Why does my Keras Conv Net only return 1?
It is only outputting 1 because softmax makes no sense when given a single input. Softmax computed with only one input $x$ is equivalent to $\frac{e^x}{e^x} = 1$.

In other words, the line

model.add(Dense(1, activation='softmax'))


is wrong. Use sigmoid instead:

model.add(Dense(1, activation='sigmoid'))


or read more about one-hot encoding your expected output and the helper function https://keras.io/utils/#to_categorical.