def _get_edge_guidances(self, tensors):
from utils.edge import get_edge
guidances = []
for batch_idx in range(tensors.size(0)):
batch_edges = []
for frame_idx in range(tensors.size(1)):
edge = get_edge(tensors[batch_idx, frame_idx:frame_idx + 1])
batch_edges.append(edge)
guidances.append(torch.cat(batch_edges, dim=0))
guidances = torch.stack(guidances)
return guidances
def edge_loss(self, output, target):
from utils.edge import get_edge
output_edge = get_edge(output)
gt_edge = get_edge(target)
loss = self.l1_loss(output_edge, gt_edge)
return loss, output_edge, gt_edge