class TableDetector(event.DecisionMaker):
def __init__(self, ev):
self.ev = ev
self.table_matcher = SIFTMatcher(templ='haarcascades/table.png', min_match_count=20)
super(TableDetector, self).__init__(ev)
def frame(self, frame):
height, width = frame.shape[:2]
frame = cv2.resize(frame, (3*width/4, 3*height/4))
result = self.table_matcher.find_match(frame)
if result is not None:
kp2, matchesMask, dst, good, dst_pts = result
else:
cv2.imshow('frame', frame)
self.sleep(0)
return
frame = cv2.polylines(frame,[np.int32(dst)],True, 255)
cv2.imshow('Table detector', cv2.resize(frame, dsize=None,
fx=0.5, fy=0.5))
self.emit('table_pos', dst)
self.sleep(0)
def __init__(self, ev):
self.ev = ev
self.table_matcher = SIFTMatcher(templ='haarcascades/table.png', min_match_count=20)
super(TableDetector, self).__init__(ev)
