Question

如何导出caffemodel参数

Answer 1

import scipy.io as sio
import caffe

def load():
# Load the net
caffe.set_mode_cpu()
# You may need to train this caffemodel first
# There should be script to help you do the training
net = caffe.Net(root + 'lenet.prototxt', root + 'lenet_iter_10000.caffemodel',\
caffe.TEST)
conv1_w = net.params['conv1'][0].data
conv1_b = net.params['conv1'][1].data
conv2_w = net.params['conv2'][0].data
conv2_b = net.params['conv2'][1].data
ip1_w = net.params['ip1'][0].data
ip1_b = net.params['ip1'][1].data
ip2_w = net.params['ip2'][0].data
ip2_b = net.params['ip2'][1].data
sio.savemat('conv1_w', {'conv1_w':conv1_w})
sio.savemat('conv1_b', {'conv1_b':conv1_b})
sio.savemat('conv2_w', {'conv2_w':conv2_w})
sio.savemat('conv2_b', {'conv2_b':conv2_b})
sio.savemat('ip1_w', {'ip1_w':ip1_w})
sio.savemat('ip1_b', {'ip1_b':ip1_b})
sio.savemat('ip2_w', {'ip2_w':ip2_w})
sio.savemat('ip2_b', {'ip2_b':ip2_b})

if __name__ == "__main__":
# You will need to change this path
root = '/Users/yuliangzou/caffe-rc3/examples/mnist/'
load()
print 'Caffemodel loaded and written to .mat files successfully!'

从代码里可以看得很清楚啦，首先导入模型，然后利用net.params就可以获取参数了，另外你也可以利用net.data导出数据进行可视化。当然，在导出参数之前…你必须要跑过一遍，不然你没有这个caffemodel…