#####################Function############################
def printImage(img):
img = img.detach().cpu()
img = torchvision.utils.make_grid(img)
img = np.transpose(img, (1, 2, 0))
img = img * 0.5 + 0.5
plt.imshow(img)
plt.show()
#################Hyper Parameter#########################
img_path = 'C:/Datasets/OverfittingTest'
fname = '1803151818-00000048.jpg'
fname2 = '1803151818-00000048.png'
#net = testNet.BasicNet()
net = testNet.TestNet_Pool()
#####################Etc#################################
device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
transform = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))
])
transform = transforms.Compose(
[transforms.ToTensor(),
transforms.Normalize((0.5, ), (0.5, ))])
l1_loss = nn.L1Loss()
if __name__ == '__main__':
img = Image.open(os.path.join(img_path, fname))
img = img.resize((256, 256))
gt = Image.open((os.path.join(img_path, fname2))).resize(
(256, 256)) #img.copy()
