add local normalization

app.py

@@ -35,6 +35,7 @@ def predict(input_image, model_name):
     pil_image = Image.fromarray(input_image.astype('uint8'), 'RGB')
     # transform image to torch and do preprocessing
     torch_img = preprocess(pil_image).to(DEVICE).unsqueeze(0).to(DEVICE)
+    torch_img = (torch_img - torch.min(torch_img)) / (torch.max(torch_img) - torch.min(torch_img))
     # model predict
     with torch.no_grad():
         output = generators[MODELS_TYPE.index(model_name)](torch_img)

test.py

@@ -40,6 +40,7 @@ preprocess = transforms.Compose([
 ])
 input_img = Image.open('demo_imgs/fake.jpg')
 torch_img = preprocess(input_img).to(DEVICE).unsqueeze(0).to(DEVICE)
+torch_img = (torch_img - torch.min(torch_img)) / (torch.max(torch_img) - torch.min(torch_img))
 with torch.no_grad():
     output = generator(torch_img)
 sr, sr_dem_selected = output[0], output[1]