artvandelay / deep_inside_convolutional_networks Goto Github PK

Hi,
I am using it for a multi-task model.
I am using a customized alexnet for a multi-task model for aesthetics prediction and classification. I have a normalized score ( 0 to 1 ) for aesthetics prediction and a single label for classification. I want to check which areas are more salient for aesthetics. After doing
net.forward()
I am setting
net.blobs['aesthetics'].data[0][0] = 1
Then I am running
bw = net.backward()
But I am getting only zero values as input image.
I have set
force_backward: true in my model prototxt file.
I think I am messing up the backward function, let me know if you have any idea about how to use it for regression problems.

hi,
I am trying to use your code for the same purpose. But there is a error in bw=net.backward(**{net.outputs[0]: caffeLabel})
ValueError: could not broadcast input array from shape(1000,1,1) into shape (1,1000).
Can you tell me the reason. Thank you. Looking forward to your reply.

When i run the visualize.py code, i got the above error as follows:-

Traceback (most recent call last):
File "visualize.py", line 69, in
bw = net.backward(**{net.outputs[0]: caffeLabel})
File "../python/caffe/pycaffe.py", line 167, in _Net_backward
self.blobs[top].diff[...] = diff
ValueError: could not broadcast input array from shape (1000,1,1) into shape (1,1000)

and when i change the net.backward line as: bw = net.backward(), it runs perfectly.
please tell me what is the problem??

Traceback (most recent call last):
File "class_saliency_extraction.py", line 25, in
image_dims=(224, 224))
File "D:/Projects/caffe-windows/caffe/python\caffe\classifier.py", line 29, in init
in_ = self.inputs[0]
IndexError: list index out of range

In visualize.py file,
I see the learning_rate is 10000,it confused me!why doing this,
also,In the optimization procedure,The sentence "caffe_data = caffe_data + learning_rate*diff " seems not used any L2 Paradigm，but in the paper, It is not like this!
thanks a lot!