def test_align():
orig_points = np.array([
[3.36748406, 1.61036404, 3.55147255],
[3.58702265, 0.06676394, 3.64695356],
[0.28452026, -0.11188296, 3.78947735],
[0.25482713, 1.57828256, 3.6900808],
[3.54938525, 1.74057692, 5.13329681],
[3.6855626 , 0.10335229, 5.26344841],
[0.25025385, -0.06146044, 5.57085135],
[0.20742481, 1.71073272, 5.41823085],
]).T
ft2inch = 12.0
inch2cm = 2.54
cm2m = 0.01
ft2m = ft2inch * inch2cm * cm2m
x1,y1,z1=0,0,0
x2,y2,z2=np.array([10,5,5])*ft2m
new_points = np.array([
[x2, y2, z2],
[x2, y1, z2],
[x1, y1, z2],
[x1, y2, z2],
[x2, y2, z1],
[x2, y1, z1],
[x1, y1, z1],
[x1, y2, z1],
]).T
print(orig_points.T)
print(new_points.T)
s,R,t = estsimt(orig_points,new_points)
print('s=%s'%repr(s))
print('R=%s'%repr(R.tolist()))
print('t=%s'%repr(t.tolist()))
Xnew = align_points( s,R,t, orig_points )
# measure distance between elements
mean_absdiff = np.mean( abs(Xnew[:3]-new_points).flatten() )
assert mean_absdiff < 0.05
M_orig = np.array([[1,2,3,4],
[5,6,7,8],
[9,10,11,12]],dtype=np.float)
print('Xnew.T')
print(Xnew.T)
M_new = align_M( s,R,t, M_orig )
print('M_new')
print(M_new)
def test_align():
orig_points = np.array([
[3.36748406, 1.61036404, 3.55147255],
[3.58702265, 0.06676394, 3.64695356],
[0.28452026, -0.11188296, 3.78947735],
[0.25482713, 1.57828256, 3.6900808],
[3.54938525, 1.74057692, 5.13329681],
[3.6855626, 0.10335229, 5.26344841],
[0.25025385, -0.06146044, 5.57085135],
[0.20742481, 1.71073272, 5.41823085],
]).T
ft2inch = 12.0
inch2cm = 2.54
cm2m = 0.01
ft2m = ft2inch * inch2cm * cm2m
x1, y1, z1 = 0, 0, 0
x2, y2, z2 = np.array([10, 5, 5]) * ft2m
new_points = np.array([
[x2, y2, z2],
[x2, y1, z2],
[x1, y1, z2],
[x1, y2, z2],
[x2, y2, z1],
[x2, y1, z1],
[x1, y1, z1],
[x1, y2, z1],
]).T
print(orig_points.T)
print(new_points.T)
s, R, t = estsimt(orig_points, new_points)
print('s=%s' % repr(s))
print('R=%s' % repr(R.tolist()))
print('t=%s' % repr(t.tolist()))
Xnew = align_points(s, R, t, orig_points)
# measure distance between elements
mean_absdiff = np.mean(abs(Xnew[:3] - new_points).flatten())
assert mean_absdiff < 0.05
M_orig = np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]],
dtype=np.float)
print('Xnew.T')
print(Xnew.T)
M_new = align_M(s, R, t, M_orig)
print('M_new')
print(M_new)
def check_align(cam_opts):
cam_orig = _build_test_camera(**cam_opts)
M_orig = cam_orig.M
cam_orig = CameraModel.load_camera_from_M( M_orig )
R1 = np.eye(3)
R2 = np.zeros((3,3))
R2[0,1] = 1
R2[1,0] = 1
R2[2,2] = -1
t1 = np.array( (0.0, 0.0, 0.0) )
t2 = np.array( (0.0, 0.0, 0.1) )
t3 = np.array( (0.1, 0.0, 0.0) )
for s in [1.0, 2.0]:
for R in [R1, R2]:
for t in [t1, t2, t3]:
cam_actual = cam_orig.get_aligned_camera( s, R, t )
M_expected = mcsc_align.align_M( s,R,t, M_orig )
cam_expected = CameraModel.load_camera_from_M( M_expected )
assert cam_actual==cam_expected
