TypeError: Input tensor should be a torch tensor. Got <class 'PIL.Image.Image'>.
时间: 2024-05-05 21:17:00 浏览: 12
This error message indicates that the input to a PyTorch function or model should be a tensor, but instead it received a PIL Image object. To fix this error, you need to convert the PIL Image object to a PyTorch tensor using the `transforms.ToTensor()` function. Here's an example:
```
import torch
from torchvision import transforms
from PIL import Image
# Load the image
img = Image.open('my_image.jpg')
# Define the transform
transform = transforms.Compose([
transforms.Resize((224, 224)),
transforms.ToTensor()
])
# Apply the transform to the image
img_tensor = transform(img)
# Pass the tensor to the PyTorch function or model
output = my_model(img_tensor)
```
相关问题
TypeError: pic should be Tensor or ndarray. Got <class 'PIL.Image.Image'>.
This error occurs when you are trying to pass a PIL Image object to a function or method that expects a Tensor or ndarray object.
To resolve this error, you can convert the PIL Image object to a Tensor or ndarray using the appropriate function. For example, if you are using PyTorch, you can use the torchvision.transforms.ToTensor() function to convert the PIL Image object to a Tensor.
Here is an example code snippet:
```
import torch
import torchvision.transforms as transforms
from PIL import Image
# Load the image using PIL
img = Image.open('image.jpg')
# Convert the image to a Tensor
tensor_img = transforms.ToTensor()(img)
# Pass the Tensor to the function/method that expects it
```
In this example, we first load the image using PIL, then convert it to a Tensor using the ToTensor() function from torchvision.transforms module. We can then pass the Tensor object to the function or method that expects it.
TypeError: pic should be PIL Image or ndarray. Got <class 'torch.Tensor'>
这个错误通常是因为传入的 pic 参数不是 PIL Image 或 ndarray 类型,而是 torch.Tensor 类型。如果要将 torch.Tensor 类型的图片转换为 PIL Image 或 ndarray 类型,可以使用以下代码:
```
from torchvision.transforms.functional import to_pil_image, to_tensor
# 将 tensor 转换为 PIL Image
pil_img = to_pil_image(tensor_img)
# 将 tensor 转换为 ndarray
ndarray_img = tensor_img.cpu().numpy()
```
在这里,我们通过 `to_pil_image()` 将 tensor 转换为 PIL Image,或者通过 `cpu().numpy()` 将 tensor 转换为 ndarray。
需要注意的是,如果 tensor 是在 GPU 上,需要先将其移动到 CPU 上,然后再进行转换。因此,可以在转换之前调用 `cpu()` 方法将其移动到 CPU 上。