示例#1
0
    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]
示例#2
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    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
示例#3
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 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')
示例#4
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 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'])
示例#5
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    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
示例#6
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 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
示例#10
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    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
示例#11
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 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))
示例#12
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        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)
示例#13
0
    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]
示例#14
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 def _check(self):
     i = self.display.widget.image
     if i is not None:
         self.setChecked(isColor(i))
示例#15
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 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'])
示例#16
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 def _check(self):
     i = self.display.widget.image
     if i is not None:
         self.setChecked(isColor(i))