class RenderDOG:
def __init__(self):
self.dog = DetectorDOG()
def __call__(self, im):
tmp = im.asPIL()
tmp = tmp.resize((160, 120))
tmp = Image(tmp)
points = self.dog.detect(tmp)
for score, pt, radius in points:
pt = Point(pt.X() * 4, pt.Y() * 4)
im.annotateCircle(pt, radius * 4)
return im
class RenderDOG:
def __init__(self):
self.dog = DetectorDOG()
def __call__(self,im):
tmp = im.asPIL()
tmp = tmp.resize((160,120))
tmp = Image(tmp)
points = self.dog.detect(tmp)
for score,pt,radius in points:
pt = Point(pt.X()*4,pt.Y()*4)
im.annotateCircle(pt,radius*4)
return im
def __init__(self, parent, id, name, demos=DEMO_DEFAULTS, size=(800, 550)):
wx.Frame.__init__(self, parent, id, name, size=size)
# ---------------- Basic Data -------------------
self.webcam = Webcam()
self.harris = DetectorHarris()
self.dog = DetectorDOG(n=100, selector='best')
self.face = CascadeDetector()
self.demos = demos
# ------------- Other Components ----------------
self.CreateStatusBar()
# ------------------- Menu ----------------------
# Creating the menubar.
# ----------------- Image List ------------------
# --------------- Image Display -----------------
self.static_bitmap = wx.StaticBitmap(self,
wx.NewId(),
bitmap=wx.EmptyBitmap(640, 480))
self.radios = wx.RadioBox(self,
wx.NewId(),
'Demos',
choices=['None'] + self.demos.keys(),
style=wx.RA_SPECIFY_ROWS)
self.mirror = wx.CheckBox(self, wx.NewId(), 'Mirror')
self.mirror.SetValue(True)
# --------------- Window Layout -----------------
grid = wx.FlexGridSizer(2, 2)
grid.Add(self.static_bitmap)
grid.Add(self.radios)
grid.Add(self.mirror)
self.SetAutoLayout(True)
self.SetSizer(grid)
self.Layout()
# -----------------------------------------------
self.timer = FrameTimer(self)
self.timer.Start(200)
# -------------- Event Handleing ----------------
wx.EVT_SIZE(self.static_bitmap, self.onBitmapResize)
wx.EVT_LEFT_DOWN(self.static_bitmap, self.onClick)
wx.EVT_TIMER(self, -1, self.onTmp)
def __init__(self):
self.dog = DetectorDOG()
im.show()
ilog.log(im)
mat = im.asMatrix2D()
high = mat > 180
low = mat < 50
mask = high#+low
edges = canny(im,100,200)
ilog.log(edges)
ilog.log(Image(1.0*mask))
e = edges.asPIL().convert('RGB')
m = Image(1.0*mask).asPIL()
i = im.asPIL()
logo = Image(composite(i,e,m))
ilog.log(logo)
#sys.exit()
sm = Image(im.asPIL().resize((320,240),LINEAR))
detector = DetectorDOG()
points = detector.detect(sm)
for score,pt,radius in points:
logo.annotateCircle(pt*4,radius*4)
ilog.log(logo)
ilog.show()
def __init__(self):
self.dog = DetectorDOG()
