goal: use deepdream flowers

Use a deep neural network trained to identify objects in images (The
ImageNet Challenge).

Some layers in that network are tuned to recognize flowers as these were
categories to classify in ImageNet.

- Start with a random image.

- How would the network update the image to make it more compatible
with the flower layer in the network?

- Push the image with those small updates.

- Iterate 20 times. Show the resulting image!

Use this tutorial
https://github.com/tensorflow/tensorflow/tree/r0.8/tensorflow/examples/tutorials/deepdream

Try on some images:

img0 = PIL.Image.open('IMG_2993.JPG')
img0 = np.float32(img0)
render_deepdream(T(layer)[:,:,:,139], img0)


img0 = PIL.Image.open('IMG_0791.JPG')
img0 = np.float32(img0)
render_deepdream(T(layer)[:,:,:,139], img0)


img0 = PIL.Image.open('IMG_3000rgb.JPG')
img0 = np.float32(img0)
render_deepdream(T(layer)[:,:,:,139], img0)



Cool! You can apply to any image. You can train a network on objects
you care about.

Here's what it get when started with an image of simple noise: