Prediction with tensorflow keras
This is the problem: model.add(keras.layers.Dense(1, activation='softmax'))

For predicting real-valued data such as age, it is customary to set the activation as linear or in this case, you can probably use relu.

To illustrate, softmax will create a distribution over the output, in this case the output of the model will be always 1. Since the age is positive definite continuous number, you need an activation that has a range of real numbers >= 0 which the relu activation satisfies.


  As another question , are my layers good to predict a number for given picture ?


The architecture seems reasonable so try changing the model's final activation first.