Combining multiple probabilities from a classifier. Propagating probabilities

Let’s say I have trained a classifier that classifies images of animals into 10 different classes. And let’s say that I have 20 different images of a particular animal and because I know the photographer, I know with certainty that all 20 images are of the same animal. So I use my classifier to make a prediction on what animal it is and get 20 predictions one for each image. The model predicts all the images to be a dog with varying probabilities.
image 1: 80% dog
image 2: 90% dog
image 3: 75% dog
and so on.
What is the probability that the animal in question is a dog?
Let’s say they predict cat with smaller probabilities, 5%, 2%, 4% … What is the probability it is a cat?

I’ve tried a few different approaches, applying Bayes Theorem but I keep getting numbers that add up to be more than one. Could it really be just the average?

[[0.0, 0.9, 0.0, 0.0, 0.0, 0.1, 0.0, 0.0, 0.0, 0.0],
 [0.0, 0.8, 0.0, 0.0, 0.0, 0.1, 0.0, 0.1, 0.0, 0.0],
 ..,
 [0.0, 0.75, 0.0, 0.0, 0.0, 0.1, 0.0, 0.1, 0.05, 0.0]]