How to know the probability of correctness of a test data in a Binary Classifier
Accuracy is a statistic that you can compute on a dataset if you know the true labels. For a single image, the accuracy is either 0% or 100% based on if you get it right or wrong.

In the newer versions of Keras, the predict method returns the probabilities of the classes, what you want to print is (if I guess correctly), the probability score for the best scoring class.

Not that this is not an unbiased estimate of the class probability. Neural classifiers tend to very confident even if their prediction is incorrect.