python - Pytorch运行时错误: The size of tensor a (4) must match the size of tensor b (3) at non-singleton dimension 0

Question

我使用 here 中的代码训练模型来预测从 0 到 9 的打印样式编号:

idx_to_class = {0: "0", 1: "1", 2: "2", 3: "3", 4: "4", 5: "5", 6: "6", 7:"7", 8: "8", 9:"9"}

def predict(model, test_image_name):
    transform = image_transforms['test']
    test_image = Image.open(test_image_name)
    plt.imshow(test_image)
    test_image_tensor = transform(test_image)
    if torch.cuda.is_available():
        test_image_tensor = test_image_tensor.view(1, 3, 224, 224).cuda()
    else:
        test_image_tensor = test_image_tensor.view(1, 3, 224, 224)
    with torch.no_grad():
        model.eval()
        # Model outputs log probabilities
        out = model(test_image_tensor)
        ps = torch.exp(out)
        topk, topclass = ps.topk(1, dim=1)
        # print(topclass.cpu().numpy()[0][0])
        print("Image class:  ", idx_to_class[topclass.cpu().numpy()[0][0]])
predict(model, "path_of_test_image")

但是当我尝试使用预测时出现错误:

Traceback (most recent call last):

  File "<ipython-input-12-f8636d3ba083>", line 26, in <module>
    predict(model, "/home/x/文档/Deep_Learning/pytorch/MNIST/test/2/QQ截图20191022093955.png")

  File "<ipython-input-12-f8636d3ba083>", line 9, in predict
    test_image_tensor = transform(test_image)

  File "/home/x/.local/lib/python3.6/site-packages/torchvision/transforms/transforms.py", line 61, in __call__
    img = t(img)

  File "/home/x/.local/lib/python3.6/site-packages/torchvision/transforms/transforms.py", line 166, in __call__
    return F.normalize(tensor, self.mean, self.std, self.inplace)

  File "/home/x/.local/lib/python3.6/site-packages/torchvision/transforms/functional.py", line 217, in normalize
    tensor.sub_(mean[:, None, None]).div_(std[:, None, None])

RuntimeError: The size of tensor a (4) must match the size of tensor b (3) at non-singleton dimension 0

我该如何解决这个问题？谢谢。

Answer 1

我怀疑您的 test_image 每个像素都有一个额外的 Alpha channel ，因此它有 4 个 channel ，而不是只有 3 个。
尝试:

test_image = Image.open(test_image_name).convert('RGB')