7258ae72e3835a6f947a983e200d3c7861a6050c,test.py,,test,#Any#Any#Any#,38

Before Change

        with torch.no_grad():
            pred = torch.zeros(1, args.num_class, segSize[0], segSize[1])
            pred = Variable(pred).cuda()

            for img in img_resized_list:
                feed_dict = batch_data.copy()
                feed_dict["img_data"] = img

After Change

                // forward pass
                pred_tmp = segmentation_module(feed_dict, segSize=segSize)
                pred = pred + pred_tmp.cpu() / len(args.imgSize)

            _, preds = torch.max(pred, dim=1)
            preds = as_numpy(preds.squeeze(0))

Instances