David Icke would get better accuracy than that.

My university background is in Machine Learning. Sounds like this person did not understand ML. Was he new at this? You should learn about false positives, false negatives and plotting ROC curves from the first experiments with simple artificial random point cloud datasets (toy problems) before you even bother stepping up to image recognition.

When a ML researcher gets a 100% accuracy rate, they go look for the bug in their program, not think "oh awesome, it must be very good then"--it's a bit of an embarassing mistake if it turns out it's because your training set only contains examples for one of your two classes ("has a lizard" vs "does not have a lizard").