Trying to use different image size to test my trained model
Generally image classification models require input images to be reshaped, because they use fully connected layers to classify features learned by the previous convolutional layers, and shapes must match to make classification. On the other hand, fully connected CNNs only use convolutional layers, so they can work images with any shape.
If your model has fully connected layers, then you should reshape your input images.  If you send your images via network to get predictions, then reshaping images before sending can decrease network load, and response time for big images. If it is not the case I think you simply can reshape them right before you input them to model.