How to use binaryproto file in Python

[Daniela G]

Hello,

I'm following this example since I'm trying to test my data with a trained net, using the deploy.prototxt file, in Python.
Since I can't declare the mean.binaryproto file in deploy.prototxt, I need to load it in Python to transform my data.

I tried to use the following code but when I run it, the Spyder IDE crashes.

MEAN_FILE = '../examples/test/mean.binaryproto'

# Open mean.binaryproto file
blob = caffe.proto.caffe_pb2.BlobProto()
data = open(MEAN_FILE , 'rb').read()
blob.ParseFromString(data)
mean_arr = caffe.io.blobproto_to_array(blob)

Is there any other possibility to use the mean file?

Thank you

[SRQ]

Change

mean_arr = caffe.io.blobproto_to_array(blob)

to

mean_arr = np.array(caffe.io.blobproto_to_array(blob))

Maybe this will work.

[Daniela G]

The problem remains :/
It doesn't give me any error message, the IDE just stops working.

[SRQ]

write it in a local editor and manually compile if that is an option.

[Daniela G]

It works through command line. Thank you.
I just don't get why Spyder stops working :/

[Erdem Akagündüz]

Hello,

I know this topic is a bit old but I need help on the same issue. 

I need to convert the attached binaryproto to a MATLAB readable format.

I am not a python/caffe user yet but trying to be one soon. I have an urgency. Would any of you be kind convert the attached binaryproto to a mat file. I think the below code is sufficient.

thanks in advance

Erdem

caffe_root = '/.../'  # this file is expected to be in {caffe_root}/examples

import sys

sys.path.insert(0, caffe_root + 'python')

import caffe

import numpy as np

import sys

if len(sys.argv) != 3:

    print "Usage: python convert_protomean.py proto.mean out.npy"

    sys.exit()

blob = caffe.proto.caffe_pb2.BlobProto()

data = open( '/.../mean.binaryproto', 'rb' ).read()

blob.ParseFromString(data)

arr = np.array( caffe.io.blobproto_to_array(blob) )

out = arr[0]

np.save('/.../mean' , out )     #first,save it to *.npy,then convert it to *.mat

import scipy.io as sio

data=np.load('/.../mean.npy')

sio.savemat('/.../data_mean.mat',{'data':data})