def insertLayer(self, index, name=None, data=None):
'''
insert a new image as layer
...add new / override existing layer
...show dialog when data.shape != self.image.shape
'''
if data is not None:
try:
self.image = np.insert(self.image, index, data, axis=0)
except IndexError:
index = -1
self.image = np.insert(self.image, index, data, axis=0)
except (ValueError, MemoryError):
if index == 0 and len(self.image) == 1:
#replace, if only has one layer
self.image = np.expand_dims(data, axis=0)
else:
if type(data) == list:
data = data[0]
s1 = self.image[0].shape
s2 = data.shape
#LAYER COLOR IS DIFFERENT:
c1 = isColor(self.image[0])
c2 = isColor(data)
if c1 and not c2:
data = toColor(data)
s2 = data.shape
elif not c1 and c2:
self.image = toColor(self.image)
s1 = self.image[0].shape
if s1 != s2:
#NEW LAYER SHAPE DOESNT FIT EXISTING:
###show DIALOG#####
d = DifferentShapeDialog(name, s1, s2)
d.exec_()
r = d.opt
if r == d.optNewDisplay:
self.moveLayerToNewImage = index
return
elif r == d.optCut:
data = data[0:s1[0],0:s1[1]]
if data.shape != s1:
d = np.zeros(s1)
d[0:s2[0], 0:s2[1]]=data
data = d
elif r == d.optResize:
data = cv2.resize(data, (s1[1],s1[0]))
elif r == d.optWarp:
data = PerspectiveTransformation(self.image[-1]).fitImg(data)
self.image = np.insert(self.image, index, data, axis=0)
self.currentIndex = index
self.setImage(self.image)
return self.image[index]
def addColorLayer(self, layer=None, name='Unnamed', tip='',
color=None, alpha=0.5):
'''
add a [layer], a np.array (2d or 3d), as colour overlay to the image
'''
if layer is None:
s = self.image.shape
if len(s) == 4: # multi layer color image
s = s[1:-1]
elif len(s) == 3:
if s[-1] == 3: # single layer color image
s = s[:-1]
else: # multi layer grey image
s = s[1:]
layer = np.zeros(shape=s)
if isColor(layer):
layer = toGray(layer)
if color is None:
# set colour as function of the number of colorItems:
color = pg.intColor(len(self.cItems)).rgb()
cItem = ColorLayerItem(layer,
imageWidget=self,
color=color,
alpha=alpha
)
name = incrementName(list(self.cItems.keys()), name)
self.cItems[name] = cItem
self.view.addItem(cItem)
self.sigOverlayAdded.emit(cItem, name, tip)
return cItem
def _chromaticity(self):
i = self.display.widget.image
assert isColor(i), 'Only works on color images'
out = np.empty_like(i)
for n, im in enumerate(i):
out[n] = rgChromaticity(im)
self.handleOutput(out, title='RG chromacity')
def separate(self):
i = self.display.widget.image
assert isColor(i), 'Only works on color images'
out = np.transpose(i, axes=(3, 0, 1, 2))
self.handleOutput(out,
title='Color channels separated',
names=['red', 'green', 'blue'])
def addColorLayer(self, layer=None, name='Unnamed', tip='',
color=None, alpha=0.5):
'''
add a [layer], a np.array (2d or 3d), as colour overlay to the image
'''
if layer is None:
s = self.image.shape
if len(s) == 4: # multi layer color image
s = s[1:-1]
elif len(s) == 3:
if s[-1] == 3: # single layer color image
s = s[:-1]
else: #multi layer grey image
s = s[1:]
layer = np.zeros(shape=s)
if isColor(layer):
layer = toGray(layer)
if color is None:
#set colour as function of the number of colorItems:
color = pg.intColor(len(self.cItems)).rgb()
cItem = ColorLayerItem(layer,
imageWidget=self,
color=color,
alpha=alpha
)
name = incrementName(self.cItems.keys(), name)
self.cItems[name] = cItem
self.view.addItem(cItem)
self.sigOverlayAdded.emit(cItem, name, tip)
return cItem
def _monochromaticWavelength(self):
i = self.display.widget.image
assert isColor(i), 'Only works on color images'
out = np.empty(shape=i.shape[:-1])
for n, im in enumerate(i):
out[n] = monochromaticWavelength(im)
self.handleOutput(out,
title='monochromatic wavelength',
axes=('x', 'y', 'wavelength [nm]'))
def _process(self):
img = self.display.widget.image[-1]
if isColor(img):
img = toGray(img)
avg = SNRaverage(SNR(img))
i = self.pOpt.opts['limits'].index(self.pOpt.value())
limit = self.SNR_LIMITS[i][1]
fac = limit / avg
return fac
def activate(self):
self._items = []
self._fns = []
nr = self.pRNRows.value()
s = self.pSpace.value()
w = self.display.widget
vb = w.view.vb
if len(w.image) < 2:
self.setChecked(False)
raise Exception('needs multiple images for grid view')
w.setCurrentIndex(0)
w.display.widget.showTimeline(False)
hist = w.ui.histogram
s0,s1 = w.image.shape[1:3]
px,py = s0+s,0
ir = 1
for img in w.image[1:]:
if isColor(img):
#TODO: I dont know why it returns an error on color ...find out
print 'only works on grayscale images at the moment'
img = toGray(img)
item = ImageItem(img)
#link colorbar
fn1 = lambda hist, i=item: i.setLookupTable(hist.getLookupTable)
fn2 = lambda hist, i=item: i.setLevels(hist.region.getRegion() )
hist.sigLookupTableChanged.connect(fn1)
hist.sigLevelsChanged.connect(fn2)
s0,s1 = img.shape[:2]
item.moveBy(px,py)
vb.addItem(item)
#update grid position coords:
ir += 1
px += s0+s
if ir == nr:
ir = 0
px = 0
py += s1+s
self._items.append(item)
self._fns.append((fn1,fn2))
hist.sigLookupTableChanged.emit(hist)
hist.sigLevelsChanged.emit(hist)
ar = vb.state['autoRange']
vb.state['autoRange'] = [True,True]
vb.updateAutoRange()
vb.state['autoRange'] = ar
def activate(self):
self._items = []
self._fns = []
w = self.display.widget
vb = w.view.vb
if len(w.image) < 2:
self.setChecked(False)
raise Exception('needs multiple images for grid view')
w.setCurrentIndex(0)
w.display.widget.showTimeline(False)
hist = w.ui.histogram
for img, (px, py) in zip(w.image[1:], self._positions()):
if isColor(img):
# TODO: I dont know why it returns an error on color ...find
# out
print('only works on grayscale images at the moment')
img = toGray(img)
item = ImageItem(img)
# link colorbar
fn1 = lambda hist, i=item: i.setLookupTable(hist.getLookupTable)
fn2 = lambda hist, i=item: i.setLevels(hist.region.getRegion())
hist.sigLookupTableChanged.connect(fn1)
hist.sigLevelsChanged.connect(fn2)
# s0,s1 = img.shape[:2]
item.moveBy(px, py)
vb.addItem(item)
self._items.append(item)
self._fns.append((fn1, fn2))
hist.sigLookupTableChanged.emit(hist)
hist.sigLevelsChanged.emit(hist)
ar = vb.state['autoRange']
vb.state['autoRange'] = [True, True]
vb.updateAutoRange()
vb.state['autoRange'] = ar
def activate(self):
self._fns = []
w = self.display.widget
vb = w.view.vb
w.subitems = []
if len(w.image) < 2:
self.setChecked(False)
raise Exception('needs multiple images for grid view')
w.setCurrentIndex(0)
w.display.widget.showTimeline(False)
hist = w.ui.histogram
for img, (px, py) in zip(w.image[1:], self._positions()):
if isColor(img):
# TODO: I dont know why it returns an error on color ...find
# out
print('only works on grayscale images at the moment')
img = toGray(img)
item = ImageItem(img)
# link colorbar
fn1 = lambda hist, i=item: i.setLookupTable(hist.getLookupTable)
fn2 = lambda hist, i=item: i.setLevels(hist.region.getRegion())
hist.sigLookupTableChanged.connect(fn1)
hist.sigLevelsChanged.connect(fn2)
# s0,s1 = img.shape[:2]
item.moveBy(px, py)
vb.addItem(item)
w.subitems.append(item)
self._fns.append((fn1, fn2))
hist.sigLookupTableChanged.emit(hist)
hist.sigLevelsChanged.emit(hist)
ar = vb.state['autoRange']
vb.state['autoRange'] = [True, True]
vb.updateAutoRange()
vb.state['autoRange'] = ar
def fn(path, img):
r = self.pRange.value()
if r == '0-max':
r = (0, w.levelMax)
elif r == 'min-max':
r = (w.levelMin, w.levelMax)
else: # 'current'
r = w.ui.histogram.getLevels()
int_img = toUIntArray(img,
# cutNegative=self.pCutNegativeValues.value(),
cutHigh=~self.pStretchValues.value(),
range=r,
dtype={'8 bit': np.uint8,
'16 bit': np.uint16}[self.pDType.value()])
if isColor(int_img):
int_img = cv2.cvtColor(int_img, cv2.COLOR_RGB2BGR)
cv2.imwrite(path, transpose(int_img))
def fn(path, img):
r = self.pRange.value()
if r == '0-max':
r = (0, w.levelMax)
elif r == 'min-max':
r = (w.levelMin, w.levelMax)
else: # 'current'
r = w.ui.histogram.getLevels()
int_img = toUIntArray(
img,
# cutNegative=self.pCutNegativeValues.value(),
cutHigh=~self.pStretchValues.value(),
range=r,
dtype={
'8 bit': np.uint8,
'16 bit': np.uint16
}[self.pDType.value()])
if isColor(int_img):
int_img = cv2.cvtColor(int_img, cv2.COLOR_RGB2BGR)
cv2.imwrite(path, int_img)
def insertLayer(self, index, name=None, data=None):
'''
insert a new image as layer
...add new / override existing layer
...show dialog when data.shape != self.image.shape
'''
if data is not None:
try:
self.image = np.insert(self.image, index, data, axis=0)
except IndexError:
index = -1
self.image = np.insert(self.image, index, data, axis=0)
except (ValueError, MemoryError):
if index == 0 and len(self.image) == 1:
# replace, if only has one layer
self.image = np.expand_dims(data, axis=0)
else:
if isinstance(data, list):
data = data[0]
s1 = self.image[0].shape
s2 = data.shape
# LAYER COLOR IS DIFFERENT:
c1 = isColor(self.image[0])
c2 = isColor(data)
if c1 and not c2:
data = toColor(data)
s2 = data.shape
elif not c1 and c2:
self.image = toColor(self.image)
s1 = self.image[0].shape
if s1 != s2:
if isRot90(s1, s2):
print('Image is rotated 90DEG.')
data = rot90(data)
else:
# NEW LAYER SHAPE DOESNT FIT EXISTING:
###show DIALOG#####
d = DifferentShapeDialog(name, s1, s2)
d.exec_()
r = d.opt
if r == d.optNewDisplay:
self.moveLayerToNewImage = index
return
elif r == d.optCut:
data = data[0:s1[0], 0:s1[1]]
if data.shape != s1:
d = np.zeros(s1)
d[0:s2[0], 0:s2[1]] = data
data = d
elif r == d.optResize:
data = cv2.resize(data, (s1[1], s1[0]))
elif r == d.optWarp:
data = PerspectiveImageStitching(
self.image[-1]).fitImg(data)
self.image = np.insert(self.image, index, data, axis=0)
self.currentIndex = index
self.setImage(self.image)
return self.image[index]
def _check(self):
i = self.display.widget.image
if i is not None:
self.setChecked(isColor(i))
def separate(self):
i = self.display.widget.image
assert isColor(i), 'Only works on color images'
out = np.transpose(i, axes=(3,0,1,2))
self.handleOutput(out, title='Color channels separated',
names=['red', 'green', 'blue'])
def _check(self):
i = self.display.widget.image
if i is not None:
self.setChecked(isColor(i))
