def add_texture_ring( current_img, pattern_step, offset, size, layer, channel ):
if pattern_step >= offset and pattern_step < offset + size:
ring_id = pattern_step - offset
ring_img = ring_masks[ring_id]
target = tfi.T(layer)[:,:,:,channel]
textured = tfi.render_deepdream( target, current_img, iter_n=3, step=1.5, octave_n=4, octave_scale=1.5 )
return tfi.masked_mix( current_img, textured, ring_img )
else:
return current_img
def process_image_step(current_img, zoom, rot, mix_ratio, mix_img, target):
current_img = tfi.affine_zoom(current_img, zoom, rot)
current_img = tfi.mix_images(current_img, mix_img, mix_ratio)
return tfi.render_deepdream(target,
current_img,
iter_n=2,
step=1.5,
octave_n=4,
octave_scale=1.5,
direct_objective=True)
import tfi
import os
import numpy as np
import PIL.Image
import tensorflow as tf
in_name = 'images/nfrac_1400x840.jpg'
out_name = 'images/start_frame_1400x840.jpeg'
img0 = PIL.Image.open(in_name)
img0 = np.float32(img0)
tfi.reset_graph_and_session()
target = tf.square(tfi.T('mixed4c'))
print('Rendering {}'.format(out_name))
test_img = tfi.render_deepdream(target,
img0,
iter_n=20,
step=0.75,
octave_n=4,
octave_scale=1.5)
tfi.savejpeg(test_img, out_name)
delta_rot = 0.1
delta_zoom = 1.05
total_rot += delta_rot
total_zoom *= delta_zoom
current_img = tfi.affine_zoom(current_img, delta_zoom, delta_rot)
r = (fno - start_frame) / (end_frame - start_frame)
mix_amount = 0.99 * (1 - r) + 0.96 * r
current_img = tfi.mix_images(current_img, end_colours, mix_amount)
current_img = tfi.render_deepdream(target,
current_img,
iter_n=2,
step=1.5,
octave_n=4,
octave_scale=1.5,
direct_objective=True)
display_img = current_img
# Fade to black
if (fno > 5400):
fade_r = 1.0 - (fno - 5400) / 45.0
display_img = tfi.mix_images(display_img, complete_fade_img, fade_r)
# Fade in credits
if (fno > 5430):
credit_fade = 1.0 - (fno - 5430) / 15.0
display_img = tfi.mix_images(display_img, credit_img, credit_fade)
img0 = PIL.Image.open(source_img)
img0 = np.float32(img0)
if not os.path.exists('explore_layers'):
os.makedirs('explore_layers')
for layer in test_layers:
num_channels = tfi.T(layer).get_shape()[3]
directory = 'explore_layers/{}'.format(layer)
if not os.path.exists(directory):
os.makedirs(directory)
print('Rendering {}, all {} channels squared'.format(layer, num_channels))
test_img = tfi.render_deepdream(tf.square(tfi.T(layer)),
img0,
iter_n=iterations,
step=2.0,
octave_n=4,
octave_scale=1.5)
tfi.savejpeg(test_img, ('{}/all_channels_squared.jpeg'.format(directory)))
for channel in range(0, num_channels):
print('Rendering {}, channel {}'.format(layer, channel))
test_img = tfi.render_deepdream(tfi.T(layer)[:, :, :, channel],
img0,
iter_n=iterations,
step=2.0,
octave_n=4,
octave_scale=1.5)
tfi.savejpeg(
test_img,
('{}/channel_{}.jpeg'.format(directory, '%03d' % channel)))