def show(type, degree):
# Load object model
model_path = 'cup.ply'
model = inout.load_ply(model_path)
# Camera parameters
K = np.eye(3)
K[0, 0] = 500.0 # fx
K[1, 1] = 500.0 # fy
K[0, 2] = 250.0 # cx
K[1, 2] = 250.0 # cy
im_size = (500, 500)
# Calculate the poses of the rotating cup
poses = []
alpha_range = np.linspace(0, 360, 361)
for alpha in alpha_range:
def d2r(d):
return np.pi * float(d) / 180.0 # Degrees to radians
R = transform.rotation_matrix(d2r(alpha),
[0, 1, 0])[:3, :3] # Rotation around Y
R = transform.rotation_matrix(d2r(30), [1, 0, 0])[:3, :3].dot(
R) # Rotation around X
t = np.array([0.0, 0.0, 180]).reshape((3, 1))
# Flip Y axis (model coordinate system -> OpenCV coordinate system)
R = transform.rotation_matrix(np.pi, [1, 0, 0])[:3, :3].dot(R)
poses.append({'R': R, 't': t})
# Set and render the ground truth pose
gt_id = 90 # ID of the ground truth pose
pose_gt = poses[gt_id]
pose_gt_indis_set_ids = range(
55, 126) # IDs of poses indistinguishable from the GT pose
pose_gt_indis_set = [poses[i] for i in pose_gt_indis_set_ids]
depth_gt = renderer.render(model,
im_size,
K,
pose_gt['R'],
pose_gt['t'],
100,
2000,
mode='depth')
# Synthesize the test depth image
depth_test = np.array(depth_gt)
depth_test[depth_test == 0] = 1000
if type == 'average':
diff(int(degree), pose_gt, poses, model, depth_test, 3, 30, K)
elif type == 'standard_deviation':
standard_dev(int(degree), pose_gt, poses, model, depth_test, 3, 30, K)
def show(type, t1, t2):
# Load object model
model_path = 'cup.ply'
model = inout.load_ply(model_path)
# Camera parameters
K = np.eye(3)
K[0, 0] = 500.0 # fx
K[1, 1] = 500.0 # fy
K[0, 2] = 250.0 # cx
K[1, 2] = 250.0 # cy
im_size = (500, 500)
# Calculate the poses of the rotating cup
poses = []
alpha_range = np.linspace(0, 360, 361)
for alpha in alpha_range:
def d2r(d):
return np.pi * float(d) / 180.0 # Degrees to radians
R = transform.rotation_matrix(d2r(alpha),
[0, 1, 0])[:3, :3] # Rotation around Y
R = transform.rotation_matrix(d2r(30), [1, 0, 0])[:3, :3].dot(
R) # Rotation around X
t = np.array([0.0, 0.0, 180]).reshape((3, 1))
# Flip Y axis (model coordinate system -> OpenCV coordinate system)
R = transform.rotation_matrix(np.pi, [1, 0, 0])[:3, :3].dot(R)
poses.append({'R': R, 't': t})
# Set and render the ground truth pose
gt_id = 90 # ID of the ground truth pose
pose_gt = poses[gt_id]
pose_gt_indis_set_ids = range(
55, 126) # IDs of poses indistinguishable from the GT pose
pose_gt_indis_set = [poses[i] for i in pose_gt_indis_set_ids]
depth_gt = renderer.render(model,
im_size,
K,
pose_gt['R'],
pose_gt['t'],
100,
2000,
mode='depth')
# Synthesize the test depth image
depth_test = np.array(depth_gt)
depth_test[depth_test == 0] = 1000
# Available errors: 'cpr' 'wivm' 'zdd'
# Errors to be calculated:
errs_active = [type]
# Calculate the pose errors
errs = {err: [] for err in errs_active}
# the for loop is calculate for 0 - 360 degrees.
for pose_id, pose in enumerate(poses):
print 'Processing pose:', pose_id
if 'cpr' in errs_active:
mint = t1
maxt = t2
errs['cpr'].append(error.cpr(model, pose_gt, pose, mint, maxt))
if 'zdd' in errs_active:
delta = 3
errs['zdd'].append(
error.zdd(pose, pose_gt, model, depth_test, delta, K))
if 'wivm' in errs_active:
delta = t1
errs['wivm'].append(
error.wivm(pose, pose_gt, model, depth_test, delta, K, t1, t2))
# draw the graph for every degree.
for err_name in errs_active:
plt.figure()
plt.plot(errs[err_name], c='r', lw='3')
plt.xlabel('Pose ID')
plt.ylabel(err_name)
plt.tick_params(labelsize=16)
plt.tight_layout()
plt.show()
from obj_pose_eval import renderer, inout, transform
# Load object model
model_path = 'cup.ply'
model = inout.load_ply(model_path)
# Camera parameters
K = np.eye(3)
K[0, 0] = 500.0 # fx
K[1, 1] = 500.0 # fy
K[0, 2] = 250.0 # cx
K[1, 2] = 250.0 # cy
im_size = (500, 500)
R = transform.rotation_matrix(np.pi, (1, 0, 0))[:3, :3]
t = np.array([[0, 0, 150]]).T
rgb, depth = renderer.render(model, im_size, K, R, t, 100, 2000, mode='rgb+depth')
# depth = renderer.render(model, im_size, K, R, t, 100, 2000, mode='depth')
# rgb = renderer.render(model, im_size, K, R, t, 100, 2000, mode='rgb')
plt.imshow(rgb)
plt.title('Rendered color image')
plt.matshow(depth)
plt.colorbar()
plt.title('Rendered depth image')
plt.show()
K = np.eye(3)
K[0, 0] = 500.0 # fx
K[1, 1] = 500.0 # fy
K[0, 2] = 250.0 # cx
K[1, 2] = 250.0 # cy
im_size = (500, 500)
# Calculate the poses of the rotating cup
poses = []
alpha_range = np.linspace(0, 360, 361)
for alpha in alpha_range:
def d2r(d):
return np.pi * float(d) / 180.0 # Degrees to radians
R = transform.rotation_matrix(d2r(alpha),
[0, 1, 0])[:3, :3] # Rotation around Y
R = transform.rotation_matrix(d2r(30), [1, 0, 0])[:3, :3].dot(
R) # Rotation around X
t = np.array([0.0, 0.0, 180]).reshape((3, 1))
# Flip Y axis (model coordinate system -> OpenCV coordinate system)
R = transform.rotation_matrix(np.pi, [1, 0, 0])[:3, :3].dot(R)
poses.append({'R': R, 't': t})
# Set and render the ground truth pose
gt_id = 90 # ID of the ground truth pose
pose_gt = poses[gt_id]
pose_gt_indis_set_ids = range(
55, 126) # IDs of poses indistinguishable from the GT pose
pose_gt_indis_set = [poses[i] for i in pose_gt_indis_set_ids]
depth_gt = renderer.render(model,