def preprocess(self, im):
mean = torch.Tensor([0.485, 0.456, 0.406])
std = torch.Tensor([0.229, 0.224, 0.225])
im = np.asarray(im)
im = t.normalize(im, mean, std)
im = np.transpose(im, (2, 0, 1))
return im
def preprocess(self, im):
mean = torch.DoubleTensor([0.485, 0.456, 0.406])
std = torch.DoubleTensor([0.229, 0.224, 0.225])
# print("mean data type : ", mean.dtype)
im = np.asarray(im)
im = t.normalize(im, mean, std)
im = np.transpose(im, (2, 0, 1))
return im
def preprocess(self, im):
mean = np.array([0.485, 0.456, 0.406])
std = np.array([0.229, 0.224, 0.225])
im = np.asarray(im)
# normalize
im = t.normalize(im, mean, std)
# (width, height, channel) to (channel, width, height)
im = np.transpose(im, (2, 0, 1))
return im