def vignettingFromRandomSteps(imgs, bg, inPlane_scale_factor=None,
debugFolder=None, **kwargs):
'''
important: first image should shown most iof the device
because it is used as reference
'''
# TODO: inPlane_scale_factor
if debugFolder:
debugFolder = PathStr(debugFolder)
s = ObjectVignettingSeparation(imgs[0], bg, **kwargs)
for img in imgs[1:]:
fit = s.addImg(img)
if debugFolder and fit is not False:
imwrite(debugFolder.join('fit_%s.tiff' % len(s.fits)), fit)
if debugFolder:
imwrite(debugFolder.join('init.tiff'), s.flatField)
smoothed_ff, mask, flatField, obj = s.separate()
if debugFolder:
imwrite(debugFolder.join('object.tiff'), obj)
imwrite(debugFolder.join('flatfield.tiff'), flatField, dtype=float)
imwrite(debugFolder.join('flatfield_smoothed.tiff'), smoothed_ff,
dtype=float)
return smoothed_ff, mask
def pathJoin(pathlist):
if len(pathlist) > 5:
mod, number, name, current, date = pathlist[:5]
date = date.replace(':', '-')
dd0 = '__'.join((number, name))
dd1 = '__'.join((current, date))
out = PathStr(mod).join(dd0, dd1)
if len(pathlist[5:]):
out = out.join(*tuple(pathlist[5:]))
return out
return PathStr(pathlist[0]).join(*pathlist[1:])
def pathJoin(pathlist):
if len(pathlist) > 5:
mod, number, name, current, date = pathlist[:5]
# date = date.replace(':', '-')
date = datetime.strptime(date, '%x %X').strftime("%Y-%m-%dT%H_%M_%S")
dd0 = '__'.join((number, name))
dd1 = '__'.join((current, date))
out = PathStr(mod).join(dd0, dd1)
if len(pathlist[5:]):
out = out.join(*tuple(pathlist[5:]))
return out
return PathStr(pathlist[0]).join(*pathlist[1:])
def checkFolder(self):
'''
Check for new files/folders in self.opts['folder']
and import them into dataArtist
'''
fo = PathStr(self.opts['folder'])
o = self.opts['files only']
files = fo.listdir()
for f in files:
if f not in self._files:
ff = fo.join(f)
if not o or ff.isfile():
self.gui.addFilePath(ff)
self._files = files
def checkFolder(self):
'''
Check for new files/folders in self.opts['folder']
and import them into dataArtist
'''
fo = PathStr(self.opts['folder'])
o = self.opts['files only']
files = fo.listdir()
for f in files:
if f not in self._files:
ff = fo.join(f)
if not o or ff.isfile():
self.gui.addFilePath(ff)
self._files = files
final_img = final_img_crop
return final_img
else:
return self.base_img_rgb
if __name__ == '__main__':
import sys
import timeit
import imgProcessor
from fancytools.os.PathStr import PathStr
d = PathStr(imgProcessor.__file__).dirname().join('media')
i1 = cv2.imread(d.join('peanut_1.jpg'))
i2 = cv2.imread(d.join('peanut_2.jpg'))
def fn(overlap=None):
# stitch 2 images taken in 2 different perspectives together:
p = PerspectiveImageStitching(i1)
fn.result = p.addImg(i2, overlap=overlap)
# lets find out which method is faster:
print(('time needed without given overlap [s]: ',
timeit.timeit(fn, number=1)))
print(('time needed with given overlap [s]: ',
timeit.timeit(lambda: fn(overlap=150), number=1)))
if 'no_window' not in sys.argv:
cv2.namedWindow("warped")
arr = image[y0 - k:y0 + k, x0 - k:x0 + k]
U = positionToIntensityUncertainty(arr, std / fx, std / fx)
return U[k:-k, k:-k]
if __name__ == '__main__':
import sys
import imgProcessor
from imgProcessor.imgIO import imread
from fancytools.os.PathStr import PathStr
from pylab import plt
d = PathStr(imgProcessor.__file__).dirname().join(
'media', 'electroluminescence')
# STITCH BOTTOM
img = imread(d.join('EL_cell_cracked.png'), 'gray')
img = img[::2, ::2] # speed up for this test case
# CASE 1: constant position uncertainty:
stdx = 9
stdy = 3
sint = positionToIntensityUncertainty(img, stdx, stdy)
# CASE2: variable position uncertainty:
# x,y 0...15
stdx2 = np.fromfunction(lambda x, y: x * y, img.shape)
stdx2 /= stdx2[-1, -1] / 9
stdy2 = np.fromfunction(lambda x, y: x * y, img.shape)
stdy2 /= stdy2[-1, -1] / 9
stdy2 = stdy2[::-1, ::-1] # flip content twice
mask = np.logical_and(img2_cut == backgroundColor,
img1_cut != backgroundColor)
inter[mask] = img1_cut[mask]
if not overlapping:
overlap = 0
return np.vstack((img1[0:sizex - overlap, :], inter, img2[overlap:, :]))
if __name__ == '__main__':
import sys
from fancytools.os.PathStr import PathStr
from imgIO import imread
import cv2
d = PathStr('').join('media', 'electroluminescence')
i1 = d.join('EL_module_a_dist.PNG')
i2 = d.join('EL_module_b_dist.PNG')
img1 = imread(i1) / 2
img2 = imread(i2)
cv2.namedWindow("stitched", cv2.cv.CV_WINDOW_NORMAL)
s0 = img1.shape[0]
for i in range(-s0, s0):
img = linearBlend(img1, img2, i)
if 'no_window' not in sys.argv:
cv2.imshow('stitched', img)
cv2.waitKey(delay=20)
if 'no_window' not in sys.argv:
for l in self._linesFromvertices(self.vertices.astype(int)):
cv2.line(img, tuple(l[:2]), tuple(l[2:]), color, thickness=thickness)
return img
if __name__ == '__main__':
import sys
import pylab as plt
from fancytools.os.PathStr import PathStr
import imgProcessor
p = PathStr(imgProcessor.__file__).dirname().join(
'media', 'electroluminescence')
img = p.join('EL_module_orig.PNG')
q = QuadDetection(img)
img = q.drawVertices()
img2 = p.join('EL_cell_cracked.png')
q = QuadDetection(img2)
img2 = q.drawVertices(thickness=10)
if 'no_window' not in sys.argv:
plt.figure('module')
plt.imshow(img)
plt.figure('cell')
plt.imshow(img2)
plt.show()
ii += 1
return ii,jj
if __name__ == '__main__':
import sys
import pylab as plt
import imgProcessor
from imgProcessor.imgIO import imread
from fancytools.os.PathStr import PathStr
p = PathStr(imgProcessor.__file__).dirname().join(
'media', 'electroluminescence')
img = imread(p.join('EL_module_orig.PNG'), 'gray')
#add nans
img[300:310]=np.nan
img[:,110:130]=np.nan
bg = fastNaNmedianFilter(img,40,5)
if 'no_window' not in sys.argv:
plt.figure('image')
plt.imshow(img, interpolation='none')
plt.figure('background')
plt.imshow(bg, interpolation='none')
plt.figure('difference')
plt.imshow(img-bg, interpolation='none')
def getBackgroundLevel(img):
#seems to be best one according of no-ref bg comparison
#as done for SNR article in BEDRICH2016 JPV
return median_filter(img[10:-10:10,10:-10:10],7).min()
if __name__ == '__main__':
import sys
from fancytools.os.PathStr import PathStr
import imgProcessor
from imgProcessor.imgIO import imread
import pylab as plt
p = PathStr(imgProcessor.__file__).dirname().join(
'media', 'electroluminescence')
img = imread(p.join('EL_cell_cracked.png'), 'gray')
snr = SNR(img)
if 'no_window' not in sys.argv:
plt.figure('image')
plt.imshow(img)
plt.colorbar()
plt.figure('SNR')
plt.imshow(snr)
plt.colorbar()
plt.show()
jj += 1
ii += 1
return ii, jj
if __name__ == '__main__':
import sys
import pylab as plt
import imgProcessor
from imgProcessor.imgIO import imread
from fancytools.os.PathStr import PathStr
p = PathStr(imgProcessor.__file__).dirname().join('media',
'electroluminescence')
img = imread(p.join('EL_module_orig.PNG'), 'gray')
#add nans
img[300:310] = np.nan
img[:, 110:130] = np.nan
bg = fastNaNmedianFilter(img, 40, 5)
if 'no_window' not in sys.argv:
plt.figure('image')
plt.imshow(img, interpolation='none')
plt.figure('background')
plt.imshow(bg, interpolation='none')
plt.figure('difference')
plt.imshow(img - bg, interpolation='none')
offsx = int(round(loc[0] - ho))
offsy = overlapDeviation + overlap - loc[1]
#print 'offset x:%s, y:%s, rotation:%s' %(offsx, offsy, angles[i])
return offsx, offsy, angles[i]
if __name__ == '__main__':
import sys
import imgProcessor
from fancytools.os.PathStr import PathStr
d = PathStr(imgProcessor.__file__).dirname().join('media',
'electroluminescence')
#STITCH BOTTOM
i1 = d.join('EL_module_a_dist.PNG')
i2 = d.join('EL_module_b_dist.PNG')
i3 = d.join('EL_module_c.PNG')
s = StitchImages(i1)
stitched1 = s.addImg(i2, side='bottom', overlap=50, overlapDeviation=20)
stitched1 = s.addImg(i3, side='bottom', overlap=50, overlapDeviation=20)
#STITCH TOP
s = StitchImages(i3)
stitched2 = s.addImg(i2, side='top', overlap=50, overlapDeviation=20)
stitched2 = s.addImg(i1, side='top', overlap=50, overlapDeviation=20)
#STITCH RIGHT
i1 = d.join('EL_module_a_dist2.PNG')
i2 = d.join('EL_module_b_dist2.PNG')
return final_img
else:
return self.base_img_rgb
if __name__ == '__main__':
import sys
import timeit
import imgProcessor
from fancytools.os.PathStr import PathStr
d = PathStr(imgProcessor.__file__).dirname().join('media')
i1 = cv2.imread(d.join('peanut_1.jpg'))
i2 = cv2.imread(d.join('peanut_2.jpg'))
def fn(overlap=None):
#stitch 2 images taken in 2 different perspectives together:
p = PerspectiveTransformation(i1)
fn.result = p.addImg(i2, overlap=overlap)
#lets find out which method is faster:
print( 'time needed without given overlap [s]: ',
timeit.timeit(fn, number=1) )
print( 'time needed with given overlap [s]: ',
timeit.timeit(lambda: fn(overlap=150), number=1) )
if 'no_window' not in sys.argv:
inter,
img2[overlap:, :]))
if __name__ == '__main__':
import sys
from fancytools.os.PathStr import PathStr
from imgProcessor.imgIO import imread
import cv2
import imgProcessor
d = PathStr(
imgProcessor.__file__).dirname().join(
'media',
'electroluminescence')
i1 = d.join('EL_module_a_dist.PNG')
i2 = d.join('EL_module_b_dist.PNG')
img1 = imread(i1) // 2
img2 = imread(i2)
cv2.namedWindow("stitched")
s0 = img1.shape[0]
for i in range(-s0, s0):
img = linearBlend(img1, img2, i)
if 'no_window' not in sys.argv:
cv2.imshow('stitched', img)
cv2.waitKey(delay=20)
if 'no_window' not in sys.argv:
##########
#to allow to execute py code from a frozen environment
#type e.g. gui.exe -exec print(4+4)
if '-exec' in sys.argv:
try:
exec(sys.argv[-1])
except Exception, err:
raw_input('-exec failed! --> %s' %err)
sys.exit()
##########
MEDIA_FOLDER = PathStr(dataArtist.__file__).dirname().join('media')
HELP_FILE = MEDIA_FOLDER.join('USER_MANUAL.pdf')
class Gui(MultiWorkspaceWindow):
'''
The main class to be called to create an instance of dataArtist
'''
def __init__(self, title='dataArtist'):
MultiWorkspaceWindow.__init__(self, Workspace, title)
s = self.app.session
self.resize(600,550)
#ALLOW DRAGnDROP
self.setAcceptDrops(True)
#INIT CHILD PARTS:
from dataArtist.widgets.GlobalTools import GlobalTools
from dataArtist.widgets.StatusBar import StatusBar
##########
#to allow to execute py code from a frozen environment
#type e.g. gui.exe -exec print(4+4)
if '-exec' in sys.argv:
try:
exec(sys.argv[-1])
except Exception, err:
raw_input('-exec failed! --> %s' % err)
sys.exit()
##########
MEDIA_FOLDER = PathStr(dataArtist.__file__).dirname().join('media')
HELP_FILE = MEDIA_FOLDER.join('USER_MANUAL.pdf')
def _showActionToolTipInMenu(menu, action):
#show tooltip on the right side of [menu]
###QMenu normaly doesnt allow QActions to show tooltips...
tip = action.toolTip()
# QtGui.QToolTip.showText(QtGui.QCursor.pos(), tip)
p = menu.pos()
p.setX(p.x() + 105)
p.setY(p.y() - 21)
if tip != action.text():
QtGui.QToolTip.showText(p, tip)
class Gui(MultiWorkspaceWindow):
for i in xrange(orientations):
out[:,:,i] = convolve2d(image, k[i], mode='same' )
return out
if __name__ == '__main__':
import sys
from imgProcessor.imgIO import imread
import pylab as plt
from fancytools.os.PathStr import PathStr
import imgProcessor
p = PathStr(imgProcessor.__file__).dirname().join(
'media', 'electroluminescence')
img = imread(p.join('EL_cell_cracked.PNG'), 'gray')
k = (15,15)
o = 4
p0=(141,91)
p1=(251,242)
p2=(667,570)
kernels = _mkConvKernel(k, o, img)
h = hog(img, ksize=k, orientations=o)
if 'no_window' not in sys.argv:
plt.figure('image')
plt.imshow(img)
plt.scatter(*p0)
plt.scatter(*p1)
n += 1
if n > 0:
out[i, j] = np.median(buff[:n])
if __name__ == '__main__':
import sys
import pylab as plt
import imgProcessor
from imgProcessor.imgIO import imread
from fancytools.os.PathStr import PathStr
p = PathStr(imgProcessor.__file__).dirname().join('media',
'electroluminescence')
img = imread(p.join('EL_module_orig.PNG'), 'gray', dtype=float)
# add nans
img[300:320] = np.nan
img[:, 110:130] = np.nan
mask = np.isnan(img)
bg1 = maskedFilter(img.copy(), mask, 80, fn='mean')
bg2 = maskedFilter(img.copy(), mask, 80, fn='median')
img2 = maskedFilter(img.copy(), mask, 80, fill_mask=False, fn='mean')
if 'no_window' not in sys.argv:
plt.figure('image')
plt.imshow(img, interpolation='none')
plt.colorbar()
'''
Quantitative ElectroLuminescence Analysis
'''
from fancytools.os.PathStr import PathStr
name = 'QELA'
__version__ = '-' # time stamp, set by server during packaging
__author__ = 'Karl Bedrich'
__email__ = '*****@*****.**'
__license__ = 'GPLv3'
# MEDIA_PATH = PathStr.getcwd().join('client', 'media') #only works if
# executed from main dir
MEDIA_PATH = PathStr(__file__).dirname().join(
'media') # TODO: works in FROZEN?
ICON = MEDIA_PATH.join('logo.svg')
PATH = PathStr.home().mkdir(".%s" % name)
n += 1
if n > 0:
out[i, j] = np.median(buff[:n])
if __name__ == '__main__':
import sys
import pylab as plt
import imgProcessor
from imgProcessor.imgIO import imread
from fancytools.os.PathStr import PathStr
p = PathStr(imgProcessor.__file__).dirname().join(
'media', 'electroluminescence')
img = imread(p.join('EL_module_orig.PNG'), 'gray', dtype=float)
# add nans
img[300:320] = np.nan
img[:, 110:130] = np.nan
mask = np.isnan(img)
bg1 = maskedFilter(img.copy(), mask, 80, fn='mean')
bg2 = maskedFilter(img.copy(), mask, 80, fn='median')
img2 = maskedFilter(img.copy(), mask, 80,
fill_mask=False, fn='mean')
if 'no_window' not in sys.argv:
plt.figure('image')
plt.imshow(img, interpolation='none')
