im_size = (obj_mask_gt.shape[1], obj_mask_gt.shape[0])
# Absolute difference of the distance images
# dist_diff = np.abs(dist_gt.astype(np.float32) -
# dist_im.astype(np.float32))
# mask_below_delta = dist_diff < delta
# mask_below_delta *= obj_mask_gt
# Bounding box of the object mask
# bbox_all = [-1, -1, -1, -1]
# if px_count_all > 0:
# ys, xs = obj_mask_gt.nonzero()
# bbox_all = misc.calc_2d_bbox(xs, ys, im_size)
# Bounding box of the object projection
bbox_obj = misc.calc_pose_2d_bbox(models[gt['obj_id']], im_size, K,
gt['cam_R_m2c'], gt['cam_t_m2c'])
# Bounding box of the visible surface part
bbox_visib = [-1, -1, -1, -1]
if px_count_visib > 0:
ys, xs = visib_gt.nonzero()
bbox_visib = misc.calc_2d_bbox(xs, ys, im_size)
gt_stats[im_id].append({
'px_count_all': int(px_count_all),
'px_count_visib': int(px_count_visib),
'px_count_valid': int(px_count_valid),
'visib_fract': float(visib_fract),
'bbox_obj': [int(e) for e in bbox_obj],
'bbox_visib': [int(e) for e in bbox_visib]
})
R_conv = np.linalg.inv(R_model.dot(R_z_90.dot(R_x_90)))
for im_id in im_ids:
if im_id % 10 == 0:
print('obj,view: ' + obj_name + ',' + str(im_id))
# Load the GT pose
pose = load_gt_pose_brachmann(pose_mpath.format(obj_name, im_id))
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.load_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)
im_size = (obj_mask_gt.shape[1], obj_mask_gt.shape[0])
# Absolute difference of the distance images
# dist_diff = np.abs(dist_gt.astype(np.float32) -
# dist_im.astype(np.float32))
# mask_below_delta = dist_diff < delta
# mask_below_delta *= obj_mask_gt
# Bounding box of the object mask
# bbox_all = [-1, -1, -1, -1]
# if px_count_all > 0:
# ys, xs = obj_mask_gt.nonzero()
# bbox_all = misc.calc_2d_bbox(xs, ys, im_size)
# Bounding box of the object projection
bbox_obj = misc.calc_pose_2d_bbox(models[gt['obj_id']], im_size,
K, gt['cam_R_m2c'], gt['cam_t_m2c'])
# Bounding box of the visible surface part
bbox_visib = [-1, -1, -1, -1]
if px_count_visib > 0:
ys, xs = visib_gt.nonzero()
bbox_visib = misc.calc_2d_bbox(xs, ys, im_size)
gt_stats[im_id].append({
'px_count_all': int(px_count_all),
'px_count_visib': int(px_count_visib),
'px_count_valid': int(px_count_valid),
'visib_fract': float(visib_fract),
'bbox_obj': [int(e) for e in bbox_obj],
'bbox_visib': [int(e) for e in bbox_visib]
})
