Update app.py

app.py

@@ -3,6 +3,8 @@ import torch
 from torch import nn
 from pathlib import Path
 
+LABELS = Path('class_names.txt').read_text().splitlines()
+
 model = nn.Sequential(
     nn.Conv2d(1, 32, 3, padding='same'),
     nn.ReLU(),
@@ -22,8 +24,6 @@ state_dict = torch.load('pytorch_model.bin',    map_location='cpu')
 model.load_state_dict(state_dict, strict=False)
 model.eval()
 
-LABELS = Path('class_names.txt').read_text().splitlines()
-
 def predict(img):
     x = torch.tensor(img, dtype=torch.float32).unsqueeze(0).unsqueeze(0) / 255.
     with torch.no_grad():