local binary pattern transform - pytorch

Question

Here is my local binary pattern function:
def lbp(x):
imgUMat = np.float32(x)
gray = cv2.cvtColor(imgUMat, cv2.COLOR_RGB2GRAY)
radius = 2
n_points = 8 * radius
METHOD = 'uniform'
lbp = local_binary_pattern(gray, n_points, radius, METHOD)
lbp = torch.from_numpy(lbp).long()
return lbp
Here I call lbp function:
input_img = plt.imread(trn_fnames[31])
x = lbp(input_img)
When I use x.shape it is:
torch.Size([600, 600])
Sounds good!!!
But my problem is when I use transforms.Lambda(lbp) in my transform function, my output image is torch.Size([600])
tfms = transforms.Compose([
transforms.Lambda(lbp)])
train_ds = datasets.ImageFolder(trn_dir, transform = tfms)
(train_ds[0][0][0]).shape
torch.Size([600])!!! >>>> my problem
I need torch.Size([600, 600])
I also different ways such as this:
tfms = transforms.Compose([
transforms.Lambda(lbp),
transforms.ToPILImage(),
transforms.Resize((sz, sz))])
And I got this error:
TypeError: pic should be Tensor or ndarray. Got <class ‘torch.Tensor’>.
I also added
transforms.ToTensor()])
But still have the same error:
TypeError: pic should be Tensor or ndarray. Got <class ‘torch.Tensor’>.
I’ll appreciate to your comments please!
Thank you.

Answer 1

def lbp_transform(x):
radius = 2
n_points = 8 * radius
METHOD = 'uniform'
imgUMat = np.float32(x)
gray = cv2.cvtColor(imgUMat, cv2.COLOR_RGB2GRAY)
lbp = local_binary_pattern(gray, n_points, radius, METHOD)
lbp = torch.from_numpy(lbp).float()
return lbp
x = np.random.randn(600, 600, 3)
out = lbp_transform(x)
print(out.shape)
> torch.Size([600, 600])
tfms = transforms.Compose([
transforms.Lambda(lbp_transform),
transforms.ToPILImage(),
transforms.Resize((300, 300)),
transforms.ToTensor()
])
out = tfms(x)
print(out.shape)
> torch.Size([1, 300, 300])