Question

我用keras训练MNIST数据集。训练后，我测试了MNIST数据集上的数据。现在我在纸上画了一张ZERO，ONE，TWO和THREE的图片，然后把它上传到我的jupiternotebook中，并想预测我画的数字。我试图对这些数字进行预处理，但在预测时仍然会出现错误。

以下是代码，以及我绘制的图片之一。

img = np.random.rand(224,224,3)
img_path = "0_a.jpg"
img = image.load_img(img_path, target_size=(224, 224))
print(type(img))

x = image.img_to_array(img)
print(type(x))
print(x.shape)
plt.imshow(x/255.)



img = np.random.rand(224,224,3)
img_path = "0_a.jpg"
img = image.load_img(img_path, target_size=(224, 224))
print(type(img))

x = image.img_to_array(img)
print(type(x))
print(x.shape)
plt.imshow(x/255.)
model.predict(x)

这是我得到的错误，我不知道该怎么做。

   ---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-166-2648d9cfd8aa> in <module>()
----> 1 model.predict(x)

/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/keras/models.py in predict(self, x, batch_size, verbose, steps)
   1025             self.build()
   1026         return self.model.predict(x, batch_size=batch_size, verbose=verbose,
-> 1027                                   steps=steps)
   1028 
   1029     def predict_on_batch(self, x):

/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/keras/engine/training.py in predict(self, x, batch_size, verbose, steps)
   1780         x = _standardize_input_data(x, self._feed_input_names,
   1781                                     self._feed_input_shapes,
-> 1782                                     check_batch_axis=False)
   1783         if self.stateful:
   1784             if x[0].shape[0] > batch_size and x[0].shape[0] % batch_size != 0:

/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/keras/engine/training.py in _standardize_input_data(data, names, shapes, check_batch_axis, exception_prefix)
    108                         ': expected ' + names[i] + ' to have ' +
    109                         str(len(shape)) + ' dimensions, but got array '
--> 110                         'with shape ' + str(data_shape))
    111                 if not check_batch_axis:
    112                     data_shape = data_shape[1:]

ValueError: Error when checking : expected dense_13_input to have 2 dimensions, but got array with shape (224, 224, 3)

  [1]: https://i.stack.imgur.com/SvB

ta.jpg

Answer 1

您的图像有三个通道（RGB），而MNIST图像只有一个通道（灰度）。您的图像需要以灰度模式打开。如果您正在使用PIL，可以在How can I convert an RGB image into grayscale in Python?找到更多信息。

使用keras

1 个答案: