def forward(self, x, flow):
x = self.conv1(x)
f1 = warp(x, flow)
x = self.conv2(x)
flow = F.interpolate(
flow, scale_factor=0.5, mode="bilinear", align_corners=False) * 0.5
f2 = warp(x, flow)
x = self.conv3(x)
flow = F.interpolate(
flow, scale_factor=0.5, mode="bilinear", align_corners=False) * 0.5
f3 = warp(x, flow)
x = self.conv4(x)
flow = F.interpolate(
flow, scale_factor=0.5, mode="bilinear", align_corners=False) * 0.5
f4 = warp(x, flow)
return [f1, f2, f3, f4]
def forward(self, x):
x = F.interpolate(x,
scale_factor=0.5,
mode="bilinear",
align_corners=False)
flow0 = self.block0(x)
F1 = flow0
warped_img0 = warp(x[:, :3], F1)
warped_img1 = warp(x[:, 3:], -F1)
flow1 = self.block1(torch.cat((warped_img0, warped_img1, F1), 1))
F2 = (flow0 + flow1)
warped_img0 = warp(x[:, :3], F2)
warped_img1 = warp(x[:, 3:], -F2)
flow2 = self.block2(torch.cat((warped_img0, warped_img1, F2), 1))
F3 = (flow0 + flow1 + flow2)
return F3, [F1, F2, F3]
def forward(self, img0, img1, flow, c0, c1, flow_gt):
warped_img0 = warp(img0, flow)
warped_img1 = warp(img1, -flow)
if flow_gt == None:
warped_img0_gt, warped_img1_gt = None, None
else:
warped_img0_gt = warp(img0, flow_gt[:, :2])
warped_img1_gt = warp(img1, flow_gt[:, 2:4])
s0 = self.down0(torch.cat((warped_img0, warped_img1, flow), 1))
s1 = self.down1(torch.cat((s0, c0[0], c1[0]), 1))
s2 = self.down2(torch.cat((s1, c0[1], c1[1]), 1))
s3 = self.down3(torch.cat((s2, c0[2], c1[2]), 1))
x = self.up0(torch.cat((s3, c0[3], c1[3]), 1))
x = self.up1(torch.cat((x, s2), 1))
x = self.up2(torch.cat((x, s1), 1))
x = self.up3(torch.cat((x, s0), 1))
x = self.conv(x)
return x, warped_img0, warped_img1, warped_img0_gt, warped_img1_gt
def forward(self, x, scale=1.0):
x = F.interpolate(x, scale_factor=0.5 * scale, mode="bilinear",
align_corners=False)
flow0 = self.block0(x)
F1 = flow0
warped_img0 = warp(x[:, :3], F1)
warped_img1 = warp(x[:, 3:], -F1)
flow1 = self.block1(torch.cat((warped_img0, warped_img1, F1), 1))
F2 = (flow0 + flow1)
warped_img0 = warp(x[:, :3], F2)
warped_img1 = warp(x[:, 3:], -F2)
flow2 = self.block2(torch.cat((warped_img0, warped_img1, F2), 1))
F3 = (flow0 + flow1 + flow2)
warped_img0 = warp(x[:, :3], F3)
warped_img1 = warp(x[:, 3:], -F3)
flow3 = self.block3(torch.cat((warped_img0, warped_img1, F3), 1))
F4 = (flow0 + flow1 + flow2 + flow3)
F4 = F.interpolate(F4, scale_factor=1 / scale, mode="bilinear",
align_corners=False) / scale
return F4, [F1, F2, F3, F4]
def forward(self, x, scale=1.0):
if scale != 1.0:
x = F.interpolate(x,
scale_factor=scale,
mode="bilinear",
align_corners=False)
flow0 = self.block0(x)
F1 = flow0
F1_large = F.interpolate(F1,
scale_factor=2.0,
mode="bilinear",
align_corners=False,
recompute_scale_factor=False) * 2.0
warped_img0 = warp(x[:, :3], F1_large[:, :2])
warped_img1 = warp(x[:, 3:], F1_large[:, 2:4])
flow1 = self.block1(torch.cat((warped_img0, warped_img1, F1_large), 1))
F2 = (flow0 + flow1)
F2_large = F.interpolate(F2,
scale_factor=2.0,
mode="bilinear",
align_corners=False,
recompute_scale_factor=False) * 2.0
warped_img0 = warp(x[:, :3], F2_large[:, :2])
warped_img1 = warp(x[:, 3:], F2_large[:, 2:4])
flow2 = self.block2(torch.cat((warped_img0, warped_img1, F2_large), 1))
F3 = (flow0 + flow1 + flow2)
F3_large = F.interpolate(F3,
scale_factor=2.0,
mode="bilinear",
align_corners=False,
recompute_scale_factor=False) * 2.0
warped_img0 = warp(x[:, :3], F3_large[:, :2])
warped_img1 = warp(x[:, 3:], F3_large[:, 2:4])
flow3 = self.block3(torch.cat((warped_img0, warped_img1, F3_large), 1))
F4 = (flow0 + flow1 + flow2 + flow3)
if scale != 1.0:
F4 = F.interpolate(F4,
scale_factor=1 / scale,
mode="bilinear",
align_corners=False) / scale
return F4, [F1, F2, F3, F4]