d95f630a7b7f88621bc4abb4ac92692647f03781,main.py,,validate,#,270

Before Change

        output = model(input_var)
        flow2_EPE = args.div_flow*realEPE(output, target_var, sparse=args.sparse)
        // record EPE
        flow2_EPEs.update(flow2_EPE.data[0], target.size(0))

        // measure elapsed time
        batch_time.update(time.time() - end)

After Change

            if epoch == 0:
                mean_values = torch.tensor([0.411,0.432,0.45], dtype=input.dtype).view(3,1,1)
                output_writers[i].add_image("GroundTruth", flow2rgb(args.div_flow * target[0], max_value=10), 0)
                output_writers[i].add_image("Inputs", (input[0,:3].cpu() + mean_values).clamp(0,1), 0)
                output_writers[i].add_image("Inputs", (input[0,3:].cpu() + mean_values).clamp(0,1), 1)
            output_writers[i].add_image("FlowNet Outputs", flow2rgb(args.div_flow * output[0], max_value=10), epoch)

Instances