Update app.py

app.py

@@ -7,26 +7,6 @@ import torch
 learn = load_learner('export.pkl')
 
 # Definimos todo lo necesario para hacer inferencia
-class TargetMaskConvertTransform(ItemTransform):
-    def __init__(self): 
-        pass
-    def encodes(self, x):
-        img,mask = x
-        
-        #Convert to array
-        mask = np.array(mask)
-        
-        # background = 0, leaves = 1, pole = 74 o 76, wood = 25 o 29, grape = 255
-        mask[mask == 255] = 1 # grape
-        mask[mask == 150] = 2 # leaves
-        mask[mask == 76] = 3 ; mask[mask == 74] = 3 # pole
-        mask[mask == 29] = 4 ; mask[mask == 25] = 4 # wood
-        mask[mask >= 5] = 0 # resto: background
-        
-        # Back to PILMask
-        mask = PILMask.create(mask)
-        return img, mask
-
 def transform_image(image, device):
     my_transforms = transforms.Compose([transforms.ToTensor(),
                                         transforms.Normalize(