Deep learning 从SSD预测的图像id和框

如何从SSD中找到预测的图像id和框，我在这里使用的是测试功能，我想保存图像id和框

def test(loader, net, criterion, device):
net.eval()
running_loss = 0.0
running_regression_loss = 0.0
running_classification_loss = 0.0
num = 0
for _, data in enumerate(loader):
images, boxes, labels = data
images = images.to(device)
boxes = boxes.to(device)
labels = labels.to(device)
num += 1

    with torch.no_grad():
        confidence, locations = net(images)
        regression_loss, classification_loss = criterion(confidence, locations, labels, boxes)
        loss = regression_loss + classification_loss

    running_loss += loss.item()
    running_regression_loss += regression_loss.item()
    running_classification_loss += classification_loss.item()
return running_loss / num, running_regression_loss / num, run

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只要检查一下你从net（images）函数中得到的变量“confidence and locations”就可以了。我打印了它们，但它们没有提供预测图像的id