def compute_pairwise_loss(tgt_img, ref_img, tgt_depth, ref_depth, pose,
intrinsic, with_ssim, with_mask, with_auto_mask,
padding_mode):
ref_img_warped, valid_mask, projected_depth, computed_depth = inverse_warp2(
ref_img, tgt_depth, ref_depth, pose, intrinsic, padding_mode)
diff_img = (tgt_img - ref_img_warped).abs().clamp(0, 1)
diff_depth = ((computed_depth - projected_depth).abs() /
(computed_depth + projected_depth)).clamp(0, 1)
if with_auto_mask == True:
auto_mask = (diff_img.mean(dim=1, keepdim=True) <
(tgt_img - ref_img).abs().mean(
dim=1, keepdim=True)).float() * valid_mask
valid_mask = auto_mask
if with_ssim == True:
ssim_map = compute_ssim_loss(tgt_img, ref_img_warped)
diff_img = (0.15 * diff_img + 0.85 * ssim_map)
if with_mask == True:
weight_mask = (1 - diff_depth)
diff_img = diff_img * weight_mask
# compute all loss
reconstruction_loss = mean_on_mask(diff_img, valid_mask)
geometry_consistency_loss = mean_on_mask(diff_depth, valid_mask)
return reconstruction_loss, geometry_consistency_loss
def compute_pairwise_loss(tgt_img,
ref_img,
tgt_depth,
ref_depth,
pose,
with_mask,
intrinsic,
with_ssim,
rotation_mode='euler',
padding_mode='zeros'):
ref_img_warped, valid_mask, projected_depth, computed_depth = inverse_warp2(
ref_img, tgt_depth, ref_depth, pose, intrinsic, rotation_mode,
padding_mode)
diff_img = (tgt_img - ref_img_warped).abs() * valid_mask
diff_depth = (
(computed_depth - projected_depth).abs() /
(computed_depth + projected_depth).abs()).clamp(0, 1) * valid_mask
if with_ssim == True:
ssim_map = (0.5 * (1 - ssim(tgt_img, ref_img_warped))).clamp(
0, 1) * valid_mask
diff_img = (0.15 * diff_img + 0.85 * ssim_map) * valid_mask
if with_mask == True:
weight_mask = (1 - diff_depth) * valid_mask
diff_img = diff_img * weight_mask
# compute loss
reconstruction_loss = mean_on_mask(diff_img, valid_mask)
geometry_consistency_loss = mean_on_mask(diff_depth, valid_mask)
return reconstruction_loss, geometry_consistency_loss
def compute_pairwise_loss(tgt_img, ref_img, tgt_depth, ref_depth, pose,
intrinsic, args):
ref_img_warped, valid_mask, projected_depth, computed_depth = inverse_warp2(
ref_img, tgt_depth, ref_depth, pose, intrinsic, args.padding_mode)
diff_img = (tgt_img - ref_img_warped).abs()
diff_depth = ((computed_depth - projected_depth).abs() /
(computed_depth + projected_depth).abs()).clamp(0, 1)
if args.with_ssim:
ssim_map = (0.5 * (1 - ssim(tgt_img, ref_img_warped))).clamp(0, 1)
diff_img = (0.15 * diff_img + 0.85 * ssim_map)
if args.with_mask:
weight_mask = (1 - diff_depth)
diff_img = diff_img * weight_mask
# compute loss
reconstruction_loss = mean_on_mask(diff_img, valid_mask)
geometry_consistency_loss = mean_on_mask(diff_depth, valid_mask)
return reconstruction_loss, geometry_consistency_loss