Update app.py

app.py

@@ -44,15 +44,11 @@ def initialize_model(model_file):
     return transform,ort_session 
 
 def get_text(img_org):
-    # img_org = Image.open(image_path)
-    # Preprocess. Model expects a batch of images with shape: (B, C, H, W)
     x = transform(img_org.convert('RGB')).unsqueeze(0)
-
-    # compute ONNX Runtime output prediction
     ort_inputs = {ort_session.get_inputs()[0].name: to_numpy(x)}
     logits = ort_session.run(None, ort_inputs)[0]
     probs = torch.tensor(logits).softmax(-1)
-    preds, probs = tokenizer_base.decode(probs)
+    preds, _ = tokenizer_base.decode(probs)
     preds = preds[0]
     print(preds)
     return preds