class ThresholdDialog(ParaDialog):
def init_view(self, items, para, hist):
self.histcvs = HistCanvas(self)
self.histcvs.set_hist(hist)
self.add_ctrl('hist', self.histcvs)
ParaDialog.init_view(self, items, para, True)
def para_check(self, para, key):
mid = 128 - para['bright']
length = 255 / np.tan(para['contrast'] / 180.0 * np.pi)
self.histcvs.set_lim(mid - length / 2, mid + length / 2)
self.reset()
return True
class ThresholdDialog(ParaDialog):
def init_view(self, items, para, hist, lim):
self.histcvs = HistCanvas(self)
self.histcvs.set_hist(hist)
self.lim = lim
self.add_ctrl('hist', self.histcvs)
ParaDialog.init_view(self, items, para, True)
def para_check(self, para, key):
if key=='thr1':para['thr2'] = max(para['thr1'], para['thr2'])
if key=='thr2':para['thr1'] = min(para['thr1'], para['thr2'])
lim1 = 1.0 * (para['thr1'] - self.lim[0])/(self.lim[1]-self.lim[0])
lim2 = 1.0 * (para['thr2'] - self.lim[0])/(self.lim[1]-self.lim[0])
self.histcvs.set_lim(lim1*255, lim2*255)
self.reset()
return True
def gray(self, hist):
panel = wx.Panel( self, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, wx.TAB_TRAVERSAL )
back = wx.BoxSizer( wx.VERTICAL )
back.Add(panel, 1, wx.EXPAND)
sizer = wx.BoxSizer( wx.VERTICAL )
histc = HistCanvas(panel)
histc.set_hist(hist)
txt = wx.StaticText( panel, wx.ID_ANY, 'Channel:'+'Gray', wx.DefaultPosition, wx.DefaultSize, 0 )
sizer.Add( txt, 0, wx.LEFT|wx.RIGHT, 8 )
sizer.Add( histc, 0, wx.LEFT|wx.RIGHT, 8 )
mean, lim = np.dot(hist, range(256))/hist.sum(), np.where(hist>0)[0]
sta = 'Statistic: Mean:%s Min:%s Max:%s'%(mean.round(1), lim.min(), lim.max())
txt = wx.StaticText( panel, wx.ID_ANY, sta, wx.DefaultPosition, wx.DefaultSize, 0 )
sizer.Add( txt, 0, wx.LEFT|wx.RIGHT|wx.BOTTOM, 8 )
panel.SetSizer( sizer )
self.SetSizer(back)
self.Fit()
class Balance_Dialog(ParaDialog):
def init_view(self, para, view, img):
hists = [
np.histogram(img[:, :, i], list(range(257)))[0] for i in (0, 1, 2)
]
hists = [(i * (100.0 / i.max())).astype(np.uint8) for i in hists]
self.redcvs = HistCanvas(self)
self.redcvs.set_hist(hists[0])
self.greencvs = HistCanvas(self)
self.greencvs.set_hist(hists[1])
self.bluecvs = HistCanvas(self)
self.bluecvs.set_hist(hists[2])
self.add_ctrl('red', self.redcvs)
self.parse(view[0])
self.parse(view[1])
self.add_ctrl('green', self.greencvs)
self.parse(view[2])
self.parse(view[3])
self.add_ctrl('blue', self.bluecvs)
self.parse(view[4])
self.parse(view[5])
self.add_check('Preview', 'preview')
self.add_confirm(True)
self.reset(para)
self.pack()
def para_check(self, para, key):
self.redcvs.set_lim(para['t1_red'], para['t2_red'])
self.greencvs.set_lim(para['t1_green'], para['t2_green'])
self.bluecvs.set_lim(para['t1_blue'], para['t2_blue'])
if key == 't1_red':
para['t2_red'] = max(para['t2_red'], para['t1_red'])
if key == 't2_red':
para['t1_red'] = min(para['t2_red'], para['t1_red'])
if key == 't1_green':
para['t2_green'] = max(para['t2_green'], para['t1_green'])
if key == 't2_green':
para['t1_green'] = min(para['t2_green'], para['t1_green'])
if key == 't1_blue':
para['t2_blue'] = max(para['t2_blue'], para['t1_blue'])
if key == 't2_blue':
para['t1_blue'] = min(para['t2_blue'], para['t1_blue'])
self.reset()
return True
class Balance_Dialog(ParaDialog):
def init_view(self, para, view, img):
hists = [
np.histogram(img[:, :, i], list(range(257)))[0] for i in (0, 1, 2)
]
hists = [(i * (100.0 / i.max())).astype(np.uint8) for i in hists]
self.redcvs = HistCanvas(self)
self.redcvs.set_hist(hists[0])
self.greencvs = HistCanvas(self)
self.greencvs.set_hist(hists[1])
self.bluecvs = HistCanvas(self)
self.bluecvs.set_hist(hists[2])
self.add_ctrl('red', self.redcvs)
self.parse(view[0])
self.parse(view[1])
self.add_ctrl('green', self.greencvs)
self.parse(view[2])
self.parse(view[3])
self.add_ctrl('blue', self.bluecvs)
self.parse(view[4])
self.parse(view[5])
self.add_check('Preview', 'preview')
self.add_confirm(True)
self.reset(para)
self.pack()
def para_check(self, para, key):
mid = 128 - para['b_red']
length = 255 / np.tan(para['c_red'] / 180.0 * np.pi)
self.redcvs.set_lim(mid - length / 2, mid + length / 2)
mid = 128 - para['b_green']
length = 255 / np.tan(para['c_green'] / 180.0 * np.pi)
self.greencvs.set_lim(mid - length / 2, mid + length / 2)
mid = 128 - para['b_blue']
length = 255 / np.tan(para['c_blue'] / 180.0 * np.pi)
self.bluecvs.set_lim(mid - length / 2, mid + length / 2)
self.reset()
return True