def openNew(self):
'''
Select and open a video file from the system file manager for analysis.
'''
self.filename = QtWidgets.QFileDialog.getOpenFileName(self, 'Open Video', self.vid_dir)
self.filename = str(self.filename[0])
# We get a zero division error on self.length if the filename is empty.
try:
# Don't even try if user pressed 'Cancel' in file dialog
if not self.filename == '':
print(self.filename+'\n')
self.vid_dir = path.dirname(path.realpath(self.filename))
self.writeConfig()
self.capture = cv2.VideoCapture(self.filename)
self.capture.open(self.filename)
self.length = int(self.capture.get(7) / self.capture.get(5))
self.endTimemsec = self.length * 1000
self.slide.setMinimum(0)
self.slide.setMaximum(self.length)
self.slide.setTracking(0)
self.ui.lcdNumber.setNumDigits(8)
self.ui.lcdNumber.display('00:00:00')
self.slide.setSliderPosition(0)
self.cont = 0
self.captureNextFrame()
except ZeroDivisionError as excpt:
print('type is: ', excpt.__class__.__name__)
print_exc()
errorNotif(self, '<br>Not a recognized video format.</br>')
self.filename = 0
def fileCheck(self):
"""Make sure user-selected file is actually a video."""
msg_video = '<br>Not a recognized video format.</br>'
# Test if the file was encoded in a recognizable video codec type. If
# not, it's not a (useable) video.
codec = self.capture.get(6)
if codec == 0.0:
errorNotif(self, msg_video)
return 'error'
def timeCheck(self, tsec):
"""
Check the following:
- Start time input is only integers (no letters or special characters)
- Start time is in correct format (hh:mm:ss)
- Second and minute input don't go above 59
"""
tsec = str(tsec)
time_check = tsec.split(':')
msg_time = '<br>Time must be in hh:mm:ss format</br>.'
# Only integers
for num in time_check:
if num.isdigit() is False:
print('false')
errorNotif(self, msg_time)
return 'error'
# Correct format
if len(tsec) != 8:
errorNotif(self, msg_time)
return 'error'
elif tsec[2] != ':' or tsec[5] != ':':
errorNotif(self, msg_time)
return 'error'
# Second and minute are not too high
elif int(time_check[-1]) > 59 or int(time_check[-2]) > 59:
errorNotif(self, msg_time)
return 'error'
def captureNextFrame(self):
'''capture frame and reverse RGB BGR and return opencv image'''
# Some file types, like .ico files, make it through the try-except in
# self.openNew since OpenCV can read them. This should catch them.
try:
if self.cont == 0:
ret, readFrame = self.capture.read()
self.currentFrame = cv2.cvtColor(readFrame, cv2.COLOR_BGR2RGB)
height,width = self.currentFrame.shape[:2]
self.img = QtGui.QImage(self.currentFrame,
width,
height,
QtGui.QImage.Format_RGB888)
self.img = QtGui.QPixmap(self.img)
self.ui.videoFrame.setPixmap(self.img.scaled(self.ui.videoFrame.size(), QtCore.Qt.KeepAspectRatio, QtCore.Qt.SmoothTransformation))
if self.capture.get(0) > self.endTimemsec:
self.capture.set(0, self.startTimemsec)
self._timer.timeout.connect(self.tick)
self._timer.start()
elif self.cont == 1:
ret, readFrame = self.capture.read()
self.currentFrame = cv2.cvtColor(readFrame,cv2.COLOR_BGR2RGB)
height,width = self.currentFrame.shape[:2]
self.img = QtGui.QImage(self.currentFrame,
width,
height,
QtGui.QImage.Format_RGB888)
self.img = QtGui.QPixmap(self.img)
self.ui.videoFrame.setPixmap(self.img.scaled(self.ui.videoFrame.size(),
QtCore.Qt.KeepAspectRatio, QtCore.Qt.SmoothTransformation))
if self.capture.get(0) >= self.endTimemsec:
self.capture.set(0, self.startTimemsec)
self._timer.timeout.connect(self.tick)
self._timer.start()
elif self.cont == 2:
self._timer.stop()
except cv2.error as excpt:
print('type is: ', excpt.__class__.__name__)
print_exc()
self.capture.release()
self._timer.stop()
errorNotif(self, '<br>Not a recognized video format.</br>')
return
def measLen(self):
"""Make sure the measurement length makes sense."""
if str(self.lenOfMeas).isdigit() is False:
msg_len = '<br>The given length of measurement cannot be understood.</br>'
errorNotif(self, msg_len)
return 'error'
def nameCheck(self):
"""Check that the video has been assigned."""
if self.filename == 0 or self.filename == u'':
msg_video = '<br>You have not selected a video!</br>'
errorNotif(self, msg_video)
return 'error'
def contourPressed(self):
"""Contour button has been pressed - begin analysis."""
self.cont = 1
# Get the number of mice, start time, and length of measurement.
mice = self.ui.lineEdit_mouseID.text()
tsec = self.ui.lineEdit_startT.text()
self.lenOfMeas = self.ui.lineEdit_lenMeasure.text()
# Do a quick scan for errors and halt execution if necessary:
# Was a video loaded before 'Contour' was pressed?
if self.test.nameCheck(self) == 'error':
return
elif self.test.fileCheck(self) == 'error':
return
# Has the time been typed incorrectly?
elif self.test.timeCheck(self, tsec) == 'error':
return
# Is the given length of measurement an integer?
elif self.test.measLen(self) == 'error':
return
# Number of mice we are using.
self.numberOfMice = len(mice.split(','))
startTimehhmmss = [int(x) for x in tsec.split(':')]
# Time (in seconds) that we begin the measurement
startTimeSec = (3600 * startTimehhmmss[0]) + (
60 * startTimehhmmss[1]) + startTimehhmmss[2]
self.startTimemsec = startTimeSec * 1000 # start-time in miliseconds
lenOfMeasmsec = int(self.lenOfMeas) * 1000
self.endTimemsec = self.startTimemsec + lenOfMeasmsec # ending time
endTime = self.endTimemsec
self.capture.set(0, self.endTimemsec)
self.lastframe = self.capture.get(1)
self.capture.set(0, self.startTimemsec)
self.firstframe = self.capture.get(1)
self.length = int(self.lenOfMeas)
# Reset slide to show length of analysis time.
self.slide.setMinimum(startTimeSec)
self.slide.setMaximum(self.length + startTimeSec)
self.slide.setSliderPosition(startTimeSec)
self._timer.start()
incontours = []
mouseNumList = []
respRates = []
bRespRates = []
minstdevs = []
try:
# Get a unique mouse ID for each mouse.
for numba in range(0, self.numberOfMice):
vid = mv.frameReader(self.filename)
img = vid.getFrame(self.firstframe)
conty = mv.contour(img)
mouseNum, ok = QtWidgets.QInputDialog.getText(
self, 'Mouse ID', 'Please enter the Mouse #')
if ok and mouseNum:
print('Mouse ID: ', mouseNum)
mouseNumList.append(mouseNum)
inconty = mv.insideContour(conty, img)
incontours.append(inconty)
else:
# If the user presses Cancel, close the contour window
cv2.destroyWindow('Click the outline of your ROI:')
return
self.cont = 2
# Parameters for Shi-Tomasi corner detection
feature_params = dict(maxCorners=10,
qualityLevel=0.3,
minDistance=7,
blockSize=7)
# Parameters for Lucas-Kanade optical flow
lk_params = dict(winSize=(15, 15),
maxLevel=2,
criteria=(cv2.TERM_CRITERIA_EPS
| cv2.TERM_CRITERIA_COUNT, 10, 0.03))
# Create some random colors
color = np.random.randint(0, 255, (100, 3))
self.capture.set(1, self.firstframe)
# Take first frame and find corners in it
_, old_frame = self.capture.read()
old_gray = cv2.cvtColor(old_frame, cv2.COLOR_BGR2GRAY)
p0s = mf.ListOfLists(self.numberOfMice)
for numba in range(0, self.numberOfMice):
p0s[numba] = cv2.goodFeaturesToTrack(old_gray,
mask=incontours[numba],
**feature_params)
# Create a mask image for drawing purposes
mask = np.zeros_like(old_frame)
xPoints = mf.ListOfLists(self.numberOfMice)
yPoints = mf.ListOfLists(self.numberOfMice)
p1s = mf.ListOfLists(self.numberOfMice)
sts = mf.ListOfLists(self.numberOfMice)
errs = mf.ListOfLists(self.numberOfMice)
good_news = mf.ListOfLists(self.numberOfMice)
good_olds = mf.ListOfLists(self.numberOfMice)
dists = mf.ListOfLists(self.numberOfMice)
pointPos = mf.ListOfLists(self.numberOfMice)
peakPos = mf.ListOfLists(self.numberOfMice)
for numba in range(0, self.numberOfMice):
for i in range(len(p0s[numba])):
xPoints[numba].append([])
yPoints[numba].append([])
l = 0
for num in range(np.int(self.firstframe),
np.int(self.lastframe + 1)):
_, frame = self.capture.read()
frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
stzeros = []
for numba in range(0, self.numberOfMice):
stzeros.append(np.array([]))
for numba in range(0, self.numberOfMice):
# Calculate optical flow
p1s[numba], sts[numba], errs[
numba] = cv2.calcOpticalFlowPyrLK(
old_gray, frame_gray, p0s[numba], None,
**lk_params)
# Select good points
if np.any(sts[numba]) == 0:
break
good_news[numba] = p1s[numba][sts[numba] == 1]
good_olds[numba] = p0s[numba][sts[numba] == 1]
if len(p0s[numba]) != len(good_olds[numba]):
stzeros[numba] = np.where(sts[numba] == 0)[0]
for j in stzeros[numba][::-1]:
for i in range(len(p0s[numba])):
if i == j:
del xPoints[numba][i]
del yPoints[numba][i]
# Draw the tracks
for i, (new, old) in enumerate(
list(zip(good_news[numba], good_olds[numba]))):
a, b = new.ravel()
c, d = old.ravel()
xPoints[numba][i].append([])
yPoints[numba][i].append([])
xPoints[numba][i][l].append(c)
yPoints[numba][i][l].append(d)
mask = cv2.line(mask, (a, b), (c, d),
color[i].tolist(), 2)
frame = cv2.circle(frame, (a, b), 5, color[i].tolist(),
-1)
p0s[numba] = good_news[numba].reshape(
-1, 1, 2) # Update the previous points
if np.any(sts[numba]) == 0:
endTime = self.capture.get(0)
break
# Show the respiratory motion in a new window
img = cv2.add(frame, mask)
cv2.imshow('flow', img)
k = cv2.waitKey(30) & 0xff
if k == 27:
endTime = self.capture.get(0)
break
# Now update the previous frame
old_gray = frame_gray.copy()
l = l + 1
for numba in range(0, self.numberOfMice):
pointx = mf.ListOfLists(len(p0s[numba]))
pointy = mf.ListOfLists(len(p0s[numba]))
peaksx = mf.ListOfLists(len(p0s[numba]))
peaksy = mf.ListOfLists(len(p0s[numba]))
distBTpeaksxt = mf.ListOfLists(len(p0s[numba]))
distBTpeaksxb = mf.ListOfLists(len(p0s[numba]))
distBTpeaksyt = mf.ListOfLists(len(p0s[numba]))
distBTpeaksyb = mf.ListOfLists(len(p0s[numba]))
avgs = mf.ListOfLists(len(p0s[numba]))
stdevs = mf.ListOfLists(len(p0s[numba]))
for i in range(len(p0s[numba])):
pointx[i] = xPoints[numba][i]
peaksx[i] = pd.peakdetect(pointx[i], None, 4,
0) # 3 for mice, 20 for human
pointy[i] = yPoints[numba][i]
peaksy[i] = pd.peakdetect(pointy[i], None, 4, 0)
for ii in range(len(p0s[numba])):
for i in range(len(peaksx[ii][0]) - 1):
distBTpeaksxt[ii].append(peaksx[ii][0][i + 1][0] -
peaksx[ii][0][i][0])
for i in range(len(peaksx[ii][1]) - 1):
distBTpeaksxb[ii].append(peaksx[ii][1][i + 1][0] -
peaksx[ii][1][i][0])
for i in range(len(peaksy[ii][0]) - 1):
distBTpeaksyt[ii].append(peaksy[ii][0][i + 1][0] -
peaksy[ii][0][i][0])
for i in range(len(peaksy[ii][1]) - 1):
distBTpeaksyb[ii].append(peaksy[ii][1][i + 1][0] -
peaksy[ii][1][i][0])
for i in range(len(p0s[numba])):
avgs[i].append(
sum(distBTpeaksxt[i]) / len(distBTpeaksxt[i])) # xtop
stdevs[i].append(np.std(distBTpeaksxt[i]) /
avgs[i][0]) # xtop
avgs[i].append(
sum(distBTpeaksxb[i]) /
len(distBTpeaksxb[i])) # xbottom
stdevs[i].append(np.std(distBTpeaksxb[i]) /
avgs[i][1]) # xbottom
avgs[i].append(
sum(distBTpeaksyt[i]) / len(distBTpeaksyt[i])) # ytop
stdevs[i].append(np.std(distBTpeaksyt[i]) /
avgs[i][2]) # ytop
avgs[i].append(
sum(distBTpeaksyb[i]) /
len(distBTpeaksyb[i])) # ybottom
stdevs[i].append(np.std(distBTpeaksyb[i]) /
avgs[i][3]) # ybottom
merged = list(itertools.chain.from_iterable(stdevs))
minst = min(merged)
matches = [match for match in mf.find(stdevs, minst)]
bestPoints = list(zip(*matches))[0]
distInd = list(zip(*matches))[1]
best = mf.ListOfLists(len(p0s[numba]))
beststdev = mf.ListOfLists(len(p0s[numba]))
for ii in range(len(p0s[numba])):
minimummy = min(stdevs[ii])
mins = [
i for i, j in enumerate(stdevs[ii]) if j == minimummy
]
for i in range(len(mins)):
best[ii] = avgs[ii][mins[i]]
beststdev[ii] = stdevs[ii][mins[i]]
minstdev = min(beststdev)
indMinStdev = [
i for i, j in enumerate(beststdev) if j == minstdev
]
bavg = [best[i] for i in indMinStdev]
avgOfbest = sum(best) / len(best)
avgOfbavg = sum(bavg) / len(bavg)
font = {
'family': 'sans-serif',
'color': 'black',
'weight': 'normal',
'size': 12
}
# Plotting
print('distInd', distInd)
xaxis = range(0, len(pointx[numba]))
xaxisYtop = list(zip(*peaksy[numba][0]))[0]
xaxisYbottom = list(zip(*peaksy[numba][1]))[0]
xaxisT = [x / 30 for x in xaxis]
xaxisYtopT = [x / 30 for x in xaxisYtop]
xaxisYbottomT = [x / 30 for x in xaxisYbottom]
# Close open figures with same name to prevent bad formatting
if plt.fignum_exists('Mouse %s' % mouseNumList[numba]):
plt.close('Mouse %s' % mouseNumList[numba])
plt.ion() # cosmetic, QCoreApplication error without this
plt.figure('Mouse %s' % mouseNumList[numba]) # Window name
plt.plot(xaxisT, pointy[numba], color='#3399FF') # Curve
plt.plot(xaxisYtopT,
list(zip(*peaksy[numba][0]))[1],
'o',
color='red',
markersize=4) # Peak
plt.plot(xaxisYbottomT,
list(zip(*peaksy[numba][1]))[1],
'o',
color='#FF9966',
markersize=4) # Valley
plt.title('Mouse ' + str(mouseNumList[numba]), fontdict=font)
pointPos[numba].append(pointy[numba])
peakPos[numba].append(peaksy[numba])
plt.xlabel('Time (s)', fontdict=font)
frame1 = plt.gca()
frame1.axes.get_yaxis().set_ticks([])
plt.tight_layout() # Don't cut off the title and x-label
plt.show()
respRate = (60 * 30) / avgOfbest
bRespRate = (60 * 30) / avgOfbavg
# Output respiratory rate and stdev to console; don't show if
# running standalone
print('\nBest: ' + str([round(elem, 3) for elem in best]))
print('Best Stdev: ' +
str([round(elem, 4) for elem in beststdev]))
print('Best Respiratory Rate: ', bRespRate, '\n')
respRates.append(respRate)
bRespRates.append(bRespRate)
minstdevs.append(minstdev)
for i, (bp, ind) in enumerate(list(zip(bestPoints, distInd))):
if ind == 0:
dists[numba].append(distBTpeaksxt[bp])
if ind == 1:
dists[numba].append(distBTpeaksxb[bp])
if ind == 2:
dists[numba].append(distBTpeaksyt[bp])
if ind == 3:
dists[numba].append(distBTpeaksyb[bp])
# Show results in main window
for numba in range(0, self.numberOfMice):
toPrint1 = mouseNumList[numba]
toPrint2 = round(bRespRates[numba], 2)
toPrint3 = round(minstdevs[numba], 4)
out = ' {:<18} {:^21.2f} {:>21.4f} '.format(
toPrint1, toPrint2, toPrint3)
self.ui.textBrowser_Output.append(out)
# Measurement terminated before full run time
if endTime != self.endTimemsec:
errorNotif(
self,
'<br>Measurement did not run for entire set length.</br>')
# Ask if we want to export data to a spreadsheet
export = askQuestion(self, 'RespiRate',
'<br>Export data to spreadsheet?</br>')
if export == 'yes':
for numba in range(0, self.numberOfMice):
videoName = path.splitext(path.basename(self.filename))[0]
toPrintList = [
str(videoName),
str(mouseNumList[numba]),
str(startTimeSec),
str(endTime / 1000),
str((endTime / 1000) - (startTimeSec)),
str(round(bRespRates[numba], 2)),
str(round(minstdevs[numba], 4))
]
workBook = 'output1.xls'
sheetName = 'Sheet1'
mf.xOutput(self, toPrintList, workBook, sheetName)
# If the measurement field on the mouse is out of focus or the mouse
# moves too much and all trackers are dropped, we get various errors.
# See TODO for more info
except (TypeError, ZeroDivisionError, IndexError) as excpt:
print('type is: ', excpt.__class__.__name__)
print_exc()
msg = ('<br>The selected region on ' + str(mouseNumList[numba]) +
' is not suitable for respiration measurements.</br>')
errorNotif(self, msg)
# Close the separate video windows.
cv2.destroyAllWindows()
def xOutput(self, toPrintList, workBook, sheetName):
'''Export data to spreadsheet for easy review and analysis.'''
if workBook == 0 and sheetName == 0:
notifiCat.errorNotif('<br>Data was not saved to spreadsheet!</br>')
else:
try:
# Check if the target file already exists.
dir_path = path.join(path.expanduser('~'), 'RespiRate')
file_path = path.join(dir_path, workBook)
if path.isfile(file_path) == False:
q = (
'<p>A suitable spreadsheet was not found.'
'<br>Would you like to generate one automatically?</br></p>'
)
new = notifiCat.askQuestion(self, 'No spreadsheet.', q)
if new == 'yes':
# Test if the folder exists. It might even if the file does not.
if not path.exists(dir_path):
mkdir(dir_path)
# Set up the spreadsheet
book = xlwt.Workbook()
sheet1 = book.add_sheet('Sheet1')
sheet1.write(0, 0, 'Video #')
sheet1.write(0, 1, 'Mouse #')
sheet1.write(0, 2, 'Start Time')
sheet1.write(0, 3, 'End Time')
sheet1.write(0, 4, 'Total Time')
sheet1.write(0, 5, 'Best RR')
sheet1.write(0, 6, 'stdev')
book.save(file_path)
created_msg = (
'Spreadsheet was created as `output1.xls` in'
' the RespiRate folder.')
notifiCat.infoNotif(self, 'Success!', created_msg)
else:
return
# The file exists (or was just created) - now write output.
wb = xlrd.open_workbook(file_path) #output1.xls
sheet = wb.sheet_by_name(sheetName) #Sheet1
rb = copy(wb)
ws = rb.get_sheet(0)
row = 0
col = 0
cell = sheet.cell(row, 0)
try:
while cell.ctype != 6:
row = row + 1
cell = sheet.cell(row, 0)
except IndexError:
print('index error') #TODO: Why do we get this for every run?
for i in range(0, len(toPrintList)):
ws.write(row, col, toPrintList[i])
col = col + 1
rb.save(file_path)
except IOError:
# If we get this far, the spreadsheet cannot be opened (most likely
# it is already opened in Excel or another program). Check it, close
# it, and rerun it. Working now?
notifiCat.errorNotif(
self, 'Data cannot be exported!\n'
'<br>Please check if the spreadsheet is already opened.</br>')
def errorCheck(self, tsec):
'''Check for common mistakes and return a notification.'''
msg_video = '<br>You have not selected a video!</br>'
msg_time = '<br>Time must be in hh:mm:ss format</br>.'
msg_len = '<br>The given length of measurement cannot be understood.</br>'
tsec = str(tsec)
time_check = tsec.split(':')
len_measure = str(self.lenOFMeas)
# A video hasn't been selected. Note that this doesn't detect if the
# selected file is actually a video, but only if a file (any type) has
# been chosen.
if self.filename == 0 or self.filename == u'':
errorNotif(self, msg_video)
return 'error'
# Check if measurement length makes sense
elif len_measure.isdigit() == False:
errorNotif(self, msg_len)
return 'error'
# Check the following:
# - Start time is in correct format (hh:mm:ss)
# - Second and minute input don't go above 59
# - Start time input is only integers (no letters or special characters)
elif len(tsec) != 8:
errorNotif(self, msg_time)
return 'error'
elif tsec[2] != ':' or tsec[5] != ':':
errorNotif(self, msg_time)
return 'error'
elif 1 == 1: # Bit of a ugly hack
for num in time_check:
if num.isdigit() == False:
errorNotif(self, msg_time)
return 'error'
elif int(time_check[-1]) > 59 or int(time_check[-2]) > 59:
errorNotif(self, msg_time)
return 'error'
