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 channel_order:
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
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:
channel_order_inverse = [channel_order.index(i)