Update app.py

app.py

@@ -33,10 +33,11 @@ ort_session = ort.InferenceSession("densenet-9.onnx")
 def predict(pil):
     input_tensor = preprocess(pil)
     img_batch = input_tensor.unsqueeze(0) # create a mini-batch as expected by the model
+    img_batch_np = img_batch.cpu().detach().numpy()
 
     outputs = ort_session.run(
         None,
-        {"data_0": img_batch.astype(np.float32)},
+        {"data_0": img_batch_np.astype(np.float32)},
     )
 
     a = np.argsort(-outputs[0].flatten())