def asHomography(self,forward=True):
'''
Get the transformation as a homography.
@keyword forward: switch between the forward and reverse transform.
@ktype forward: True|False
'''
fw,fh = self.frame_size
tw,th = self.frame_size
if forward:
if self.homography == None:
matrix = np.eye(3)
else:
matrix = np.linalg.inv(pv.OpenCVToNumpy(self.homography))
matrix = np.dot(np.diag([tw/fw,th/fh,1.0]),matrix)
perspective = pv.PerspectiveTransform(matrix,self.frame_size)
else:
if self.homography_rev == None:
matrix = np.eye(3)
else:
matrix = np.linalg.inv(pv.OpenCVToNumpy(self.homography_rev))
matrix = np.dot(np.diag([tw/fw,th/fh,1.0]),matrix)
perspective = pv.PerspectiveTransform(matrix,self.frame_size)
return perspective
def annotateFrame(self,frame,color='white'):
'''
Renders optical flow information to the frame.
@param frame: the frame that will be annotated
@type frame: pv.Image
@keyword type:
@ktype type: "TRACKING"
'''
w,h = self.tile_size
rect = pv.Rect(0,0,w,h)
affine = pv.AffineFromRect(rect,frame.size)
for pt in affine.transformPoints(self.tracks[:self.n]):
frame.annotatePoint(pt,color=color)
for pt in affine.transformPoints(self.tracks[self.n:]):
frame.annotatePoint(pt,color='red')
for pt in affine.transformPoints(self.bad_points):
frame.annotatePoint(pt,color='gray')
if self.homography != None:
matrix = pv.OpenCVToNumpy(self.homography)
perspective = pv.PerspectiveTransform(matrix,frame.size)
for pt in self.tracks[:self.n]:
# Transform the point multiple times to amplify the track
# for visualization
old = perspective.invertPoint(pt)
old = perspective.invertPoint(old)
old = perspective.invertPoint(old)
frame.annotateLine(pt,old,color=color)