def preprocessing(self, imgs, msks, sz=(48, 48), augx=0):
print len(imgs)
if augx > 0:
print "augmenting train data ..."
# augx = 2xnSample+1
n_sample = np.int(augx / 2.0) - 1
imH, imW = imgs[0].shape[0:2]
borderH = np.int(imH * 0.2)
borderW = np.int(imW * 0.2)
w = imW - borderW
h = imH - borderH
x1s = np.random.randint(0, borderW, n_sample)
y1s = np.random.randint(0, borderH, n_sample)
imgs_crop = imgs
msks_crop = msks
for img, msk in zip(imgs, msks):
imgs_crop += [imcrop(img, [x1, y1, w, h]) for x1, y1 in zip(x1s, y1s)]
msks_crop += [imcrop(msk, [x1, y1, w, h]) for x1, y1 in zip(x1s, y1s)]
print len(imgs_crop)
imgs_flip = [pl.fliplr(im) for im in imgs_crop]
msks_flip = [pl.fliplr(im) for im in msks_crop]
imgs = imgs_crop + imgs_flip
msks = msks_crop + msks_flip
print len(imgs)
imgs_rs = [imresize(im, sz, interp="bicubic") for im in imgs]
imgs_norm = [imnormalize(im) for im in imgs_rs]
msks_norm = [imresize(im, sz, interp="bicubic") for im in msks]
imgs_final, msks_final = self.convert_data(imgs_norm, msks_norm)
print len(imgs_final)
return imgs_final, msks_final
def vertFlipCheckBoxChanged(self, event):
self.vertFlip = self.ui.vertFlipCheckBox.isChecked()
if hasattr(self, 'meas'):
self.plotImage(pl.fliplr(self.meas),
autoLevels=self.autolevels,
eqHist=self.equalizeHist,
scale=self.scale)
def generate_masks(pattern,scattMaskRadius=50,scattMaskCenterX=523, scattMaskCenterY=523, background=30, slit=60):
[dimy,dimx] = pattern.shape
mask = euclid(dimx, dimx, scattMaskCenterX, scattMaskCenterY, scattMaskRadius)
#mask[518:518+slit,:] = 0
#mask[370:480,520:650] = 0
#mask[:370,520:580] = 0
#mask[590:600,505:515] = 0
crosswidth = 10
shiftx = 10
shifty = 5
mask[512-crosswidth+shiftx:512+crosswidth+shiftx, :] = 0
mask[:, 512-crosswidth+shifty:512+crosswidth+shifty] = 0
mask[470:512, 400:512] = 0
mask = fliplr(rot90(mask,3))
H = numpy.array([map(float,line.strip('\n').split(',')) for line in filterwindow.split('\n')])
blurred = imfilter(mask,H)
newMask = 1-(blurred<0.99)
H2 = H
newMask = imfilter(newMask.astype('double'), H2)
#newMask = imfilter(newMask.astype('double'), H2)
mask *= newMask
gMask = gaussian_mask(dimx,dimx,400,700,300)
centerMask = euclid(dimx,dimx,numpy.round(dimx/2),numpy.round(dimx/2),90)
return mask, gMask, centerMask
def generate_masks(pattern,scattMaskRadius=50,scattMaskCenterX=523, scattMaskCenterY=523, background=30, slit=17):
print 'getting shape'
[dimy,dimx] = pattern.shape
print 'mask bad areas'
mask = euclid(dimx, dimx, scattMaskCenterX, scattMaskCenterY, scattMaskRadius)
mask[518:518+slit,:] = 0
mask[370:480,520:650] = 0
mask[:370,520:580] = 0
mask[590:600,505:515] = 0
print 'doint some flipping...'
mask = fliplr(rot90(mask,3))
# H = numpy.array([map(float,line.strip('\n').split(',')) for line in open('/Users/Goldmund/Documents/MATLAB/H.txt').readlines()])
print 'generate smear object'
H = zeropad(strel(9, shape = 'disk'), mask.shape[0], mask.shape[1])
print 'broaden mask by blurring it'
blurred = numpy.abs(myconv2(mask,H))
newMask = 1-(blurred<0.99)
H2 = H
print 'blurring new mask'
newMask = numpy.abs(myconv2(newMask.astype('double'),H2))
mask *= newMask
print 'creating gaussian and center mask'
gMask = gaussian_mask(dimx,dimx,400,700,300)
centerMask = euclid(dimx,dimx,numpy.round(dimx/2),numpy.round(dimx/2),150)
return mask, gMask, centerMask
def generate_masks(pattern,
scattMaskRadius=50,
scattMaskCenterX=523,
scattMaskCenterY=523,
background=30,
slit=60):
[dimy, dimx] = pattern.shape
mask = euclid(dimx, dimx, scattMaskCenterX, scattMaskCenterY,
scattMaskRadius)
#mask[518:518+slit,:] = 0
#mask[370:480,520:650] = 0
#mask[:370,520:580] = 0
#mask[590:600,505:515] = 0
crosswidth = 10
shiftx = 10
shifty = 5
mask[512 - crosswidth + shiftx:512 + crosswidth + shiftx, :] = 0
mask[:, 512 - crosswidth + shifty:512 + crosswidth + shifty] = 0
mask[470:512, 400:512] = 0
mask = fliplr(rot90(mask, 3))
H = numpy.array([
map(float,
line.strip('\n').split(',')) for line in filterwindow.split('\n')
])
blurred = imfilter(mask, H)
newMask = 1 - (blurred < 0.99)
H2 = H
newMask = imfilter(newMask.astype('double'), H2)
#newMask = imfilter(newMask.astype('double'), H2)
mask *= newMask
gMask = gaussian_mask(dimx, dimx, 400, 700, 300)
centerMask = euclid(dimx, dimx, numpy.round(dimx / 2),
numpy.round(dimx / 2), 90)
return mask, gMask, centerMask
def startAcq(self):
"""
Function called when pressing the Start button. Will launch the
integration loop and stay going as long as no stopping action has
happened (pressing Stop button, closing the window, changed integration
time).
"""
self.ui.stopBut.setEnabled(True)
self.ui.startBut.setEnabled(False)
camId = self.ui.cameraID.value()
try:
with StarlightCCD(camId) as self.ccd:
self.meas = pl.zeros((self.ccd.ccdParams['height'],
self.ccd.ccdParams['width']))
i = 0
# flags for the event loop
startThread = True # needs to start a new acquisition
self.plotMeas = False # needs to plot the acquisition (acq finished)
self.acquire = True # CCD should be acquiring
# wait for a loop to finish
while self.acquiring:
pass
self.acquiring = True # the event loop below is active
# acquisition event loop
while self.acquire:
if startThread:
ccdThread = ExposureThread(
self.ccd,
self.exposureTime,
ilAcq=self.ilAcq,
ilCorrDoubleExpo=self.ilDoubleExpo)
ccdThread.start()
startThread = False
if self.capture and self.exposureTime > 1:
self.captureStartSound.play()
#print 'start sound'
if not ccdThread.is_alive(): # acquisition finished
self.plotMeas = True
startThread = True
if self.plotMeas:
self.meas = ccdThread.ccd.pixels.transpose()
if self.ccd.ccdParams[
'isInterlaced'] and not self.ilAcq: ##not self.ilAcq and
self.scale = (1, 2)
else:
self.scale = (1, 1)
# flip image according to user specification
# note that due to pyqtgraph behaviour, the array
# columns are the rows in the displayed image
if self.horizFlip:
self.meas = pl.flipud(self.meas)
if self.vertFlip:
self.meas = pl.fliplr(self.meas)
# plot image preview
self.plotImage(self.meas,
autoLevels=self.autolevels,
eqHist=self.equalizeHist,
scale=self.scale)
if self.capture:
self.captureStopSound.play()
#print 'stop sound'
break # will stop and record file in self.stop()
else:
self.plotMeas = False # go for another acquisition
if ccdThread.ccd.completionPercentage == 100 or i % 100 == 0:
self.ui.progressBar.setValue(
ccdThread.ccd.completionPercentage)
self.displayStats()
# process events to catch a stop push and refresh image preview
self.app.processEvents()
i = i + 1
#self.ui.progressBar.setValue(0)
ccdThread.stop()
while ccdThread.is_alive(): # wait before closing device
pass
self.acquiring = False
except IndexError:
self.ui.modelName.setText('No device')
self.ccd = None
finally:
self.stop(userStop=False)