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do some minor formatting to apply PEP8 #18

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do some minor formatting to apply PEP8 #18

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32 changes: 16 additions & 16 deletions deepdreamer/deepdreamer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,20 +23,20 @@

def _select_network(netname):
if netname == 'bvlc_googlenet':
NET_FN = "deploy.prototxt" # Make sure force_backward: true
PARAM_FN = "bvlc_googlenet.caffemodel"
CHANNEL_SWAP = (2, 1, 0)
net_fn = "deploy.prototxt" # Make sure force_backward: true
param_fn = "bvlc_googlenet.caffemodel"
channel_swap = (2, 1, 0)
# ImageNet mean, training set dependent
CAFFE_MEAN = np.float32([104.0, 116.0, 122.0])
return NET_FN, PARAM_FN, CHANNEL_SWAP, CAFFE_MEAN
caffe_mean = np.float32([104.0, 116.0, 122.0])
return net_fn, param_fn, channel_swap, caffe_mean
elif netname == 'googlenet_place205':
# TODO: refit SWAP and MEAN for places205? These work for now.
NET_FN = "deploy_places205.protxt" # Make sure force_backward: true
PARAM_FN = "googlelet_places205_train_iter_2400000.caffemodel"
CHANNEL_SWAP = (2, 1, 0)
net_fn = "deploy_places205.protxt" # Make sure force_backward: true
param_fn = "googlelet_places205_train_iter_2400000.caffemodel"
channel_swap = (2, 1, 0)
# ImageNet mean, training set dependent
CAFFE_MEAN = np.float32([104.0, 116.0, 122.0])
return NET_FN, PARAM_FN, CHANNEL_SWAP, CAFFE_MEAN
caffe_mean = np.float32([104.0, 116.0, 122.0])
return net_fn, param_fn, channel_swap, caffe_mean
else:
print("Error: network {} not implemented".format(netname))

Expand Down Expand Up @@ -138,9 +138,9 @@ def _create_video(video, frame_rate=24):

def list_layers(network="bvlc_googlenet"):
# Load DNN model
NET_FN, PARAM_FN, CHANNEL_SWAP, CAFFE_MEAN = _select_network(network)
net_fn, param_fn, channel_swap, caffe_mean = _select_network(network)
net = Classifier(
NET_FN, PARAM_FN, mean=CAFFE_MEAN, channel_swap=CHANNEL_SWAP)
net_fn, param_fn, mean=caffe_mean, channel_swap=channel_swap)
net.blobs.keys()


Expand All @@ -159,9 +159,9 @@ def deepdream(
set_mode_gpu()

# Select, load DNN model
NET_FN, PARAM_FN, CHANNEL_SWAP, CAFFE_MEAN = _select_network(network)
net_fn, param_fn, channel_swap, caffe_mean = _select_network(network)
net = Classifier(
NET_FN, PARAM_FN, mean=CAFFE_MEAN, channel_swap=CHANNEL_SWAP)
net_fn, param_fn, mean=caffe_mean, channel_swap=channel_swap)

img_pool = [img_path]

Expand Down Expand Up @@ -205,9 +205,9 @@ def deepdream_video(
frame_rate=24):

# Select, load DNN model
NET_FN, PARAM_FN, CHANNEL_SWAP, CAFFE_MEAN = _select_network(network)
net_fn, param_fn, channel_swap, caffe_mean = _select_network(network)
net = Classifier(
NET_FN, PARAM_FN, mean=CAFFE_MEAN, channel_swap=CHANNEL_SWAP)
net_fn, param_fn, mean=caffe_mean, channel_swap=channel_swap)

print("Extracting video...")
_extract_video(video)
Expand Down