After the class introduction to DeepDream, I was quite intrigued by the effects and results that this computer vision program produces. I decided to explore it further by trying different image inputs.
I started out with these images
The parameters are
settings = {
‘features’: {
‘mixed2’: 1.,
‘mixed3’: 1.5.,
‘mixed4’: 1.,
‘mixed5’: 1.5.,
},
}step = 0.01 # Gradient ascent step size
step = 0.01 # Gradient ascent step size
num_octave = 3 # Number of scales at which to run gradient ascent
octave_scale = 3.4 # Size ratio between scales
iterations = 50 # Number of ascent steps per scale
max_loss = 10.
I thought the effect of the night sky star photo was the most interesting. So I continued with that and tuned the parameters to get different output.
The difference between having mixed3 and mixed 5 as the main feature. Mixed5 looked more pleasing. I then changed the iterations:
Difference between 20 iterations and 50
Looking at the overall picture, I think the 20-iteration output looks better. But as I zoom in, 50 iterations produces much more refined details.
