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Conveiro (convolutional + oneiro, Greek for "dream") is an open source library for feature visualization in deep convolutional networks. It implements multiple techniques for visualization, such as laplace, multiscale, deep dream and CDFS.
All of these methods are based on:
Deep dream is implementation of technique based on
- https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/tutorials/deepdream/deepdream.ipynb
- https://ai.googleblog.com/2015/06/inceptionism-going-deeper-into-neural.html
How it works:
- We create random image (or we can use seed image)
- We feed this image to network and optimize it based on calculated gradients
- We employ few clever tricks based on scaling and frequencies
There are few more steps but this is the essence of this technique.
CDFS (color-decorrelated fourier space) is custom implementation of technique based on
How it works:
- We generate random complex coefficient
- We use said coefficients to generate image by inverse fourier transformation
- After we feed this image to network we can calculate gradients and use gradient descent to optimize these coefficient
There are few more steps but this is the essence of this technique.
- Python 3.4 and above
- Tensorflow (CPU or GPU variant, version 2 not yet supported)
- Numpy
- Matplotlib
- click, tensornets, pillow, graphviz (if you want to use the command-line tool with examples)
pip install conveiro
Development version
pip install -e . # from cloned repository
This library comes with a command-line tool called conveiro
that can visualize and hallucinate networks from tensornets library.
Usage: conveiro COMMAND [OPTIONS] [ARGS]...
Commands:
graph Create a graph of the network architecture.
layers List available layers (operations) in a network.
networks List available network architectures (from tensornets).
render Hallucinate an image for a layer / neuron.
Run conveiro --help or conveiro [command-name] --help to
show the list of capabilities and options.
For examples how to use this library please take a look at jupyter notebooks in docs/ folder:
- https://github.com/Showmax/conveiro/tree/master/docs/deep_dream.ipynb
- https://github.com/Showmax/conveiro/tree/master/docs/cdfs.ipynb
Simplest example:
import tensorflow as tf
import tensornets as nets
from conveiro import cdfs
input_t, decorrelated_image_t, coeffs_t = cdfs.setup(224)
model = nets.Inception1(input_t)
graph = tf.get_default_graph()
with tf.Session() as sess:
sess.run(model.pretrained())
objective = graph.get_tensor_by_name("inception1/block3b/concat:0")
image = cdfs.render_image(sess, decorrelated_image_t, coeffs_t, objective[..., 55], 0.01)
cdfs.show_image(cdfs.process_image(image))
Note The API is preliminary and may change in future versions.