Made in collaboration with Chris George for Art + ML Spring 2019. Course Website: https://kangeunsu.com/artml19s/
layer = ‘mixed4d_3x3_bottleneck_pre_relu’
T(layer)[:,:,:,142] + T(layer)[:,:,:,8]
The code we wrote was only for easily running a photo on a specific layer and every channel in that layer. We modified the render_deapdream function so that it returned the image to be saved into the correct directory.
def render_deepdream(...)
...
return PIL.Image.fromarray(np.uint8(np.clip(img/255.0, 0, 1)*255))
image_name = 'insert_image_path'
layer = 'mixed4d_3x3_bottleneck_pre_relu'
new_file_path = './'+layer+'/'
for i in range(1, 84):
img0 = PIL.Image.open(image_name)
img0 = np.float32(img0)
deep_dream_image = render_deepdream(T(layer)[:,:,:,i], img0)
deep_dream_image.save(new_file_path+str(i)+'.jpeg')
We included two of those tests in this repo. One was for mized4d_3x3_bottleneck_pre_relu and another was for mixed4b_3x3_bottleneck_pre_relu.
We also had some intermediate results before we settled on eyes for our final project. Some of those results can be found in the intermediate results folder.