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tensorflow - ValueError：输入必须有3个通道；得到了`input_shape=(200, 200, 1)`

问题描述

我正在尝试将迁移学习与 VGG16 一起使用。我正在使用 Keras。但我得到了错误

vgg = vgg16.VGG16(include_top=False, weights='imagenet', input_shape=(IMG_SIZE, IMG_SIZE, 1))

任何帮助有什么问题吗？

注：IMG_SIZE= 200

错误的痕迹是

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-5-1b17094c93e2> in <module>
      3 import keras
      4 
----> 5 vgg = vgg16.VGG16(include_top=False, weights='imagenet', input_shape=(IMG_SIZE, IMG_SIZE, 1))
      6 
      7 output = vgg.layers[-1].output

c:\users\hiteshsom\documents\deepanshu_q2\env\lib\site-packages\tensorflow\python\keras\applications\vgg16.py in VGG16(include_top, weights, input_tensor, input_shape, pooling, classes, classifier_activation)
    124                      ' as true, `classes` should be 1000')
    125   # Determine proper input shape
--> 126   input_shape = imagenet_utils.obtain_input_shape(
    127       input_shape,
    128       default_size=224,

c:\users\hiteshsom\documents\deepanshu_q2\env\lib\site-packages\tensorflow\python\keras\applications\imagenet_utils.py in obtain_input_shape(input_shape, default_size, min_size, data_format, require_flatten, weights)
    363           raise ValueError('`input_shape` must be a tuple of three integers.')
    364         if input_shape[-1] != 3 and weights == 'imagenet':
--> 365           raise ValueError('The input must have 3 channels; got '
    366                            '`input_shape=' + str(input_shape) + '`')
    367         if ((input_shape[0] is not None and input_shape[0] < min_size) or

ValueError: The input must have 3 channels; got `input_shape=(200, 200, 1)`

标签： tensorflowkerasdeep-learningtransfer-learningvgg-net

解决方案

您不能对单通道图像使用 imagenet 权重。这可能会解决您的问题：

vgg = vgg16.VGG16(include_top=False, weights=None, input_shape=(IMG_SIZE, IMG_SIZE, 1))

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