:/

app.py

@@ -1,3 +1,4 @@
+from pipline import Transformer_Regression, extract_regions_Last , compute_ratios
 import torch
 import torchvision.transforms as transforms
 from torch.nn import functional as F
@@ -5,7 +6,6 @@ import cv2
 import gradio as gr
 import numpy as np
 from PIL import Image
-from pipline import Transformer_Regression, extract_regions_Last , compute_ratios
 
 
 device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
@@ -122,7 +122,6 @@ def infer(img):
     # img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
 
     sample_batch = dict()
-
     sample_batch['image_original'] = img
 
     im_retina_pil = Image.fromarray(img)

pipline.py

@@ -1,11 +1,11 @@
 #### This is an implmentation of deeplabv3 plus for retina detection
+from skimage.measure import label, regionprops
 import torch
 import torchvision
 from torch.nn import functional as F
 import torch.nn as nn
 import numpy as np
 import cv2
-from skimage.measure import label, regionprops
 import torch
 from collections import namedtuple