torchvision.transforms.ToTensor（細節）對應caffe的轉換

目錄

1）torchvision.transforms.ToTensor

2）pytorch的圖像預處理和caffe中的圖像預處理 

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寫這篇文章的初衷，就是同事跑過來問我，pytorch對圖像的預處理爲什麼和caffe的預處理存在差距，我也是第一次注意到這個問題；

1）torchvision.transforms.ToTensor

直接貼代碼：

第一段代碼：

class ToTensor(object):
    """Convert a ``PIL Image`` or ``numpy.ndarray`` to tensor.

    Converts a PIL Image or numpy.ndarray (H x W x C) in the range
    [0, 255] to a torch.FloatTensor of shape (C x H x W) in the range [0.0, 1.0].
    """

    def __call__(self, pic):
        """
        Args:
            pic (PIL Image or numpy.ndarray): Image to be converted to tensor.

        Returns:
            Tensor: Converted image.
        """
        return F.to_tensor(pic)

    def __repr__(self):
        return self.__class__.__name__ + '()'

第二段代碼： 

def to_tensor(pic):
    """Convert a ``PIL Image`` or ``numpy.ndarray`` to tensor.

    See ``ToTensor`` for more details.

    Args:
        pic (PIL Image or numpy.ndarray): Image to be converted to tensor.

    Returns:
        Tensor: Converted image.
    """
    if not(_is_pil_image(pic) or _is_numpy_image(pic)):
        raise TypeError('pic should be PIL Image or ndarray. Got {}'.format(type(pic)))

    if isinstance(pic, np.ndarray):
        # handle numpy array
        img = torch.from_numpy(pic.transpose((2, 0, 1)))
        # backward compatibility
        if isinstance(img, torch.ByteTensor):
            return img.float().div(255)
        else:
            return img

在第二段代碼中，可以看出圖像進來以後，先進行通道轉換，然後判斷圖像類型，若是uint8類型，就除以255；否則返回原圖。

在使用opencv讀圖時，圖像讀入後的數據類型就是uint8，所以若是自己做實驗，想看看transform後的效果，傳入隨意數據作爲圖片，記得使用方法如下：

im = np.ones([112, 112, 3])#圖像是3*112*112大小，像素值爲1，數據類型float64
im = np.array(im, dtype = np.uint8)#將數據float64轉換成uint8

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2）pytorch的圖像預處理和caffe中的圖像預處理 

在常規使用中，pytorch的圖像預處理：

test_transform = transforms.Compose(
    [transforms.ToTensor(),  # range [0, 255] -> [0.0,1.0]
    transforms.Normalize(mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5))])  # range [0.0, 1.0] -> [-1.0,1.0]

im_tensor = test_transform(im).to(torch.device("cuda:0" if torch.cuda.is_available() else "cpu")).unsqueeze(0)

對應到caffe中的預處理操作：

scale = 0.0078125
mean_value = 127.5

tempimg = (tempimg - mean_value) * scale  # done in imResample function wrapped by python

tempimg = tempimg.transpose(0, 3, 1, 2)

 參考：

https://pytorch-cn.readthedocs.io/zh/latest/package_references/Tensor/

https://blog.csdn.net/bublebee/article/details/88993467