从固态硬盘预测的映像ID和盒子 [英] Predicted Image id and box from SSD

问题描述

如何从SSD中找到预测的图像ID和Box，我正在使用GitHub link这里是我想要保存图像ID和Box的测试函数

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

推荐答案

假设

y = net(x)
detections = y.data

您可以使用以下内容打印检测信息

# this will loop over predictions class by class
for i in range(detections.size(1)): 
    # this will loop over each detection in the class
    for j in range(detections.size(2)):
        score = detection[0,i,j,0]
        coords = detections[0,i,j,1:]
        print(f"Class id: {i} 	 Score: {score} 	 Coords: {coords}")

有关详细信息，请参阅demo。

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