分类： macOS

在执行macOS Sierra (10.12.4)下Caffe通过Python接口加载binaryproto格式的均值文件的时候，最后报告错误：

Traceback (most recent call last):
  File "analysis_memnet.py", line 29, in <module>
    detector = caffe.Detector(model_def, pretrained_model, mean=means)
  File "/Users/Source/caffe/distribute/python/caffe/detector.py", line 46, in __init__
    self.transformer.set_mean(in_, mean)
  File "/Users/Source/caffe/distribute/python/caffe/io.py", line 259, in set_mean
    raise ValueError('Mean shape incompatible with input shape.')
ValueError: Mean shape incompatible with input shape.

这个错误发生的原因是由于memnet提供的均值文件是256*256的，但是提供的配置文件却是227*227的，导致在io.py里面的代码在进行判断的时候发生异常。调整源代码中的python/caffe/io.py里面的代码：

    def set_mean(self, in_, mean):
        """
        Set the mean to subtract for centering the data.

        Parameters
        ----------
        in_ : which input to assign this mean.
        mean : mean ndarray (input dimensional or broadcastable)
        """
        self.__check_input(in_)
        ms = mean.shape
        if mean.ndim == 1:
            # broadcast channels
            if ms[0] != self.inputs[in_][1]:
                raise ValueError('Mean channels incompatible with input.')
            mean = mean[:, np.newaxis, np.newaxis]
        else:
            # elementwise mean
            if len(ms) == 2:
                ms = (1,) + ms
            if len(ms) != 3:
                raise ValueError('Mean shape invalid')
            if ms != self.inputs[in_][1:]:
                raise ValueError('Mean shape incompatible with input shape.')
        self.mean[in_] = mean

调整为：

    def set_mean(self, in_, mean):
        """
        Set the mean to subtract for centering the data.

        Parameters
        ----------
        in_ : which input to assign this mean.
        mean : mean ndarray (input dimensional or broadcastable)
        """
        self.__check_input(in_)
        ms = mean.shape
        if mean.ndim == 1:
            # broadcast channels
            if ms[0] != self.inputs[in_][1]:
                raise ValueError('Mean channels incompatible with input.')
            mean = mean[:, np.newaxis, np.newaxis]
        else:
            # elementwise mean
            if len(ms) == 2:
                ms = (1,) + ms
            if len(ms) != 3:
                raise ValueError('Mean shape invalid')
            if ms != self.inputs[in_][1:]:
                in_shape = self.inputs[in_][1:]
                m_min, m_max = mean.min(), mean.max()
                normal_mean = (mean - m_min) / (m_max - m_min)
                mean = resize_image(normal_mean.transpose((1,2,0)),in_shape[1:]).transpose((2,0,1)) * (m_max - m_min) + m_min
                #raise ValueError('Mean shape incompatible with input shape.')
        self.mean[in_] = mean

调整完成后，需要重新编译Caffe:

$ make clean
$ make
$ make pycaffe
$ make distribute

参考链接

• 运行classify.py时报错 Mean shape incompatible with input shape
• Error when using classify in caffe