Question

我想从人物的照片中提取脸部描述符。这就是我到目前为止所做的：

首先使用python中的opencv库从照片中检测到面孔。
将这些脸部保存在另一张图片中。
接下来我必须从脸部图像中提取描述符。

为此，我从这里下载了vgg face caffemodel CNN：http://www.robots.ox.ac.uk/~vgg/software/vgg_face/

要提取描述符，首先我这样做了：

 net = caffe.Net('CAFFE_FACE_deploy.prototxt','CAFFE_FACE.caffemodel',caffe.TEST)
 img = caffe.io.load_image( "detectedface.jpg" )
 img = img[:,:,::-1]*255.0 
 avg = np.array([129.1863,104.7624,93.5940])
 img = img - avg 
 img = img.transpose((2,0,1)) 
 img = img[None,:]
 out = net.forward_all( data = img )

但是它会给出维度不匹配错误，即数据应该是维度(50,3,224,224)而不是(50,3,490,490)

然后我尝试了这个：

  # input preprocessing: 'data' is the name of the input blob ==  net.inputs[0]
  transformer = caffe.io.Transformer({'data': net.blobs['data'].data.shape})
  transformer.set_transpose('data', (2,0,1))
  transformer.set_mean('data', np.load(caffe_root + 'python/caffe/imagenet/ilsvrc_2012_mean.npy').mean(1).mean(1)) # mean pixel
  transformer.set_raw_scale('data', 255)  # the reference model operates on   images in [0,255] range instead of [0,1]
  transformer.set_channel_swap('data', (2,1,0))  # the reference model has channels in BGR order instead of RGB

  net.blobs['data'].reshape(50,3,224,224)

  net.blobs['data'].data[...] = transformer.preprocess('data', caffe.io.load_image('detectedface.jpg'))
  out = net.forward()

  feats = net.blobs['fc7'].data[0]

此时，当我print feats时，它会显示全部为零。为什么会这样？

为什么net.blobs ['fc7']。data [0]给出全零

0 个答案: