update stuff

app.py

@@ -39,16 +39,13 @@ transform = transforms.Compose([
 
 def predict(image):
     image = image['composite']
-    image = transform(image)
-    print(image)
-
-    x = torch.tensor(im, dtype=torch.float32).unsqueeze(0).unsqueeze(0) / 255.
+    input = transform(image)
+    print(input)
 
     with torch.no_grad():
-        out = model(x)
+        out = model(input)
 
     probabilities = F.softmax(out[0], dim=0)
-
     values, indices = torch.topk(probabilities, 5)
 
     return {LABELS[i]: v.item() for i, v in zip(indices, values)}