TypeError: pic should be PIL Image or ndarray. Got <class 'torch.Tensor'>
时间: 2023-06-12 18:02:00 浏览: 55
这个错误表示您传递给代码的“pic”变量是一个torch.Tensor对象,但是您的代码需要一个PIL图像或一个ndarray数组。您可以将torch Tensor转换为PIL图像或ndarray数组,以便您的代码能够正确处理它。您可以使用Pillow软件包将torch Tensor转换为PIL图像,或使用numpy将其转换为ndarray数组。
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.
small_image_tensor = torchvision.transforms.functional.to_tensor(small_image) TypeError: pic should be PIL Image or ndarray. Got <class 'NoneType'>
这个错误提示意味着 `small_image` 变量是一个空值(`NoneType`),无法被转换为张量。你可以检查一下代码中 `small_image` 变量的来源,确保它指向了一个可用的图像文件或图像数据。
通常情况下,可以使用 `PIL` 库加载图像,并将其转换为张量。你可以尝试使用以下代码加载图像,并将其转换为张量:
```
import torch
import torchvision.transforms as transforms
from PIL import Image
# 加载图像
small_image = Image.open('path/to/image.jpg')
# 转换为张量
transform = transforms.Compose([
transforms.Resize((224, 224)),
transforms.ToTensor()
])
small_image_tensor = transform(small_image)
```
在这里,我们使用 `Image.open` 方法加载图像,并使用 `transforms.Compose` 方法创建一个转换函数,其中包括将图像大小调整为 `(224, 224)` 并将图像转换为张量。最后,我们可以使用转换函数将图像转换为张量 `small_image_tensor`。如果你的图像不是 `.jpg` 格式,可以相应地更改文件扩展名。