Keras Model question for Pre trained model extension
Short answer - Yes.

The pretrained Resnet model has trained parameters (weights and biases). When you add extra layers on top of it, the parameters of these layers are randomly initialized. Therefore the final model will give random results.

You need to train the new model after adding extra layers on your new dataset. You don't need to train all the previous layers, just few of them.

For further reading search for - transfer learning. That's what you're trying to do.