def getLimbTransforms(joints1, joints2):
n_limbs = len(limbs)
n_joints = joints1.shape[0]
Ms = np.zeros((2, 3, 10))
ctr = 0
for i in xrange(n_limbs):
n_joints_for_limb = len(limbs[i])
p1 = np.zeros((n_joints_for_limb, 2))
p2 = np.zeros((n_joints_for_limb, 2))
for j in xrange(n_joints_for_limb):
p1[j, :] = [joints1[limbs[i][j], 0], joints1[limbs[i][j], 1]]
p2[j, :] = [joints2[limbs[i][j], 0], joints2[limbs[i][j], 1]]
tform = transformations.make_similarity(p2, p1, False)
Ms[:, :, ctr] = np.array([[tform[1], -tform[3], tform[0]],
[tform[3], tform[1], tform[2]]])
ctr += 1
'''
if(i >= 1 and i <= 4):
tform = transformations.make_similarity(p2,p1,True)
Ms[:,:,ctr] = np.array([[tform[1],tform[3],tform[0]],[tform[3],-tform[1],tform[2]]])
ctr+=1
'''
#M = np.array([[tform[1], tform[2], tform[0]],[tform[5],tform[6],tform[4]]])
#Ms[:,:,i] = M
return Ms
def get_limb_transforms(limbs, joints1, joints2):
n_limbs = len(limbs)
Ms = np.zeros((2, 3, n_limbs))
for i in range(n_limbs):
n_joints_for_limb = len(limbs[i])
p1 = np.zeros((n_joints_for_limb, 2))
p2 = np.zeros((n_joints_for_limb, 2))
for j in range(n_joints_for_limb):
p1[j, :] = [joints1[limbs[i][j], 0], joints1[limbs[i][j], 1]]
p2[j, :] = [joints2[limbs[i][j], 0], joints2[limbs[i][j], 1]]
tform = transformations.make_similarity(p2, p1, False)
Ms[:, :, i] = np.array([[tform[1], -tform[3], tform[0]],
[tform[3], tform[1], tform[2]]])
return Ms