fanwuyang/neural-enhance-super-resolution
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Fix formatting, minor tweaks to Docker build files for release.

Browse Source
This commit is contained in:
Alex J. Champandard
2016-11-03 22:27:28 +01:00
parent 448e7b93dc
commit 03914db364
3 changed files with 9 additions and 9 deletions
Download Patch File Download Diff File Expand all files Collapse all files
docker-cpu.df
+2 -3
View File
@@ -26,9 +26,8 @@ RUN /opt/conda/bin/python3.5 -m pip install -q -r "requirements.txt"
COPY enhance.py . COPY enhance.py .
# Get a pre-trained neural networks, non-commercial & attribution. # Get a pre-trained neural networks, non-commercial & attribution.
RUN wget -q "https://github.com/alexjc/neural-enhance/releases/download/v0.1/ne4x-small-0.1.pkl.bz2" 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/v0.1/ne4x-medium-0.1.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/v0.1/ne4x-large-0.1.pkl.bz2"
# Set an entrypoint to the main enhance.py script # Set an entrypoint to the main enhance.py script
ENTRYPOINT ["/opt/conda/bin/python3.5", "enhance.py", "--device=cpu"] ENTRYPOINT ["/opt/conda/bin/python3.5", "enhance.py", "--device=cpu"]
docker-gpu.df
+2 -3
View File
@@ -24,9 +24,8 @@ RUN /opt/conda/bin/python3.5 -m pip install -q -r "requirements.txt"
COPY enhance.py . COPY enhance.py .
# Get a pre-trained neural networks, non-commercial & attribution. # Get a pre-trained neural networks, non-commercial & attribution.
RUN wget -q "https://github.com/alexjc/neural-enhance/releases/download/v0.1/ne4x-small-0.1.pkl.bz2" 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/v0.1/ne4x-medium-0.1.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/v0.1/ne4x-large-0.1.pkl.bz2"
# Set an entrypoint to the main enhance.py script # Set an entrypoint to the main enhance.py script
ENTRYPOINT ["/opt/conda/bin/python3.5", "enhance.py", "--device=gpu"] ENTRYPOINT ["/opt/conda/bin/python3.5", "enhance.py", "--device=gpu"]
enhance.py
+5 -3
View File
@@ -180,7 +180,8 @@ class DataLoader(threading.Thread):
seed = PIL.Image.open(buffer) seed = PIL.Image.open(buffer)
seed = scipy.misc.fromimage(seed, mode='RGB').astype(np.float32) seed = scipy.misc.fromimage(seed, mode='RGB').astype(np.float32)
seed += scipy.random.normal(scale=args.train_noise, size=(seed.shape[0], seed.shape[1], 1)) if args.train_noise else 0.0 seed += scipy.random.normal(scale=args.train_noise, size=(seed.shape[0], seed.shape[1], 1))\
if args.train_noise else 0.0
orig = scipy.misc.fromimage(orig).astype(np.float32) orig = scipy.misc.fromimage(orig).astype(np.float32)
@@ -441,7 +442,7 @@ class Model(object):
# Helper function for rendering test images during training, or standalone inference mode. # Helper function for rendering test images during training, or standalone inference mode.
input_tensor, seed_tensor = T.tensor4(), T.tensor4() input_tensor, seed_tensor = T.tensor4(), T.tensor4()
input_layers = {self.network['img']: input_tensor, self.network['seed']: seed_tensor} input_layers = {self.network['img']: input_tensor, self.network['seed']: seed_tensor}
output = lasagne.layers.get_output([self.network[k] for k in ['seed', 'out']], input_layers, deterministic=True) output = lasagne.layers.get_output([self.network[k] for k in ['seed','out']], input_layers, deterministic=True)
self.predict = theano.function([seed_tensor], output) self.predict = theano.function([seed_tensor], output)
if not args.train: return if not args.train: return
@@ -541,7 +542,8 @@ class NeuralEnhancer(object):
print(' - generator {}'.format(' '.join(gen_info))) print(' - generator {}'.format(' '.join(gen_info)))
real, fake = stats[:args.batch_size], stats[args.batch_size:] real, fake = stats[:args.batch_size], stats[args.batch_size:]
print(' - discriminator', real.mean(), len(np.where(real > 0.5)[0]), fake.mean(), len(np.where(fake < -0.5)[0])) print(' - discriminator', real.mean(), len(np.where(real > 0.5)[0]),
fake.mean(), len(np.where(fake < -0.5)[0]))
if epoch == args.adversarial_start-1: if epoch == args.adversarial_start-1:
print(' - generator now optimizing against discriminator.') print(' - generator now optimizing against discriminator.')
self.model.adversary_weight.set_value(args.adversary_weight) self.model.adversary_weight.set_value(args.adversary_weight)