Horizontal Flip throws error

I’m using transforms.RandomHorizontalFlip for data augmentation. However it throws the following error.

  File "/home/usr/Courses/Projects/Iceberg_id/load_data.py", line 129, in __getitem__
    imgs = self.transform(imgs)

  File "/home/usr/anaconda3/lib/python3.6/site-packages/torchvision-0.1.9-py3.6.egg/torchvision/transforms.py", line 34, in __call__
    img = t(img)

  File "/home/usr/anaconda3/lib/python3.6/site-packages/torchvision-0.1.9-py3.6.egg/torchvision/transforms.py", line 326, in __call__
    return img.transpose(Image.FLIP_LEFT_RIGHT)

  TypeError: transpose received an invalid combination of arguments - got (int), but expected (int dim0, int dim1)

My Transform is is follows:

    txfm = transforms.Compose([Resize((80,80)), ToTensor(),\

Here Resize and ToTensor were defined by me, the other two are from transforms library.

These transforms are implemented as follows:

class req_data(Dataset):
    Creates the dataset for the data
    initiates the __len__ and __getitem__
    def __init__(self,images,labels, transform = None):
        self.images = images
        self.labels = labels
        self.transform = transform
    def __len__(self):
        return len(self.labels)
    def __getitem__(self,indx):
        imgs = self.images[indx]
        labls = self.labels[indx]
        if self.transform:
            imgs = self.transform(imgs)
        return (imgs,labls)

# Create the transforms

class Resize(object):
    Inputs: a tuple of the form (h,w)
    Returns: a resized image of the given dimensions
    def __init__(self,output_size):
        self.output_size = output_size
    def __call__(self,inpt):
        image = inpt
        new_h, new_w = self.output_size
        image = image.transpose((1,2,0))
        image = transform.resize(image,self.output_size)
        image = image.transpose((2,0,1))
        return image

class ToTensor(object):
    '''Convert ndarrays in sample to Tensors
        We don't need to make a tensor out of labels
        as it is only 1 dim array

    def __call__(self, inpt):

        image = inpt
        return torch.from_numpy(image).float()

The transform in transform.resize(image,self.output_size) is from skimage, not PyTorch.

My PyTorch is installed from source.

Could someone please help me out?

HorizontalFlip works on images. You should put it before ToTensor. The error message is from pytorch’s transpose. The code intended to call numpy/PIL transpose by doing img.trasnpose

1 Like

Thanks, it’s working now.

I had one more question though. It seems that my transforms library doesn’t have RandomVerticalFlip and a few other transforms. However I had built PyTorch from source just a few weeks back. Do I need to build from source again?

They are under torchvision module, which is separate from pytorch. Your torchvision seems to be on 0.1.9. If you update to latest, i.e. 0.2.0, I believe you will be able to use those.

Oh, I didn’t know they were separate. How do I update only the torchvision module?

Ok, building torchvision directly from source worked for this. Had to manually extract the .egg zip file though. Also, updating to torchvision-0.2.0 seemed to solve the above error as well.

Say I have signal data and I want to flip that signal, how do you suggest I do that? also adding noise on the on the fly. how to do that in pytorch?