scene_gt[im_id_out] = []
for pose in poses:
R_m2c = pose['R']
t_m2c = pose['t']
t_m2c *= 1000.0 # Convert to [mm]
# Transfom the GT pose (to compensate transformation of the models)
t_m2c = t_m2c + R_m2c.dot(t_model)
# Get 2D bounding box of the object model at the ground truth pose
obj_bb = misc.calc_pose_2d_bbox(model, par.cam['im_size'], par.cam['K'], R_m2c, t_m2c)
# Visualisation
if False:
ren_rgb = renderer.render(model, par.cam['im_size'], par.cam['K'],
R_m2c, t_m2c, mode='rgb')
vis_rgb = 0.4 * rgb.astype(np.float32) + 0.6 * ren_rgb.astype(np.float32)
vis_rgb = vis_rgb.astype(np.uint8)
vis_rgb = misc.draw_rect(vis_rgb, obj_bb)
plt.imshow(vis_rgb)
plt.show()
scene_gt[im_id_out].append(
{
'obj_id': obj_id,
'cam_R_m2c': R_m2c.flatten().tolist(),
'cam_t_m2c': t_m2c.flatten().tolist(),
'obj_bb': [int(x) for x in obj_bb]
}
)
elev_range)
print('Sampled views: ' + str(len(views)))
view_sampler.save_vis(out_views_vis_mpath.format(str(radius)), views,
views_level)
# Render the object model from all the views
for view_id, view in enumerate(views):
if view_id % 10 == 0:
print('obj,radius,view: ' + str(obj_id) + ',' + str(radius) +
',' + str(view_id))
# Render depth image
depth = renderer.render(model,
par.cam['im_size'],
par.cam['K'],
view['R'],
view['t'],
clip_near,
clip_far,
mode='depth')
# Convert depth is in the same units as for test images
depth /= par.cam['depth_scale']
# Render RGB image
rgb = renderer.render(model,
im_size_rgb,
K_rgb,
view['R'],
view['t'],
clip_near,
clip_far,
if pose['R'].size != 0 and pose['t'].size != 0:
# Transfom the GT pose
R_m2c = pose['R'].dot(R_conv)
t_m2c = pose['t'] * 1000 # from [m] to [mm]
# Get 2D bounding box of the object model at the ground truth pose
obj_bb = misc.calc_pose_2d_bbox(model, par.cam.im_size, par.cam.K,
R_m2c, t_m2c)
# Visualisation
if False:
rgb = inout.read_im(rgb_mpath.format(im_id, im_id))
ren_rgb = renderer.render(model,
par.cam.im_size,
par.cam.K,
R_m2c,
t_m2c,
mode='rgb')
vis_rgb = 0.4 * rgb.astype(np.float32) + 0.6 * ren_rgb.astype(
np.float32)
vis_rgb = vis_rgb.astype(np.uint8)
vis_rgb = misc.draw_rect(vis_rgb, obj_bb)
plt.imshow(vis_rgb)
plt.show()
scene_gt.setdefault(im_id, []).append({
'obj_id':
obj_id,
'cam_R_m2c':
R_m2c.flatten().tolist(),
'cam_t_m2c':
ren_depth = np.zeros(depth.shape, np.float)
gt_ids_curr = range(len(scene_gt[im_id]))
if gt_ids:
gt_ids_curr = set(gt_ids_curr).intersection(gt_ids)
for gt_id in gt_ids_curr:
gt = scene_gt[im_id][gt_id]
model = models[gt['obj_id']]
K = scene_info[im_id]['cam_K']
R = gt['cam_R_m2c']
t = gt['cam_t_m2c']
# Rendering
if vis_rgb:
m_rgb = renderer.render(model, im_size, K, R, t, mode='rgb')
if vis_depth or (vis_rgb and vis_rgb_resolve_visib):
m_depth = renderer.render(model,
im_size,
K,
R,
t,
mode='depth')
# Get mask of the surface parts that are closer than the
# surfaces rendered before
visible_mask = np.logical_or(ren_depth == 0,
m_depth < ren_depth)
mask = np.logical_and(m_depth != 0, visible_mask)
ren_depth[mask] = m_depth[mask].astype(ren_depth.dtype)