update getting logits

inference_resnet_v2.py

@@ -67,8 +67,9 @@ def inference_resnet_finer_v2(x,model,size=384,n_classes=142,n_top=10):
     # predictions = tf.math.top_k(batch_logits, k=10)
     # print(predictions)
     logits = model.predict(np.array([x]))
+    print(len(logits[0][0]))
     print(logits)
-    logits = tf.nn.softmax(logits[0][0]).cpu().numpy()
+    logits = tf.nn.softmax(logits[1][0]).cpu().numpy()
     print(logits)
     top_n = select_top_n(logits,n=n_top)
     print(top_n)