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Prepare build scripts for merge and update README.

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Alex J. Champandard
2016-11-10 17:20:20 +01:00
parent b706599cb1
commit 80d7b57bec
3 changed files with 8 additions and 8 deletions
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README.rst
+4 -4
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@@ -65,7 +65,7 @@ Pre-trained models are provided in the GitHub releases. Training your own is a
.. code:: bash
# Remove the model file as don't want to reload the data to fine-tune it.
rm -f ne4x*.pkl.bz2
rm -f ne?x*.pkl.bz2
# Pre-train the model using perceptual loss from paper [1] below.
python3.4 enhance.py --train "data/*.jpg" --model custom --scales=2 --epochs=50 \
@@ -79,7 +79,7 @@ Pre-trained models are provided in the GitHub releases. Training your own is a
--discriminator-size=64
# The newly trained model is output into this file...
ls ne4x-custom-*.pkl.bz2
ls ne?x-custom-*.pkl.bz2
.. image:: docs/BankLobby_example.gif
@@ -109,14 +109,14 @@ Here's the simplest way you can call the script using ``docker``, assuming you'r
alias enhance='function ne() { docker run --rm -v "$(pwd)/`dirname ${@:$#}`":/ne/input -it alexjc/neural-enhance ${@:1:$#-1} "input/`basename ${@:$#}`"; }; ne'
# Now run any of the examples above using this alias, without the `.py` extension.
enhance --zoom=1 --model=small images/example.jpg
enhance --zoom=1 --model=repair images/broken.jpg
**Multiple Images** — To enhance multiple images in a row (faster) from a folder or widlcard specification, make sure to quote the argument to the alias command:
.. code:: bash
# Process multiple images, make sure to quote the argument!
enhance --zoom=2 --model=small "images/*.jpg"
enhance --zoom=2 "images/*.jpg"
If you want to run on your NVIDIA GPU, you can instead change the alias to use the image ``alexjc/neural-enhance:gpu`` which comes with CUDA and CUDNN pre-installed. Then run it within `nvidia-docker <https://github.com/NVIDIA/nvidia-docker>`_ and it should use your physical hardware!
docker-cpu.df
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@@ -26,8 +26,8 @@ RUN /opt/conda/bin/python3.5 -m pip install -q -r "requirements.txt"
COPY enhance.py .
# Get a pre-trained neural networks, non-commercial & attribution.
RUN wget -q "https://github.com/alexjc/neural-enhance/releases/download/v0.2/ne1x-small-0.2.pkl.bz2"
RUN wget -q "https://github.com/alexjc/neural-enhance/releases/download/v0.2/ne2x-small-0.2.pkl.bz2"
RUN wget -q "https://github.com/alexjc/neural-enhance/releases/download/v0.3/ne1x-photo-repair-0.3.pkl.bz2"
RUN wget -q "https://github.com/alexjc/neural-enhance/releases/download/v0.3/ne2x-photo-default-0.3.pkl.bz2"
# Set an entrypoint to the main enhance.py script
ENTRYPOINT ["/opt/conda/bin/python3.5", "enhance.py", "--device=cpu"]
docker-gpu.df
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@@ -24,8 +24,8 @@ RUN /opt/conda/bin/python3.5 -m pip install -q -r "requirements.txt"
COPY enhance.py .
# Get a pre-trained neural networks, non-commercial & attribution.
RUN wget -q "https://github.com/alexjc/neural-enhance/releases/download/v0.2/ne1x-small-0.2.pkl.bz2"
RUN wget -q "https://github.com/alexjc/neural-enhance/releases/download/v0.2/ne2x-small-0.2.pkl.bz2"
RUN wget -q "https://github.com/alexjc/neural-enhance/releases/download/v0.3/ne1x-photo-repair-0.3.pkl.bz2"
RUN wget -q "https://github.com/alexjc/neural-enhance/releases/download/v0.3/ne2x-photo-default-0.3.pkl.bz2"
# Set an entrypoint to the main enhance.py script
ENTRYPOINT ["/opt/conda/bin/python3.5", "enhance.py", "--device=gpu"]