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Small improvements to pycaffe #733

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merged 3 commits into from
Jul 28, 2014
Merged

Small improvements to pycaffe #733

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fc48d5d
pycaffe: allow unspecified mean. Fixes #671.
longjon Jul 18, 2014
32fefa9
pycaffe: reorder exceptions
longjon Jul 18, 2014
fb2f7c1
pycaffe: test channel_order and input_scale against None
longjon Jul 18, 2014
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26 changes: 12 additions & 14 deletions python/caffe/pycaffe.py
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Original file line number Diff line number Diff line change
Expand Up @@ -57,10 +57,10 @@ def _Net_forward(self, blobs=None, **kwargs):
# Set input according to defined shapes and make arrays single and
# C-contiguous as Caffe expects.
for in_, blob in kwargs.iteritems():
if blob.shape[0] != self.blobs[in_].num:
raise Exception('Input is not batch sized')
if blob.ndim != 4:
raise Exception('{} blob is not 4-d'.format(in_))
if blob.shape[0] != self.blobs[in_].num:
raise Exception('Input is not batch sized')
self.blobs[in_].data[...] = blob

self._forward()
Expand Down Expand Up @@ -91,10 +91,10 @@ def _Net_backward(self, diffs=None, **kwargs):
# Set top diffs according to defined shapes and make arrays single and
# C-contiguous as Caffe expects.
for top, diff in kwargs.iteritems():
if diff.shape[0] != self.blobs[top].num:
raise Exception('Diff is not batch sized')
if diff.ndim != 4:
raise Exception('{} diff is not 4-d'.format(top))
if diff.shape[0] != self.blobs[top].num:
raise Exception('Diff is not batch sized')
self.blobs[top].diff[...] = diff

self._backward()
Expand Down Expand Up @@ -259,17 +259,16 @@ def _Net_preprocess(self, input_name, input_):
caffe_in = input_.astype(np.float32)
input_scale = self.input_scale.get(input_name)
channel_order = self.channel_swap.get(input_name)
mean = self.mean.get(input_name)
in_size = self.blobs[input_name].data.shape[2:]
if caffe_in.shape[:2] != in_size:
caffe_in = caffe.io.resize_image(caffe_in, in_size)
if input_scale:
if input_scale is not None:
caffe_in *= input_scale
if channel_order:
if channel_order is not None:
caffe_in = caffe_in[:, :, channel_order]
caffe_in = caffe_in.transpose((2, 0, 1))
if mean is not None:
caffe_in -= mean
if hasattr(self, 'mean'):
caffe_in -= self.mean.get(input_name, 0)
return caffe_in


Expand All @@ -280,15 +279,14 @@ def _Net_deprocess(self, input_name, input_):
decaf_in = input_.copy().squeeze()
input_scale = self.input_scale.get(input_name)
channel_order = self.channel_swap.get(input_name)
mean = self.mean.get(input_name)
if mean is not None:
decaf_in += mean
if hasattr(self, 'mean'):
decaf_in += self.mean.get(input_name, 0)
decaf_in = decaf_in.transpose((1,2,0))
if channel_order:
if channel_order is not None:
channel_order_inverse = [channel_order.index(i)
for i in range(decaf_in.shape[2])]
decaf_in = decaf_in[:, :, channel_order_inverse]
if input_scale:
if input_scale is not None:
decaf_in /= input_scale
return decaf_in

Expand Down