class OpenCloseClassifier():
DEFECTS_DEPTH_FACTOR = config.DEFECTS_DEPTH_FACTOR
NUM_DEFECTS = config.NUM_DEFECTS
OPEN = config.HAND_OPEN
CLOSE = config.HAND_CLOSE
NONE = config.HAND_NONE
def __init__(self):
self._cvxdefects = ConvexityDefects()
def run(self, contour):
(defects, box) = self._cvxdefects.run(contour)
if not defects:
return self.NONE
if defects == None:
return self.CLOSE
if self._is_open(defects, box):
pose = self.OPEN
else:
pose = self.CLOSE
return pose
def _is_open(self, defects, box):
asd = (box[2] * box[3]) / 2.0
num = defects.size
mean = defects[:, :, -1].mean()
c1 = mean >= (float(asd) / self.DEFECTS_DEPTH_FACTOR)
c2 = num >= self.NUM_DEFECTS
return (c1 and c2)
class OpenCloseClassifier():
DEFECTS_DEPTH_FACTOR = config.DEFECTS_DEPTH_FACTOR
NUM_DEFECTS = config.NUM_DEFECTS
OPEN = config.HAND_OPEN
CLOSE = config.HAND_CLOSE
NONE = config.HAND_NONE
def __init__(self):
self._cvxdefects = ConvexityDefects()
def run(self, contour):
(defects, box) = self._cvxdefects.run(contour)
if not defects:
return self.NONE
if defects == None:
return self.CLOSE
if self._is_open(defects, box):
pose = self.OPEN
else:
pose = self.CLOSE
return pose
def _is_open(self, defects, box):
asd = (box[2] * box[3]) / 2.0
num = defects.size
mean = defects[:, :, -1].mean()
c1 = mean >= (float(asd) / self.DEFECTS_DEPTH_FACTOR)
c2 = num >= self.NUM_DEFECTS
return (c1 and c2)
def __init__(self):
self._cvxdefects = ConvexityDefects()
def __init__(self):
self._cvxdefects = ConvexityDefects()