def visualize(eigens):
l1 = eigens[:,:,0]
l2 = eigens[:,:,1]
m1 = np.min(l1)
m2 = np.min(l2)
r1 = np.max(l1) - m1
r2 = np.max(l2) - m2
if r1 == 0:
r1 = 1
if r2 == 0:
r2 = 1
l1cv = ut.np2cv(np.array( (1 - ((l1-m1) / r1)) * 255, dtype='uint8'))
l2cv = ut.np2cv(np.array( (1 - ((l2-m2) / r2)) * 255, dtype='uint8'))
hg.cvNamedWindow('eigen value 1', 1)
hg.cvNamedWindow('eigen value 2', 1)
hg.cvShowImage('eigen value 1', l1cv)
hg.cvShowImage('eigen value 2', l2cv)
while True:
k = hg.cvWaitKey(33)
if k == ' ':
return
if k == 'x':
exit()
def convert_ROS_image_to_cvimage(ROS_image, width, height):
ROS_image = np.array(ROS_image, dtype='uint8')
imNP = np.reshape(ROS_image,(height,width, 3))
cvimage = ut.np2cv(imNP)
return cvimage