def select_roi(self, roi=None):
if roi is None:
roi = tracking.select_roi(self.frame)
self.roi = roi
# ROI for saving must be at least 65x65 otherwise buffer might be to small
roisave = self.roi.copy()
nx, ny = roisave['x2'] - roisave['x1'], roisave['y2'] - roisave['y1']
if nx < 64:
roisave['x1'] -= floor((64 - nx) / 2)
nx = 64
roisave['x2'] = roisave['x1'] + nx
if ny < 64:
roisave['y1'] -= floor((64 - ny) / 2)
ny = 64
roisave['y2'] = roisave['y1'] + ny
self.roisave = roisave
self.nxsave, self.nysave = nx, ny
self.roi_selected = True
# Re-init tracker if necessary
if self.dotrack:
self.eye = tracking.resize_roi(self.frame, self.roi)
self.tracker = tracking.Tracker(self.eye)
def select_roi(self, roi=None):
if roi is None:
roi = tracking.select_roi(self.frame)
self.roi = roi
# ROI for saving must be at least 65x65 otherwise buffer might be to small
roisave = self.roi.copy()
nx, ny = roisave['x2'] - roisave['x1'], roisave['y2'] - roisave['y1']
if nx < 64:
roisave['x1'] -= floor((64 - nx) / 2)
nx = 64
roisave['x2'] = roisave['x1'] + nx
if ny < 64:
roisave['y1'] -= floor((64 - ny) / 2)
ny = 64
roisave['y2'] = roisave['y1'] + ny
self.roisave = roisave
self.nxsave, self.nysave = nx, ny
self.roi_selected = True
# Re-init tracker if necessary
if self.dotrack:
self.eye = tracking.resize_roi(self.frame, self.roi)
self.tracker = tracking.Tracker(self.eye)
def process_one_frame(self):
# grab frame (locked to clock if maxfreq is defined)
t = clock()
if self.maxfreq:
tick = t*self.maxfreq
ticklast = floor(self.tlast*self.maxfreq+0.0001) # add a small quantity to avoid numerical error resulting in a value 1 less than it should
if tick-ticklast<1:
# we did not miss a tick, wait for next tick
ticknext = ceil(tick)
sleep((ticknext-tick)/self.maxfreq)
t = ticknext/self.maxfreq
self.maxgap = max(self.maxgap,t-self.tlast)
self.tlast = t
ret, self.frame = self.film.read()
# no frame -> indicate that there is some "idle" time
if not ret:
if self.DOREC:
if not self.idle:
self.idle = True
print 'some idle time'
sleep(.001)
return
else:
self.film.release()
self.film = cv2.VideoCapture("mouseeyetracking.avi")
ret, self.frame = self.film.read()
else:
self.idle = False
# follow speed of processing frames
t = clock()
self.nprocessed += 1
if t > self.t0 + 1:
fps = self.nprocessed / (t - self.t0)
self.grabdesc = " (%.1ffps, max %.0fms gap)" % (fps,self.maxgap*1000)
self.t0 = t
self.nprocessed = 0
self.maxgap = 0
# make frame single channel
if self.frame.ndim == 3:
self.frame = cv2.cvtColor(self.frame, cv2.COLOR_BGR2GRAY)
# display frame
cv2.imshow('movie', self.frame)
# change between acquisition states
# note that acquisition will never start as long as ROI and filename are not selected
if self.running and self.acqstate == 'off':
self.acqstate = 'wait'
self.curacq += 1
self.status = 'waiting for trigger ' + str(self.curacq) + '/' + str(self.numacq)
# open audio stream to detect trigger
self.audio.load()
# open movie for writing
fourcc = cv2.VideoWriter_fourcc(*'i420')
self.curname = self.filename + '_%.3i' % self.curacq
self.out = cv2.VideoWriter(self.curname + '.avi', fourcc, 60.0, (self.nxsave, self.nysave))
# prepare for saving time vector and tracking results
self.timevector = []
if self.acqstate == 'wait':
if self.audio.check(): # once trigger will be detected, audio stream will be automatically closed
self.acqstate = 'on'
self.acqstart = clock()
self.status = 'ACQUISITION ' + str(self.curacq) + '/' + str(self.numacq)
if self.dotrack:
self.tracker.startsave()
elif self.acqstate == 'on' and (clock() - self.acqstart) > self.acqlen:
self.acqstate = 'off'
self.status = ''
if self.dotrack:
self.tracker.dosave = False
# close output movie, save time vector and tracking results
self.out.release()
savedata = {'timevector': self.timevector}
if self.dotrack:
savedata['xshift'] = self.tracker.xshift
savedata['yshift'] = self.tracker.yshift
savedata['rshift'] = self.tracker.rshift
savemat(self.curname + '.mat', savedata)
if self.dotrack:
pass
# finished repetition, or user interrupted them?
if self.curacq == self.numacq or not self.running:
self.buttons['startstop'].setChecked(False)
self.curacq = 0
# save
if self.acqstate == 'on':
eyesave = tracking.resize_roi(self.frame, self.roisave)
eyesave = eyesave.reshape((self.nysave, self.nxsave, 1)).repeat(3, axis=2)
self.timevector.append(clock() - self.acqstart)
#print 'write', eyesave.dtype, eyesave.shape
self.out.write(eyesave)
# track
if self.dotrack:
self.tracker.track(self.eye)
# display eye
if self.roi_selected:
self.eye = tracking.resize_roi(self.frame, self.roi)
scale = 4
img = np.repeat(np.repeat(self.eye, scale, axis=0), scale, axis=1)
if self.dotrack:
circle = self.tracker.fit*scale
cv2.circle(img, (int(circle[0]),int(circle[1])),int(circle[2]),255,1)
cv2.imshow('eye', img)
# update status
self.statusbar.setText(self.status + self.grabdesc)
def process_one_frame(self):
# grab frame (locked to clock if maxfreq is defined)
t = clock()
if self.maxfreq:
tick = t * self.maxfreq
ticklast = floor(
self.tlast * self.maxfreq + 0.0001
) # add a small quantity to avoid numerical error resulting in a value 1 less than it should
if tick - ticklast < 1:
# we did not miss a tick, wait for next tick
ticknext = ceil(tick)
sleep((ticknext - tick) / self.maxfreq)
t = ticknext / self.maxfreq
self.maxgap = max(self.maxgap, t - self.tlast)
self.tlast = t
ret, self.frame = self.film.read()
# no frame -> indicate that there is some "idle" time
if not ret:
if self.DOREC:
if not self.idle:
self.idle = True
print 'some idle time'
sleep(.001)
return
else:
self.film.release()
self.film = cv2.VideoCapture("mouseeyetracking.avi")
ret, self.frame = self.film.read()
else:
self.idle = False
# follow speed of processing frames
t = clock()
self.nprocessed += 1
if t > self.t0 + 1:
fps = self.nprocessed / (t - self.t0)
self.grabdesc = " (%.1ffps, max %.0fms gap)" % (fps,
self.maxgap * 1000)
self.t0 = t
self.nprocessed = 0
self.maxgap = 0
# make frame single channel
if self.frame.ndim == 3:
self.frame = cv2.cvtColor(self.frame, cv2.COLOR_BGR2GRAY)
# display frame
cv2.imshow('movie', self.frame)
# change between acquisition states
# note that acquisition will never start as long as ROI and filename are not selected
if self.running and self.acqstate == 'off':
self.acqstate = 'wait'
self.curacq += 1
self.status = 'waiting for trigger ' + str(
self.curacq) + '/' + str(self.numacq)
# open audio stream to detect trigger
self.audio.load()
# open movie for writing
fourcc = cv2.VideoWriter_fourcc(*'i420')
self.curname = self.filename + '_%.3i' % self.curacq
self.out = cv2.VideoWriter(self.curname + '.avi', fourcc, 60.0,
(self.nxsave, self.nysave))
# prepare for saving time vector and tracking results
self.timevector = []
if self.acqstate == 'wait':
if self.audio.check(
): # once trigger will be detected, audio stream will be automatically closed
self.acqstate = 'on'
self.acqstart = clock()
self.status = 'ACQUISITION ' + str(self.curacq) + '/' + str(
self.numacq)
if self.dotrack:
self.tracker.startsave()
elif self.acqstate == 'on' and (clock() - self.acqstart) > self.acqlen:
self.acqstate = 'off'
self.status = ''
if self.dotrack:
self.tracker.dosave = False
# close output movie, save time vector and tracking results
self.out.release()
savedata = {'timevector': self.timevector}
if self.dotrack:
savedata['xshift'] = self.tracker.xshift
savedata['yshift'] = self.tracker.yshift
savedata['rshift'] = self.tracker.rshift
savemat(self.curname + '.mat', savedata)
if self.dotrack:
pass
# finished repetition, or user interrupted them?
if self.curacq == self.numacq or not self.running:
self.buttons['startstop'].setChecked(False)
self.curacq = 0
# save
if self.acqstate == 'on':
eyesave = tracking.resize_roi(self.frame, self.roisave)
eyesave = eyesave.reshape(
(self.nysave, self.nxsave, 1)).repeat(3, axis=2)
self.timevector.append(clock() - self.acqstart)
#print 'write', eyesave.dtype, eyesave.shape
self.out.write(eyesave)
# track
if self.dotrack:
self.tracker.track(self.eye)
# display eye
if self.roi_selected:
self.eye = tracking.resize_roi(self.frame, self.roi)
scale = 4
img = np.repeat(np.repeat(self.eye, scale, axis=0), scale, axis=1)
if self.dotrack:
circle = self.tracker.fit * scale
cv2.circle(img, (int(circle[0]), int(circle[1])),
int(circle[2]), 255, 1)
cv2.imshow('eye', img)
# update status
self.statusbar.setText(self.status + self.grabdesc)
nprocessed = 0
if frame.ndim == 3:
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
cv2.imshow('image2',frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# user select ROI
roi = tracking.select_roi(frame)
else:
# fixed ROI
roi = {'x1': 222, 'y1': 163, 'x2': 268, 'y2': 210}
eye = tracking.resize_roi(frame, roi)
# OUTPUT MOVIE
if dosave:
# ROI for saving must be at least 65x65 otherwise buffer might be to small
roisave = roi.copy()
nxsave, nysave = roi['x2']-roi['x1'], roi['y2']-roi['y1']
if nxsave<65:
roisave['x1'] = roi['x1'] - floor((65-nxsave)/2)
nxsave = 65
roisave['x2'] = roisave['x1'] + nxsave
if nysave<65:
roisave['y1'] = roi['y1'] - floor((65-nysave)/2)
nysave = 65
roisave['y2'] = roisave['y1'] + nysave