caffe_functions.py 文件源码

def make_net(mean=None, net_dir='VGG_S_rgb'):
    # net_dir specifies type of network 
    # Options are: (rgb, lbp, cyclic_lbp, cyclic_lbp_5, cyclic_lbp_10)

    caffe_root = '/home/gshine/Data/Caffe'
    sys.path.insert(0, caffe_root + 'python')

    plt.rcParams['figure.figsize'] = (10, 10)
    plt.rcParams['image.interpolation'] = 'nearest'
    plt.rcParams['image.cmap'] = 'gray'

    net_root = 'models'

    net_pretrained = os.path.join(net_root, net_dir, 'EmotiW_VGG_S.caffemodel')
    net_model_file = os.path.join(net_root, net_dir, 'deploy.prototxt')
    VGG_S_Net = caffe.Classifier(net_model_file, net_pretrained,
                       mean=mean,
                       channel_swap=(2,1,0),
                       raw_scale=255,
                       image_dims=(256, 256))
    return VGG_S_Net

# Load a minibatch of images