def Test10(self
): # Description: Add noise and interpolate (take image at end)
# do STLs with noise after this.
V = Vis()
Hand1 = HandVis(V)
Hand1.loadHand()
Hand2 = HandVis(V)
Hand2.loadHand()
Obj1 = ObjectVis(V)
Obj1.loadObject(4)
Data = ParseGraspData()
grasps = Data.findGrasp(objnum=4,
subnum=4,
graspnum=11,
list2check=Data.all_transforms)
grasp = grasps[1]
HandT, ObjT, Arm_JA, Hand_JA = Data.matricesFromGrasp(grasp)
Hand1.orientHandtoObj(HandT, ObjT, Obj1)
Hand1.setJointAngles(Hand_JA)
Hand1.getPalmPoint()
contact_points1, contact_links1 = Hand1.retractFingers(Obj1)
Contact_JA = Hand1.obj.GetDOFValues()
filename_base = "obj%s_sub%s_graspnum%s_grasptype%s" % (4, 4, 11,
'extreme0')
if False:
T_noise, JA_noise = Hand2.addNoiseToGrasp(
Obj1,
T_zero=Hand1.obj.GetTransform(),
Contact_JA=Contact_JA,
TL_n=0.01,
R_n=0.1,
JA_n=0.1)
np.savetxt(filename_base + "_%s.txt" % 'T_noise', T_noise)
np.savetxt(filename_base + "_%s.txt" % 'JA_noise', JA_noise)
else:
JA_noise = np.genfromtxt(filename_base + "_%s.txt" % 'JA_noise')
T_noise = np.genfromtxt(filename_base + "_%s.txt" % 'T_noise')
Hand2.setJointAngles(JA_noise)
Hand2.obj.SetTransform(T_noise)
contact_points2, contact_links2 = Hand2.retractFingers(Obj1)
alpha = np.linspace(0, 1, 6)[1:-1]
start_axis_angle = np.array([0, 0, 0])
end_axis_angle = np.array([0, np.pi, 0])
Hand1.hide()
for a in alpha:
filename = filename_base + "_alpha%s.png" % (int(10 * a))
Hand2.ZSLERP(start_axis_angle, end_axis_angle, a, T_zero=T_noise)
V.clearPoints()
V.takeImage(filename)
time.sleep(1)
pdb.set_trace()
def Test11(self): # Description: Generating Images for Interpolated Grasps
# Oriignal is grey
# 180 + noise grasp is pink
# interpolated is violet
# do STLs with noise after this.
V = Vis()
Hand1 = HandVis(V)
Hand1.loadHand()
Hand2 = HandVis(V)
Hand2.loadHand()
Obj1 = ObjectVis(V)
Obj1.loadObject(4)
Obj1.changeColor('green')
Data = ParseGraspData()
Data.parseOutputData()
Data.parseAllTransforms()
# obj4_cluster13_sub5_grasp2_optimal0_prime.jpg obj4_cluster13_sub5_grasp3_extreme1_target.jpg -- don't have the data. Tried without class but extreme grasp was too far!
# grasp1 = Data.findGrasp(objnum = 4, subnum = 5, graspnum = 2, grasptype = 'optimal0', list2check = Data.all_transforms)
# grasp2 = Data.findGrasp(objnum = 4, subnum = 5, graspnum = 3, grasptype = 'extreme1', list2check = Data.all_transforms)
# obj4_cluster8_sub4_grasp14_extreme1_prime.jpg obj4_cluster8_sub4_grasp14_optimal0_target.jpg -- don't have the data
# grasp1 = Data.findGrasp(objnum = 4, subnum = 4, graspnum = 14, grasptype = 'extreme1', list2check = Data.all_transforms)
# grasp2 = Data.findGrasp(objnum = 4, subnum = 4, graspnum = 14, grasptype = 'optimal0', list2check = Data.all_transforms)
# obj4_cluster8_sub4_grasp14_extreme1_prime.jpg obj4_cluster8_sub4_grasp9_optimal0_target.jpg -- don't have the data
case = 4
#ones that I think look good
if case == 1:
grasp1 = Data.findGrasp(objnum=4,
subnum=4,
graspnum=11,
grasptype='optimal0',
list2check=Data.all_transforms)
grasp2 = Data.findGrasp(objnum=4,
subnum=4,
graspnum=11,
grasptype='optimal0',
list2check=Data.all_transforms)
filename_base = "obj%s_sub%s_graspnum%s_%s_%s" % (
4, 4, 11, 'optimal0', 'optimal0')
elif case == 2:
grasp1 = Data.findGrasp(objnum=4,
subnum=5,
graspnum=2,
grasptype='optimal0',
list2check=Data.all_transforms)
grasp2 = Data.findGrasp(objnum=4,
subnum=5,
graspnum=3,
grasptype='extreme1',
list2check=Data.all_transforms)
filename_base = "obj%s_sub%s_graspnum%s_%s_%s" % (
4, 5, '2&3', 'optimal0', 'extreme1')
elif case == 3:
grasp1 = Data.findGrasp(objnum=4,
subnum=4,
graspnum=14,
grasptype='extreme1',
list2check=Data.all_transforms)
grasp2 = Data.findGrasp(objnum=4,
subnum=4,
graspnum=14,
grasptype='optimal0',
list2check=Data.all_transforms)
filename_base = "obj%s_sub%s_graspnum%s_%s_%s" % (
4, 4, 14, 'extreme1', 'optimal0')
elif case == 4:
grasp1 = Data.findGrasp(objnum=4,
subnum=4,
graspnum=14,
grasptype='extreme1',
list2check=Data.all_transforms)
grasp2 = Data.findGrasp(objnum=4,
subnum=4,
graspnum=9,
grasptype='optimal0',
list2check=Data.all_transforms)
filename_base = "obj%s_sub%s_graspnum%s_%s_%s" % (
4, 4, '14&9', 'extreme1', 'optimal0')
HandT1, ObjT1, Arm_JA1, Hand_JA1 = Data.matricesFromGrasp(grasp1[0])
HandT2, ObjT2, Arm_JA2, Hand_JA2 = Data.matricesFromGrasp(grasp2[0])
Hand1.orientHandtoObj(HandT1, ObjT1, Obj1)
Hand1.setJointAngles(Hand_JA1)
Hand1.changeColor('greyI')
Hand2.orientHandtoObj(HandT2, ObjT2, Obj1)
Hand2.setJointAngles(Hand_JA2)
Hand2.changeColor('pinkI')
Hand1.getPalmPoint()
contact_points1, contact_links1 = Hand1.retractFingers(Obj1)
contact_points2, contact_links2 = Hand2.retractFingers(Obj1)
start_axis_angle = np.array([0, 0, 0])
end_axis_angle = np.array([0, np.pi, 0])
Hand2.ZSLERP(start_axis_angle,
end_axis_angle,
1,
T_zero=Hand2.obj.GetTransform())
Hand3 = HandVis(V)
Hand3.loadHand()
Hand3.makeEqual(Hand1)
Hand3.changeColor('blueI')
alpha = np.linspace(0, 1, 6)[1:-1]
if case == 1:
V.setCamera(60, 0, 5 / 4 * np.pi - 0.75)
elif case == 2:
V.setCamera(60, np.pi / 4 - 1.5, -np.pi - 1)
elif case == 3:
V.setCamera(40, np.pi / 3 + 0.2, -np.pi - 0.5)
elif case == 4:
V.setCamera(40, np.pi / 3 - np.pi, -np.pi - 0.75)
# pdb.set_trace()
# function to get out dist, az, el of camera from current view
for a in alpha:
filename = filename_base + "_alpha%s.png" % (int(10 * a))
Hand3.ZSLERP(start_axis_angle,
end_axis_angle,
a,
T_zero=Hand1.obj.GetTransform())
V.clearPoints()
V.takeImage(filename)
time.sleep(1)