
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[A, B]=size(Ia);
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%disp(B)
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I = medfilt2(Ia); % To smoothen the image
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%imshow(I);
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I = adapthisteq(I); % to improve contrast of the image
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%imshow(I);
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%I1 = medfilt2(I);
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%imshow(I1);
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%Irgb = cat(3, I1, I1, I1);
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%imshow(Irgb)
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se = strel('disk',5);
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Ie = imerode(AdjBGSub,se);
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Iobr = imreconstruct(Ie,AdjBGSub);
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Iobrd = imdilate(Iobr,se);
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Iobrcbr = imreconstruct(imcomplement(Iobrd),imcomplement(Iobr));
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Iobrcbr = imcomplement(Iobrcbr);
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%imshow(Iobrcbr)
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%imwrite(Iobrcbr,strcat('C:\Users\DOIAP\Desktop\OFM\images\set8-80\image\image',num2str(V),'.jpg'));
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%meanIntensityValue(V) = mean2(Iobrcbr); % Finds the mean of the intensities of the image pixels
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%stdIntensityValue = std2(Iobrcbr); % Finds the standard deviation of the intensities of the image pixels
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% Selection of max and minimum of intensities for the thresholding
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%This multipication factor can be varied when you are optimizing the
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%thresholding
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%Imax = meanIntensityValue(V)+stdIntensityValue*4; % mean+ 4*standard deviation
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%Imin = meanIntensityValue(V)-stdIntensityValue*4; % mean- 4*standard deviation
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% Further processing of the thresholded image
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%Mask = createMask(Irgb,Imax,Imin);%figure;
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%imshow(Mask);
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MaskInv = imbinarize(Iobrcbr);
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%imshow(MaskInv);
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Maskopen =bwareaopen(MaskInv,5);%figure;imshow(Maskfinal);
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%imshow(Maskopen);
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% Maskdil = imdilate(Maskopen, [se90 se0]);%figure;imshow(Maskdil);
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%Maskdil = imclose(Maskopen, strel('disk',5));
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%imshow(Maskopen);
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Maskfill = imfill(~Maskopen, 'holes');%figure;imshow(Maskfill);
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%imshow(Maskfill);
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Maskclose = Maskfill;
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%imshow(Maskclose);
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% Maskclose = imclose(Maskfill, strel('disk',5));
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Maskclear = imclearborder(Maskclose, 4);%figure;
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%imshow(Maskclear);
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Maskfinal = Maskclear;
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D = bwdist(~Maskfinal);
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D=-D;
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mask = imextendedmin(D,2);
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D2 = imimposemin(D,mask);
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L = watershed(D2);
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L(Maskfinal==0)=0;
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%imshow(L);
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new_final=(L);
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new_final=logical(new_final);
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%imshow(new_final)
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%imwrite(new_final,strcat(path '/image/image',num2str(V),'.jpg')));
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% Filter image based on image properties.
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%new_final = bwpropfilt(new_final, 'Area', [20 + eps(20), Inf]); % Area greater than 20 pixels
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%new_final = bwpropfilt(new_final, 'Solidity', [0.6 + eps(0.6), Inf]); % 1 is completely solid region
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%new_final = bwpropfilt(new_final, 'EulerNumber', [4.94065646e-324 + eps(4.94065646e-324), Inf]);
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%Extract properties of all the cells in the thresholded image
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%imwrite(new_final,strcat('C:\Users\DOIAP\Desktop\OFM\images\set8-80\image1\image',num2str(V),'.jpg'));
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Maskproperties = regionprops(new_final, {'Area', 'ConvexArea', 'Eccentricity', 'EquivDiameter', 'EulerNumber', 'Extent', 'FilledArea', 'MajorAxisLength', 'MinorAxisLength', 'Orientation', 'Perimeter', 'Solidity',});
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% Creates a feature table of all the above listed properties for all the
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% segmented cells/regions in the image
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Shape_Features = struct2table(Maskproperties);
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%Plotting of 200 images to see the performance of segmetation operations
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%if V<200
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%h= figure;
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%subplot(2,3,1);
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%subimage(Mask);
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%title('Mask');
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%subplot(2,3,2);
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%subimage(Maskfill);
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%title('Maskfill');
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%subplot(2,3,3);
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%subimage(Maskdil);
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%title('Maskdil');
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%subplot(2,3,4);
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%subimage(uint8(MaskInv).*I1);
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%title('Maskclose');
|
||||
% subplot(1,2,1);
|
||||
%subplot(2,3,5);
|
||||
%subimage(I1);
|
||||
%title('I1');
|
||||
% subplot(1,2,2);
|
||||
%subplot(2,3,6);
|
||||
%subimage(uint8(Maskfinal).*I1);
|
||||
%title(' Maskfinal');
|
||||
%saveas(h,strcat('C:\Users\DOIAP\Desktop\OFM\images\set8-80\gate4\FrameNumber','-',num2str(V)),'jpg');
|
||||
%close(h);
|
||||
% figure;imshow(uint8(Maskfinal).*I);
|
||||
% figure;imshow(I);
|
||||
%end
|
||||
% Generation of the traning images for the classification program
|
||||
CComp = bwconncomp(new_final);
|
||||
Areas = regionprops(CComp,'Area');
|
||||
Centroids1=regionprops(CComp,'Centroid');
|
||||
Perimeters=regionprops(CComp,'Perimeter');
|
||||
Texture_Features=[];
|
||||
for i = 1:CComp.NumObjects
|
||||
Cent = Centroids1(i).Centroid;
|
||||
HighX = round(Cent(1))+20;
|
||||
if HighX>B
|
||||
HighX =B;
|
||||
end
|
||||
HighY = round(Cent(2))+20;
|
||||
if HighY>A
|
||||
HighY =A;
|
||||
end
|
||||
LowX = round(Cent(1))-19;
|
||||
if LowX<=0
|
||||
LowX =1;
|
||||
end
|
||||
|
||||
LowY = round(Cent(2))-19;
|
||||
if LowY<=0
|
||||
LowY =1;
|
||||
end
|
||||
|
||||
ccount = ccount +1;%,num2str(V),'.avi'
|
||||
Icrop1=Ia(LowY:HighY,LowX:HighX);
|
||||
|
||||
%Icrop1=I(LowY:HighY,LowX:HighX);
|
||||
%imshow(Icrop1)
|
||||
Maskcrop=new_final(LowY:HighY,LowX:HighX);
|
||||
imwrite(Icrop1,strcat(path,'/gate3/image',num2str(ccount),'.bmp'));
|
||||
% Additional texture features for the feature table
|
||||
glcm = graycomatrix(Icrop1);%gray level covariance matrix
|
||||
maxglcm(ccount)=max(max(glcm)); %Feature 1
|
||||
stats(ccount) = graycoprops(glcm,{'Contrast','Correlation','homogeneity'});
|
||||
Texture_Features = struct2table(stats(ccount));
|
||||
% Cont(ccount)= stats(ccount).Contrast; %Feature 2
|
||||
% Corr(ccount) = stats(ccount).Correlation; %Feature 3
|
||||
% Homo(ccount)= stats(ccount).Homogeneity;%Feature 4
|
||||
% Ent(ccount)= stats(ccount).Entropy;
|
||||
I_mean(ccount) = mean2(Icrop1); %Feature 5
|
||||
I_std(ccount)=std2(Icrop1); %Feature 6
|
||||
I_cir(ccount) = ((Shape_Features.Perimeter(i))^ 2)/ (4 * pi * Shape_Features.Area(i)); %Feature 7
|
||||
Peri(ccount) = Shape_Features.Perimeter(i)*(5.6/25.7);
|
||||
Diameter(ccount) = Peri(ccount)/3.14;
|
||||
%category(ccount) =0;
|
||||
|
||||
% Percentage of stained area
|
||||
BWthresh = imbinarize(Icrop1,0.15);
|
||||
|
||||
BWthreshtemp =~(BWthresh).*Maskcrop;
|
||||
|
||||
CC1 =bwconncomp(imcomplement(BWthresh).*Maskcrop);
|
||||
MaxLength = regionprops(CC1,'MajorAxisLength');
|
||||
MinLength = regionprops(CC1,'MinorAxisLength');
|
||||
Solid = regionprops(CC1,'Solidity');
|
||||
% imwrite(~BWthresh,strcat('E:\Experiments\odroid\A2\A2a\gate2\FrameNumber','-',num2str(V),'_',num2str(ccount),'.jpg'));
|
||||
Areas_stained = regionprops(CC1,'Area');
|
||||
StainNumobj(ccount) = CC1.NumObjects;
|
||||
if CC1.NumObjects ==0
|
||||
C_Percentstained(ccount) = 0;
|
||||
StainMaxlength(ccount) = 0;StainMinlength(ccount) = 0;
|
||||
StainSolid(ccount) = 0; StainSolid(ccount) = 0; Stainlength(ccount)=0;
|
||||
else
|
||||
if (max(struct2array(MaxLength))/max(struct2array(MinLength)))<2
|
||||
F = [F; max(struct2array(MaxLength))/max(struct2array(MinLength))];
|
||||
% imwrite(Icrop,strcat('E:\Experiments\odroid\A2\A2a\P\FrameNumber','-',num2str(V),'_',num2str(ccount),'.jpg'));
|
||||
end
|
||||
C_Percentstained(ccount) = sum(struct2array(Areas_stained))/max((Shape_Features.Area(i)))*100;
|
||||
StainMaxlength(ccount) = max(struct2array(MaxLength));
|
||||
StainMinlength(ccount) = max(struct2array(MinLength));
|
||||
Stainlength(ccount) = StainMinlength(ccount)*(5.6/25.7);
|
||||
StainSolid(ccount) = max(struct2array(Solid));
|
||||
end
|
||||
% Stainproperties = regionprops(BWthreshtemp, {'Area', 'ConvexArea', 'Eccentricity', 'EquivDiameter', 'EulerNumber', 'Extent', 'FilledArea', 'MajorAxisLength', 'MinorAxisLength', 'Orientation', 'Perimeter', 'Solidity'});
|
||||
% Parasite_Features = struct2table(Stainproperties);
|
||||
%if (((3.5<=Diameter(ccount)) && (12>=Diameter(ccount))) &&(Stainlength(ccount)==0))
|
||||
% category(ccount) =0;
|
||||
%elseif (((1<=Diameter(ccount)) && (3.5>=Diameter(ccount))) &&(Stainlength(ccount)==0))
|
||||
% category(ccount) =2;
|
||||
%elseif (((5.5<=Diameter(ccount)) && (25>=Diameter(ccount))) && (Stainlength(ccount)>0))
|
||||
% category(ccount) =1;
|
||||
%else
|
||||
% category(ccount) =3;
|
||||
%end
|
||||
|
||||
|
||||
Texture_Features1 = [Texture_Features; Texture_Features1];
|
||||
end
|
||||
if CComp.NumObjects>0
|
||||
Features = [Shape_Features Texture_Features1]; %Variable Addition
|
||||
|
||||
Features_table = [Features_table; Features]; % Table update
|
||||
end
|
||||
cell = table(I_mean', I_std', I_cir', maxglcm', C_Percentstained',StainMaxlength',StainMinlength',StainSolid', StainNumobj',Stainlength', Peri', Diameter');
|
||||
cell.Properties.VariableNames = {'Mean' 'Std' 'Circularity' 'MaxGLCM' 'Percentage_Stain' 'StainMaxlength' 'StainMinlength' 'StainSolid' 'StainNumobj' 'Stainlength' 'Peri' 'Diameter'};
|
||||
CellFeature_table = [Features_table cell]; % Table update
|
||||
save('test_table.mat','CellFeature_table')
|
||||
end
|
||||
toc
|
||||
%classificationcode
|
||||
load('trainedModel.mat');
|
||||
%mkdir('I:\ofm\im\im\gate3\cells\rbc');
|
||||
%mkdir('I:\ofm\im\im\gate3\cells\wbc');
|
||||
%mkdir('I:\ofm\im\im\gate3\cells\platelets');
|
||||
%%
|
||||
%Classifier Function obtained after training the classifier with the
|
||||
%generated training data set and the feature table
|
||||
% There are 4 different catergories of classification
|
||||
yfit = trainedModel.predictFcn(CellFeature_table);
|
||||
rbc=0;wbc=0;platelets=0;cant_classify=0;
|
||||
|
||||
for i = 1:length(yfit)
|
||||
image = imread(strcat(path,'/gate3/image',num2str(i),'.bmp'));
|
||||
if(yfit(i)== 0)
|
||||
rbc=rbc+1;
|
||||
%imwrite(image,strcat('I:\ofm\im\im\gate3\cells\rbc\image',num2str(i),'.jpg'),'jpeg');
|
||||
elseif (yfit(i)== 1)
|
||||
wbc=wbc+1;
|
||||
%imwrite(image,strcat('I:\ofm\im\im\gate3\cells\wbc\image',num2str(i),'.jpg'),'jpeg');
|
||||
elseif (yfit(i)== 2)
|
||||
%imwrite(image,strcat('I:\ofm\im\im\gate3\cells\platelets\image',num2str(i),'.jpg'),'jpeg');
|
||||
platelets=platelets+1;
|
||||
else
|
||||
cant_classify=cant_classify+1;
|
||||
end
|
||||
|
||||
end
|
||||
rows=height(CellFeature_table);
|
||||
total_cells = sprintf('total count %d',rows);
|
||||
disp(total_cells);
|
||||
RBC = sprintf('rbc count %d',rbc);
|
||||
disp(RBC);
|
||||
WBC = sprintf('wbc count %d',wbc);
|
||||
disp(WBC);
|
||||
PLATELETS = sprintf('platelets count %d',platelets);
|
||||
disp(PLATELETS);
|
||||
C= sprintf('cells that cant be classified %d',cant_classify);
|
||||
disp(C);
|
||||
184
src/ofm_code_cbc_v1/simple.ui
Normal file
184
src/ofm_code_cbc_v1/simple.ui
Normal file
@@ -0,0 +1,184 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<ui version="4.0">
|
||||
<class>MainWindow</class>
|
||||
<widget class="QMainWindow" name="MainWindow">
|
||||
<property name="geometry">
|
||||
<rect>
|
||||
<x>0</x>
|
||||
<y>0</y>
|
||||
<width>700</width>
|
||||
<height>500</height>
|
||||
</rect>
|
||||
</property>
|
||||
<property name="windowTitle">
|
||||
<string>MainWindow</string>
|
||||
</property>
|
||||
<property name="styleSheet">
|
||||
<string notr="true"/>
|
||||
</property>
|
||||
<widget class="QWidget" name="centralwidget">
|
||||
<widget class="QGroupBox" name="groupBox">
|
||||
<property name="geometry">
|
||||
<rect>
|
||||
<x>30</x>
|
||||
<y>80</y>
|
||||
<width>670</width>
|
||||
<height>500</height>
|
||||
</rect>
|
||||
</property>
|
||||
<property name="styleSheet">
|
||||
<string notr="true">background-color: rgb(90, 90, 90);</string>
|
||||
</property>
|
||||
<property name="sizePolicy">
|
||||
<sizepolicy hsizetype="Preferred" vsizetype="Preferred">
|
||||
<horstretch>0</horstretch>
|
||||
<verstretch>0</verstretch>
|
||||
</sizepolicy>
|
||||
</property>
|
||||
<property name="title">
|
||||
<string></string>
|
||||
</property>
|
||||
<widget class="QWidget" name="ImgWidget" native="true">
|
||||
<property name="geometry">
|
||||
<rect>
|
||||
<x>0</x>
|
||||
<y>0</y>
|
||||
<width>700</width>
|
||||
<height>500</height>
|
||||
</rect>
|
||||
</property>
|
||||
</widget>
|
||||
</widget>
|
||||
<widget class="QPushButton" name="startButton">
|
||||
<property name="geometry">
|
||||
<rect>
|
||||
<x>60</x>
|
||||
<y>10</y>
|
||||
<width>100</width>
|
||||
<height>61</height>
|
||||
</rect>
|
||||
</property>
|
||||
<property name="text">
|
||||
<string>Start Camera</string>
|
||||
</property>
|
||||
</widget>
|
||||
<widget class="QPushButton" name="startButton4">
|
||||
<property name="geometry">
|
||||
<rect>
|
||||
<x>180</x>
|
||||
<y>10</y>
|
||||
<width>100</width>
|
||||
<height>61</height>
|
||||
</rect>
|
||||
</property>
|
||||
<property name="text">
|
||||
<string>Auto Focus</string>
|
||||
</property>
|
||||
</widget>
|
||||
<widget class="QPushButton" name="startButton1">
|
||||
<property name="geometry">
|
||||
<rect>
|
||||
<x>340</x>
|
||||
<y>600</y>
|
||||
<width>50</width>
|
||||
<height>50</height>
|
||||
</rect>
|
||||
</property>
|
||||
<property name="text">
|
||||
<string> X +</string>
|
||||
</property>
|
||||
</widget>
|
||||
<widget class="QPushButton" name="startButton2">
|
||||
<property name="geometry">
|
||||
<rect>
|
||||
<x>410</x>
|
||||
<y>600</y>
|
||||
<width>50</width>
|
||||
<height>50</height>
|
||||
</rect>
|
||||
</property>
|
||||
<property name="text">
|
||||
<string> X -</string>
|
||||
</property>
|
||||
</widget>
|
||||
<widget class="QPushButton" name="startButton3">
|
||||
<property name="geometry">
|
||||
<rect>
|
||||
<x>300</x>
|
||||
<y>10</y>
|
||||
<width>100</width>
|
||||
<height>61</height>
|
||||
</rect>
|
||||
</property>
|
||||
<property name="text">
|
||||
<string>Frame Capture</string>
|
||||
</property>
|
||||
</widget>
|
||||
<widget class="QPushButton" name="startButton5">
|
||||
<property name="geometry">
|
||||
<rect>
|
||||
<x>420</x>
|
||||
<y>10</y>
|
||||
<width>100</width>
|
||||
<height>61</height>
|
||||
</rect>
|
||||
</property>
|
||||
<property name="text">
|
||||
<string>Home</string>
|
||||
</property>
|
||||
</widget>
|
||||
<widget class="QPushButton" name="startButton6">
|
||||
<property name="geometry">
|
||||
<rect>
|
||||
<x>540</x>
|
||||
<y>10</y>
|
||||
<width>100</width>
|
||||
<height>61</height>
|
||||
</rect>
|
||||
</property>
|
||||
<property name="text">
|
||||
<string>Start</string>
|
||||
</property>
|
||||
</widget>
|
||||
<widget class="QPushButton" name="startButton7">
|
||||
<property name="geometry">
|
||||
<rect>
|
||||
<x>270</x>
|
||||
<y>600</y>
|
||||
<width>50</width>
|
||||
<height>50</height>
|
||||
</rect>
|
||||
</property>
|
||||
<property name="text">
|
||||
<string> X++</string>
|
||||
</property>
|
||||
</widget>
|
||||
<widget class="QPushButton" name="startButton8">
|
||||
<property name="geometry">
|
||||
<rect>
|
||||
<x>200</x>
|
||||
<y>600</y>
|
||||
<width>50</width>
|
||||
<height>50</height>
|
||||
</rect>
|
||||
</property>
|
||||
<property name="text">
|
||||
<string> X--</string>
|
||||
</property>
|
||||
</widget>
|
||||
</widget>
|
||||
<widget class="QMenuBar" name="menubar">
|
||||
<property name="geometry">
|
||||
<rect>
|
||||
<x>0</x>
|
||||
<y>0</y>
|
||||
<width>639</width>
|
||||
<height>21</height>
|
||||
</rect>
|
||||
</property>
|
||||
</widget>
|
||||
<widget class="QStatusBar" name="statusbar"/>
|
||||
</widget>
|
||||
<resources/>
|
||||
<connections/>
|
||||
</ui>
|
||||
BIN
src/ofm_code_cbc_v1/test_table.mat
Normal file
BIN
src/ofm_code_cbc_v1/test_table.mat
Normal file
Binary file not shown.
BIN
src/ofm_code_cbc_v1/trainedModel.mat
Normal file
BIN
src/ofm_code_cbc_v1/trainedModel.mat
Normal file
Binary file not shown.
@@ -0,0 +1,125 @@
|
||||
#define Zdir 12
|
||||
#define motorPulse 13
|
||||
#define M0 9
|
||||
#define M1 10
|
||||
#define M2 11
|
||||
|
||||
long ZcurrStep=0L;
|
||||
long Ax=0L,Ay=0L,Az=0L,Bx=0L,By=0L,Bz=0L,Cx=0L,Cy=0L,Cz=0L;
|
||||
long nextZstep = 0;
|
||||
int needtocheckXmovement=0,needtocheckYmovement=0,needtocheckZmovement=0;
|
||||
long limitTOZfocus = 20000L;
|
||||
|
||||
void setup() {
|
||||
// setup serial baud rate
|
||||
Serial.begin(57600);
|
||||
pinMode(5,OUTPUT);
|
||||
pinMode(6,INPUT);
|
||||
digitalWrite(5,HIGH);
|
||||
pinMode(M0,OUTPUT);
|
||||
pinMode(M1,OUTPUT);
|
||||
pinMode(M2,OUTPUT);
|
||||
|
||||
// motor dir and pulse pin set as outputs
|
||||
pinMode(Zdir,OUTPUT); pinMode( motorPulse ,OUTPUT);
|
||||
digitalWrite(M0, HIGH);
|
||||
digitalWrite(M1, HIGH);
|
||||
digitalWrite(M2, HIGH);
|
||||
}
|
||||
|
||||
void loop() {
|
||||
|
||||
int choice = Serial.read();
|
||||
|
||||
switch(choice){
|
||||
|
||||
case('T') : digitalWrite(Zdir,LOW); delayMicroseconds(10); doZSteps(1); ZcurrStep=ZcurrStep-1; // T == Z up by 5 counts
|
||||
break;
|
||||
|
||||
case('G') : digitalWrite(Zdir,HIGH); delayMicroseconds(10); doZSteps(1); ZcurrStep=ZcurrStep+1; // G == Z down
|
||||
break;
|
||||
|
||||
case('A') : digitalWrite(Zdir,LOW); delayMicroseconds(10); doZSteps(20);
|
||||
break;
|
||||
|
||||
case('D') : digitalWrite(Zdir, HIGH ); delayMicroseconds(10); doZSteps(20);
|
||||
break;
|
||||
|
||||
case('M') : gotoZSetStep(getStep());
|
||||
break;
|
||||
|
||||
case('Q') : gohome();
|
||||
break;
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
void doZSteps(long num) {
|
||||
while (num > 0 ) {
|
||||
digitalWrite( motorPulse ,LOW); delayMicroseconds(15);
|
||||
digitalWrite( motorPulse ,HIGH); delayMicroseconds(15);
|
||||
num--;
|
||||
}
|
||||
}
|
||||
|
||||
long getStep()
|
||||
{
|
||||
long index = 0, inpStep[7]={0,0,0,0,0,0,0}, invalidInput = 0;
|
||||
long setStep = 0L;
|
||||
|
||||
|
||||
for(index=0; index<7; index++ )
|
||||
{
|
||||
while ( Serial.available() < 1 );
|
||||
inpStep[index] = Serial.read() - 48;
|
||||
Serial.println(inpStep[index]);
|
||||
}
|
||||
|
||||
// DISCARD first byte : MATLAB sends the terminator character there. We need it since if we turn it off, MATALB won't read the Tx from this arduino
|
||||
// ALSO igmore the second byte : that's the sign symbol
|
||||
setStep = (inpStep[1]*100000) + (inpStep[2]*10000) + (inpStep[3]*1000) + (inpStep[4]*100) + (inpStep[5]*10) + (inpStep[6]*1) ;
|
||||
//Serial.println(inpStep[index])
|
||||
// check what sign was sent. If it was anything other than a '-' then dont worry
|
||||
if (inpStep[0] + 48 == '-' ) { setStep = setStep*(-1); }
|
||||
Serial.println(setStep);
|
||||
return setStep;
|
||||
}
|
||||
|
||||
void gotoZSetStep(long ZsetStep)
|
||||
{
|
||||
//if(ZsetStep > ZMaxStep) {ZsetStep = ZMaxStep;}
|
||||
long stepstodo = abs(ZsetStep - ZcurrStep)/5 ;
|
||||
Serial.println(ZcurrStep);
|
||||
Serial.println(stepstodo);
|
||||
|
||||
if (ZsetStep > ZcurrStep)
|
||||
{ needtocheckZmovement=0 ;
|
||||
Serial.println(ZcurrStep);
|
||||
Serial.println("hi");
|
||||
digitalWrite(Zdir,HIGH); delayMicroseconds(10); ZcurrStep=ZsetStep; doZSteps( stepstodo ); }
|
||||
|
||||
if (ZsetStep < ZcurrStep)
|
||||
{
|
||||
needtocheckZmovement=1 ;
|
||||
Serial.println(ZcurrStep);
|
||||
Serial.println("hello");
|
||||
digitalWrite(Zdir,LOW); delayMicroseconds(10); ZcurrStep=ZsetStep; doZSteps( stepstodo );
|
||||
Serial.println(ZcurrStep);
|
||||
}
|
||||
}
|
||||
|
||||
void gohome()
|
||||
{
|
||||
int v=digitalRead(6);
|
||||
//Serial.println(v);
|
||||
while(v<1)
|
||||
{ gotoZSetStep(6400);
|
||||
ZcurrStep=0L;
|
||||
v=digitalRead(6);
|
||||
Serial.println(v);
|
||||
|
||||
//gotoZSetStep(limitTOZfocus);
|
||||
}
|
||||
//doZSteps( 100000 );
|
||||
ZcurrStep=0L;
|
||||
}
|
||||
Reference in New Issue
Block a user