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]