Improve the README for applying and training models.

main
Alex J. Champandard 9 years ago
parent f868514be3
commit b1c054ce9f

@ -19,8 +19,6 @@ The catch? The neural network is hallucinating details based on its training fro
|Python Version| |License Type| |Project Stars|
----
1. Examples & Usage
===================
@ -36,29 +34,37 @@ The default is to use ``--device=cpu``, if you have NVIDIA card setup with CUDA
.. code:: bash
# Run the super-resolution script for one or more images.
# Run the super-resolution script for one image.
python3 enhance.py example.png
# Display output image that has `_enhanced.png` suffix.
open example_enhanced.png
# Also process multiple files with a single run.
python3 enhance.py file1.jpg file2.jpg
# Display output images that were given `_ne4x.png` suffix.
open *_ne4x.png
1.b) Training Super-Resolution
------------------------------
Pre-trained models are provided in the GitHub releases. Training your own is a delicate process that may require you to pick parameters based on your image dataset.
.. code:: bash
rm -f ne4x.pkl.bz2
# Remove the model file as don't want to reload the data to fine-tune it.
rm -f ne4x*.pkl.bz2
python3.4 enhance.py --train --epochs=25 \
--scales=2 --perceptual-layer=conv2_2 \
--generator-block=16 --generator-filters=128 \
--smoothness-weight=1e7 --adversary-weight=0.0
# Pre-train the model using perceptual loss from paper [1] below.
python3.4 enhance.py --train --scales=2 --epochs=50 \
--perceptual-layer=conv2_2 --smoothness-weight=1e7 --adversary-weight=0.0 \
--generator-blocks=4 --generator-filters=64
# Train the model using an adversarial setup based on [4] below.
python3.4 enhance.py --train --scales=2 --epochs=250 \
--perceptual-layer=conv5_2 --smoothness-weight=2e4 --adversary-weight=1e3 \
--generator-start=5 --discriminator-start=0 --adversarial-start=5 \
--discriminator-size=64
python3.4 enhance.py --train --epochs=250 \
--scales=2 --perceptual-layer=conv5_2 \
--smoothness-weight=5e4 --adversary-weight=2e2 \
--generator-start=1 --discriminator-start=0 --adversarial-start=1
.. image:: docs/BankLobby_example.gif

@ -504,7 +504,7 @@ if __name__ == "__main__":
for filename in args.files:
print(filename)
out = enhancer.process(scipy.ndimage.imread(filename, mode='RGB'))
out.save(os.path.splitext(filename)[0]+'_ne%ix-%s.png'%(2**args.scales, args.model))
out.save(os.path.splitext(filename)[0]+'_ne%ix.png'%(2**args.scales))
if args.files:
print(ansi.ENDC)

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